in vitro and genetic aspects of treatments for …

IN VITRO AND GENETIC ASPECTS OF

TREATMENTS FOR FALCIPARUM MALARIA:

STUDIES OF CONVENTIONAL AND NOVEL DRUGS

WITH A PARTICULAR FOCUS ON

PAPUA NEW GUINEA

Rina Pok-Man Fu nee Wong

B. Sc. (First Hons)

School of Medicine & Pharmacology

This thesis is submitted to the University of Western Australia

for the degree of DOCTOR OF PHILOSOPHY OF MEDICINE

2011

DECLARATION

The research presented in this thesis is my own work unless otherwise stated. The majority of this work was undertaken in the School of Medicine and Pharmacology (Fremantle Unit), the University of Western Australia. Field components were carried out at collaborating institutions, specifically the Papua New Guinea Institute of Medical Research (PNGIMR), Madang, Papua New Guinea and Case Western Reserve University, Cleveland, Ohio, United States of America. This thesis has not been submitted for any other degree at this or any other tertiary institution.

• Patient recruitment, blood collection and P. falciparum screening were carried out by the nursing team at Alexishafen Health Centre, Madang, Papua New Guinea as part of an antimalarial treatment trial.

• Restriction fragment length polymorphism assays of P. falciparum field isolates were performed by laboratory staff at the PNGIMR as part of the same treatment trial.

Rina Pok-Man Fu nee Wong Perth, Australia 2011

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DECLARATION FOR THESIS CONTAINING PUBLISHED WORK AN D/OR WORK PREPARED FOR PUBLICATION

This thesis contains published work and/or work prepared for publication, some of which has been co-authored. The bibliographical details and where it appears in the thesis are outlined below. The candidate must attach to this declaration a statement for each publication detailing the percentage contribution by the candidate. This statement must be signed by all authors. If signatures from all the authors cannot be obtained, the statement detailing the candidate’s contribution to the published work must be signed by the coordinating supervisor.

• Harin, A. Karunajeewa, Ivo Mueller, Michele Senn, Enmoore Lin, Irwin Law, Servina P. Gomorrai, Olive Oa, Suzanne Griffin, Kaye Kotab, Penias Suano, Nandao Tarongka, Alice Ura, Dulcie Lautu, Madhu Page-Sharp, Rina P. M. Wong, Sam Salman, Peter Siba, Kenneth F. Ilett and Timothy M. E. Davis. (2008) A trial of combination antimalarial therapies in children from Papua New Guinea. N Engl J Med 359 (24) 2545-57. Precise Contributions: performed in vitro drug sensitivity testing and analysis, assisted with patient recruitment and sample processing. Overall Contribution: 5%.

• Rina P. M. Wong and Timothy M. E. Davis. (2009) Statins as potential antimalarial drugs: Low relative potency and lack of synergy with conventional antimalarial drugs. Antimicrob Agents Chemother 53 (5) 2212-2214. Precise Contributions: designed and performed all in vitro experiments, data analysis and interpretation, drafting of manuscript. Overall Contribution: 90%.

• Stephan Karl and Rina P.M. Wong (equal-first author), Tim St. Pierre, Timothy M.E. Davis. (2009) A comparative study of a flow-cytometry-based assessment of in vitro Plasmodium falciparum drug sensitivity. Malaria Journal 8, 294. Precise Contributions: designed and performed drug sensitivity assays suitable for three methods of growth response assessment, data collection for the reference isotopic and enzyme methods, data analysis and drafting of manuscript. Overall Contribution: 40%.

• Rina P. M. Wong, Dulcie Lautu, Livingstone Tavul, Sarah L. Hackett, Peter Siba, Harin A. Karunjeewa, Kenneth F Ilett, Ivo Mueller, Timothy M. E. Davis. (2010) In vitro sensitivity of Plasmodium falciparum to conventional and novel antimalarial drugs in Papua New Guinea. Trop Med Int Health 15(2) 342-349.

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Precise Contributions: designed and performed drug sensitivity assays, method validation and optimisation, assisted with sample collection and processing, data analysis and interpretation, drafting of manuscript. Overall Contribution: 80%.

• Rina P. M. Wong, Harin Karunajeewa, Ivo Mueller, Peter Siba, Peter A. Zimmerman, Timothy M. E. Davis. (2011) Molecular assessment of Plasmodium falciparum resistance to antimalarial drugs in Papua New Guinea using an extended ligase detection reaction-fluorescent microsphere assay. Antimicrob Agents Chemother 55(2) 798-805. Precise Contributions: performed molecular screening of Plasmodium species, and drug resistant genes, optimisation and extension of the LDR-FMA technique to include the screening of 10 additional SNPs in the pfmdr1 gene, data analysis and interpretation, determination of positive threshold parameters, drafting of manuscript. Overall Contribution: 85%.

• Rina P. M. Wong, Sam Salman, Kenneth F Ilett, Ivo Mueller, Timothy M. E. Davis. (2011) Desbutyl-lumefantrine is a metabolite of lumefantrine with potent in vitro antimalarial activity that may influence artemether-lumefantrine treatment outcome. Antimicrob Agents Chemother 55(3) 1194-1198. Precise Contributions: designed and performed in vitro antimalarial assays, drug interaction asssays, data analysis and interpretation, drafting of manuscript. Overall Contribution: 75%.

• Louise R. Whittell, Kevin T. Batty, Rina P. M. Wong, Erin Bolitho, Simon A. Fox, Timothy M. E. Davis, and Paul E. Murray. (2011) Synthesis and antimalarial evaluation of novel isocryptolepine derivatives. Bioorg Med Chem 19, 7519-7525. Precise Contributions: designed and performed in vitro antimalarial assays, data analysis and interpretation, manuscript preparation. Overall Contribution: 25%.

• Rina P. M. Wong and Timothy M. E. Davis. (2011) In vitro antimalarial efficacy and drug interactions of fenofibric acid. Antimicrob Agents Chemother (Manuscript submitted # AAC05076-11) Precise Contributions: designed and performed in vitro antimalarial assays, drug interaction asssays, data analysis and interpretation, drafting of manuscript. Overall Contribution: 90%.

• Rina P. M. Wong, Gavin R. Flematti and Timothy M. E. Davis. (2011) Detection of volatile organic compounds produced by Plasmodium falciparum in culture. Manuscript in preparation. Precise Contributions: designed culture-volatile compounds capture apparatus, performed experiments, GCMS and data analysis, and drafting of manuscript. Overall Contribution: 70%.

Candidate Signature: __________ Coordinating Supervisor Signature: __________

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PUBLICATIONS

• Harin, A. Karunajeewa, Ivo Mueller, Michele Senn, Enmoore Lin, Irwin Law, Servina P. Gomorrai, Olive Oa, Suzanne Griffin, Kaye Kotab, Penias Suano, Nandao Tarongka, Alice Ura, Dulcie Lautu, Madhu Page-Sharp, Rina P. M. Wong, Sam Salman, Peter Siba, Kenneth F. Ilett and Timothy M. E. Davis. (2008) A trial of combination antimalarial therapies in children from Papua New Guinea. N Engl J Med 359 (24) 2545-57.

• Rina P. M. Wong & Timothy M. E. Davis. (2009) Statins as potential antimalarial drugs: Low relative potency and lack of synergy with conventional antimalarial drugs. Antimicrob Agents Chemother 53 (5) 2212-2214.

• Stephan Karl and Rina P.M. Wong (equal-first author), Tim St. Pierre, Timothy M.E. Davis. (2009) A comparative study of a flow-cytometry-based assessment of in vitro Plasmodium falciparum drug sensitivity. Malaria Journal 8, 294-305.

• Rina P. M. Wong, Dulcie Lautu, Livingstone Tavul, Sarah L. Hackett, Peter Siba, Harin A. Karunjeewa, Kenneth F Ilett, Ivo Mueller, Timothy M. E. Davis. (2010) In vitro sensitivity of Plasmodium falciparum to conventional and novel antimalarial drugs in Papua New Guinea. Trop Med Int Health 15(2) 342-349.

• Rina P. M. Wong, Harin Karunajeewa, Ivo Mueller, Peter Siba, Peter A. Zimmerman, Timothy M. E. Davis. (2011) Molecular assessment of Plasmodium falciparum resistance to antimalarial drugs in Papua New Guinea using an extended ligase detection reaction-fluorescent microsphere assay. Antimicrob Agents Chemother 55(2) 798-805.

• Rina P. M. Wong, S. Salman, Kenneth F Ilett, Ivo Mueller, Timothy M. E. Davis. (2011) Desbutyl-lumefantrine is a metabolite of lumefantrine with potent in vitro antimalarial activity that may influence artemether-lumefantrine treatment outcome. Antimicrob Agents Chemother 55(3) 1194-1198.

• Louise R. Whittell, Kevin T. Batty, Rina P. M. Wong, Erin Bolitho, Simon A. Fox, Timothy M. E. Davis, and Paul E. Murray. (2011) Synthesis and antimalarial evaluation of novel isocryptolepine derivatives. Bioorg Med Chem 19, 7519-7525.

• Rina P. M. Wong and Timothy M. E. Davis. (2011) In vitro antimalarial efficacy and drug interactions of fenofibric acid. Antimicrob Agents Chemother (Manuscript submitted # AAC05076-11)

• Rina P. M. Wong, Gavin R. Flematti and Timothy M. E. Davis. (2011) Detection of volatile organic compounds produced by Plasmodium falciparum in culture. Manuscript in preparation.

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CONFERENCE PRESENTATIONS

• Rina P. M. Wong & Timothy M. E. Davis. In vitro susceptibility and inter-relationships of nine standard and new antimalarials against Plasmodium falciparum isolates from Papua New Guinean children. (2008) Research Showcase: School of Medicine & Pharmacology, Perth, Australia. (Oral)

• Rina P. M. Wong & Timothy M. E. Davis. Malaria and statins. (2008) Annual Research Showcase: School of Medicine & Pharmacology, Perth, Australia. (Oral: Best Student Oral Award)

• Rina P. M. Wong & Timothy M. E. Davis. Statins and fibrates as potential antimalarial agents. (2009) The Australian Society for Medical Research, Medical Research Week Scientific Symposium, Perth, Australia. (Oral)

• Rina P. M. Wong, Harin Karunajeewa, Ivo Mueller, Peter Siba, Eric P. Carnevale, Peter A. Zimmerman and Timothy M. E. Davis. Drug Resistance Polymorphisms in Plasmodium falciparum from children in Papua New Guinea by a recently developed LDR-FMA technique. (2009) Combined Biological Sciences Meeting, Perth, Western Australia. (Oral: New Investigator Award)

• Rina P. M. Wong, Harin Karunajeewa, Ivo Mueller, Peter Siba, Eric P. Carnevale, Peter, A. Zimmerman and Timothy M.E. Davis. Novel molecular detection of drug resistance markers in Plasmodium falciparum from paediatric uncomplicated malaria in Papua New Guinea. (2010) 14th International Congress on Infectious Diseases, Miami, Florida, United States of America. (Oral)

• Rina P. M. Wong, S. Salman, Kenneth F. Ilett, Ivo Mueller and Timothy M. E. Davis. In vitro and in vivo evaluation of desbutyl-benflumetol, a promising antimalarial drug. (2010) XII International Congress on Parasitology, Melbourne, Australia. (Oral)

• Rina P. M. Wong, S. Salman, Kenneth F. Ilett, Ivo Mueller and Timothy M. E. Davis. Desbutyl-lumefantrine, a promising antimalarial drug. (2010) Combined Biological Sciences Meeting, Perth, Western Australia. (Poster: Best Postgraduate Poster Award)

• Rina. P. M. Wong – Three Minute Thesis Oration, Resistance of Plasmodium falciparum to antimalarials in Papua New Guinea. (2010) The Australian Society for Medical Research, Medical Research Week, Scientific Symposium, Perth, Australia (Song).

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• Rina. P. M. Wong – Three Minute Thesis Oration, Multi-resistant malaria: drugs, genes and sick babies. (2010) Three Minute Thesis Competition: The University of Western Australia, Perth, Australia (Finalist).

• Rina. P. M. Wong and Timothy. M. E. Davis. Fenofibric acid, metabolite of fenofibrate is a promising, novel antimalarial drug. (2011) Australian Society for Parasitology Annual Conference, Carins, Queensland, Australia. (Oral: Best Student Oral Prize).

• Rina. P. M. Wong, Gavin. R. Flematti and Timothy M. E. Davis. Detection of volatile organic compounds produced by Plasmodium falciparum in culture. (2011) The Australian Society for Medical Research, Medical Research Week, Scientific Symposium, Perth, Australia. (Oral).

• Rina. P. M. Wong and Timothy M. E. Davis. Lipid-modifying drugs as novel antimalarial therapy. (2011) BIT’s 1st Annual World Congress of Microbes: 1st Annual Symposium of Antiparasites, Beijing, China. (Oral, submitted by Invitation).

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ABSTRACT

Malaria remains a significant global health problem. Plasmodium falciparum, the

predominant and most virulent infecting species, has developed resistance to most

antimalarial drugs. Drug sensitivity is monitored by i) in vivo (clinical) outcome, ii) in

vitro response of cultured parasites to a range of drug concentrations, and iii) presence

of resistance-associated molecular markers. Few studies have integrated these

approaches which can all contribute to the development of treatment regimens that

improve clinical outcome and delay spread of resistance.

Recent clinical studies have shown high rates of treatment failure in Papua New Guinea

(PNG), necessitating a proposed change from chloroquine (CQ) or amodiaquine (AQ)

plus sulfadoxine-pyrimethamine (SP) to artemisinin combination therapy (ACT). The in

vitro sensitivity of 64 P. falciparum isolates from Madang Province to CQ, AQ,

monodesethyl-amodiaquine (DAQ), piperaquine (PQ), naphthoquine (NQ), mefloquine

(MQ), lumefantrine (LM), dihydroartemisinin (DHA) and azithromycin was assessed

by colorimetric lactate dehydrogenase growth inhibition assay. Its non-isotopic, semi-

automated, high-throughput nature makes it suitable for field use in developing

countries. The mean [95% confidence interval] concentration required to inhibit

parasite growth by 50% (IC50) was 215 [175-254] nM for CQ; 82% of strains were CQ-

resistant. Except for azithromycin, the mean IC50s of the other drugs were <27 nM.

There were strong associations between the IC50s of 4-aminoquinoline (CQ, AQ, DAQ

and NQ), bisquinoline (PQ) and aryl-aminoalcohol (MQ) drugs, suggesting cross-

resistance. The only such correlation for LM was with MQ which, with the low

artemisinin IC50s, supports artemether-LM as new first-line therapy in PNG.

Parasite mutations compromising treatment effectiveness were also evaluated using a

modified high-throughput post-PCR multiplexed ligase detection reaction-fluorescent

microsphere assay. The assay was used to detect single nucleotide polymorphisms

(SNPs) in 402 P. falciparum isolates from PNG children participating in an antimalarial

treatment trial. There was fixation of pfcrt K76T, pfdhfr C59R and S108N, and pfmdr1

mutations (92%, 93%, 95% and 91%, respectively). Multiple mutations were frequent,

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88% of isolates possessed a quintuple mutation SVMNT+NRNI+KAA+YYSND in

codons 72-76 for pfcrt, 51, 59, 108, 164 for pfdhfr, 540, 581, 613 for pfdhps, and 86,

184, 1034, 1042, 1246 for pfmdr1, and four carried the K540E pfdhps allele. Pfmdr1

D1246Y was associated with PCR-corrected day 42 treatment failure in children

allocated PQ-DHA (P=0.004). Although the pfmdr1 NFSDD haplotype was found in

only four isolates, it has been associated with artemether-LM treatment failure in

Africa. The assay allowed large-scale assessment of resistance-associated SNPs that

reflected previous heavy 4-aminoquinoline/SP use in PNG. Since artemether-LM and

PQ-DHA will become first- and second-line treatment, respectively, in PNG,

monitoring pfmdr1 SNPs appears a high priority.

Desbutyl-lumefantrine (DBL) is a metabolite of LM. Its in vitro activity and

interactions were assessed from tritium-labelled hypoxanthine uptake in laboratory-

adapted P. falciparum. DBL was more potent than LM. Isobolographic analysis of

DBL-LM combinations showed no interaction but mild synergy with DBL-DHA. Mean

plasma DBL concentrations in 94 day-7 samples from an antimalarial treatment trial

predicted treatment response, suggesting that it could be a useful alternative to LM as

part of ACT.

Drugs licensed for other indications can sometimes have antimalarial properties, an

example being lipid-lowering therapy which is becoming affordable even in malaria-

endemic developing countries. In vitro drug sensitivity experiments confirmed

atorvastatin to have the highest activity of available statins against P. falciparum

regardless of strain CQ sensitivity but at an IC50 well above plasma concentrations after

therapeutic doses in vivo. Fibrates have a different mechanism of action to that of

statins. Fenofibric acid had a relatively low in vitro IC50, similar to those of

conventional antimalarial drugs. It may act by interfering with parasite P-glycoprotein

and ABC-1 mediated transport and/or via a putative peroxisome proliferator-activated

receptor-like protein, and could have an adjunctive role in combination antimalarial

therapy.

The detection of P. falciparum-specific volatile organic compounds (VOCs) in

breath/other samples as a way of enhancing diagnosis and therapeutic monitoring was

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explored using culture-capture apparatus. Optimised conditions supported cultures of

high parasitaemia (>20%) from which VOCs within the headspace and supernatant

were extracted using traditional (solvent) and novel (solid-phase) methods. Gas

chromatography-mass spectrometry data revealed the production of a variety of volatile

compounds but no unique malarial finger-prints. Future in vivo studies analysing the

breath of patients with severe malaria may yet reveal specific clinically-useful volatile

biomarkers.

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ACKNOWLEDGEMENTS

My PhD journey would not have been successful without the unyielding support of my

family, friends and colleagues.

To my supervisor Prof. Tim Davis, I have admired your expertise in the field and your

driven-nature since day-one. You have taught me to think critically, work

independently as well as providing opportunities for me to do research as part of a team

abroad. You have amazing writing skills that I can only learn to mimic. Thank you so

much for supporting me through the highs and lows. I’m grateful for your financial

support which helped to sustain my newly established family. It is a privilege to be part

of your team and have the chance to travel/work in two very different worlds: Papua

New Guinea (PNG) and the United States of America. The experiences gained from

these collaborations are extraordinary and most unforgettable, “Tenkyu tru!” (Pidgin).

Special thanks to Drs Wendy Davis, Martin Firth and Shih Ching Fu for your time and

invaluable advice on statistical modelling and analyses for the molecular aspect of this

project. To Dr Pete Zimmerman, Laurie Gray and many colleagues at Case Western

Reserve University, thank you for sharing your cutting edge molecular techniques and

being so accommodating when I used your machines up to 12 hours a day! I treasure

the time I spent in your lab and thank you for giving me this wonderful opportunity.

This project would not have been possible without support from Drs Peter Siba, Pascal

Michon, Ivo Mueller, study volunteers and administrative staff from the PNG Institute

of Medical Research. Thanks to Livingstone Tavul and Dulcie Lautu for your technical

support for the in vitro drug assays. Dr Harin Karunajeewa who led a dedicated team of

nurses at the Alexishafen Health Clinic, a big thank you for collecting the field samples

and allowing me to take part in this amazing experience.

Dr Jane Allan, you have always been there for me (literally) to offer comforting words

when I’m disheartened and provided tips that often facilitated my trouble shooting.

Thank you for looking after the parasites when I was sick and for your continuous

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support. I really appreciate your friendly and approachable qualities; you are an

awesome lab manager. To my colleagues at the Medical Sciences Lab, Fremantle

Hospital – Janet, Ross, Debbie, Caryn, Stephan, Eng, Carly, Angela, Yoke Leng, Bruce,

Roheeth, Frances, Borut, Kristine, Janina, Anita, Gwen and Chun Wei, thank you for

your friendship and amazing support throughout my PhD journey.

To our school administrator, Brenda Riley, thank you for your time and care in ironing

out the many hiccups and providing a listening ear. Michelle England and “the nurses

upstairs”, thank you for spicing things up and taking my blood every few weeks!

I’m grateful and indebted to Mr Graham Icke, aka.‘Pop’, my honours supervisor and

mentor. Thanks for your encouragement and time in critiquing this thesis. Thanks to

Rolf and friends from church, for your encouragements throughout this journey.

Shih Ching Fu, my loving husband who is also under the pump with his own thesis, you

have been a tremendous support. Thanks for sacrificing countless weekends to

accompany me to the lab and giving your red cells for my parasites. Thank you for your

patience, encouragement, understanding and lending me your shoulders to cry on. To

my Mum (Yolanda) and Dad (Siu Kee), thank you for spurring me on when I’m

discouraged and pulling me back when I’m exhausted. You have supported me so much

through words, deeds and prayers. Louis, although you can’t talk, I know you are

always supporting your sister in your heart. Thank you for being understanding and I

will strive to spend more time with you.

Most of all I would like to thank God for blessing me with this amazing PhD experience

and the love from his son Jesus that has carried me through these years and beyond.

The studies herein are supported by grants from the WHO Western Pacific Region, the National

Health and Medical Research Council of Australia (grant no. 353663, T. Davis as CIA) and the

U.S. National Institutes of Health (grants AI52312 and TW 007872). R. P. M. Wong is

supported by the Australian Postgraduate Award, Ad hoc Scholarship (School of Medicine and

Pharmacology), the UWA Student Travel Award and the UWA PhD Completion Scholarship.

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PREFACE

For the in vitro work presented in Chapter 3 and published in Tropical Medicine and

International Health (2010), I went to Papua New Guinea (PNG) for a period of 5

months to collect and test field isolates of P. falciparum. I was based in the Vector

Borne Disease Unit in the PNG Institute of Medical Research at Yagaum Hospital,

Madang. I took primary responsibility in setting up drug sensitivity assays, data analysis

and interpretation of results. A small number of assays were set up by local colleagues

Dulcie Lautu and Livingstone Tavul in my absence. Two to three times each week, I

helped out at a remote Health Clinic at Alexishafen, where young children presenting

with fever were screened for malaria infection and enrolled into a standard treatment

trial. The samples included in this thesis were mainly derived from this cohort but a few

were from children who presented to Modilon Hospital, Madang Town.

I travelled to Case Western Reserve University, Cleveland, Ohio for the molecular

analysis of parasite DNA for drug-resistant markers as described in Chapter 4 and

published in Antimicrobial Agents and Chemotherapy (2011). I spent three and a half

months at the Centre for Global Health and Diseases under the supervision of Dr Peter

Zimmerman and learnt a post-PCR technique that has been developed there, namely the

Ligase Detection Reaction-Fluorescence Microsphere Assay (LDR-FMA). After

familiarisation of the laboratory and equipment, I performed LDR-FMA for

Plasmodium species, and single nucleotide polymorphisms (SNPs) detection in the

pfcrt, pfdhps, pfdhfr and pfmdr1 genes of blood samples from the treatment trial cohort.

Initial PCR primers had been designed for the pfmdr1 LDR-FMA by Eric Carnevale,

which required further modifications. I continued to develop and optimise the assay and

successfully applied this to the field samples. I took primary responsibility for the

generation and analysis of the molecular data. Since there were no standard cutoff

points for discriminating between positive and negative SNPs signals, I liaised with Dr

Martin Firth from the Mathematics department, UWA. With his advice, I was able to

establish a new way of calculating appropriate thresholds. The SNPs data were then

used to predict treatment failure rates using the clinical data from the trial. I received

xiii

advice from Dr Wendy Davis regarding statistical methods and software tools, and I

took responsibility for performing these analyses.

Due to direct and indirect evidence in the published literature that fibrates and statins,

as well as being lipid-altering drugs, might also have antimalarial properties, I initiated

the investigation into these drug classes with the support of my supervisor W/Prof. Tim

Davis. Fibrates showed antimalarial activity in the experiments I conducted. The in

vitro studies regarding desbutyl-lumefantrine (DBL) (Chapter 5 and published in

Antimicrobial Agents and Chemotherapy (2011), fibrates and statins (Chapter 6, in part

published in Antimicrobial Agents and Chemotherapy (2009)) were performed at the

Malaria Culture Facilities at the University Department of Medicine, Fremantle

Hospital. I took responsibility for parasite culture maintenance, the design of

experiments and in establishing a renewed approach to assess drug interactions. Due to

the labour intensive nature of this work, I was assisted by a research assistant, Miss

Jenny Wong on a casual basis. The pharmacokinetic component of the DBL work

(Chapter 5) was performed by my colleague and fellow PhD student Sam Salman.

The investigation of volatile organic compounds in P. falciparum was carried out in

collaboration with the Chemistry Department, UWA. I was under the supervision of Dr

Gavin Flematti, School of Biomedical, Biomolecular and Chemical Sciences. Together

we designed two prototypes of culture flasks that enabled the capture and analysis of

the head space atmosphere. I was responsible for optimising culture conditions in these

and performed various extractions followed by GC-MS analysis. I received technical

support with the use of equipments and machinery, and advice regarding the analysis of

chromatogram peaks from Dr Gavin Flematti.

The work presented in this thesis was performed within the time constraints of my PhD

enrolment.

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ABBREVIATIONS

ABC ATP-binding cassette sub-family A member

ACPR Adequate clinical and parasitological response

ACR Adequate clinical response

ACTs Artemisinin based combination therapies

AL Artemether-lumefantrine

amu Atomic mass unit

ANOVA Analysis of variance

APAD 3-acetylpyridine adenine dinucleotide

ARMD Accelerated resistance to multidrug

ART-SP Artesunate-sulfadoxine-pyrimethamine

AQ Amodiaquine

AV Atorvastatin

AZ Azithromycin

bp base-pairs

CDC Centre for Disease Control and Prevention (Atlanta, USA)

cfu Colony-forming units

CI Confidence interval

xv

CO2 Carbon dioxide

CPM Counts per minute

CSP Circumsporozoite protein

CQ Chloroquine

CYC Cycloguanil

CQ-SP Chloroquine-sulfadoxine-pyrimethamine

dAQ Monodesethyl-amodiaquine

DBL Desbutyl-lumefantrine

DDT Dichloro-diphenyl-trichloroethane

DELI Double-site enzyme-linked pLDH immunodetection

d. H2O Distilled water

DHA Dihydroartemisinin

DHFR Dihydrofolate reductase

DHPS Dihydropteroate synthase

DMSO Dimethylsulphoxide

DNA Deoxyribonucleic acid

dNTPs Deoxynucleotide triphosphate

DVB Divinylbenzene

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EDTA Ethylenediaminetetraacetic acid

ETF Early treatment failure

fmol femtomole

FI Fluorescent intensities

FIC Fractional inhibitory concentration

GC-MS Gas chromatography- mass spectrometry

H2O Water

HCl Hydrochloric acid

hct Haematocrit

HDL High-density lipoprotein

HEPES N-2-hydroxyethylipiperazine-N-2ethanesulfonic acid

HF Halofantrine

HMG-CoA 3-hydroxy-methyl-glutaryl coenzyme A

HPLC High performance liquid chromatography

HRP-2 Histidine-rich protein-2

hr Hour

HTPBS Human tonicity phosphate buffered saline

xvii

IC50 Drug concentration required to inhibit parasite growth by 50%



ICAM-1 Intercellular cell adhesion molecule-1

IFN-γ Interferon-gamma

IL-10 Interleukin-10

LCF Late clinical failure

LC-MS Liquid chromatography-mass spectrometry

LDH Lactate dehydrogenase

LDL Low-density lipoprotein

LDR Ligase detection reaction

LDR-FMA Ligase detection reaction-fluorescent microsphere assay

LM Lumefantrine

LPF Late parasitological failure

LTF Late treatment failure

mg Milligram

min Minute(s)

xviii

mL Millilitre

mM Millimolar

MOI Multiplicity of infection

MR4 Malaria research and reference reagent centre

MQ Mefloquine

ng Nanogram

nm Nanometre

nM Nanomolar

NaCl Sodium chloride

NAD Nicotinamide adenine dinucleotide

NaOH Sodium hydroxide

NBF Nitro blue formazan

NBT Nitro blue tetrazolium

NQ Naphthoquine

O2 Oxygen

OD Optical density

PBS Phosphate saline buffer

PCR Polymerase chain reaction

xix

PDMS Polydimethylsiloxane

PfATP6 (see Pfserca)

Pfcrt Plasmodium falciparum chloroquine resistant transporter

Pfdhfr Plasmodium falciparum dihydrofolate reductase

Pfdhps Plasmodium falciparum dihydropteroate synthase

Pfmdr1 Plasmodium falciparum multidrug resistant-1

Pfserca Plasmodium falciparum sarco-endoplasmic reticulum calcium ATPase6

piRBC Packed infected red cells

pLDH Plasmodium lactate dehydrogenase

pmol Picomole

PNG Papua New Guinea

PPAR Peroxisome proliferator-activated receptor

PQ Piperaquine

PQ-DHA Piperaquine-dihydroartemisinin

PV Pravastatin

PYR Pyrimethamine

RBC Red blood cells

rDNA Ribosomal deoxyribonucleic acid

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RI Low grade resistance

RII Moderate resistance

RIII High grade resistance

rpm Revolutions per minute

RPMI Roswell Park Memorial Institute

RNA ribonucleic acid

rRNA ribosomal ribonucleic acid

RT Room temperature

RV Rosuvastatin

sec Second (s)

SD Standard deviation

SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis

SNPs Single nucleotide polymorphisms

SP Sulfadoxine-Pyrimethamine (Fansidar)

SPME Solid phase micro-extraction

SV Simvastatin

TA Annealing temperature

TGF-β Transforming growth factor-β

xxi

TNF Tumour necrosis factor

v/v Percentage volume per volume

vs Versus

VOCs Volatile organic compounds

WARN World Antimalarial Resistance Network

WHO World Health Organisation

w/v Percentage weight per volume

3H Tritium

⁰ Degree

⁰C Celsius

% Percentage

α Alpha

β Beta

ΣFIC Sum of fractional inhibitory concentrations

µCi Microcurie

µg Microgram

µL Microlitre

xxii

µm Micron

µM Micromolar

Nucleotide Code

Adenine A

Cytosine C

Guanine G

Thymine T

Amino acid Single letter code

Alanine A

Arginine R

Asparagine N

Aspartic acid D

Cysteine C

Glutamic acid E

Glycine G

Isoleucine I

Leucine L

Lysine K

Methionine M

Phenylalanine F

Serine S

Threonine T

Tyrosine Y

Valine V

xxiii

TABLE OF CONTENTS

DECLARATION........................................................................................................................................ I

PUBLICATIONS .................................................................................................................................... IV

CONFERENCE PRESENTATIONS ......................................................................................................V

ABSTRACT............................................................................................................................................VII

ACKNOWLEDGEMENTS......................................................................................................................X

PREFACE...............................................................................................................................................XII

ABBREVIATIONS .............................................................................................................................. XIV

TABLE OF CONTENTS.................................................................................................................. XXIII

LIST OF TABLES .............................................................................................................................XXIX

LIST OF FIGURES ...........................................................................................................................XXXI

CHAPTER 1. GENERAL INTRODUCTION.........................................................................................2

1.1 INTRODUCTION..........................................................................................................................2

1.2 DISEASE DISTRIBUTION .............................................................................................................3

1.3 PLASMODIUM LIFE CYCLE AND BIOLOGY ..................................................................................4

1.3.1 Development in the Human Host..........................................................................................5

1.3.2 Development in the Mosquito...............................................................................................7

1.4 PATHOLOGY...............................................................................................................................8

1.5 CLINICAL SIGNS AND SYMPTOMS ............................................................................................10

1.6 DIAGNOSIS...............................................................................................................................11

1.7 TRANSMISSION........................................................................................................................13

1.8 PREVENTION............................................................................................................................14

1.9 TREATMENT.............................................................................................................................14

1.10 MALARIA IN WESTERN PACIFIC...............................................................................................15

1.11 EMERGENCE OF ANTIMALARIAL RESISTANCE IN PAPUA NEW GUINEA ...................................16

1.12 ANTIMALARIAL CHEMOTHERAPY............................................................................................18

1.12.1 Quinoline Related Compounds......................................................................................19 1.12.1.1 Quinine .......................................................................................................................................... 19 1.12.1.2 Chloroquine ................................................................................................................................... 20 1.12.1.3 Amodiaquine.................................................................................................................................. 21 1.12.1.4 Mefloquine..................................................................................................................................... 23 1.12.1.5 Lumefantrine.................................................................................................................................. 24 1.12.1.6 Naphthoquine................................................................................................................................. 25

xxiv

1.12.1.7 Piperaquine.....................................................................................................................................26 1.12.2 Antifolate Combination Drugs...................................................................................... 26

1.12.3 Artemisinin and its Derivatives..................................................................................... 27

1.12.4 Antibiotics..................................................................................................................... 28

1.12.5 Summary of Antimalarial Activities .............................................................................. 31

1.13 LIPID-LOWERING AGENTS AS ANTIMALARIALS ...................................................................... 33

1.13.1 Statins ........................................................................................................................... 33

1.13.2 Fibrates......................................................................................................................... 35

1.14 ANTIMALARIAL DRUG RESISTANCE........................................................................................ 36

1.14.1 Definitions .................................................................................................................... 36

1.14.2 Treatment Failure and Drug Resistance....................................................................... 37

1.14.3 Emergence of Resistance to Principal Antimalarials ................................................... 38

1.14.4 Determinants of Antimalarial Resistance ..................................................................... 39

1.14.5 Mechanism of Resistance to 4-Aminoquinolines and Arylaminoalcohols .................... 42

1.14.6 Mechanism of Resistance to Antifolates........................................................................ 43

1.14.7 Mechanism of Resistance to Artemisinin and Derivatives............................................ 43

1.15 IN VITRO DETECTION OF RESISTANCE IN P. FALCIPARUM......................................................... 45

1.15.1 Schizont Maturation...................................................................................................... 46 1.15.1.1 Macro test.......................................................................................................................................46 1.15.1.2 Micro test........................................................................................................................................47

1.15.2 3H-Hypoxanthine Incorporation Assay......................................................................... 48

1.15.3 Plasmodium Lactate Dehydrogenase (pLDH) Detection ............................................. 48 1.15.3.1 Colourimetric pLDH microtests .....................................................................................................49 1.15.3.2 Immunocapture of pLDH ...............................................................................................................50

1.15.4 Histidine-Rich Protein II (HRP2) Assay....................................................................... 51

1.15.5 Dual Detection of HRP2 and PLDH............................................................................. 52

1.16 ASSESSMENT OF ANTIMALARIAL DRUG COMBINATIONS ........................................................ 52

1.17 IN VIVO DETECTION OF DRUG RESISTANCE IN P. FALCIPARUM................................................ 54

1.18 MOLECULAR MARKERS OF DRUG RESISTANCE....................................................................... 56

1.19 BREATH TEST FOR MALARIA .................................................................................................. 58

1.20 SCOPE OF THE STUDIES PRESENTED IN THIS THESIS................................................................ 59

CHAPTER 2. METHODS AND MATERIALS ................................................................................... 62

2.1 IN VITRO CULTURE TECHNIQUES............................................................................................... 62

2.1.1 Parasites............................................................................................................................ 62

2.1.2 Retrieval from Liquid Nitrogen ......................................................................................... 62

2.1.3 Maintenance of Cultures ................................................................................................... 63

2.1.4 Erythrocytes Preparation .................................................................................................. 63

2.1.5 Determination of Parasitaemia ......................................................................................... 64

2.1.6 Synchronisation of Parasite Forms ................................................................................... 64

xxv

2.1.7 Cryopreservation................................................................................................................66

2.2 DRUG SUSCEPTIBILITY ASSAYS...............................................................................................67

2.2.1 Drug/Compound Preparation ............................................................................................67

2.2.2 Preparation of parasitised cells .........................................................................................67

2.2.3 Controls..............................................................................................................................68

2.2.4 Plasmodium Lactate Dehydrogenase Assay.......................................................................70 2.2.4.1 Principle of pLDH Assay................................................................................................................. 70 2.2.4.2 Assay Set Up.................................................................................................................................... 70

2.2.5 3H-Hypoxanthine Incorporation Assay ..............................................................................71

2.3 MOLECULAR TECHNIQUES.......................................................................................................72

2.3.1 DNA Extraction..................................................................................................................73

2.3.2 Polymerase Chain Reaction (PCR)....................................................................................73 2.3.2.1 PCR for Plasmodium Species .......................................................................................................... 73 2.3.2.2 PCR for pfcrt, pfdhfr and pfdhps genes ........................................................................................... 74 2.3.2.3 Controls ........................................................................................................................................... 74

2.3.3 Detection of Amplified Products ........................................................................................75

2.3.4 Ligase Detection Reaction Fluorescent Microsphere Assay (LDR-FMA) .........................76 2.3.4.1 Ligase Detection Reaction for Plasmodium species ........................................................................ 76 2.3.4.2 Ligase Detection Reaction for pfcrt, pfdhfr, pfdhps SNPs............................................................... 77 2.3.4.3 Hybridisation and Reporter Labelling.............................................................................................. 78 2.3.4.4 Bio-plex Fluorescent Detection ....................................................................................................... 80

2.4 SOLID PHASE M ICRO-EXTRACTION (SPME) ............................................................................80

CHAPTER 3. IN VITRO SENSITIVITY OF P. FALCIPARUM TO NEW AND CONVENTIONAL

DRUGS IN PAPUA NEW GUINEA ......................................................................................................84

3.1 INTRODUCTION........................................................................................................................84

3.2 MATERIALS AND METHODS.....................................................................................................88

3.2.1 Study Site and Sample Collection.......................................................................................88

3.2.2 In vitro Culture of Parasite Isolates...................................................................................88

3.2.3 Drug Susceptibility Assays .................................................................................................89

3.2.4 Assay Validation.................................................................................................................90

3.2.5 Data Analysis .....................................................................................................................90

3.3 RESULTS..................................................................................................................................91

3.3.1 Comparison of pLDH and Isotopic Assays ........................................................................91

3.3.2 Effect of pLDH Reaction Duration on IC50 Values ............................................................91

3.3.3 Field Application of the pLDH Assay.................................................................................93

3.3.4 Antimalarial Susceptibility of PNG P. falciparum Isolates................................................97

3.3.5 Correlations of in vitro Responses to Nine Antimalarials..................................................98

3.4 DISCUSSION...........................................................................................................................100

CHAPTER 4. CHARACTERISATION OF DRUG RESISTANT POLYM ORPHISMS OF P.

xxvi

FALCIPARUM USING A NEW MOLECULAR ASSAY.................................................................. 106

4.1 INTRODUCTION ..................................................................................................................... 106

4.2 MATERIALS AND METHODS.................................................................................................. 108

4.2.1 Field Studies, P. falciparum isolates ............................................................................... 108

4.2.2 Genomic DNA.................................................................................................................. 109

4.2.3 Plasmodium Speciation ................................................................................................... 109

4.2.4 Detection of Drug Resistant Polymorphisms................................................................... 110

4.2.5 Data Analysis .................................................................................................................. 112

4.3 RESULTS............................................................................................................................... 113

4.3.1 Pfmdr1 LDR-FMA Development ..................................................................................... 113 4.3.1.1 PCR Optimisation...........................................................................................................................113 4.3.1.2 LDR Optimisation ..........................................................................................................................118 4.3.1.3 Optimised LDR-FMA for pfmdr1 and Multiplexed Detection of SNPs in pfdhfr, pfdhps and pfcrt

genes ..........................................................................................................................................................122 4.3.2 Assay Validation.............................................................................................................. 124

4.3.2.1 Comparison between LDR-FMA and RFLP speciation .................................................................124 4.3.2.2 Inter-assay concordance .................................................................................................................124 4.3.2.3 Identification of drug resistance alleles ..........................................................................................125

4.3.3 Field Application of the LDR-FMA ................................................................................. 126 4.3.3.1 Speciation and drug resistance genes in PNG field isolates............................................................126 4.3.3.2 Prevalence of polymorphic alleles in pfcrt, pfmdr1, pfdhfr and pfdhps .........................................127 4.3.3.3 Parasite drug resistance mutations and treatment outcome.............................................................130

4.4 DISCUSSION ...................................................................................................................... 131

CHAPTER 5. ANTIMALARIAL PROPERTIES OF DESBUTYL-LUME FANTRINE ............... 138

5.1 INTRODUCTION ..................................................................................................................... 138

5.2 MATERIALS AND METHODS.................................................................................................. 139

5.2.1 Parasite Cultures............................................................................................................. 139

5.2.2 Antimalarial Drugs.......................................................................................................... 139

5.2.3 In vitro Drug Susceptibility ............................................................................................. 140

5.2.4 Drug Interaction Studies ................................................................................................. 140

5.2.5 Study Site and Sample Collection.................................................................................... 141

5.2.6 Liquid Chromatography and Mass Spectrometry............................................................ 142

5.2.7 Statistical Analysis........................................................................................................... 143

5.3 RESULTS............................................................................................................................... 144

5.3.1 In vitro Antimalarial Potency of DBL ............................................................................. 144

5.3.2 DBL Interaction with Conventional Antimalarials.......................................................... 146

5.3.3 DBL Plasma Levels on Day 7 Post-Treatment ................................................................ 148

5.3.4 Influence of DBL Plasma Levels on Clinical Outcome ................................................... 148

5.4 DISCUSSION.......................................................................................................................... 150

xxvii

CHAPTER 6. STATINS AND FIBRATES: LIPID-MODIFYING DR UGS AS ANTIMALARIALS

.................................................................................................................................................................154

6.1 INTRODUCTION ......................................................................................................................154

6.1.1 Statins as Lipid-lowering and Antimicrobial Agents........................................................154

6.1.2 Fibrates as Potential Antimalarial Drugs........................................................................155

6.2 MATERIALS AND METHODS...................................................................................................156

6.2.1 In vitro Parasite Growth Inhibition..................................................................................156

6.2.2 Drug Interaction Studies ..................................................................................................157

6.2.3 Dosed Plasma Bioassay ...................................................................................................158

6.3 RESULTS................................................................................................................................160

6.3.1 In vitro Antimalarial Activities of Statins.........................................................................160

6.3.2 In vitro Antimalarial Activities of Fibrates ......................................................................160

6.3.3 Interaction of Atorvastatin with Conventional Antimalarials ..........................................164

6.3.4 Interaction of Fibrates with Conventional Antimalarials ................................................164

6.3.5 Bioassay of Atorvastatin...................................................................................................167

6.3.6 Bioassay of Fenofibric Acid .............................................................................................167

6.3.7 BLAST Analysis for PPAR-like Region in Plasmodium ...................................................170

6.3.8 BLAST Analysis for ABC-1 transporter in P. falciparum.................................................170

6.4 DISCUSSION...........................................................................................................................174

CHAPTER 7. CHARACTERISATION OF VOLATILE ORGANIC COM POUNDS OF P.

FALCIPARUM IN VITRO .....................................................................................................................178

7.1 INTRODUCTION......................................................................................................................178

7.2 MATERIALS AND METHODS...................................................................................................180

7.2.1 Parasites...........................................................................................................................180

7.2.2 Solid Phase Micro-Extraction (SPME) ............................................................................180

7.2.3 Solvent Extraction ............................................................................................................181

7.2.4 Thermal Desorption: Purge and Trap..............................................................................181

7.2.5 Gas Chromatography and Mass Spectrometry ................................................................183

7.2.6 Data Analysis ...................................................................................................................184

7.3 RESULTS................................................................................................................................184

7.3.1 Malaria VOCs Assay Development ..................................................................................184 7.3.1.1 Design of culture-capture apparatus............................................................................................... 184 7.3.1.2 Optimisation of culture conditions................................................................................................. 186

7.3.2 Analysis of VOCs..............................................................................................................187

7.4 DISCUSSION...........................................................................................................................190

CHAPTER 8. CONCLUDING DISCUSSION ....................................................................................196

8.1 OVERVIEW.............................................................................................................................196

xxviii

8.1.1 Major Findings and Contributions.................................................................................. 196

8.2 THE ROLE OF IN VITRO RESISTANCE AND PARASITE GENETIC MUTATIONS IN TREATMENT

OUTCOME............................................................................................................................................ 198

8.2.1 Limitations of PNG field studies...................................................................................... 200

8.3 UNCONVENTIONAL AND NOVEL ANTIMALARIAL AGENTS ...................................................202

8.3.1 Desbutyl-lumefantrine and its Potential Implementation ................................................202

8.3.2 Lipid-modifying Agents as Antimalarials ........................................................................ 204

8.4 A PILOT STUDY OF MALARIA VOCS..................................................................................... 206

8.5 CONCLUSION AND FUTURE DIRECTIONS............................................................................... 207

8.5.1 Directions for Future Research....................................................................................... 208

BIBLIOGRAPHY ................................................................................................................................. 209

APPENDICES ....................................................................................................................................... 259

APPENDIX A. ISOLATE INFORMATION .................... .................................................................. 261

APPENDIX B. RECIPES FOR SOLUTIONS.................................................................................... 263

Culture of P. falciparum ................................................................................................................ 263

LDH Assay ..................................................................................................................................... 268

Molecular Assays........................................................................................................................... 269

APPENDIX C. EFFECTS OF LDR ANNEALING TEMPERATURE AN D DILUTION............. 272

APPENDIX D. ISOBOLOGRAM ANALYSIS .................................................................................. 277

APPENDIX E. VOCS ANAYLSIS ...................................................................................................... 280

xxix

LIST OF TABLES

TABLE 1.1 ANTIMALARIAL DRUGS AND THEIR SPECIFIC ACTIVITIES. ..........................................................32

TABLE 1.2 DETERMINANTS OF ANTIMALARIAL RESISTANCE. ......................................................................40

TABLE 1.3 CLASSIFICATIONS OF IN VIVO ANTIMALARIAL SUSCEPTIBILITY OUTCOMES. ...............................55

TABLE 1.4 MOLECULAR MARKERS FOR ANTIMALARIAL DRUG RESISTANCE................................................58

TABLE 2.1 SOLVENTS AND OPTIMISED ASSAY CONCENTRATION RANGES FOR DRUG SUSCEPTIBILITY

TESTING.............................................................................................................................................69

TABLE 2.2 PCR PRIMER SEQUENCES AND THERMOCYCLING CONDITIONS FOR PFCRT, PFDHPS AND PFDHFR

TARGET SEQUENCES. .........................................................................................................................75

TABLE 2.3 LDR PRIMER SEQUENCES FOR PLASMODIUM SPECIES DIAGNOSIS...............................................77

TABLE 2.4 LDR PRIMER SEQUENCES FOR DRUG RESISTANCE MARKERS PFCRT, PFDHFR AND PFDHPS. .......79

TABLE 3.1 OVERVIEW OF IN VITRO DRUG SENSITIVITY FINDINGS IN PNG....................................................86

TABLE 3.2 IN VITRO SUSCEPTIBILITIES OF P. FALCIPARUM PNG ISOLATES AGAINST 4-AMINOQUINOLINES

AND OTHER ANTIMALARIAL DRUGS. ..................................................................................................98

TABLE 3.3 SPEARMAN CORRELATION CO-EFFICIENTS FOR ASSOCIATIONS BETWEEN IC50 VALUES..............99

TABLE 4.1 PRIMER SEQUENCES AND THERMOCYCLING CONDITIONS FOR PFMDR1 ASSAYS. ......................115

TABLE 4.2 OPTIMISED PCR CONDITIONS FOR PFMDR1 REGION 1. ……………………………………….120

TABLE 4.3 OPTIMISED PCR CONDITIONS FOR PFMDR1 REGION 2…….. ....................................................120

TABLE 4.4 LDR PRIMERS FOR P. FALCIPARUM PFMDR1 MOLECULAR MARKERS. .......................................121

TABLE 4.5 OPTIMISED LDR CONDITIONS FOR PFMDR1 REGION 1…………………………………… …..123

TABLE 4.6 OPTIMISED LDR CONDITIONS FOR PFMDR1 REGION 2…..........................................................123

TABLE 4.7 CONCORDANCE BETWEEN RFLP AND LDR-FMA DIAGNOSIS OF PLASMODIUM SPECIES IN PNG

FIELD SAMPLES. ...............................................................................................................................125

TABLE 4.8 LDR-FMA EVALUATION OF PFMDR1 SNPS IN LABORATORY-ADAPTED P. FALCIPARUM STRAINS.

........................................................................................................................................................126

TABLE 4.9 FLUORESCENCE DETECTION THRESHOLDS AND MAXIMA FOR P. FALCIPARUM PFDHPS, PFDHFR,

PFCRT AND PFMDR1 IN PNG FIELD SAMPLES. ..................................................................................128

TABLE 4.10 OCCURRENCE OF P. FALCIPARUM ISOLATES CARRYING MULTIPLE MUTATIONS ACROSS 4 GENES

ASSOCIATED WITH DRUG RESISTANCE. ............................................................................................130

TABLE 5.1 DRUG COMBINATION RATIOS FOR ISOBOLOGRAM ASSAYS. ......................................................140

TABLE 5.2 IN VITRO SENSITIVITY OF LABORATORY-ADAPTED P. FALCIPARUM TO DESBUTYL-LUMEFANTRINE

AND OTHER ANTIMALARIAL DRUGS. ................................................................................................144

TABLE 5.3 IN VITRO EFFICACY OF ANTIMALARIAL DRUG COMBINATIONS AGAINST P. FALCIPARUM CLONES

3D7 AND W2MEF AS ASSESSED BY ISOBOLOGRAPHIC ANALYSIS. ....................................................146

TABLE 6.1 INTERACTION RATIOS OF STATINS, FIBRATES AND CONVENTIONAL ANTIMALARIALS. .............158

TABLE 6.2 IN VITRO ACTIVITIES OF STATINS AGAINST CQ-SENSITIVE AND CQ-RESISTANT STRAINS OF P.

FALCIPARUM. ...................................................................................................................................161

xxx

TABLE 6.3 IN VITRO ACTIVITIES OF FIBRATES AGAINST CQ-SENSITIVE AND CQ-RESISTANT STRAINS OF P.

FALCIPARUM.................................................................................................................................... 162

TABLE 6.4 IN VITRO EFFICACY OF FIBRATES AND ANTIMALARIAL DRUG COMBINATIONS.......................... 166

TABLE 7.1 VOCS DETECTED IN CULTURE HEADSPACE. ............................................................................ 188

xxxi

LIST OF FIGURES

FIGURE 1.1 DISTRIBUTION OF MALARIA INCIDENCE BY COUNTRY. ...............................................................4

FIGURE 1.2 LIFE CYCLE OF PLASMODIUM. .....................................................................................................5

FIGURE 1.3 CHILD WITH MALARIA . .............................................................................................................11

FIGURE 1.4 ANOPHELES ALBIMANUS TAKING A BLOOD MEAL. ......................................................................13

FIGURE 1.5 MALARIA MORTALITY IN WESTERN PACIFIC. ...........................................................................15

FIGURE 1.6 REGIONS AND PROVINCES OF PAPUA NEW GUINEA. .................................................................16

FIGURE 1.7 ARTEMISIA AND CINCHONA. ....................................................................................................18

FIGURE 1.8 CHEMICAL STRUCTURE OF QUININE..........................................................................................19

FIGURE 1.9 CHEMICAL STRUCTURE OF CHLOROQUINE. ...............................................................................20

FIGURE 1.10 CHEMICAL STRUCTURE OF AMODIAQUINE. .............................................................................21

FIGURE 1.11 CHEMICAL STRUCTURE OF MEFLOQUINE. ...............................................................................23

FIGURE 1.12 CHEMICAL STRUCTURE OF LUMEFANTRINE. ...........................................................................24

FIGURE 1.13 CHEMICAL STRUCTURE OF NAPHTHOQUINE. ..........................................................................25

FIGURE 1.14 CHEMICAL STRUCTURE OF PIPERAQUINE. ..............................................................................26

FIGURE 1.15 CHEMICAL STRUCTURES OF SULFADOXINE (LEFT) AND PYRIMETHAMINE (RIGHT)..................26

FIGURE 1.16 CHEMICAL STRUCTURE OF ARTEMISININ (LEFT) AND ITS DERIVATIVES (RIGHT). ....................27

FIGURE 1.17 TARGETS OF ANTI-BACTERIAL DRUGS IN P. FALCIPARUM APICOPLAST....................................29

FIGURE 1.18 CHEMICAL STRUCTURE OF AZITHROMYCIN. ..........................................................................30

FIGURE 1.19 OVERVIEW OF ISOPRENOID BIOSYNTHESIS..............................................................................34

FIGURE 1.20 RIGHT-WARD SHIFT OF CONCENTRATION-EFFECT RELATIONSHIP DUE TO DRUG RESISTANCE. 37

FIGURE 1.21 EMERGENCE OF RESISTANCE TO PRINCIPAL ANTIMALARIAL DRUGS. ......................................39

FIGURE 1.22 REPRESENTATION OF ISOBOLES. .............................................................................................53

FIGURE 2.1 NALGENE DESICCATOR USED FOR P. FALCIPARUM CULTURE.....................................................63

FIGURE 2.2 GIEMSA-STAINED THIN SMEAR OF SYNCHRONISED P. FALCIPARUM CULTURE. ..........................65

FIGURE 2.3 PREPARATION OF A THIN SMEAR...............................................................................................66

FIGURE 2.4 LAYOUT OF A DRUG SUSCEPTIBILITY PANEL. ............................................................................68

FIGURE 2.5 COLOURIMETRIC DETECTION OF PLDH ACTIVITY . ...................................................................70

FIGURE 2.6 PLDH REACTION IN FIELD ISOLATES OF P. FALCIPARUM. ..........................................................71

FIGURE 2.7 TOMTEC HARVESTER 96 SYSTEM. ............................................................................................72

FIGURE 2.8 WOLSTEIN RESEARCH BUILDING, CWRU, CLEVELAND, OHIO, USA. .....................................73

FIGURE 2.9 ELECTROPHORESIS AND IMAGE PROCESSING FOR DNA VISUALISATION FOR EVALUATING PCR

AMPLIFICATION EFFICIENCY. .............................................................................................................76

FIGURE 2.10 BIO-PLEX ARRAY READER. .....................................................................................................80

FIGURE 2.11 SOLID PHASE MICRO-EXTRACTION SAMPLER. .........................................................................81

FIGURE 3.1 CANDLE JAR METHOD USED FOR P. FALCIPARUM CULTURE IN PNG..........................................89

FIGURE 3.2 COMPARISON OF PLDH AND 3H-HYPOXANTHINE INCORPORATION METHODS FOR ANALYSIS OF

xxxii

ANTIMALARIAL SENSITIVITY IN CULTURE -ADAPTED P. FALCIPARUM. ............................................... 92

FIGURE 3.3 EFFECT OF PLDH REACTION TIME ON IC50S IN PNG P. FALCIPARUM. ...................................... 94

FIGURE 3.4 SCATTER PLOT OF IC50S DETERMINED FROM THREE PLDH TIME POINTS.................................. 95

FIGURE 3.5 DISTRIBUTION OF 50% INHIBITORY CONCENTRATIONS (IC50) OF ANTIMALARIALS AGAINST PNG

P. FALCIPARUM ISOLATES.................................................................................................................. 96

FIGURE 4.1 PRINCIPLE OF LDR-FMA DIAGNOSIS OF DRUG RESISTANT POLYMORPHISMS. ....................... 111

FIGURE 4.2 PCR AMPLIFICATION OF PFMDR1 REGIONS 1 AND 2 IN 7G8 OVER A TEMPERATURE GRADIENT.

....................................................................................................................................................... 116

FIGURE 4.3 GEL SCAN OF PCR PRODUCTS GENERATED USING NEW PFMDR1 PRIMERS. ............................ 117

FIGURE 4.4 EFFECT OF PCR CYCLES ON PFMDR1 AMPLIFICATION............................................................ 119

FIGURE 4.5 PREVALENCE OF PFCRT, PFMDR1, PFDHFR, PFDHPS ALLELES IN P. FALCIPARUM-INFECTED

INDIVIDUALS FROM THE MADANG AND EAST SEPIK PROVINCES, PNG. ......................................... 129

FIGURE 4.6 FREQUENCY DISTRIBUTIONS OF PFCRT, PFDHPS, PFDHFR, PFMDR1 HAPLOTYPES IN P.

FALCIPARUM-INFECTED INDIVIDUALS FROM PNG FIELD SITES. ....................................................... 129

FIGURE 5.1 IN VITRO SUSCEPTIBILITY OF LABORATORY STRAINS OF P. FALCIPARUM TO CHLOROQUINE,

DESBUTYL-LUMEFANTRINE AND LUMEFANTRINE. .......................................................................... 145

FIGURE 5.2 ISOBOLOGRAMS ILLUSTRATING INTERACTIONS BETWEEN DESBUTYL-LUMEFANTRINE WITH

CONVENTIONAL ANTIMALARIALS . .................................................................................................. 147

FIGURE 5.3 BOXPLOTS SUMMARISING DAY 7 PLASMA LEVELS OF LUMEFANTRINE AND DESBUTYL-

LUMEFANTRINE. ............................................................................................................................. 149

FIGURE 6.1 IN VITRO SUSCEPTIBILITY OF LABORATORY STRAINS OF P. FALCIPARUM TO CHOLESTEROL-

LOWERING DRUGS AND CHLOROQUINE. .......................................................................................... 163

FIGURE 6.2 INTERACTION BETWEEN ATORVASTATIN AND CONVENTIONAL ANTIMALARIALS . .................. 165

FIGURE 6.3 ATORVASTATIN BIOASSAY. ................................................................................................... 168

FIGURE 6.4 FENOFIBRATE BIOASSAY........................................................................................................ 169

FIGURE 6.5 DISTRIBUTION OF PLASMODIUM BLAST HIT SEQUENCES ON HUMAN PPARΑ. ...................... 172

FIGURE 6.6 DISTRIBUTION OF P. FALCIPARUM BLAST HIT SEQUENCE ON HUMAN ABC-1....................... 173

FIGURE 7.1 EXTRACTION OF VOCS FROM CULTURE SUPERNATANT BY AN ORGANIC SOLVENT................ 182

FIGURE 7.2 PURGE AND TRAP SET-UP FOR THERMAL DESORPTION. .......................................................... 183

FIGURE 7.3 PROTOTYPE 1 CULTURE-CAPTURE APPARATUS WITH SPME.................................................. 185

FIGURE 7.4 DESIGN AND DIMENSIONS OF CULTURE CONTAINER (PROTOTYPE 2) FOR HEADSPACE CAPTURE.

....................................................................................................................................................... 186

FIGURE 7.5 CHROMATOGRAMS OF VOCS IN THE HEADSPACE OF CULTURED P. FALCIPARUM................... 189

CHAPTER 1

GENERAL INTRODUCTION

Chapter 1 General Introduction

2

CHAPTER 1. GENERAL INTRODUCTION

1.1 INTRODUCTION

The term malaria was derived from the Italian words “Mala aria” or bad air, as the

sickness was once thought to be associated with inhalation of foul smelling air near

swampy areas (Harrison 1978). The disease has been recognised for over 4000 years

and has significantly influenced human history (Cox 2002; Rich et al. 2009). Malaria

caused more casualties than those due to bullets during the World Wars and other

military campaigns, with famous victims including Alexander the Great, Genghis Khan,

Ho Chi Minh and George Clooney (MVI 2004; Kakkilaya 2008; News 2011). Malaria

inflicts greater detrimental impacts on the human population than other parasitic

diseases (CDC 2004). Close to 3 billion people are exposed to malaria world-wide, with

the disease accounting for 1 - 2 million deaths per year, most of which are in pregnant

women and children due to their low immunity (Bloland 2001; Snow et al. 2005; WHO

2008).

Five Plasmodium species are known to cause human malaria infections: P. falciparum,

P. vivax, P. malariae, P. ovale and P. knowlesi. The latter species originated from

macaque monkeys in Malaysian Borneo, and has been recently identified in naturally

acquired infections with mortality reported in South-East Asia and in European

travellers (Singh et al. 2004; Cox-Singh et al. 2008; Luchavez et al. 2008). P.

falciparum and P. vivax are the most common but P. falciparum is the most virulent

species. It is capable of invading erythrocytes (RBC) of all ages and RBC containing

mature forms sequester in the microvasculature of vital organs. P. vivax only infects

young RBC and may exhibit relatively weak cytoadherence (Carvalho et al. 2010). P.

falciparum has also developed rapid resistance to antimalarial drugs (Al-Yaman et al.

1996; Dondorp et al. 2009; Preechapornkul et al. 2009) and is responsible for

approximately 500 million cases annually and the highest morbidity of all infectious

diseases (Bloland 2001; Snow et al. 2005; WHO 2009).

The impact of malaria varies with local epidemiology. Developed countries such as

Australia, European countries and North America do not have local transmission apart


3

from occasional autochthonous outbreaks, and virtually all cases are imported. (Gratz

2005; Berry et al. 2008). The most intense transmission occurs in sub-Saharan Africa

and other areas of the rural tropics such as Papua New Guinea (PNG) where young

children with limited immunity are at greatest risk of morbidity and death (Mueller et

al. 2003; Ouellette et al. 2003). Although both preventable and curable, malaria remains

a substantial social and economic burden in tropical regions (WHO 2009).

Mass treatment programs, variable drug compliance and counterfeit antimalarial drugs

have all contributed to widespread parasite drug resistance (White 2004; Newton et al.

2008). In particular, P. falciparum has developed resistance to multiple antimalarial

agents including, most recently, the potent artemisinin derivatives (Wongsrichanalai et

al. 1992a; Bloland 2001; Dondorp et al. 2009). Not only is the arsenal of effective

antimalarial drugs diminishing, our current understanding of their mechanisms of action

is still limited.

The present review outlines the basic epidemiology of falciparum malaria, and the

status of parasite drug resistance and its underlying mechanisms. It examines current

methods employed for the assessment of drug resistance and pharmacological strategies

for limiting its effects and spread, with particular reference to PNG. In addition, several

novel compounds with potential antimalarial properties are reviewed.

1.2 DISEASE DISTRIBUTION

According to a recent report, malaria is present in 109 countries, with the highest

transmission occurring in subtropical and tropical regions in sub-Saharan Africa,

Central and South America, the Middle East, the Indian subcontinent, South-East Asia

and Oceania (Figure 1.1) (WHO 2009). Transmission intensity and risk of infection are

dependent on climatic factors such as temperature, humidity, rainfall, altitude, and the

presence of the Anopheles mosquito vector. Typically, malaria transmission is rare in

the highlands at altitudes above 1500 m and in arid areas with <1,000 mm of rainfall

per year (Bloland 2001). However, these tropical areas suffer greater risks of epidemic

malaria especially with increased movement of people between these areas and

malarious lowlands (John et al. 2005; Mueller et al. 2005). Climatic conditions


4

favourable to vector breeding coupled with the lack of, or low, immunity to malaria

within a local population have led to devastating epidemics with high mortality rates

(Fontaine et al. 1961; Mueller et al. 2005). Malaria intensity is generally higher in

regions adjacent to the equator where transmission is year-round. PNG is no exception,

with 1000-10000 reported cases per year (Figure 1.1). At temperatures below 16°C, P.

falciparum cannot complete a normal growth cycle in the mosquito host and hence

there is no transmission (Teklehaimanot et al. 2004).

Figure 1.1 Distribution of malaria incidence by country. (WHO 2004)

1.3 PLASMODIUM LIFE CYCLE AND BIOLOGY

The malaria parasite has developed an intricate relationship with its mammalian and

insect hosts. The sexual reproduction of the parasite takes place in the mosquito gut

whereas asexual replication occurs within RBC of the human host. Mammalian blood

stage of the P. falciparum life cycle starts with rupture and release of merozoites from

intra-hepatic schizonts into the blood stream (Figure 1.2).


5

Figure 1.2 Life cycle of Plasmodium. (CDC 2006)

1.3.1 Development in the Human Host

As the female Anopheles mosquito probes for a blood meal, P. falciparum sporozoites

are injected with its saliva into the dermis of the host. The sporozoites migrate slowly

out of the inoculation site and penetrate dermal capillaries upon contact to enter the

circulation (Sidjanski et al. 1997; Matsuoka et al. 2002; Yamauchi et al. 2007). A

portion of the sporozoites move through the lymphatics of the host (Amino et al. 2006;

Yamauchi et al. 2007). The sporozoites invade the liver (Shin et al. 1982) and pass

through the endothelial lining of the sinusoids (Figure 1.2-A). Circumsporozoite protein

(CSP) is released to facilitate invasion and exo-erythrocytic development, making it a


6

target for vaccine development (Cohen et al. 2009; Kester et al. 2009).

The asexual reproduction cycle of P. falciparum occurs at 48 hr intervals. It begins with

the release of merozoites from hepatic schizonts into the peripheral circulation (Figure

1.2-B). The merozoite is oval-shaped (1 to 1.5 µm) with a single nucleus and adjacent

cytoplasm. It is equipped with erythrocyte binding antigen (EBA 175), merozoite

surface protein-1 (MSP-1) and other proteins specific for adherence to the RBC

membrane (Camus et al. 1985; Perkins et al. 1988; Sam-Yellowe et al. 1988). During

invasion, the merozoite positions its apical end to form a tight junction with the RBC

membrane. Invasion is rapid, complete in 30 sec, and is facilitated by anterior

organelles such as polar rings, rhoptries and micronemes, and the posterior actin-

myosin network that drives the parasite into its host RBC (Kilejian 1976; Aikawa et al.

1978).

At entry, the outer structures of the merozoite degrade and the parasite rounds up as a

uninuclear trophozoite (Aikawa 1966). The young trophozoite is surrounded by a

parasitophorous vacuole membrane originated from the host cell. A vacuole develops,

forming the characteristic ‘ring stage’ of the malaria parasite. The trophozoite continues

to develop as it digests host cell cytoplasm and haemoglobin. This process however,

produces free haem by-products, the accumulation of which leads to toxicity and

parasite death. To circumvent this, the parasite polymerises the free haem into

haemazoin crystals, which is easily recognised microscopically as the ‘malaria pigment’

within the food vacuole in mature parasites (Dorn et al. 1995). The beginning of

parasitic nuclear division marks the beginning of the schizont stage. During schizogony,

rapid DNA synthesis and nuclear mitosis proceeds as the parasite becomes enlarged and

multinucleated. Mitochondrial budding occurs, and merozoite organelles reappear to

form 15 to 20 new merozoites within each schizont that are subsequently released for

re-invasion (Aikawa 1966).

Gametocytogenesis may take place instead of asexual replication where the merozoite

develops into gametocytes, sex cells that are subdivided into either microgametocyte

(male) or macrogametocyte (female). The events that trigger this process are not well

understood. The gametocyte develops through five morphologically distinctive stages to


7

reach maturity (Hawking et al. 1971; Carter et al. 1979; Ponnudurai et al. 1982). It

features a single unagglomerated nucleus with the male being larger and has a paler

cytoplasm compared to the female gametocyte. It develops as a small rounded globule

to a triangular body taking up half the RBC to ellipsoidal and finally crescentic forms

(Figure 1.2-B7) (Jensen 1979) and is infective to its mosquito host.

1.3.2 Development in the Mosquito

Both sexual and asexual stages of malaria parasites are ingested through the blood meal

by a female Anopheles mosquito (Figure l.2-8). The presence of xanthurenic acid and

the decrease in temperature within the mosquito triggers gamete formation. The

macrogametocyte exits the RBC to form a macrogamete within 10 min, whereas

microgametogenesis is less rapid. Mitotic division begins as the nucleus divides into

eight portions. Each of these portions enters a projection on the surface of the

microgamete and breaks free as an individual microgamete in a process known as

exflagellation (Gao 1981; Aikawa et al. 1984). The microgamete promptly fertilises a

macrogamete forming a zygote (Figure 1.2-9). Within 24 hr of fertilisation, the zygote

develops into a slow moving ookinete (Gao 1981; Aikawa et al. 1984). With structures

similar to the merozoite stage (Garnham et al. 1962) the ookinete invades the microvilli

of the mosquito gut and secretes digestive enzymes to gain entry into the epithelial cell

(Huber et al. 1991). On reaching the cell basal membrane, it develops into a vegetative

oocyst (Figure 1.2-10) (Torii et al. 1992). After 6 days of repeated nuclear division, the

oocyst develops into a polypoid measuring 50 µm containing as many as 10,000

sporozoites (Aikawa 1988).

The motile sporozoite exits the oocyst and travels to the salivary glands of the

mosquito. It contains similar apical organelles as the merozoite stage (Aikawa 1988),

equipped with CSP and the thrombospondin-related anonymous protein (TRAP)

(Rogers et al. 1992) required for sporozoite formation (Menard et al. 1997) and cell

invasion in the mosquito salivary glands and hepatocytes of the human host,

respectively (Sultan et al. 1997). The infectivity of the sporozoite to the human host is

low then increases with residency in the mosquito salivary glands and gradually


8

decreases with age. At the next feeding, sporozoites are injected subcutaneously into the

human host. From the site of inoculation, the sporozoites then migrate through the

circulation to the liver to begin the asexual cycle.

1.4 PATHOLOGY

P. falciparum is responsible for the most severe forms of malaria, causing diverse

clinical and pathological conditions in multiple organ systems. Several parasite factors

contribute to disease severity and manifestations. The predilection of P. falciparum

merozoites for RBC of all ages, augmented by the speed and abundance of schizogony,

makes them efficient in re-invasion. Progeny amplification at every 48 hr intervals

results in the rapid increase of parasite numbers to as many as 1013 per host

(Greenwood et al. 2008). Another distinguishing characteristic of P. falciparum is its

ability to bind to endothelium during the intra-erythrocytic stage of infection (Aikawa et

al. 1980). The sequestration of infected RBC in the microvasculature of organs

including the heart, liver and the brain in cerebral malaria (Sachanonta et al. 2008) can

alter or occlude blood flow and lead to potentially fatal complications (Luse et al.

1971). A number of studies have shown that P. falciparum infected RBC can bind

platelets to form erythrocyte clumps referred to as ‘platelet-mediated clumping’, a

cytoadherence phenomenon distinct from sequestration and rosette formation of

infected RBC, all of which have largely been associated with disease severity (Pain et

al. 2001; Miller et al. 2002; Chotivanich et al. 2004). However, a Malian study

demonstrated that platelet-mediated clumping of P. falciparum infected RBC is

primarily associated with high parasitaemia and not with severe clinical manifestations

of malaria (Arman et al. 2007) and the causality of malarial encephalopathy appears

multifactorial (Coltel et al. 2004; Mackintosh et al. 2004; Clark et al. 2009; Idro et al.

2010). A systemic host response relating to the release of inflammatory cytokines has

been proposed as a primary cause for disease (Clark et al. 2004; Clark et al. 2008). The

cyclic destruction of RBC via schizont rupture can result in anaemia and tissue anoxia.

The absence of reticulocytes during acute infection suggests defective erythropoiesis

which can further aggravate anaemia (Boonpucknavig et al. 1988).


9

Recent views regard the primary pathogenesis of malaria as similar to viral and

bacterial infectious diseases in which, the host’s unbridled response to the invading

organism rather than the organism itself is the cause of disease (Clark et al. 2000; Clark

et al. 2004). The importance of these “cytokine storms” in the pathogenesis of cerebral

malaria has been consistently championed by Clark since the late 1980s (Clark et al.

1987; Clark et al. 2008). Although this concept was criticised initially, it has gained

some support with the recognition that cytokines and immune effector cells may play

pivotal roles in severe malaria (Hunt et al. 2003; Kusi et al. 2008). The release of pro-

inflammatory cytokines such as tumour necrosis factor (TNF) by host cells as triggered

by malaria antigens has been considered a primary factor in the onset of pathology,

especially the pathogenesis of cerebral malaria (Gimenez et al. 2003; Hunt et al. 2003).

Clinical studies in African and PNG children have demonstrated a correlation between

circulating levels of TNF and disease severity as characterised by fever and parasite

density (Butcher et al. 1990; Kwiatkowski 1990a; Al-Yaman et al. 1998; Tchinda et al.

2007). Some clinical observations suggest circulating TNF levels predict death. Serum

levels of TNF were twice as high in cerebral malaria survivors, and up to ten-fold

higher amongst fatal cases compared to those with uncomplicated malaria

(Kwiatkowski et al. 1990b; Al-Yaman et al. 1998). Other evidence in support of the

importance of TNF include the in vivo prevention of the onset of neurological syndrome

in murine models by neutralisation of cytokines (Grau et al. 1987) and the absence of

cerebral malaria in transgenic murine models (Garcia et al. 1995).

The current understanding of severe malaria pathogenesis is that there is no longer a

clear-cut, single pathogenic correlate (Mackintosh et al. 2004; Haldar et al. 2007).

There is likely to be a complex interplay of inflammatory, pro-inflammatory cytokines

and cellular responses. TNF increases the expression of intercellular cell adhesion

molecule-1 (ICAM-1), particularly on brain endothelial cells and on some sequestered,

intravascular leukocytes in human and murine models (Turner et al. 1994). ICAM-1 is a

receptor for P. falciparum infected RBC, and both leukocytes and other parasitised

RBC have the potential to adhere to capillaries when its expression is up-regulated.

Therefore, subsequent blockages may be an outcome secondary to the surge of TNF

from host effector cells. Several findings from murine models have also shown the


10

activation of platelets in contributing to the formation of neurovascular lesions seen in

cerebral cases (Grau et al. 1993a; Grau et al. 1993b). Other cytokines released by

natural killer T cells such as interferon-gamma (IFN-γ) and lymphotoxin (LT) have also

been implicated in driving the immunopathological progression to cerebral malaria

(Amani et al. 2000; Hansen et al. 2003), whilst the anti-inflammatory cytokines

interleukin-10 (IL-10) and transforming growth factor-beta (TGF-β) appear to counter

this process (Ho et al. 1998). In uncomplicated malaria however, pro-inflammatory

cytokines particularly IFN-γ have been associated with a more favourable role, limiting

the progression to severe disease (Torre et al. 2002). The literature on IL-10 is generally

consistent on its host-protective effect by inhibiting the production of cytokines that are

suspected to cause complications of severe and cerebral malaria (Hunt et al. 2003).

However, a recent report indicated that IL-10 may indeed down-regulate pro-

inflammatory responses, but at the same time exacerbate the infection by inhibiting

anti-parasitic immune function. Hugosson et al found high baseline IL-10 levels were

associated with higher parasite densities post treatment after adjusting for initial

parasitaemia, age temperature and sex. The authors concluded that the induction of high

IL-10 production might be a direct or indirect mechanism whereby the parasite evades

host immune response (Hugosson et al. 2004). All in all, severe malaria is not a single

and discrete syndrome as coma develops through multiple pathways with many

mechanisms of brain injury (Idro et al. 2010).

1.5 CLINICAL SIGNS AND SYMPTOMS

The incubation period of malaria varies with the level of host immunity acquired

through prior exposure and the use of antimalarial prophylaxis. In non-immune

individuals, the time of infection to detectable parasitaemia ranges from 5 to 10 days,

and the development of symptoms from 6 to 14 days (Trampuz et al. 2003). Clinical

symptoms are primarily due to the destruction of RBC with the release of merozoites.

The presentation of malaria may be non-specific, often with symptoms resembling

those of a common cold. Infection with P. falciparum can be associated with well-

defined febrile paroxysms, consisting of fever, chills and rigors at regular intervals.

Other symptoms include headache, diaphoresis, nausea, vomiting, dizziness, malaise,

abdominal pain, mild diarrhoea and dry cough. Clinical signs include jaundice, pallor,


11

tachycardia, orthostatic hypotension, hepatomegaly, splenomegaly, metabolic acidosis,

hypoglycaemia, seizures, coma, renal failure and cerebral oedema (Gilles 1988; Clark et

al. 2000; Trampuz et al. 2003; Mackintosh et al. 2004). Figure 1.3 demonstrates a child

infected by P. falciparum who was found to have splenomegaly and fever.

Figure 1.3 Child with malaria. Father comforting his malaria-infected son whilst

waiting outside the Alexishafen Health Care Centre, Madang Province, PNG.

1.6 DIAGNOSIS

Light microscopic examination of intracellular parasites on Giemsa stained thick and

thin blood smears remain the definitive method of diagnosis of malaria (Bloland 2001).

This method enables the quantification and identification of different Plasmodium

species, and the presence of mixed-species infection, diagnosis of which will have a

bearing on treatment selection. Parasite densities are liable to considerable fluctuation

due to the impact of chemo-suppression, development of host immunity, and their

cyclic multiplication patterns. In some instances, infection with P. falciparum may

produce scanty intra-erythrocytic stages with parasitaemia below detectable threshold,

as synchronous mature parasites are sequestered away from the peripheral circulation in

the microvasculature. In these circumstances, the identification of schizonts,


12

gametocytes and malarial pigments in macrophages are of value (Shute 1988).

Before a blood slide is considered negative, at least 200 fields should be examined

under 1000 × magnification. With positive smears, the level of parasitaemia is reported

as a percentage of infected RBC or as the number of parasites per microliter (µL) of

blood. Microscopy diagnosis can be time consuming and requires trained personnel to

ensure consistent reliability. It has relatively low sensitivity compared to other

techniques, especially when parasitaemia is low and in areas of unstable, low

transmission (John et al. 2005; Coleman et al. 2006; Menge et al. 2008). Whilst the

availability of microscopy has been shown to reduce drug use in trial settings, in

practice blood film results are often disregarded by clinicians as presumptive clinical

diagnosis is customary and a cost saving approach in malaria endemic areas (Jonkman

1995; Barat et al. 1999; PNGDOH 2000).

Alternative diagnostic methods include rapid dipstick immunochromatographic assays

that detect species-specific parasite antigens targeting either histidine-rich protein-2

(HRP-2) by, for example, the Parasight®F test or Plasmodium lactate dehydrogenase

(pLDH) by the OptiMAL® test (Schiff et al. 1993; Makler et al. 1998). However,

persistence of the HRP-2 antigen in the circulation after parasite clearance can give rise

to false positives (Makler et al. 1998). The first generation of OptiMAL® tests were

prone to loss of sensitivity caused by humidity and high temperature. However, this

instability has been overcome in the second generation OptiMAL IT® tests (Moody et

al. 2002). Occasional cases of false-positive results for P. falciparum were observed in

samples containing high levels of heterophile antibodies (Moody et al. 2002). One field

evaluation of the OptiMAL® test showed 96% sensitivity, 100% specificity and with

100% and 97.5% positive and negative predictive values respectively compared to

conventional microscopy. However sensitivity decreased when parasitaemia was <300

parasites/µL whole blood (Zerpa et al. 2008). Although dipsticks tests may enhance the

speed of diagnosis, microscopy remains the most cost-effective diagnostic method in

malaria endemic areas.

The use of polymerase chain reaction (PCR) based assays for the detection of species-

specific Plasmodium genome is highly specific and sensitive, with a detection limit as


13

low as 1 parasite/µL (Hanscheid et al. 2002). However, in addition to the cost of

reagents, this method requires a stable electricity supply and sophisticated equipment

that is often not available in field settings. PCR methods are more useful in

epidemiological studies and for the diagnosis of imported malaria in developed

countries (Berry et al. 2008; Menge et al. 2008).

1.7 TRANSMISSION

Malaria parasites are transmitted through the bite of infected female Anopheles

mosquitoes (Figure 1.4). On taking a blood meal as a requirement by the mosquito for

ovulation, malarial sporozoites harboured in the salivary glands of the insect are

inoculated into the capillary of the human host. At the same time, gametocytes from the

human host can be transferred into the mosquito to continue the sexual phase of its life

cycle (Section 1.3) (Garnham 1988). In this way, infected populations of both human

and Anopheles mosquitoes function as reservoirs for each other. Transmission can also

occur congenitally by transplacental transfer of infected RBC into the neonate, and

malaria in pregnancy contributes to a significant number of maternal and infant deaths

(Malhotra et al. 2006; Brabin 2007).

Figure 1.4 Anopheles albimanus taking a blood meal. (Cook et al. 2006)


14

1.8 PREVENTION

In malaria endemic areas, the use of insect repellent and clothing that provides covering

are important measures to reduce the chance of mosquito biting. Anopheles generally

feeds in the evening, hence staying indoors and sleeping within insecticide-treated bed

nets are effective night-time preventive measures. The use of chemoprophylaxis is also

recommended for travellers to malaria endemic areas. Other community based

interventions include indoor residual spraying of insecticides, reducing mosquito

breeding sites such as stagnant water and improving drainage. Significant challenges in

mosquito control include increasing resistance to key insecticides such as DDT and

pyrethroids with the development of new pesticides proving costly and time consuming

(WHO 2009).

1.9 TREATMENT

The best treatment currently recommended for P. falciparum infection is artemisinin-

based combination therapy (ACT). Examples of ACTs include artemether-lumefantrine

(Coartem®), artesunate-SP, dihydroartemisinin-piperaquine (Duo-Cotecxin®) and

artemisinin-naphthoquine (ARCO®). However, the spread of parasite resistance is

undermining malaria control efforts and there are no effective alternatives to

artemisinins currently on the market or near completion of the drug development

process (WHO 2009). Recent clinical and molecular studies from the Cambodia-

Thailand border where artesunate-mefloquine is the standard treatment regimen suggest

the emergence of ACT-resistant parasite strains (Denis et al. 2006; Vijaykadga et al.

2006; Alker et al. 2007). The reported treatment failures were considered most likely

due to the high level of mefloquine resistance rather than to the artemisinin component,

as mefloquine was used for monotherapy long before the introduction of ACTs.

Molecular findings of increased pfmdr1 copy number in local P. falciparum isolates

attested to mefloquine resistant in conjunction with the loss of sensitivity in vivo (Price

et al. 2004; Wongsrichanalai and Meshnick 2008; Chaijaroenkul et al. 2010). However,

recent studies have also suggested that initial parasite clearance, the hallmark of

artemisinin efficacy, is delayed in this area. This suggests that resistance to this

valuable group of antimalarial drugs has now started to develop (Dondorp et al. 2010).


15

1.10 MALARIA IN WESTERN PACIFIC

Ten of the thirty-seven Western Pacific countries are malaria endemic; China,

Philippines, Cambodia, Korea, Malaysia, Laos Peoples Democratic Republic, Viet

Nam, PNG, Solomon Islands and Vanuatu, accounting for 340,000 cases per year.

Recent statistics showed a substantial reduction in malaria cases and mortality from

760,000 cases in 1990 to half this figure in 2005. However, malaria still claims many

lives in the Pacific region (Figure 1.5). PNG has the highest mortality within the Pacific

region where the up-scaling of vector control has been sluggish (WHO and WPRO

2007).

Figure 1.5 Malaria mortality in Western Pacific. Malaria mortality rate (per 100,000

population) in selected countries in the Western Pacific Region, 1994-2007 (WHO

2009).


16

1.11 EMERGENCE OF ANTIMALARIAL RESISTANCE IN

PAPUA NEW GUINEA

Similar to the situation in Africa, young children in PNG carry the major disease burden

due to their lack of immunity (Michon et al. 2007). In the 1970s, reports from a

missionary station in Milne Bay (Figure 1.6) described cases of P. falciparum infection

that apparently did not respond to chloroquine (CQ) treatment. A cascade of in vivo

trials soon followed (Saint-Yves 1971; Han et al. 1976). Investigations conducted in

Maprik and Popondetta reported on the retained effectiveness of CQ. These studies

however, encountered immense difficulties with patient recruitment as only a small

number (22 of 1000) of children screened were eligible, all of whom were aged 7 to 12

years old, and thus probably semi-immune. The early Maprik and Popondetta findings

may not therefore, have reflected true resistance, especially when younger children are

found to harbour resistant parasites (Michon et al. 2007).

Figure 1.6 Regions and provinces of Papua New Guinea. ENB = East New Britain,

WNB = West New Britain , EH = Eastern Highlands, SH = Southern Highlands, WH =

Western Highlands.


17

Not long after the initial alert from Milne Bay, two cases of CQ treatment failure in

non-immune expatriates were confirmed in Port Moresby, the capital city of PNG. Both

patients had travelled to the Kiunga area of the Western Province. Six patients from the

same region who used CQ as a prophylaxis also suffered malaria that did not respond to

standard treatment (Grimmond et al. 1976). Subsequent studies confirmed the presence

of CQ-resistant P. falciparum particularly along the border with Indonesia and nearby

provinces in the Northern coast of PNG (Han 1978). The appearance of CQ-resistant P.

falciparum coincided with the decreased effectiveness of residual insecticide spraying

initiated in the 1950s which further exacerbated the spread of resistant parasites

(Colbourne et al. 1970). Three decades on, resistance to other 4-aminoquinolines

particularly amodiaquine (AQ) and quinine have been reported under vigilant in vivo

and in vitro surveillance (Schuurkamp and Kereu 1989; Trenholme et al. 1993; al-

Yaman et al. 1996; Marfurt et al. 2007). The rapid spread of resistant P. falciparum

across the provinces of PNG has been documented in clinical (Darlow et al. 1982;

Sapak et al. 1991; Genton et al. 2005; Marfurt et al. 2007) and in vitro studies

(summarised in Chapter 3).

In addition to a long history of monotherapy, mass dosing of pyrimethamine during the

era of malaria control/eradication has ensured constant drug pressure on the parasite

population thus selecting for resistance. A high level of resistance has been documented

in numerous in vivo (Schuurkamp and Kereu 1989; Karunajeewa et al. 2008; Darlow et

al. 1980) and in vitro studies (Reeder et al. 1996; Hombhanje 1998). In 2000, PNG

health authorities replaced CQ monotherapy with sulfadoxine-pyrimethamine (SP)

combination therapy as first-line treatment to improve clinical efficacy (Nsanzabana et

al. 2010) and to delay the development of drug resistance (Casey et al. 2004; Genton et

al. 2005). The year 2011 marked the beginning of another era in antimalarial drug usage

as PNG implemented artemether-lumefantrine as first-line treatment (Mueller, 2010,

personal communication).


18

1.12 ANTIMALARIAL CHEMOTHERAPY

Quinine and artemisinin derivatives are, respectively, the most employed and most

active antimalarial compounds, both of which have a long history as ancient herbal

therapies. The famous sweet wormwood (Artemisia Annua) also known as Qinghaosu

(Figure 1.7) was recorded as early as 200 BC in a Chinese medical treatise; the “Fifty-

two Prescriptions” discovered in the Mawangdui Tomb of the Hunan Province. The

antimalarial application of Qinghaosu was also documented in "The Handbook of

Prescriptions for Emergencies" by Ge Hong in the 4th century. In other parts of the

world, Cinchona tree bark had been used by indigenous South American tribes for its

antipyretic properties. The use of Cinchona bark (Figure 1.7) for treating fever was

subsequently popularised by the 17th century Spanish Jesuit missionaries (Lee 2002).

Both natural sources served as prototypes of the potent antimalarials available today.

Despite tremendous resources devoted to the search for antimalarial drugs, only a

handful of compounds have been discovered. Despite extensive research, our

understanding of the molecular basis of antimalarial activity remains incomplete. The

following section outlines the history of current antimalarials, their proposed

mechanism of action and the development of drug resistance.

Figure 1.7 Artemisia and Cinchona. Artemisia annua (left) (NomadRSI 2002).

Cinchona bark (right) (KEW 2007).


19

1.12.1 Quinoline Related Compounds

1.12.1.1 Quinine

Figure 1.8 Chemical structure of quinine. (O'Neill et al. 2006)

Quinine (Figure 1.8), derived from the bark of the Cinchona tree, was first employed as

an effective malaria treatment in South America in the 17th century. This alkaloid

compound was isolated in the early 1800s by Portuguese chemists and its synthesis was

described in 1944 (Turner et al. 1953). Under political and military influences,

Cinchona plantations outside Peru were established. The demand for quinine intensified

with the advent of World Wars I and II, as supplies were inadequate and unstable. The

associated neurotoxicity and other side-effects have provided an impetus to research

synthetic alternatives. The availability of better tolerated drugs such as CQ has reduced

its usage and slowed the development of widespread resistance to this drug

(Wongsrichanalai et al. 1992b).

Quinine is by far the most commonly used treatment for severe malaria in the world,

being the standard treatment for severe disease across Africa and other malaria endemic

regions (WHO 2000; Sinclair et al. 2011), however recent findings suggest that this is

likely to change in favour of artesunate (Checkley and Whitty, 2007; Dondorp et al.

2005; Dondorp and Day, 2007; Dondorp et al. 2010). Quinine is used with SP as a

second-line regimen for uncomplicated malaria and for the treatment of severe malaria

in PNG (Genton et al. 2005). Quinine has remained increasingly important for the

treatment of CQ-resistant P. falciparum in other parts of the world, particularly for


20

treatment during pregnancy (SANDH 2007; Chico et al. 2010).

1.12.1.2 Chloroquine

Figure 1.9 Chemical structure of chloroquine. (O'Neill et al. 2006)

Originally known as Resochin, CQ (Figure 1.9) was first synthesised in Germany and

thought to be too toxic for further development. After World War II, re-evaluation

proved its clinical safety, high efficacy and low toxicity (Loeb et al. 1946). CQ has

since been used extensively, and has been the drug of choice for uncomplicated malaria

and chemoprophylaxis. In 1950s to 1960s, the WHO devised population-based dosing

regimens for the Global Eradication Programme in which over 84,000 tons of CQ was

supplied to Brazil, parts of Africa and Asia for incorporation in table salt as means of

chemoprophylaxis (Greenwood et al. 2008). Resistant P. falciparum emerged rapidly

and has since spread to many endemic areas of the world, compromising its usefulness

(Peters 1987; Fidock et al. 2004). In spite of this, CQ is still employed as first-line

treatment in PNG in combination with SP for the treatment of uncomplicated malaria

during pregnancy (Casey et al. 2004; Mueller et al. 2008) despite increasing evidence

for the loss of effectiveness (Marfurt et al. 2007; Karunajeewa et al. 2008). Although

generally perceived to have “timed out”, CQ remains effective in some parts of the

world. A study has shown that P. falciparum isolates from Malawi have regained their

sensitivity to CQ a decade after its withdrawal (Laufer et al. 2006; Nkhoma et al. 2007).

A similar trend to reduction in resistance to CQ was also evident in Kilifi, a coastal

town in Kenya, following its official withdrawal, although at a much slower rate (Mwai

et al. 2009a). Recent microsatellite analyses of resurgent CQ-susceptible parasites

revealed they are likely to be a re-expansion of pre-existing CQ-sensitive population,


21

rather than a reverse mutation in a previously resistant parasite or a new selective sweep

(Laufer et al. 2010).

Extensive research has been devoted into elucidating CQ’s mechanism of action. Early

studies suggested the inhibition of DNA replication and RNA synthesis, albeit at rather

high concentrations (Allison et al. 1965; Thelu et al. 1994). Subsequent characterisation

of enzymes involved in DNA replication proved that they are unlikely targets of CQ

(Chavalitshewinkoon et al. 1993; White et al. 1993). To date, it is widely accepted that

CQ acts within the parasite food vacuole and exerts its antiplasmodial effect by

interfering with detoxification (Pagola et al. 2000; Ursos et al. 2002; Fidock et al.

2004). In uninfected RBC, the uptake of CQ is minimal (Macomber et al. 1966). In

parasitised RBC, its accumulation is several thousand-fold higher, localising within the

parasite food vacuole perhaps reflecting ion-trapping due to its dibasic nature

(Macomber et al. 1966; Aikawa 1972; Ginsburg et al. 1989; Hawley et al. 1996). As

the parasite digests haemoglobin, free haem (ferriprotoporphyrin IX) and reactive

oxygen species are produced as toxic by-products. To counter this, the parasite

polymerises the toxic haem into non-toxic haemazoin crystals (Figure 2.2) (Blauer et al.

1997). CQ acts by binding to these free haem moieties, thus interfering with

detoxification where toxic by-products accumulate, leading to parasite death (Fitch

1998; Foley et al. 1998; Pagola et al. 2000; Fidock et al. 2004).

1.12.1.3 Amodiaquine

Figure 1.10 Chemical structure of amodiaquine. (O'Neill et al. 2006)


22

During World War II, the US government invested in a massive screening program

involving 300,000 compounds, and in 1955, AQ (Figure 1.10) was identified as one of

three compounds that were active against P. falciparum (Peters 1987).

AQ served as an alternative prophylaxis for falciparum malaria for over 40 years (Foley

et al. 1998). However, support for its prophylactic use was withdrawn by the WHO

after reports of fatal adverse reactions in the mid 1980s, and associated high incidence

of hepatitis and agranulocytosis (Greenwood 1995). However, the rapid spread of CQ

resistance has prompted the re-evaluation of AQ for therapeutic use. A subsequent

systematic review of AQ treatment in uncomplicated malaria found the rates of adverse

events were no higher than that of CQ and SP treatments in controlled trials, without

life-threatening events (Olliaro et al. 1996). In vitro studies have shown AQ to be more

potent than CQ against less susceptible strains of P. falciparum (Rieckmann 1971;

Siddiqui et al. 1972). Despite this, clinical resistance to AQ soon followed and AQ

monotherapy is not recommended (Al-Yaman et al. 1996). AQ has found its use as

first-line treatment and as seasonal intermittent preventative treatment for malaria as

part of ACT regimens (Adjei et al. 2008; Sokhna et al. 2008). AQ (Camoquine) has

been used as first-line treatment with SP, but more recently in combination with

artesunate for young children in PNG and Africa (PNGDOH 2000; Brasseur 2007;

Marfurt et al. 2007).

AQ and its active metabolite monodesethyl-AQ share structural similarity with CQ and

partial cross resistance has been reported (Basco and Ringwald 2003; Wong et al 2010).

AQ competitively inhibits CQ accumulation in the parasitic food vacuole (Fitch 1973).

As a diprotic weak base with lower pKa values compared to CQ, it may accumulate less

efficiently in the parasite food vacuole via ion-trapping. However, AQ is found in

higher concentrations than CQ in the parasite, indicative of enhanced uptake by an

additional pathway (Hawley et al. 1996). Several studies have demonstrated the ability

of AQ to bind to haem and inhibit haem polymerisation, analogous to CQ (Chou et al.

1993).


23

1.12.1.4 Mefloquine

Figure 1.11 Chemical structure of mefloquine. (O’Neill et al. 2006)

Mefloquine (MQ) (Figure 1.11) was also selected from a screening program and

developed through global collaborative efforts. A distinguishing property of MQ is its

long terminal elimination half-life of 2 to 3 weeks, hence it can achieve clinical efficacy

with a single dose. It is well tolerated by adults and children. Common side-effects

include nausea, dizziness, headache, rash, pruritis, in some instances bradycardia and

the well publicised psychiatric disturbances (Palmer et al. 1993). It was first deployed

in Thailand in 1984, initially in combination with SP, but resistance developed

relatively quickly. It has been more recently incorporated with artesunate as part of

ACT. The relative high cost of MQ in addition to concerns regarding toxicity limits its

use in many resource-poor malaria endemic countries.


24

1.12.1.5 Lumefantrine

Figure 1.12 Chemical structure of lumefantrine. (Basco et al. 1998)

Formerly known as benflumetol, lumefantrine is a 2, 3 benzindene that belongs to the

amino-alcohol class that also includes quinine, mefloquine and halofantrine (WHO

2006) (Figure 1.12). The compound was first synthesised in China and has high clinical

efficacy against multidrug resistant P. falciparum as a co-formulation with artemether

(Coartem®) (WHO 2006; Karunajeewa et al. 2008b). The oral formulation is

efficacious for the treatment of children with uncomplicated malaria and drug-related

adverse events are rare (Adjei et al. 2008; Karunajeewa et al. 2008b). Bioavailability of

lumefantrine is variable and its absorption is significantly increased when administrated

with fatty foods (Ezzet et al. 1998; White et al. 1999; Borrmann et al. 2010).

Lumefantrine-artemether is the current first-line treatment for uncomplicated malaria in

Africa (Kabanywanyi et al. 2007; Borrmann et al. 2010) and PNG (WHO 2007;

Schoepflin et al. 2010).


25

1.12.1.6 Naphthoquine

Figure 1.13 Chemical Structure of Naphthoquine. (Wang et al. 2004)

Naphthoquine (NQ) (Figure 1.13) is a relatively new drug first registered in 1993 in

China. This drug exhibits potent schizontocidal effects in CQ-resistant parasites.

Clinical studies of NQ monotherapy carried out on Hainan Island, China reported 100%

and 96.7% cure rate that compared favourably with artemisinin monotherapy which had

a cure rate of 73.3% (Pang et al. 1999; Guo et al. 2000). No distinctive adverse

reactions have been associated with NQ use, although transient abdominal discomfort

has been reported in some patients. Elimination half-life of NQ ranges from 41 hr to

255 hr (Wang et al. 2004; Qu et al. 2010). The long half-life of NQ makes it a suitable

partner with artemisinin in the relatively new ARCOTM therapy that is undergoing

safety and efficacy trials in PNG (Hombhanje et al. 2009; Davis, unpublished). Parasite

susceptibility data outside of Chinese literature are limited, with only one study

performed in PNG field isolates (Wong et al. 2010), the findings of which will be

discussed in subsequent chapters.


26

1.12.1.7 Piperaquine

Figure 1.14 Chemical Structure of Piperaquine. (Davis et al. 2005)

Piperaquine (PQ) (Figure 1.14) is a bisquinoline compound first synthesised from

screening programs in France and China during the 1960s. It was thought to offer little

advantage over CQ and hence development was not pursued except in China. PQ was

developed for clinical use and was the drug of choice in China and Indochina for two

decades until the emergence of resistance (Chen 1991; Fan et al. 1998). In the 1990s,

renewed interest has seen PQ as a long half-life partner in ACTs. Examples include

CV8® (PQ-dihydroartemisinin-trimethoprim-primaquine), Artecom® (PQ-primaquine)

and more recently Artekin® or Duo-Cotecxin® (PQ-dihydroartemisinin), the latter

producing high cure rates and tolerability in areas of CQ-resistant P. falciparum (WHO

2006; Karunajeewa et al. 2008b). A recent in vitro study from Cameroon has also

shown PQ to be highly active against both CQ sensitive and resistant strains of P.

falciparum isolates (Basco and Ringwald 2003) with a long elimination half-life of 33

days (Tarning et al. 2005).

1.12.2 Antifolate Combination Drugs

Figure 1.15 Chemical structures of sulfadoxine (left) and pyrimethamine (right).

(WHO 2006)


27

Antifolate combinations comprise of inhibitors of Plasmodium dihydrofolate reductase

(dhfr) and dihydropteroate synthase (dhps), both of which are involved in parasite DNA

synthesis. Examples of pfdhfr inhibitors include pyrimethamine (Figure 1.15),

proguanil, chlorproguanil, and trimethoprim. Sulfa drugs that inhibit pfdhps include

sulfadoxine (Figure 1.15), dapsone, sulfalene and sulfamethoxazole. Genetic mutations

in parasite pfdhfr and pfdhps genes confer rapid resistance against these drugs,

particularly when used alone. When used in combination however, these drugs produce

a synergistic effect where they are effective even in the presence of parasite resistance

to individual components. Common antifolate combinations include SP, which is useful

in pregnant women for placental malaria, sulfamethoxazole-trimethoprim (co-

trimoxazole), sulfalene-pyrimethamine (metakelfin) and a more recent combination of

dapsone-chlorproguanil (LapDap) that is more affordable and provides higher cure rates

(Watkins et al. 1997) but which has now been withdrawn because of adverse effects

(haemolytic anaemia) in patients with glucose-6-phosphate dehydrogenase deficiency

(Bukirwa et al. 2004; Fanello et al. 2008).

1.12.3 Artemisinin and its Derivatives

Figure 1.16 Chemical structure of artemisinin (left) and its derivatives (right).

Artemether (R = OCH3); Artesunate (R = OCH2CH2CO2Na); Dihydroartemisinin (R =

OH).

Artemisinin and its derivatives (Figure 1.16) are frontline antimalarial treatments that

facilitate rapid parasitaemia clearance and prompt resolution of symptoms. Artemisinin

is a sesquiterpine lactone isolated from the plant Artemisia annua or Qinghaosu (Figure

1.7) which has been used for thousands of years by Chinese herbalists for curing febrile


28

illnesses. Qinghaosu was re-discovered in 1972 from a mass screening project of

traditional medicinal herbs funded by the Chinese military (Tu You-you 1982; Zhang

2007). Artemisinin and its derivatives are the most potent antimalarials to date,

characterised by a rapid clearance of parasitaemia (Skinner et al. 1996). These have

proven to be efficacious and well tolerated as monotherapy although these are not

recommended to be used alone due to their short half-lives with associated high rates of

recrudescence related to rapid elimination. Examples of semi-synthetic artemisinin

derivatives include artemether and artesunate.

Since artemisinin and its derivatives are rapidly eliminated from the body and long

courses are required for high long-term cure rates, greater efficacy can be obtained by

partnering these potent but short-lived compounds with those with a longer half-life

such as in lumefantrine, MQ or AQ as ACTs. These strategies are now recommended in

Africa and PNG to delay the development of resistance (WHO 2006; Ekland et al.

2008; O'Neill et al. 2010). These regimens include artemisinin-NQ (Wang et al. 2004),

artesunate-AQ and artemether-lumefantrine (Adjei et al. 2008).

Dihydroartemisinin (DHA) is an active metabolite of artemether and artesunate. In

comparison to other derivatives, in vitro studies have shown DHA to act on all stages of

intra-erythrocytic P. falciparum, and is the most potent in achieving 100% inhibition

within 2 to 4 hr of exposure (Skinner et al. 1996).

1.12.4 Antibiotics

Several antibiotics are currently in use as prophylaxis and in combinations with other

antimalarials as treatment for uncomplicated P. falciparum infections (Nakornchai et al.

2006; Ejaz et al. 2007; Noedl et al. 2007). However, the exact mechanism and cellular

effects of these parasiticidal anti-bacterial drugs remain largely unknown. As with other

apicomplexa parasites such as Babesia spp, Toxoplasma gondii and Cyclospora

cayetanensis, Plasmodium species have an apicoplast similar to the plastid structure

found in algae and bacteria. This organelle is non-photosynthetic but contains essential

house-keeping machineries for DNA replication, transcription, translation and post-

translational modification, and various anabolic pathways (Goodman et al. 2007).


29

Recent identification and characterisation of this unique apicomplexan structure has

revealed a number of putative targets with the potential to help explain the mysterious

activities of antibiotics against malaria (McFadden et al. 1996; Wilson et al. 1996;

Goodman et al. 2007b). The absence of a similar structure in mammalian cells renders

the Plasmodium apicoplast a valuable drug target.

A number of antibiotics have been shown to target the prokaryotic 70S ribosome in

Plasmodium apicoplast thus affecting protein synthesis (Figure 1.17). Examples include

azithromycin (AZ), clindamycin, tetracycline, doxycycline and thiostrepton. The

macrolides (AZ, clindamycin) block the peptide exit tunnel, preventing peptide

elongation, lincosamides (clindamycin) and tetracyclines interfere with the

translocation and binding of peptidyl tRNAs to the acceptor site, respectively

(Auerbach et al. 2002).

Figure 1.17 Targets of anti-bacterial drugs in P. falciparum apicoplast. Anti-

bacterial drugs targeting the “house-keeping” functions of the P. falciparum apicoplast.

(Modified and adapted from Goodman and McFadden, 2007)

An interesting phenomenon with antibiotics observed in apicomplexan parasite is the

delayed-death effect, where the drug has no apparent effect on the parasite as it

continues to grow and divide and its daughter cells re-invade a new host. It is not until

the second generation where the progenies fail to develop and eventually die (Fichera et


30

al. 1995; Fichera et al. 1997). Various studies have shown the significant reduction of

IC50 values when in vitro antibiotic drug trials against P. falciparum were extended

from 48 hr to 96 hr (Yeo et al. 1995; Goodman et al. 2007b). It was hypothesised that

drugs targeting prokaryote-like translation, as those mentioned previously, would

produce this effect. Antibiotics that target DNA replication, transcription and interfere

with fatty acid and isoprenoid pathways such as fosmidomycin and triclosan, cause

immediate parasite death within the first intra-erythrocytic cycle (Jomaa et al. 1999;

Goodman et al. 2007a; Wiesner et al. 2008).

1.12.4.1 Azithromycin

Figure 1.18 Chemical Structure of Azithromycin.

Azithromycin (AZ) (Figure 1.18) is a broad spectrum macrolide derived from

erythromycin with more favourable pharmacokinetics and longer elimination half-life

(Girard et al. 1987). It is used clinically for the treatment of streptococcal,

staphylococcal, chlamydial and gonorrhoeal infections. Since the discovery of AZ’s

activity against CQ-resistant P. falciparum (Gingras et al. 1992; Gingras et al. 1993),

this drug has been studied with renewed interest in the campaign against multidrug

resistant malaria. Only recently has its mode of action been elucidated. According to

this report, AZ binds to the 50S ribosomal subunit in the apicoplast translation

machinery, interfering with protein synthesis and subsequently leads to a classic

delayed-death (Sidhu et al. 2007).

Despite its slow onset and considerably lower potency compared to other antimalarials

(Noedl et al. 2001; Noedl et al. 2007; Wong et al. 2010), the safety profile in young


31

children and extensive experience with its use during pregnancy (Bace et al. 1999;

Arrieta et al. 2003; Sarkar et al. 2006) render it an attractive candidate to partner with

fast-acting conventional antimalarials. An earlier study with AZ-artesunate combination

in Thai adults with uncomplicated falciparum malaria resulted in an unexpectedly low

cure rate (Na-Bangchang et al. 1996). This was likely due to inadequate AZ dosage.

With a higher dose, a phase 2 clinical trial demonstrated the safe and efficacious use of

AZ-quinine and AZ-artesunate (Noedl et al. 2006).

1.12.5 Summary of Antimalarial Activities

The following table provides a list of common antimalarial drugs and their specific

activities (Table 1.1).


32

Table 1.1 Antimalarial drugs and their specific activities. (WHO 2006)

Drug Class Compound Specific Activities 4-Aminoquinoline Chloroquine

Amodiaquine Naphthoquine

Blood schizontocides Interference of haem detoxification in parasite

food vacuole

8-Aminoquinoline Primaquine Tafenoquine

Intra-hepatic schizontocides Gametocytocides

Bis-quinoline Piperaquine Blood schizontocides

Arylaminoalcohol Quinine/Quinidine Mefloquine Halofantrine Lumefantrine

Mature trophozoites Blood schizontocides

Early stage gametocytocides

Antifolates Sulfadoxine Sulfamethoxazole

Dapsone Pyrimethamine

Proguanil Chlorproguanil Trimethoprim

Inhibitors of dihydropteroate synthase Inhibitors of dihydrofolate reductase

Slow-acting blood schizontocide Sporontocide

Possible activity against intra-hepatic forms

Artemisinin Artemisinin Artesunate

Dihydroartemisinin Arteether

Artemether

Fast-acting blood schizontocides Gametocytocides,

Inhibitors of calcium adenosine triphosphatase

Antibiotics Azithromycin Clindamycin Doxycycline Tetracycline

Ciprofloxacin Rifampicin

Thiostrepton

Slow-acting blood schizontocides Inhibitors of aminoacyl-tRNA binding during

protein synthesis

Naphthoquinones Atorvaquone Inhibits intra-hepatic forms Inhibits oocyte development in the mosquito

Interferes cytochrome electron transport


33

1.13 LIPID-LOWERING AGENTS AS ANTIMALARIALS

Recent interest in alternative antimalarial drugs led to the discovery of P-glycoprotein,

an efflux transporter encoded by the multidrug resistant gene which actively removes

compounds from cells and prevents intracellular drug accumulation. Interestingly,

certain statins and fibrates have been shown to interact with P-glycoprotein in

mammalian cells expressing multidrug resistance (Wu et al. 2000; Ehrhardt et al.

2004). Although a P-glycoprotein homologue 1 has been identified in P. falciparum,

studies investigating the antimalarial activity of these lipid-lowering agents are limited.

1.13.1 Statins

Statins are cholesterol-lowering drugs that are considered first-line therapies for

reducing morbidity and mortality associated with atherosclerotic disease (Grundy et al.

2004; Wilt et al. 2004; Thavendiranathan et al. 2006). They are inhibitors of 3-hydroxy-

methyl-glutaryl coenzyme A (HMG-coA) reductase that decreases cholesterol synthesis

and plasma cholesterol and lipoprotein levels (Figure 1.19) (Maron et al. 2000).

Examples include atorvastatin (Lipitor®), rosuvastatin (Crestor®), pravastatin

(Pravacol®) and simvastatin (Zocor®). Despite a common mechanism of action, statins

differ in their chemical structures, pharmacokinetic profiles and lipid-modifying

efficacy. Pravastatin and simvastatin are derived from fungal metabolites and have

elimination half-lives of 1 to 3 hr. Atorvastatin and rosuvastatin are both synthetic

compounds, with elimination half-lives of 14 hr and 19 hr respectively. Rosuvastatin

(Crestor®) is a recently developed drug with the most potent LDL-cholesterol-lowering

properties, followed by atorvastatin, simvastatin and pravastatin (Soran et al. 2008).

In addition to their cholesterol-lowering efficacy and good clinical safety profile (Cilla

et al. 1996; Bellosta 2004), statins exhibit a wide range of antimicrobial activities

against bacteria, yeasts and protozoan including P. falciparum (Montalvetti 2000; Song

et al. 2003; Catron et al. 2004; Pradines et al. 2007; Wong et al. 2009). Atorvastatin

and lovastatin reduced the growth of Salmonella enterica in mouse model and in

cultured macrophages (Catron et al. 2004). They acted synergistically with fluconazole

to inhibit the eukaryotic sterol pathway, as demonstrated by the reduced growth of


34

Candida albicans after exposure (Song et al. 2003). In addition, they reduced the

growth of Schistosoma mansoni, Trypanosoma cruzi and Leishmania species through

inhibition of 3HMG-CoA reductase (Chen et al. 1990; Urbina 1993; Andersson et al.

1996; Montalvetti 2000).

Figure 1.19 Overview of isoprenoid biosynthesis. In humans, the biosynthesis of

isopenteny-diphosphate and dimethylallyl-diphosphate and ultimately cholesterol

proceeds entirely via the mevanlonate pathway. In Plasmodium, these isoprenoid

building blocks are supplied by the 1-deoxy-D-xylulose-5-phosphate/2-C-methyl-

erythritol 4-phosphate (DOXP/MEP) pathway. Statins inhibit the mevalonate pathway

as indicated (Moreno et al. 2008).


35

The antimalarial effects of statins have also been described. Lovastatin and simvastatin

inhibited intra-erythrocytic development of P. falciparum in vitro (Grellier et al. 1994).

In other recent studies, atorvastatin exhibited high in vitro activity against P. falciparum

(Pradines et al. 2007; Parquet et al. 2009; Wong et al. 2009). Despite these encouraging

findings, neither simvastatin nor atorvastatin given in high doses improved outcome in

P. berghei-infected mice (Bienvenu et al. 2008; Kobbe et al. 2008) and there was no

effect on parasitaemia (Bienvenu et al. 2008). No study to date has included the most

potent statin in clinical use, rosuvastatin (Soran et al. 2008). In addition, despite

demonstration of in vitro synergy between mevastatin and the P-glycoprotein inhibitor

tunicamycin against P. falciparum (Naik 2001), the interaction between statins and

conventional antimalarial drugs has not been assessed.

1.13.2 Fibrates

While statins decrease cholesterol synthesis, fibrates primarily intensify catabolism of

triglyceride-rich lipoproteins and increase HDL-cholesterol. Gemfibrozil, fenofibrate,

clofibrate are examples of fibrates in clinical use. The fibrates are agonists of

peroxisome proliferator-activated receptor alpha (PPARα). Fenofibrate has also been

shown to inhibit P-glycoprotein mediated transport with a similar potency to

simvastatin (Ehrhardt et al. 2004) and modulate the expression of the lipid-efflux

protein, ATP-binding cassette sub-family A member (ABC-1) (Arakawa et al. 2005).

If malaria pathology is attributable to systemic inflammation (Clark et al. 2008), the use

of fibrates to hinder the release of inflammatory cytokines may constitute a novel

treatment approach. A number of studies have investigated the anti-inflammatory

effects of fibrates. Gemfibrozil reduced TNF production in monocytes and down-

regulated the production of superoxide and expression of nuclear factor κB, both of

which regulate inflammation (Zhao et al. 2003; Calkin et al. 2006). Furthermore,

gemfibrozil and fenofibrate both inhibited TNF, IL-1 beta, IL-6 and nitric oxide

production (Xu et al. 2006). In a murine influenza model, where severe systemic

disease is thought to arise through overproduction of proinflammatory cytokines, Budd

et al. (2007) found gemfibrozil offered some protection against the virus, with an


36

increased survival rate from 26% to 52% compared to vehicle-treated mice (Clark et al.

2004; Budd et al. 2007).

An early study exploring the effect of plasma free fatty acid concentrations and

temperature on parasitaemia in P. berghei infected mice used clofibrate as a lipid-

lowering agent. Coincidentally, the study reported on a significant retardation in the

development of parasitaemia in the clofibrate treatment group, suggesting a direct

inhibition on parasite growth (McQuistion 1979). A recent report highlighted the

potential use of PPAR agonists as a novel treatment for cerebral malaria (Balachandar

et al. 2011). However, no other study to date has investigated the effects of fibrates

against malaria.

The antimalarial activities of fibrates and statins, and their interactions with

conventional antimalarials will be explored in Chapter 6.

1.14 ANTIMALARIAL DRUG RESISTANCE

1.14.1 Definitions

The development of drug resistance has been a major obstacle in the battle against

malaria. The WHO defines antimalarial drug resistance as “the ability of parasite strains

to survive and/or multiply despite the administration and absorption of a drug given in

doses equal to or higher than those usually recommended but within tolerance of the

subject.” This was later modified in 1986 to specify that “the form of the drug active

against the parasite must be able to gain access to the parasite or the infected RBC for

the duration of the time necessary for its normal action” (Bruce-Chwatt 1986). This

refined definition takes into account the variations in drug pharmacodynamics and

pharmacokinetics between individuals, such as in the metabolism of sulfonamides and

sulfones (Trenholme 1975; WHO 2005). Drug resistance causes a right shift in the dose

response curve that can be observed in vitro (Figure 1.20).

Confirmation of drug resistance requires evidence of parasite recrudescence in a patient

(microscopically or by PCR) after receiving a treatment dose of antimalarial.


37

Simultaneous demonstration of effective concentrations of the drug or its metabolite in

the blood using established laboratory methods such as HPLC is also required. Results

from in vitro drug susceptibility tests and detection of molecular markers associated

with drug resistance are additional indicators of resistance. In practice however, these

tests are seldom performed alongside in vivo studies. For this reason, inadequate

parasitological clearance is conventionally considered to be associated with resistance

(WHO 2005).

Figure 1.20 Right-ward shift of concentration-effect relationship due to drug

resistance. Changes in the concentration-effect relationship may occur as a parallel

shift (B) from the “normal” profile (A) or, the slope changes and/or a reduction in the

maximum parasite killing effect (C) (WHO treatment guideline 2006-Annex 6).

1.14.2 Treatment Failure and Drug Resistance

A distinction must be made between antimalarial drug resistance and treatment failure,

the latter of which is a failure to clear parasitaemia and/or resolve clinical symptoms

after treatment. While drug resistance may cause treatment failure, other factors may

contribute. These include incorrect dosage, patient non-compliance regarding duration

of dosing, poor drug quality, drug interactions, poor absorption or rapid elimination

(diarrhoea and vomiting), and misdiagnosis (WHO 2005). Many of these factors may

also accelerate the development and spread of drug resistance as parasites are exposed


38

to suboptimal drug levels.

1.14.3 Emergence of Resistance to Principal Antimalarials

Despite an apparently replete list of antimalarials (Table 1.1), the emergence of P.

falciparum exhibiting resistance to multiple antimalarials has resulted in a gradual

degradation of the effectiveness of all available drugs. This along with the failure of

multifaceted approaches to eradicate and control the spread of malaria has seen

resurgence in the incidence of this life threatening infection on a global scale. For

comprehensive reviews on the evolution and selection of malarial drug resistance, see

(Plowe 2009) and (Mackinnon et al. 2010).

Resistance to CQ first observed in South-East Asia and South America about half a

century ago, now occurs almost everywhere that P. falciparum is transmitted. It is

important to recognise that the acquisition of resistance to quinine and CQ took many

years (278 and 12, respectively) compared with the rapid appearance of resistance to

proguanil, SP, MQ, and atovaquone, all within 5 years of their introduction

(Wongsrichanalai et al. 2002). Figure 1.21 illustrates the emergence of resistance to

principal antimalarials. Quinine, CQ and SP have remained effective for a considerable

length of time even after the initial reports of resistance. AQ was withdrawn by the

WHO in 1990 as denoted by the dotted line (Figure 1.21), but was re-introduced for

therapeutic usage after confirmation of its clinical safety and efficacy. Recent reports

from the Cambodia-Thailand border has indicated modest increase in P. falciparum

resistance to ACTs (artesunate-MQ) (Wongsrichanalai et al. 2008; Carrara et al. 2009;

Rogers et al. 2009).


39

Figure 1.21 Emergence of resistance to principal antimalarial drugs. (Modified

and adapted from Ekland and Fidock 2008). Coloured bars represent antimalarial

regimen in combination and as monotherapy along with the year since its first

introduction and the first report of resistance. Rectangles signify the approximate time

when resistance has spread to various geographical regions. Timelines were derived

from (Al-Yaman et al. 1996; Wongsrichanalai et al. 2002; Ekland et al. 2008;

Wongsrichanalai et al. 2008) and references therein. ACTs = artemisinin-based

combination therapies; Atov/Prog = atovaquone/proguanil; AQ = amodiaquine; CQ =

chloroquine, Q = quinine; R = resistance; MQ = mefloquine; SP =

sulfadoxine/pyrimethamine; PNG = Papua New Guinea; E = East; S = South.

1.14.4 Determinants of Antimalarial Resistance

Numerous factors contribute to the advent, spread and intensification of malaria

resistance, although their relative contribution remains unknown. Gene mutations

conferring resistance occur naturally in low frequencies as parasite populations show


40

heterogeneity. Therefore, selection of the most “fit” parasites occurs in the face of

chemotherapy, where parasites harbouring single or multiple point mutations that

provide survival advantage would recover and multiply (Wongsrichanalai et al. 2002;

Mackinnon et al. 2010). Other aspects attributing to resistance concern the dynamic

interplay of drug characteristics and usage, human behaviour and host factors, the

mosquito vector and environmental factors (Table 1.2).

Drug characteristics are important determinants of antimalarial resistance. Firstly, drugs

with a long elimination half-life, such as MQ and SP have the benefit of simpler, single-

dose regimen which can greatly improve compliance and dosing. However, the

subtherapeutic drug concentrations in plasma during slow elimination exert substantial

selection on parasites from new infections acquired after the initial treatment

(Wernsdorfer 1994; Bloland 2001). This is particularly common in areas with intense

malaria transmission (Wongsrichanalai et al. 2002).

Host factors such as immunity increase the efficacy of chemotherapy and may offset the

spread of resistance. A semi-immune individual may be cured by a drug despite partial

drug resistance of the infecting parasites. The specific immune response elicited by

repeated exposure to the pathogen is more effective in parasite clearance compared to

the non-specific response generated by those naïve to malaria. Introduction of resistant

parasites in migrant and refugee populations may thus increase the opportunity for

manifestation and spread of resistance (Wongsrichanalai et al. 2002).

Table 1.2 Determinants of antimalarial resistance. (Modified and adapted from

Wongsrichanalai et al. 2002*). pfcrt = Plasmodium falciparum chloroquine resistance

transporter; pfmdr1 = P. falciparum multidrug resistance 1; pfdhps, P. falciparum

dihydropteroate synthase; pfdhfr, P. falciparum dihydrofolate reductase; pfserca, P.

falciparum sarco-endoplasmic reticulum calcium ATPase6. Examples were obtained

from (Wernsdorfer et al. 1991** ; Jonkman 1995#; Molyneux et al. 1999§; PNGDOH

2000҂; Winstanley 2001^; Bloland 2001٭; Newton et al. 2008^^ ). (Wernsdorfer et al.

1991; Jonkman 1995; Molyneux et al. 1999; PNGDOH 2000; Winstanley 2001;

Newton et al. 2008).


41

Factor and characteristic Example

Drug Half-life Resistance to chlorproguanil-dapsone (short half-life) develops more slowly than that to SP (long

half-life)^.

Dosing Use of subtherapeutic doses in self-treatment such as with antifolate drugs in Thailand in the 1970s; poor drug compliance; mass drug administration with subtherapeutic doses; use of chloroquinised

salt** .

Non-target drug pressure

Presumptive use of antimalarial drugs without laboratory diagnosis or for indications other than

malaria#,҂.

Pharmacokinetics Use of drug formulations with reduced bioavailability*.

Cross-resistance SP and sulfamethoxazole-trimethoprim*.

Quality Poor manufacturing practices with substandard content of active ingredients, intentional

counterfeiting, deterioration due to storage and handling^^.

Human Host immunity Non-immune, migrant gem-miners and resistance to mefloquine on the Thai-Cambodian border*.

Health Malnourished and HIV infected individuals have significantly poorer parasitological response٭.

Maintenance of resistant parasite

reservoir

Non-detection of drug failure*.

Parasite Genetic mutations Polymorphisms in the genes: pfcrt, pfmdr1, pfdhps, pfdhfr, pfserca*.

Transmission level

Whether low or high transmission has more influence on drug resistance is debatable;

prevalence of drug resistance is higher in regions of low transmission, whereas a model suggests the

benefits of transmission control in delaying resistance development§.

Vector and environment

Mosquito affinity of parasites

Increased infectivity and productivity of CQ-resistant parasites in Anopheles dirus and the

propagation of CQ resistance in South-East Asia and Western Oceania*.


42

The interactions between parasite genetic polymorphisms have been identified to confer

or modulate antimalarial drug resistance. These involve genes that encode membrane

transporter proteins such as pfcrt and P-glycoprotein homologue 1 (pfmdr1) associated

with 4-aminoquinoline resistance. Mutations in the enzymes dihydrofolate reductase

and dihydropteroate synthase involved in folate synthesis, decreases sensitivity to

pyrimethamine and sulfadoxine respectively. The involvement of parasite genetics and

drug resistance are discussed in Section 1.18.

P. falciparum strains that already demonstrate resistance to a number of antimalarials

display a level of genetic plasticity that enables them to rapidly adapt to a new drug not

chemically related (Rathod et al. 1997; Nzila et al. 2010). Early reports using rodent

malaria have shown a strain resistant to one drug is more prone to give rise to resistant

lines to another drug, compared to strains that are fully susceptible (Powers et al. 1969;

Peters et al. 1976). Similar observations are evident during in vitro induction of

resistance, where the chance of generating parasite resistant lines increases with the

number of drug-resistant phenotypes. For instance, the ease of generating parasite

resistant line against atovaquone was greatest using the culture-adapted P. falciparum

strains W2 (cycloguanil, pyrimethamine and sulfadoxine resistant), followed by FCR3

(pyrimethamine and cycloguanil resistant), then 3D7 (sulfadoxine resistant) and the

least in the fully drug-susceptible D6 strain which failed to generate any drug resistant

parasite line (Rathod et al. 1997). This phenomenon is termed ‘accelerated resistance to

multidrug (ARMD)’, which is different to the known multidrug-resistant phenotype

(Rathod et al. 1997). The occurrence of ARMD may be due to low efficiency of DNA

repair mechanisms (Trotta et al. 2004), which can be attributed to the high mutation rate

during parasite multiplication. Hence, under drug pressure, parasites with the ARMD

phenotype have higher ability to produce a drug-resistant clone.

1.14.5 Mechanism of Resistance to 4-Aminoquinolines and Arylaminoalcohols

Much evidence attributes the activity of CQ to its capacity to concentrate itself from nM

concentrations in the extra-cellular environment to mM levels within the parasite food-

vacuole (Bray et al. 1998; Le Bras et al. 2003). Resistant parasites are found to

accumulate CQ less efficiently (Saliba et al. 1998). Verapamil is a modulator of P-


43

glycoprotein in mammalian cells expressing multidrug resistance. The observation that

CQ resistance is reversible by verapamil has led to the discovery of an analogous efflux

protein in the food vacuole of P. falciparum. Mutations in the corresponding gene, the

pfmdr1 gene has been associated with in vivo CQ resistance which modulates in vitro

resistance (Foote et al. 1990; Reed et al. 2000; Nagesha et al. 2001). It also plays a

significant role in the parasite’s sensitivity to structurally related compounds such as

quinine and AQ. Genetic and field studies have linked parasite possession of the wild

type pfmdr1 gene and its amplification is associated with increased resistance to MQ,

lumefantrine, halofantrine and artemisinin (Price et al. 2004; Sidhu et al. 2006;

Chavchich et al. 2010). Interestingly, there is an inverse relationship between parasite

sensitivity to CQ and MQ (Duraisingh et al. 2005). Mutations in the pfcrt gene which

encodes for another transmembrane protein in the parasite digestive vacuole also confer

CQ resistance. Specific polymorphisms encoding for resistance in the pfmdr1 and pfcrt

genes are discussed in Section 1.18.

1.14.6 Mechanism of Resistance to Antifolates

Antifolate combination drugs such as SP act via sequential and synergistic inhibition of

two key enzymes involved in parasite folate synthesis. Dihydrofolate reductase and

dihydropteroate synthetase are encoded by the P. falciparum dihydrofolate reductase

(pfdhfr) and P. falciparum dihydropteroate synthase (pfdhps) genes respectively.

Mutation in pfdhfr reduces its affinity to pyrimethamine or related compounds, whereby

inhibition is attenuated (Le Bras et al. 2003). Similarly, mutation in the pfdhps is

associated with sulfadoxine resistance (Wang et al. 1997). Specific combinations of

mutations in both pfdhfr and pfdhps have been associated with varying degrees of

antifolate resistance; these are discussed in more detail in Section 1.18.

1.14.7 Mechanism of Resistance to Artemisinin and Derivatives

Although a number of putative targets have been proposed, the exact mechanisms of

action of artemisinin remain uncertain (O'Neill et al. 2010). Chavchich et al have

selected parasite lines that are resistant to artemisinin and artelinic acid under


44

continuous drug pressure (Chavchich et al. 2010). The changes in parasite susceptibility

were accompanied by concomitant increase in pfmdr1 gene copy number and protein

expression. In additional to these molecular changes, the authors reported a reduction in

parasite sensitivity to MQ, quinine, lumefantrine and halofantrine, in concordance with

field observations (Sidhu et al. 2006). Besides pfmdr1 gene copy number, the

acquisition of artemisinin tolerance has been associated with parasite developmental

arrest and changes in transcriptomic modifications as a result of drug pressure

(Witkowski et al. 2010).

Studies of the cytotoxic effects of artemisinin suggested its mechanism of action may

be via interactions between the artemisinin endoperoxide bridge and haem-iron

(Kannan et al. 2005). Subsequent production of alkylated haem derivatives of

artemisinin (i.e. haemarts) has been proposed to cause parasite death due to its

interference with haemazoin formation as well as harmful effects due to free radicals

(Kannan et al. 2005). This hypothesis is consistent with studies demonstrating that

artemisinin activity can be enhanced by oxidising agents and attenuated by reducing

agents (Krungkrai et al. 1987). However, this theory has been challenged since

artemisinin is active against ring-stage parasites that do not harbour high concentrations

of haem (Olliaro et al. 2001). Wu et al proposed that artemisinin is activated on the

reductive cleavage of the peroxide bond by iron-sulfur redox centres common to

Plasmodium enzymes. As a result, alkylation of these enzymes may be responsible for

parasite death (Wu 2002a). This hypothesis is supported by the interactions between

radiolabelled artemisinin and various parasite proteins, highlighting the possibility that

parasite death may be due to endogenous protein alkylation and inactivation

(Bhisutthibhan et al. 2001). Some of the proposed target proteins for artemisinin

include those involved in the electron transport chain, cysteine protease, translationally

controlled tumour protein, and pfATP6 (Eckstein-Ludwig 2003; Li 2005). The latter is a

SERCA-type calcium ATPase where field and in vitro evidence show parasites

expressing the L263E mutation in pfATP6 have decreased sensitivity to artemisinin and

its derivatives (Uhlemann 2005; Krishna et al. 2006; Fidock et al. 2008).


45

1.15 IN VITRO DETECTION OF RESISTANCE IN P.

FALCIPARUM

Vigilant detection and monitoring of antimalarial resistance is prudent for ensuring the

best choice of treatment within a given locality. In vitro testing of parasite susceptibility

is a valuable tool for resistance surveillance to complement clinical trials which are

much more time and resource-consuming. In vitro susceptibility testing involves the

short term culture of parasites isolated from an infected individual, and determining the

level of growth inhibition after exposing them to various drug concentrations.

Sensitivity is usually measured in terms of the concentration of drug required to inhibit

growth by 50% (IC50) (Rieckmann et al. 1978; WHO 2001; Noedl et al. 2007). The IC50

is subsequently compared against a threshold value for in vitro resistance, which is

uniquely determined for each drug. In the example of CQ for which the in vitro

resistance threshold is 100 nM, the value was determined by comparing IC50 values

obtained from 11 geographically distinct culture-adapted and field isolates (Cremer et

al. 1995). Most in vitro drug resistance thresholds were selected without information on

clinical outcome hence may not directly predict in vivo resistance (Ekland et al. 2008).

Nevertheless, IC50s have been used extensively as an international currency in the

assessment of drug susceptibility from different geographic regions.

The first in vitro drug sensitivity test was published in the late 1960s where infected

blood samples were treated with CQ, QN and cycloguanil and the extent of parasite

maturation in the presence of these drugs was assessed (Rieckmann et al. 1968). This

marked the beginning of short-term in vitro culture of malaria parasites and continuous

culture methods were described shortly after (Trager et al. 1976). Based on the new

milestones in malaria culture techniques, assessments of drug inhibition against all

developmental stages of parasites using 48 or 96 hr assays were developed (Trager

1978; Richards et al. 1979). These methods involved longer test periods which enabled

the testing of slower-acting antimalarials. Further development over the next few

decades produced diverse approaches including visual examination and counting of

mature parasite stages, determination of parasite enzyme activity, and sophisticated

assays that quantify the amount of newly synthesised DNA during parasite development


46

by radio-isotope labelling (Rieckmann et al. 1978; Desjardin 1979; Makler et al. 1993a;

Radfar et al. 2009). The following sections provide an overview of the main types of in

vitro assays used for the assessment of P. falciparum growth inhibition in response to

different drug doses.

1.15.1 Schizont Maturation

1.15.1.1 Macro test

The WHO macro in vitro test is based on maturation of trophozoites and formation of

schizonts in the presence of different concentrations of drugs (WHO 1978). This assay

is supplied in a kit, primarily developed for the field assessment of P. falciparum

susceptibility to CQ. Briefly, 8 mL of venous blood are collected and transferred into a

sterile Erlenmeyer flask (25 mL) containing glass beads and stoppered. The sample is

defibrinated by physical rotation for 5 min. Into each test vial, 1 mL of blood is

aliquoted in the specified sequence for areas with suspected resistance: 2 control vials,

CQ vials containing 0.5, 1, 1.5, 2, 3, 0.25, 0.75, 1.25 nM and, for areas with no prior

indication of resistance 2 control vials, CQ vials containing 0.5, 1.0, 0.75, 0.25, 1.5, 2,

1.25, 3 nM. This sequence of testing increases the chance of parasite sensitivity being

assessed in the optimal range of drug concentrations in case of inadequate sample

volume. After gentle mixing the vials are closed and incubated in water at 38.5°C for 24

- 28 hr. Thick and thin blood smears are prepared after incubation, and the percentage

of schizonts in test wells relative to those of control wells are determined (Dulay et al.

1987).

The macro in vitro method is simple to use with little specialised equipment required. In

view of the fact that there are limited resources in malaria endemic areas, it has been

useful in field settings (Cattani et al. 1986). One limitation however, is the need for a

large-volume blood sample and waterbath space. Many large scale studies employ a

micro technique as a result (Rieckmann et al. 1978).


47

1.15.1.2 Micro test

A scaled down modification of the macro test commonly known as the Rieckmann

microtechnique enables the assessment of parasite drug sensitivity using a small amount

of blood (Rieckmann et al. 1978). Briefly, finger-prick blood samples (100 µL) are

diluted 1:10 with complete culture medium and dispensed (50 µL) into 96-well plates

provided by the WHO that are pre-dosed with drugs at final concentrations from 0.25 to

16 pmol/well. Test plates are incubated in a candle jar to achieve a microaerophilic

atmosphere at 37°C for 24 to 36 hr depending on the rate of maturation in control wells.

Thick smears are subsequently prepared and the number of schizonts, which is defined

as intra-erythrocytic parasites with 3 or more nuclei, per 200 asexual parasites is

counted. Sensitivity is reported as the highest concentration of drug in which

schizogony occurred.

The in vitro microtechnique has been widely employed in field studies due to its

simplicity and requirement for minimal specialised equipment and technical personnel

(Kouznetsov et al. 1980; Trenholme et al. 1993; Noedl et al. 2001; Menezes et al.

2002). With further refinement, the microtechnique (Mark III) is now the WHO

standard assessment of P. falciparum antimalarial drug susceptibility (WHO 2001).

Despite these advantages, a number of limiting factors should be considered. Since the

sample is used directly in the test system, the parasite density in the inoculum

influences the susceptibility outcome (Kouznetsov et al. 1980; Ponnudurai et al. 1981).

Thaithong et al evaluated the effect of initial parasitaemia on parasite survival in the

presence of 5 antimalarials. The authors found that the actions of CQ, AQ, MQ and

quinine were significantly reduced in the presence of parasitaemia >1% (Thaithong et

al. 1983). In addition, the WHO in vitro micro kit only caters for a single test per

sample and not duplicates or triplicates as in the isotope incorporation assay and

Plasmodium lactate dehydrogenase measurement (Desjardin 1979; Makler et al.

1993b). In practical terms this is advantageous as schizont counting is labour intensive

and time consuming, especially when the method already requires the counting of 8

thick films per sample to determine sensitivity outcome. Another consideration

important for data interpretation is that schizont enumeration by microscopy tends to


48

produce IC50 values that are two to three times higher than by the isotopic method

(Wernsdorfer et al. 1988).

1.15.2 3H-Hypoxanthine Incorporation Assay

The isotopic assay utilises the parasite’s requirement for hypoxanthine as a nucleic acid

precursor during its development (Desjardin 1979). The assay is applicable for both

field isolates and culture-adapted samples as detailed in Section 2.2.5. The isotopic

assay provides a semi-automated technique to assess drug susceptibility. It is

reproducible and sensitive, and is considered the reference method for drug sensitivity

assays (Makler et al. 1993b; Druilhe et al. 2001). Numerous in vitro studies have used

this method, and have circumvented the need for specialised equipment in the field by

transporting samples to a centralised laboratory for testing (Basco et al. 1998; Pradines

et al. 2006). This approach has proven successful in various African countries where

the high throughput assay enables more effective monitoring of resistance epidemiology

(Nzila-Mounda et al. 1998; Pradines et al. 1999a; Basco et al. 2003a; Jambou et al.

2005). However, the use of radioisotope involves high costs for consumables and

laboratory infrastructure, requiring supporting facilities such as safe disposal of

radioactive waste and reliable couriers. Technical training of research personnel to

perform meticulous handling of unsealed radio-isotopes is usually unavailable in

developing countries such as PNG. The high costs and technical constraints have

hindered the implementation of the isotopic method in many malaria-endemic

countries. Nonetheless, strategic collaboration between developing and developed

countries should enable the use of this sensitive method for the prudent ‘gold standard’

surveillance of P. falciparum drug resistance.

1.15.3 Plasmodium Lactate Dehydrogenase (pLDH) Detection

Plasmodium lactate dehydrogenase (pLDH) is the terminal enzyme of the anaerobic

Embden-Meyerhoff glycolytic pathway and is essential for energy production in

malaria parasites (Sherman 1979). Early interest in using pLDH as a marker for

parasitaemia and parasite growth stem from the favourable characteristics of the

enzyme. PLDH can be distinguished from human LDH based on its ability to rapidly


49

utilise 3-acetyl pyridine adenine dinucleotide (APAD) as a coenzyme to convert lactate

to pyruvate at a rate 200-fold more effectively than the human isoforms (Sherman 1961;

Gomez et al. 1997). In addition, the clearance of pLDH from plasma is rapid (3 - 5

days) and correlates with parasitaemia in vitro and in vivo (Makler et al. 1993a). The

pLDH level declines rapidly when parasites are no longer metabolically viable (Piper et

al. 1999). These biochemical features constitute a sensitive and specific marker for the

determination of parasite growth. It has been applied to various assay formats for

assessing in vitro drug susceptibility as described in Section 2.2.4.

1.15.3.1 Colourimetric pLDH microtests

The original drug sensitivity assay using pLDH was described by Makler et al (Makler

et al. 1993a). The assay follows a similar set up for parasite drug exposure in the

isotopic assay, as described in Section 2.2.4. The reaction is allowed to develop at room

temperature (RT) and the consequential change in colour can be monitored visually or

measured spectrophotometrically at 650 nm (Figure 2.6). PLDH activity can also be

determined kinetically at 30 sec intervals for 30 min by the formation of reduced

APAD. The enzymatic approach has been successfully used in field studies (Makler et

al. 1993a; Basco et al. 1995; Wong et al. 2010). Inhibition profiles and IC50s obtained

by pLDH are comparable to those determined by the isotopic and microscopic assay

(Makler et al. 1993; Basco et al. 1995). For optimal sensitivity, however, the enzymatic

assay requires an initial parasitaemia between 1 and 2% at 1.5% haematocrit (hct), with

a detection limit of 0.4% parasitaemia. This range of initial parasitaemia is often too

high for most field isolates from sub-Saharan Africa where patients with acute

uncomplicated falciparum malaria usually present with parasitaemia <1% (Basco et al.

1995). The method is therefore not sensitive enough as a diagnostic method.

Nonetheless, it has been employed in monitoring therapeutic efficacy of drug treatments

in Chinese patients infected with P. falciparum and P. vivax (Wu et al. 2002b). A

modification to the colourimetric assay is the use of sodium-2,3-bis-[2-methoxy-4-

nitro-5-sulphophenyl]-2H-tetrazolium-5-carboxanilid (XTT) in place of NBT and the

reaction is followed by optical density (OD) measurement at 450 nm (Delhaes 1999).

However, this method requires even higher initial hct and parasitaemia, therefore, offers


50

no advantage over the unmodified version.

1.15.3.2 Immunocapture of pLDH

Other variations based on immunocapture of pLDH have been developed with the use

of monoclonal antibodies (Makler et al. 1998; Kaddouri et al. 2006; Mayxay et al.

2007). This approach significantly improves assay sensitivity, as it is less prone to non-

specific reduction of NBT in the haemolysate and in the reagent mixture (Knobloch et

al. 1995; Oduola et al. 1997). In a Nigerian clinical study, Oduola et al (1997)

developed an enzyme-linked immunosorbent assay (ELISA) that combines the use of

antibody capture technique with APAD to enhance sensitivity and specificity of pLDH

detection. The immunocapture pLDH (IcpLDH) assay uses 96-well plate coated with

mouse monoclonal antibody specific to pLDH, to which the blood sample is added.

During incubation, pLDH is captured on the plate by antibodies, whilst non-specific

contents are washed off. NBT is subsequently added and end point absorbance is

measured. The authors observed a specific and immediate relationship between

dissipation of pLDH enzyme activities and resolution of infection in vivo (Oduola et al.

1997; Piper et al. 1999). Further refinement of this technique led to the development of

a double-site enzyme-linked pLDH immunodetection (DELI) assay (Moreno et al.

2001). Field trials in Thailand, Laos and Senegal demonstrated the DELI microtest to

be highly sensitive, allowing for the inclusion of isolates with parasitaemia as low as

0.005% (Moreno et al. 2001; Brockman et al. 2004; Mayxay et al. 2007). The IC50s

obtained using the DELI approach correlated well with the isotopic test, showing

similar proportions of drug resistant and sensitive isolates. It is also easier and faster to

implement than the isotopic test, and does not require sophisticated equipment (Moreno

et al. 2001; Kaddouri et al. 2008). A current drawback to its implementation is that

monoclonal antibodies towards pLDH are not commercially available, with its use

limited to collaborating laboratories. Overall, immunocapture pLDH colourimetric

assays are cost-effective and straight forward to perform, with great potential for world-

wide implementation for epidemiological monitoring of drug resistance.


51

1.15.4 Histidine-Rich Protein II (HRP2) Assay

Histidine-rich protein II is a naturally occurring protein found in several cellular

compartments in the parasite including the cytoplasm. It has been implicated as an

important factor in the detoxification of haem and is readily recovered from plasma,

infected RBC membrane and culture supernatants (Howard et al. 1986; Sullivan et al.

1996; Lynn et al. 1999; Papalexis et al. 2001). The level of HRP2 in malaria cultures

increases with parasite development and multiplication (Desakorn et al. 1997), hence

making it an excellent indicator of parasite growth in response to antimalarial drugs. In

2002, a novel approach was described to assess drug sensitivity in Thai isolates by

measuring the level of HRP2 in an ELISA (Noedl et al. 2002). Briefly, parasitised RBC

samples were standardised (0.05% parasitaemia, 1.5% hct) and incubated with various

drug concentrations in 96-well plates similar to that in the pLDH assay. These were

subsequently frozen-thawed and the haemolysed samples transferred to commercial

ELISA plates pre-coated with mononclonal antibodies against HRP2. The plates were

incubated at RT for one hr and washed repeatedly to remove unbound content. Diluted

antibody conjugate was added to each well and incubated as previously. After several

washes, diluted chromogen was added for colour development in the dark for 15 min.

At the end of the reaction, a stop solution was added and OD measured at 450 nm for

IC50 determination (Noedl et al. 2002).

A number of field studies have implemented the new HRP2 microtest and found it

highly sensitive and simple to perform with results closely aligned to those obtained by 3H-hypoxanthine incorporation and the WHO schizont maturation test (Noedl et al.

2003; Attlmayr et al. 2005; Noedl et al. 2005). HRP2 assay is expensive to perform for

the purpose of in vitro drug susceptibility as three columns of the ELISA plates are

required for one drug to be tested in triplicate per sample. For multiple drug testing

required in large scale studies, the use of commercial kits (~AUD $100/plate) is costly

(Cellabs, Australia). More recently, an in-house HRP2 ELISA has been described using

commercially available monoclonal antibodies and is a cheaper alternative to using test

kits (~AUD $20/plate) (Noedl et al. 2005). The method requires additional coating of

test plates which is labour intensive and potentially introduces a bias if antibodies are


52

not coated evenly across the wells. This in-house version produces similar results to

those by commercial kits (Noedl et al. 2005), and the availability of monoclonal

antibodies facilitates a more rapid implementation of a cost effective and sensitive in

vitro assay.

1.15.5 Dual Detection of HRP2 and PLDH

It is presently accepted that HRP2 levels reflect both past and current infections due to

its slow clearance (10 - 14 days) while pLDH levels reflect the current infection. The

concurrent measurement of these two bio-markers by means of a unified ELISA

approach has been recently described (Martin et al. 2009). The unified protocol enables

the direct comparison of both HRP2 and pLDH results and provide a more enhanced

assessment of parasite burden to include sequestered parasites, which would be

clinically relevant during pregnancy where microscopy can be unreliable (Martin et al.

2009).

1.16 ASSESSMENT OF ANTIMALARIAL DRUG

COMBINATIONS

Combination antimalarial therapies play a pivotal role in delaying the onset of

resistance to new agents and in reducing the effects of resistance to current agents

(White 1998). Effective combination drug regimens often achieve a therapeutic efficacy

greater than that achieved with monotherapy (Fivelman et al. 2004). In vitro drug

interaction studies provide essential information for the selection of optimal drug

combinations for further clinical trials. However, in vitro combination efficacy does not

necessarily translate to efficacy in vivo, as therapeutic efficacy is dependent on

pharmacokinetic characteristics of both drugs within the host (Fivelman et al. 2004).

The biological responses of two agents in combination can be assessed in vitro by the

construction of an isobologram, which graphically displays the effects of each agent

alone and in combination (Figure 1.22) (Berenbaum 1978; Czarniecki et al. 1984;

Chawira et al. 1987; Davis et al. 2006). The outcomes of drug interactions are either

synergistic, indifferent (no interaction) or antagonistic. The concentrations of agents,


53

either in combination or alone, required to achieve 50% inhibition of parasite growth

are calculated and normalised to fractional inhibitory concentrations (FICs)

(Berenbaum 1978). The sum (Σ) of FICs can be calculated by the addition of FICs of

agents A and B, i.e. (IC50 of A in a mixture resulting in 50% inhibition/IC50 of A alone)

+ (IC50 of B in a mixture resulting in a 50% inhibition/IC50 of B alone) (Berenbaum

1978). When the ΣFIC equals 1.0, the combination is additive, or has no interaction. In

this case, the plotted points should fall close to the straight line drawn between the FICs

of 1.0 on the abscissa and ordinate (Figure 1.22). A ΣFIC of <1 indicates synergistic

interaction, the data points from which would form a concave isobole beneath the line

of additivity, and a ΣFIC of >1 is indicative of an antagonistic interaction represented

by a convex isobole (Berenbaum 1978; Chawira et al. 1987; Fivelman et al. 2004;

Davis et al. 2006). A more conservative interpretation of isobolographic results have

been recommended, where synergy is defined as ΣFIC values ≤ 0.5, antagonism as

ΣFIC values ≥ 4.0, and no interaction when ΣFIC >0.5 – 4.0 (Odds 2003).

Figure 1.22 Representation of isoboles.

The original checkerboard method by Berenbaum (1978) has been widely used to

evaluate antimalarial interactions (Hassan Alin et al. 1999; Skinner-Adams et al. 1999;

Gupta et al. 2002). An alternative fixed-ratio isobologram method formerly developed

for studies in bacteria has been applied for P. falciparum (Hall et al. 1983; Fivelman et

al. 2004; Wong et al. 2009). This newer approach demonstrated comparable findings

with the checkerboard method and is less labour intensive with fewer calculation steps


54

(Fivelman et al. 2004). Both checkerboard and fixed-ratio methods require

predetermination of IC50 values of each drug alone. From these data, a starting

concentration for each agent is selected and drug mixtures are prepared in various ratios

of the initial concentrations and subjected to serial dilution. In the checkerboard

method, the concentration of agent A is fixed whilst that of agent B is varied and vice

versa. The fixed-ratio method on the other hand, uses serial dilutions of fixed ratios of

both agents, so that drug concentrations are varied at the same time over predetermined

sets of concentrations (Fivelman et al. 2004). The fixed-ratio method is more resilient

in terms of inter-day variations in IC50s where inaccurate initial IC50s may cause poor fit

of the sigmoidal growth response curve, resulting in clustering of data points at the

extremities of the isobole axes. In addition, dose-response curves from the fixed-ratio

approach are based on drug concentration ratios, each of which is constructed to range

from 100 to 0% parasite inhibition, thus enabling a more accurate regression curve fit

and IC50 determination (Fivelman et al. 2004).

1.17 IN VIVO DETECTION OF DRUG RESISTANCE IN P.

FALCIPARUM

The level of P. falciparum resistance to antimalarial drugs is often assessed by

therapeutic response (Wongsrichanalai et al. 2002). In vivo response involves the

assessment of clinical and parasitological response over a period of time post-treatment

(WHO 2006). Parasitological responses are classified by the clearance of parasitaemia

and are graded as sensitive (S) and three levels of resistance (RI, RII, and RIII) (Table

1.3). This classification system, though remaining valid in areas with low transmission,

may be difficult to apply in areas with intensive transmission, where new infections and

recrudescences cannot be differentiated on the basis of microscopy and complicates the

outcome (Wongsrichanalai et al. 2002). More recently, the WHO introduced a modified

system based on clinical symptoms and the level of parasitaemia (Table 1.3) (Bloland

2001). The previously established follow-up period of 14 days is considered insufficient

as a significant proportion of recrudescence often appeared after this period and shorter

observation periods have led to the overestimation of treatment efficacy (WHO 2006).

The current recommended duration of follow-up is a minimum of 28 days for most

antimalarial drugs in areas of intense as well as low to moderate transmission. Extended


55

follow-up periods of 42 days and 63 days are recommended for slowly eliminated drugs

(i.e. lumefantrine and MQ, respectively) to effectively capture recrudescences (WHO

2006). Clinical studies however are costly and often confounded by poor compliance,

difficulty with recruitment and patient follow-up particularly in remote villages (Han et

al. 1976; Karunajeewa et al. 2008b).

Table 1.3 Classifications of in vivo antimalarial susceptibility outcomes. (Talisuna et

al. 2004)

Parasitological classifications Treatment failure classifications

Sensitive

Clearance of parasites after treatment without subsequent recrudescence within a defined period

Adequate clinical response (ACR)

Absence of parasitaemia on day 14, irrespective of fever status, without previously meeting any of the criteria for ETF or LTF

Absence of fever irrespective of the parasitaemia status without previously meeting any of the criteria for ETF or LTF

RI parasitological failure Initial clearance followed by recrudescence after day 7

Early treatment failure (ETF) Danger signs or severe malaria on day 1, 2, or 3 in the presence of parasitaemia Fever (axillary temperature, ≥37.5°C) persists on day 2 and the parasite density is greater than that on day 0. Fever and parasitaemia on day 3 Parasite density on day 3 is ≥25% of the day 0 parasite density

RII parasitological failure

Reduction of parasitaemia on day 2 to less than 25% of day 0 parasitaemia, but no complete clearance

RIII parasitological failure

On day 2, either no reduction of parasitaemia or reduction to a level equal to or greater than 25% of the day 0 parasitaemia

Late treatment failure (LTF) Danger signs or severe malaria develop in the presence of parasitaemia on any day from day 4 to day 14 Fever and parasitaemia on any day from day 4 to day 14, and yet the patient could not be classified as ETF


56

1.18 MOLECULAR MARKERS OF DRUG RESISTANCE

Recent advances have provided powerful molecular tools to detect drug resistance

(Ekland et al. 2007). Molecular methods are renowned for their rapid quantitative

assessment for genetic markers of drug resistance, providing an attractive and relatively

inexpensive alternative to clinical approaches for monitoring the prevalence and spread

of resistant parasites (Ekland et al. 2008). The sequencing and annotation of the P.

falciparum genome in 2002 has greatly enhanced the identification of gene candidates

as genetic markers of drug resistance (Gardner et al. 2002). Conserved polymorphisms

within the genome including microsatellites (repeats of short nucleotide sequence),

single nucleotide polymorphisms (SNPs), and small insertions or deletions, act as

surrogate markers for drug resistance determinants (Ekland et al. 2007). The P.

falciparum genome contains an estimate of 25,000 to 50,000 SNPs that tend to cluster

in blocks known as haplotypes surrounded by recombination hotspots (Mu et al. 2005).

Since the number of polymorphisms is different within different genes, and by tracking

a signature set of SNP tags, various haplotypes associated with drug resistance can be

identified (Mehlotra et al. 2001; Carnevale et al. 2007; Ekland et al. 2007).

The identification of pfcrt as the primary determinant in CQ resistance has enabled the

development of a simple PCR assay that identifies the presence of resistant strains

(Fidock et al. 2000). Mutations in the pfcrt gene, particularly the substitution of lysine

(K) to threonine (T) at residue 76 (K76T), is central to CQ resistance. The K76T

polymorphism is consistently found in CQ-resistant strains regardless of geographic

origin. It can occur within different amino acid haplotypes between residues 72 to 76:

CVIET, CVMNT, CVMET, and SVMNT, all of which are associated with CQ

resistance (Fidock et al. 2000). Higher levels of CQ resistance can be attributed to

changes in the pfmdr1 gene in point mutation 86Y (Foote et al. 1990; Reed et al. 2000;

Babiker et al. 2001; Djimde et al. 2001; Pickard et al. 2003). Clinical resistance to AQ

has been associated with SNPs in pfcrt K76T, pfmdr1 N86Y, F184Y, D1246Y, in

particular the triple tyrosine pfmdr1 haplotype YYY at codons 86, 184 and 1246 has

been selected post AQ monotherapy (Humphreys et al. 2007; Tinto et al. 2008). The

predictive value of pfcrt and pfmdr1 polymorphisms for both CQ and AQ underscores

the similarity in their mode of action, and the predisposition of high level of CQ


57

resistance in endemic regions may compromise the future use of AQ-artesunate as an

alternative ACT (Thwing et al. 2009). Allelic substitution experiments have also shown

both pfcrt and pfmdr1 polymorphisms contribute to quinine resistance (Reed et al.

2000; Sidhu et al. 2005). Another molecular determinant, the pfnhe1 gene located on

chromosome 13 which encodes a putative sodium/hydrogen exchanger was associated

with reduced quinine sensitivity in culture-adapted P. falciparum (Bennett et al. 2007).

Mutations in the pfmdr1 gene also confer resistance to multiple other antimalarials

including MQ, lumefantrine, halofantrine and quinine (Cowman et al. 1994; Peel et al.

1994; Reed et al. 2000). In a pfmdr1 gene allelic replacement study, Reed et al (2000)

demonstrated pfmdr1 mutations altered artemisinin susceptibility in parasite lines from

PNG (D10) and South America (7G8). This finding has serious implications for future

artemisinin effectiveness in endemic areas such as PNG. Polymorphic changes in the

pfdhfr and pfdhps genes encoding dihydrofolate reductase and dihydropteroate synthase

respectively are good indicators for pyrimethamine and sulfadoxine resistance. The

S108N mutation in pfdhfr has been implicated in pyrimethamine resistance with

additional mutations at positions 16, 50, 51, 59, 140 and 164 contributing to elevated

levels of resistance (Cowman et al. 1988; Peterson et al. 1988). Similarly, the A437G

mutation in pfdhps confers initial resistance to sulfadoxine. Other mutations including

K540E, A581G, S613A, S436A/F lead to higher resistance (Triglia and Cowman 1994;

Triglia and Cowman 1999). Table 1.4 provides a summary of molecular markers

associated with drug resistance.


58

Table 1.4 Molecular markers for antimalarial drug resistance. (Triglia et al. 1994;

Reed et al. 2000; Chaijaroenkul et al. 2010).

Antimalarial Gene mutation Remarks

pfcrt 76T Strong association Chloroquine

pfmdr1 86Y, 184F, 1034C, 1042D, 1246Y

Possible association

Sulfadoxine-pyrimethamine

pfdhfr 108, 51, 59, 164 pfdhps 436, 437, 540, 581,

623

pfdhfr 108 essential for pyrimethamine resistance, degree of resistance

increases with additional mutations Leu51 and Arg59 or triple mutation. Absolute resistance conferred by the addition of Leu164, thus quadruple

mutation, irrespective of dhps mutations

Mefloquine, Quinine

pfmdr1 Not clearly understood, pfmdr1 copy number is associated with reduced sensitivity to mefloquine, quinine

Artemisinin pfmdr1 pfATPase6

pfmdr1 copy number is associated with reduced sensitivity to artesunate

1.19 BREATH TEST FOR MALARIA

Breath tests have been developed to assist in the early diagnosis of infections with

Mycobacterium tuberculosis and Helicobacter pylori (Lechner et al. 2005b; Phillips et

al. 2007). The procedure involves the trapping of a sample of a patient’s breath in a

sorbent column followed by extraction and analysis of the retained volatile organic

compounds (VOCs). The profile or ‘fingerprint’ of VOCs that is generated can be used

in determining whether a particular disease is present (Lechner et al. 2005a). Recent

developments of breath-collection apparatus allow portability of equipment and thus

testing may be performed promptly and more cost-effectively wherever the patient

presents (Phillips 1997; Lindstrom et al. 2002; Martin et al. 2010).

The identification of P. falciparum using conventional microscopy, antigen detection

and PCR are inadequate in circumstances where the peripheral parasitaemia is low. This

includes cases of severe malaria in which the majority of parasites are sequestered


59

within the microvasculature (Sachanonta et al. 2008). In addition, antigen detection

methods and PCR in this context may not, if positive, differentiate between viable and

non-viable parasites, an important consideration for therapeutic monitoring. In such

instances, breath tests may provide a novel, non-invasive approach for the sensitive

detection of an active malaria infection.

1.20 SCOPE OF THE STUDIES PRESENTED IN THIS THESIS

The preceding literature review has provided an overview of malaria infection in

humans, the use of conventional and novel antimalarial agents in malaria management,

the role of in vitro and in vivo methods in the detection of parasite drug resistance, and

how these factors contribute to the understanding of malaria pathophysiology and

treatment outcome.

The proximity of PNG to Australia and the political and economic relationships

between the two countries mean that malaria control in PNG should be of concern to

Australia. A significant proportion of imported malaria in Australia originates in PNG

(Charles et al. 2005) while malaria outbreaks in the Torres Strait Islands are regularly

reported (Needham 2011). The studies reported in Chapters 3 and 4 of this thesis

include a multifaceted investigation into the efficacy of treatment for falciparum

malaria, including mechanisms underlying P. falciparum resistance, in PNG children.

Although this is an extremely important public health issue in PNG with clear

implications for Australians visiting PNG or living close to the southern part of the

country, there have been few studies of this type conducted to date.

The data from the present PNG paediatric malaria studies and the evolution of

resistance of P. falciparum and P. vivax to available antimalarial drugs in other parts of

the tropics underscore the need for the identification of novel treatments. This can

include compounds within existing or new classes of antimalarial drugs. Studies in

Chapters 5 and 6 of this thesis address both these possibilities, providing pre-clinical

and some clinical data that are essential to the further development and clinical

application of desbutyl-lumefantrine and fenofibrate. Desbutyl-lumefantrine is the

active metabolite of lumefantrine which is part of the recommended first-line ACT


60

treatment of uncomplicated malaria in PNG. The impetus to examine lipid-modifying

drugs was provided by the recognition that non-communicable diseases, especially

cardiovascular disease, represent an increasing disease burden in developing countries

such as PNG (Ōtsuka et al. 2007). Drugs such as statins and fibrates will be

increasingly used as a result and antimalarial effects could provide significant health

and economic benefits to the individual and community in PNG and other countries

with similar epidemiology. This has been investigated in the case of the blood glucose-

lowering drug rosiglitazone (Boggild et al. 2009) but lipid-altering therapies have even

wider potential therapeutic application.

During the course of the foregoing studies, the deficiencies in available techniques for

diagnosis and antimalarial therapeutic monitoring provided the impetus to evaluating

VOCs as a surrogate sensitive biomarker of viable parasites in the circulation. At the

same time as data collection for the studies presented in Chapters 3 and 4 was

proceeding, a separate investigation done in Madang, PNG, by another group identified

the VOCs methyl nicotinate in the breath of tuberculosis patients (Syhre et al. 2009).

This suggested that a similar breath test might be feasible in malaria. A corollary of

parasite-specific VOCs production might be that these compounds have biological

activity including acting as anaesthetic agents in patients with cerebral sequestration

and consequent coma. The experiments in Chapter 7 detail attempts to determine, as the

first step in this line of investigation, whether cultured P. falciparum generates specific

VOCs as quantified using the most sensitive chemical assay techniques.

The main implications of these various studies, their inter-relationships and prospects

for future related research are discussed in Chapter 8.

CHAPTER 2

METHODS AND MATERIALS

Chapter 2 Methods and Materials

62

CHAPTER 2. METHODS AND MATERIALS

2.1 IN VITRO CULTURE TECHNIQUES

Culture techniques for P. falciparum described in the following section have been

adapted from previously published methods (Trager et al. 1976).

2.1.1 Parasites

PNG field isolates of P. falciparum were collected from children with uncomplicated

malaria (Chapter 3). Laboratory-adapted strains 3D7, Dd2, W2mef, K1 and E8B used in

other in vitro studies were obtained from The Walter and Eliza Hall Institute in

Melbourne and from Dr. Tina Skinner-Adams and colleagues of the Queensland

Institute of Medical Research, Australia.

2.1.2 Retrieval from Liquid Nitrogen

Intra-erythrocytic stages of P. falciparum preserved in cryo-suspensions were retrieved

from long term liquid nitrogen storage as described previously (Meryman et al. 1972;

Skinner-Adams 1999). Briefly, parasite stock vials were thawed at 37°C in a waterbath

and transferred into a centrifuge tube. Pre-warmed 12% NaCl solution (Appendix B)

was added drop-wise (1 drop/sec) with gentle mixing until a fifth of the original volume

was added (i.e. 200 µL to 1 mL cell suspension) and allowed to stand at RT for 3 min.

With gentle mixing, pre-warmed 1.6% NaCl solution (Appendix B) was added drop-

wise to reach 10 times the volume (i.e. 10 mL to 1 mL) then centrifuged (1200 rpm for

5 min). The supernatant was removed and pre-warmed 0.9% NaCl solution (Appendix

B) was added drop-wise to reach 10 times pellet volume whilst ensuring the RBC were

fully resuspended. After centrifugation, the supernatant was removed and the cells were

resuspended in complete media (Appendix B) at 5% haematocrit (hct) using RBC

(Section 2.1.4) and cultured in a microaerophilic environment (Section 2.1.3).


63

2.1.3 Maintenance of Cultures

P. falciparum cultures were cultured in sterile lidded-dishes (5 mL, 10 mL or 20 mL) at

5% hct in a Nalgene desiccator (Figure 2.1). This provided a controlled microaerophilic

atmosphere for the culture of P. falciparum (Trager et al. 1976; Scheibel et al. 1979).

Non-infected RBC (Section 2.1.4) were added to the cultures at 2 - 3 day intervals to

maintain parasitaemia between 0.5 to 5%. To prevent accumulation of metabolic by-

products, high parasitaemia were reduced by expanding the culture to a larger dish or

by aspirating out part of the culture and re-adjusting the hct by replenishing with non-

parasitised RBC.

Figure 2.1 Nalgene desiccator used for P. falciparum culture. Parasite cultures were

maintained at 37⁰C in an airtight chamber (modified Nalgene desiccator cabinet,

Nalgene, U.S.A) flushed with a gas mixture of 1% (or 5%) O2 and 5% CO2 balanced in

N2 (BOC gases, Australia) for 90 sec daily or when opened. The oxygen concentration

within the chamber ranged between 3 - 9% over 24 hr as indicated by an O2 monitor

(ToxiRAE II, San Jose, CA USA).

2.1.4 Erythrocytes Preparation


64

Blood from a healthy volunteer was collected into sodium heparin Vacuette® and

centrifuged (1300 rpm for 5 min). Buffy coat was removed and plasma was stored at -

20⁰C for later use as media supplement (Appendix B). Packed RBC was transferred into

a 50 mL tube topped with 3 times cell volume of media. After centrifugation (1300 rpm

for 15 min), the supernatant was discarded and the process repeated twice. After the

final wash, the cells were resuspended 1:1 (i.e. 50% RBC) in non-supplemented media.

The stock was refrigerated and used within 3 weeks for cultures and assays.

2.1.5 Determination of Parasitaemia

Parasite viability and development can be visually monitored by light microscopy

(Figure 2.2). A thin blood smear was prepared by taking 3 - 10 µL of RBC in an equal

volume of media and applied as a drop on a glass slide (Menzel-Glӓser, Lomb

Scientific) (Figure 2.3). After air drying, the thin smear was fixed in methanol and

stained for 10 min using freshly prepared 5% Giemsa Solution (Appendix B). After

rinsing under tap water, it was air-dried and examined under oil or anisole (Fluka)

immersion (100 × objective). The parasitaemia was determined by counting the number

of infected RBC in at least 1000 RBC and expressed as a percentage of total RBC.

2.1.6 Synchronisation of Parasite Forms

One developmental cycle prior to use, parasite cultures were synchronised by sorbitol

lysis to achieve ≥90% ring forms (Lambros 1979). RBC harbouring mature forms are

more fragile and lyse under osmotic stress. Briefly, cultures with >40% rings were

centrifuged and the pellet was resuspended in 10 mL of pre-warmed 5% sorbitol

(Appendix B) and incubated at 37°C for 10 min. This was centrifuged and resuspended

in complete media for culture.


65

Figure 2.2 Giemsa-stained thin smear of synchronised P. falciparum culture.

Cultured parasites under anisole immersion (× 1000 magnification). From top to

bottom: rings, trophozoites and schizonts. Note the rupture of a schizont with two

newly released merozoites (M) about to invade an adjacent erythrocyte. Characteristic

malaria brown pigment or haemazoin crystals (H) were also observed within RBC or as

free crystals released into the culture space during schizont rupture.


66

Figure 2.3 Preparation of a thin smear.

Thin smear is useful for detailed examination of parasite structures and developmental

stages. This was prepared by spreading a spot of blood along the edge of another glass

slide at a 45° angle and bringing it forward by a smooth gliding motion.

.

2.1.7 Cryopreservation

Field isolates or culture-adapted parasite strains were cryopreserved for future use.

Cryopreservation was performed on a routine basis to maintain stocks of various

parasite strains in liquid nitrogen. Cultures should be of high parasitaemia i.e. (>5%)

and mostly in the ring stage, as RBC infected with young parasites are more resilient to

lysis during the procedure. Briefly, after centrifugation (1300 rpm for 5 min) and

removal of the supernatant, the pellet was resuspended in an equal volume of cryo-

protective solution (Appendix B) and transferred into a cryopreservation vial (Nunc,

U.S.A.) and snap frozen in liquid nitrogen


67

2.2 DRUG SUSCEPTIBILITY ASSAYS

2.2.1 Drug/Compound Preparation

Drug susceptibility assays were carried out in 96-well plates (Sarstedt) where parasites

were treated with low to high doses of drug. Most assays were carried out over 48 hr,

with the exception of AZ for 72 hr. A typical lay-out of a drug susceptibility panel is

shown in Figure 2.4.

The antimalarial drugs used in this study consisted of chloroquine (CQ), amodiaquine

(AQ) and its metabolite monodesethyl-amodiaquine (dAQ), piperaquine (PQ),

mefloquine (MQ), naphthoquine (NQ), lumefantrine (LM) and its metabolite desbutyl-

lumefantrine (DBL), dihydroartemisinin (DHA) and azithromycin (AZ). Details for

statins and fibrates are described in subsequent chapters. On solubilisation, stock

standards of 1 mM concentration were prepared in compatible solvents (Table 2.1) and

stored in aliquots protected from light at -20°C. Due to the slow-acting nature of AZ, it

was tested on a different panel. On the day of assay, drug stocks were thawed and

further diluted in media to prepare 5 µM working standards. These were used for two-

fold serial dilutions in media at double assay concentrations (Table 2.1) and dispensed

in triplicates at 100 µL per well for pLDH and 3H-hypoxanthine incorporation assays.

2.2.2 Preparation of parasitised cells

Prior to assay, parasite cultures were centrifuged with the supernatant removed and

packed RBC were used directly. For field isolates, whole blood samples were

centrifuged with plasma and buffy coat removed. RBC were washed 3 times in non-

supplemented media before use. Each drug panel comprised of four drugs tested in

triplicates hence a minimum of 10 mL suspension of cells standardised to 3% hct at 0.5

to 1% parasitaemia (depending on the method of growth assessment) was required. For

pLDH assessment, 100 µL per well of the suspension was added giving a final 1%

parasitaemia and 1.5% hct in a 200 µL mixture of drug/RBC/media. If growth was

assessed by 3H-hypoxanthine incorporation, 90 µL suspension/ well was used instead.


68

Figure 2.4 Layout of a drug susceptibility panel.

The top row of the panel consisted of drug-free parasitised and non-parasitised controls.

Antimalarial drugs were serially diluted from the bottom row (highest concentration) to

the second row (lowest concentration) in triplicates.

2.2.3 Controls

For parasitised drug-free controls, 100 µL (or 90 µL for 3H-hypoxanthine

incorporation) of infected RBC suspension were added to 100 µL of assay media per

well. These wells should exhibit the highest parasite growth. For non-parasitised control

wells, uninfected RBC were used instead.


69

Table 2.1 Solvents and optimised assay concentration ranges for drug

susceptibility testing.

Drug (Supplier) Solvent Assay Range

Chloroquine diphosphate (Sigma Chemicals, St Louis, USA)

Sterile d.H2O 12.5 nM – 1600 nM

Amodiaquine dihydrochloride (Sigma)

Sterile d.H2O 5 nM – 320 nM

Monodesethyl-amodiaquine (Sapec Fine Chemicals, Lugano, Switzerland)


Naphthoquine phosphate (ZYF Pharm Chemical, Shanghai, China)

50% v/v ethanol 3.13 nM – 200 nM

Piperaquine tetraphosphate (Yick-Vic Chemicals and Pharmaceuticals, Hong Kong)

0.5% w/v lactic acid 6.25 nM – 400 nM

Mefloquine hydrochloride (Sigma)

70% v/v ethanol 0.78 nM – 200 nM

Dihydroartemisinin (Sigma) 70% v/v ethanol 0.78 nM – 51.2 nM

Lumefantrine (Novartis Pharma, Basel, Switzerland)

1:1:1 v/v/v mixture of linoleic acid, ethanol

and Tween 80

3.12 nM – 400 nM

Desbutyl-lumefantrine (Novartis Pharma, Basel, Switzerland)

1:1:1 v/v/v mixture of linoleic acid, ethanol

and Tween 80

3.12 nM – 400 nM

Azithromycin (Pfizer, NSW, Australia)


Pravastatin sodium (Bristol-Myers Squibb, Australia)

DMSO 3.12 µM – 400 µM

Simvastatin (Alphapharm, QLD, Australia)

DMSO 3.12 µM – 400 µM

Rosuvastatin (AstraZeneca, NSW, Australia)

DMSO 3.12 µM – 400 µM

Atorvastatin calcium (Pfizer, NSW, Australia)

DMSO 3.12 µM – 400 µM


70

2.2.4 Plasmodium Lactate Dehydrogenase Assay

2.2.4.1 Principle of pLDH Assay

P. falciparum multiplication correlates with a rise of pLDH activity thus this can be

used to assess parasite growth in response to drug treatment (Roth 1988; Makler et al.

1993a). A modification of the colourimetric method was used (Makler et al. 1993b;

Wong et al. 2010). PLDH is produced as a terminal glycolytic enzyme that converts

lactate to pyruvate in the presence of NAD+ (Figure 2.5). Activities of Plasmodium and

human isoforms can be distinguished by using 3-acetyl pyridine adeninedinucleotide

(APAD), an analogue of NAD+ that is specifically utilised by parasite LDH. Colour

intensity was then measured by absorbance. Inclusion of diaphorase in the solution

amplifies colour production (Figure 2.5).

Figure 2.5 Colourimetric detection of pLDH activity. As the reaction proceeds, the

APADH generated reduces nitro blue tetrazolium (NBT), a yellow compound, to nitro

blue formazan (NBF), a purple compound.

2.2.4.2 Assay Set Up

After incubation, the drug susceptibility plates were subjected to three cycles of freeze-

thawing to facilitate the release of pLDH. The haemolysate was homogenised by

pipetting up and down with a multichannel pipette. A 10 μL sample from each well was

added to 200 µL of Malstat solution (Appendix B), 10 µL of NBT solution (Appendix

B) and 10 µL of diaphorase solution (Appendix B). The pLDH reaction was allowed to

proceed at RT for 45 to 90 min to allow development of colour within the wells.


71

Interference by air bubbles was circumvented by directing a blow-dryer over the plate.

Colour intensity was measured by absorbance at 650 nm (FLUOstar OPTIMA, BMG

biotechnologies) and the data were analysed by non-linear regression (Graphpad Prism

4.0) to construct dose-response curves for determination of drug-specific IC50.

Figure 2.6 pLDH reaction in field isolates of P. falciparum.

2.2.5 3H-Hypoxanthine Incorporation Assay

Hypoxanthine is required for DNA synthesis during parasite replication. The radio-

activity of the incorporated tritium (3H) reflects parasite sensitivity to antimalarial

compounds (Desjardin 1979). Briefly, drug susceptibility assays were set up at a final

mixture of 0.5% parasitaemia at 1.5% hct as previously described (Section 2.2). Each

well consisted of 90 µL of RBC suspension, 100 µL of drug diluted in media and 10 µL

of a 3H-hypoxanthine working solution (5 mg/mL) (Appendix B), resulting in a final

concentration of 0.5 µCi per well. After incubation, the plates were subjected to three

cycles of freeze-thawing and harvested onto a 96-well glass-fibre filtermat (Perkin

Elmer) using a Harvester 96 (Tomtec Incorporated, USA) (Figure 2.7). The filtermat


72

was air-dried and sealed in a plastic envelope with 4 mL beta scintillant (Perkin Elmer)

and counted on a Wallac microbeta liquid scintillation counter (1450 Microbeta Plus).

The data generated were analysed by non-linear regression analysis (Graphpad Prism

4.0).

Figure 2.7 Tomtec Harvester 96 system.

2.3 MOLECULAR TECHNIQUES

The multiplex PCR ligase techniques for the detection of Plasmodium species and

genetic markers for drug resistance were recently developed by collaborators at Case

Western Reserve University (McNamara et al. 2004; Carnevale et al. 2007) (Figure

2.8). This platform enables high-throughput, sensitive and simultaneous diagnosis of

infection by different Plasmodium species. In a similar assay, this approach can

simultaneously detect a large number of SNPs from the pfcrt, pfdhfr, pfdhps, and

pfmdr1 genes that are associated with malarial drug resistance.


73

2.3.1 DNA Extraction

P. falciparum DNA was isolated from whole blood from study participants or parasite

cultures using a DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer’s

protocol. The resulting DNA extracts (~200 µL) were stored at -20°C.

Figure 2.8 Wolstein Research Building, CWRU, Cleveland, Ohio, USA.

2.3.2 Polymerase Chain Reaction (PCR)

2.3.2.1 PCR for Plasmodium Species

A small-subunit ribosomal RNA gene fragment (491 to 500 bp) was amplified for

Plasmodium species diagnosis using oligoprimers and conditions previously described

(Mehlotra et al. 2000; McNamara et al. 2004). Briefly, PCR plates (ThermoGrid™ C-

18096, Denville Scientific Inc, USA) were irradiated with ultraviolet light in a

Stratalinker 2400 UV Crosslinker (Stratagene, CA, USA) before use to destroy any


74

residual nucleic acid. Each well contained 25 µL of PCR master mix solution

(Appendix B) containing 67 mM Tris-HCl (pH 8.8), 6.7 mM MgSO4, 16.6 mM

(NH4)2SO4, 10 mM 2-mercapto-ethanol, 100 µM of dNTPs (Appendix B), 2.5 units of

thermo-stable DNA polymerase and 3 µL of genomic DNA sample. Sequences for

Plasmodium genus specific upstream and downstream primers were 5’-TTC AGA TGT

CAG AGG TGA AAT TCT-3’ and 3’-AAT TAG CAG GTT AAG ATC TCG TTC-3’

respectively (Integrated DNA Technologies, Iowa). The plates were sealed using

Microseal® ‘A’ film (Bio-Rad, USA) and mixed by centrifugation (3000 rpm for 30

sec) and amplification reactions were performed in a PTC-225 Peltier Thermal Cycler

(MJ Research, Iowa). The specific thermocycling conditions used were 92°C for 2 min

(1 cycle), 92°C for 30 sec and 63°C for 2 min (35 cycles), 63°C for 5 min (1 cycle)

(McNamara et al. 2004). PCR amplicons were stored at -20°C until assayed.

2.3.2.2 PCR for pfcrt, pfdhfr and pfdhps genes

The amplification of target sequences for P. falciparum pfcrt, pfdhfr, and pfdhps were

achieved using oligoprimers as described by Carnevale et al (2007). Primers and

thermocycling conditions for the amplification of pfcrt and pfdhfr were optimised to

eliminate the necessity of performing nested reactions (Table 2.2). The upstream and

downstream primers listed in (Table 2.2) were used to prepare master mixtures

(Appendix B) for each drug resistance gene.

2.3.2.3 Controls

Laboratory-adapted P. falciparum strains were obtained from the Malaria Research and

Reference Reagent Resource (MR4; ATCC, VA) and the haemolysate of various strains

(HB3, Dd2, 3D7, K1, 7G8, VS/1 and FCB) were kindly provided by Dr. Peter

Zimmerman (CWRU, Cleveland, Ohio, USA). DNA extracts from seven strains of P.

falciparum were included in each PCR run as batch controls in the Plasmodium species

and drug resistant SNPs assays. Distilled water used in the PCR reaction served as a

negative control for each amplification assay.


75

Table 2.2 PCR primer sequences and thermocycling conditions for pfcrt, pfdhps

and pfdhfr target sequences. Conditions for pfdhfr and pfcrt (Carnevale et al. 2007)

were optimised to eliminate the necessity for performing nested reactions. apfcrt for

SNPs at codons 72 to 76. bdhfr fragment for SNPs at codons 51, 59, 108 and 164. cpfdhps gene fragment for SNPs at codons 540, 581, 613. dPCR programs were

preceded by an initial denaturation step at 95°C for 2 min.

Gene PCR Primer Sequence Thermocycling Condition

d

pfcrt a 5’ -TAATACGACTCACTATAGGGCCGTTA-3’ 5’-ATTAACCCTCACTAAAGGGACGGATG-3’

35 cycles of 95°C for 30 sec, 56°C for 30 sec, 60°C for 1 min

pfdhfr b 5’-TAACTACACATTTAGAGGTCTA-3’

5’-GTTGTATTGTTACTAGTATATAC-3’


pfdhps c 5’-AATGATAAATGAAGGTGCTAGT-3’

5’-ATGTAATTTTTGTTGTGTATTTA-3’


2.3.3 Detection of Amplified Products

To evaluate amplification efficiency, 5 µL of PCR product were premixed with 3 µL of

loading dye buffer and loaded (5 µL) on 2% agarose I gels (Appendix B). For a 96-well

gel, electrophoresis was performed at 290V for 30 min. The gel was subsequently

stained in SYBR Gold (Molecular Probes, Eugene, Oreg.) diluted 1:10,000 in 1 X TBE

buffer (Appendix B) on a rocking platform for 20 min and DNA products were

visualised on a Storm 860 PhosphorImager coupled with Image-Quant version 5.2

software (Molecular Dynamics, CA) (Figure 2.9).


76

Figure 2.9 Electrophoresis and Image processing for DNA visualisation for

evaluating PCR amplification efficiency.

2.3.4 Ligase Detection Reaction Fluorescent Microsphere Assay (LDR-FMA)

The multiplex LDR-FMA facilitates both rapid and specific detection of Plasmodium

species in a single reaction, avoiding cumbersome, separate procedures (McNamara et

al. 2004; McNamara et al. 2006). Similarly, this platform has been adapted to analyse

simultaneously an assortment of SNPs associated with CQ and SP resistance (Carnevale

et al. 2007). The development of a LDR-FMA for pfmdr1 SNPs is described in Chapter

4.

2.3.4.1 Ligase Detection Reaction for Plasmodium species

Briefly, PCR products from the Plasmodium species assay were used directly for LDR

in a master mix solution (Appendix B) containing 20 mM Tris-HCl buffer (pH 7.6), 25

mM potassium acetate, 10 mM magnesium acetate, 1 mM NAD+, 10 mM dithiothreitol,

0.1% Triton X-100, 10 nM (200 fmol) of each LDR primer, 1 µL PCR product and 2

Units of Taq DNA ligase (New England Biolabs, MA). Thermocycling conditions

involved initial heating at 95°C for 1 min, followed by 32 cycles of denaturation at

95°C for 15 sec and annealing/ligation at 58°C for 2 min. LDR primer sequences for

species diagnosis are shown in Table 2.3 (McNamara et al. 2006).


77

Table 2.3 LDR primer sequences for Plasmodium species diagnosis. aLowercased

nucleotides are nonspecific and were added to the rRNA gene LDR primers to reach a

desired specific length. Nucleotide W and R correspond to T or A and G or A

degeneracy, respectively. Pf1 and Pf2, P. falciparum 1 and 2; Pv, P. vivax; Pm, P.

malariae; Po, P. ovale; Common 1 and 2, common sequence. bID, identification. One

hundred unique Luminex microsphere sets are synthesised to exhibit unique

fluorescence. Each microsphere set is coupled to different anti-tag sequences. Anti-tag

sequences are complementary to species-specific tag sequences (adapted from

McNamara et al 2006).

Primer Sequence a ID

b

Pf1 5’-tacactttctttctttctttctttAAA AGT CAT CTT TCG AGG TGA CTT-3’ 12

Pf2 5’-ctatctatctaactatctatacaTGT AGC ATT TCT TAG GGA A TG TTG ATT TTA TAT-3’

78

Pv 5’-cttttcatcttttcatctttcaatAAA ATA AGA ATT TTC TCT TCG GAG TTT ATT C-3’

37

Pm 5’-ttacctttatacctttctttttacAAG AGA CAT TCT TAT ATA TGA GTG TTT CTT-3’

30

Po 5’-ctactatacatcttactatactttTAA GAA AAT TCC TTT CGG GGA AAT TTC-3’ 14

Common1 5’-phosphate-TAG AAT TGC TTC CTT CAG TAC CT T ATG-biotin-3’ 2

Common2 5’-phosphate-TTA GAT WGC TTC CTT CAG TRC CTT ATG-biotin-3’ 3

2.3.4.2 Ligase Detection Reaction for pfcrt, pfdhfr, pfdhps SNPs

Following the PCR amplifications of the pfcrt, pfdhps and pfdhfr genes carrying drug

resistance associated SNPs, the products were combined by transferring 5 µL of each

gene product into a fresh 96 well plate. Pooled PCR products were mixed by

centrifugation and 1 µL was used to prepare the LDR master mixture (Appendix B) and

sealed (sealing film B-1212-5, Denville Scientific Inc) prior to the multiplexed LDR.

Primer sequences for each drug resistance gene are detailed in Table 2.4 (Carnevale et

al. 2007). The LDR thermocycling conditions used were as for Plasmodium species.


78

2.3.4.3 Hybridisation and Reporter Labelling

The second stage of the reaction initiates specific classification of the LDR products,

where hybridisation occurs between anti-tag oligonucleotides probes that are bound to

fluorescent microspheres (Luminex Corporation, TX) specific for the various tag

sequences at the 5’end of the LDR products. The hybridisation and reporter labelling

protocols are the same for Plasmodium species and drug resistance SNPs diagnosis.

This required adding 5 µL of LDR products to 60 µL of pre-warmed hybridisation

solution (Appendix B) containing 250 Luminex FlexMAP microspheres from each

allelic set (total of 18 alleles). The reaction mixture was heated to 95°C for 90 sec and

incubated at 37°C for 35 - 45 min. Reporter labelling of the conjugate followed with the

addition of 6 µL streptavadin-R-phycoerythrin dye (Molecular Probes, OR) diluted 1:50

v:v in TMAC (20 ng/µL) as it binds to the 3’biotin on the conserved sequence primers

at 37°C for 35 - 45 min in 96-well V-bottom plates (Costar 6511 M polycarbonate,

Corning Inc., Corning NY).


79

Table 2.4 LDR primer sequences for drug resistance markers pfcrt, pfdhfr and

pfdhps. aLowercased nucleotides (24 bases) represent tag sequences added to the 5’

ends of each allele-specific LDR primer. bID, identification of Luminex microsphere. cCM, common sequence primer immediately downstream from the allele-specific

primer.

Gene Primer

c Sequence a ID

b

pfcrt CVMNK 5'-aatctacaaatccaataatctcatATTTAAGTGTATGTGTAATGAATAA-3' 60

CVIET 5'-tcataatctcaacaatctttctttAATTAAGTGTATGTGTAATTGAAAC-3' 68

SVMNT 5'-aatcctttctttaatctcaaatcaATTTAAGTGTAAGTGTAATGAATAC-3' 21

72-76 CM 5'-phosphate-AATTTTTGCTAAAAGAACTTTAAAC-biotin-3'

pfdhfr 51 I 5'-caatttcatcattcattcatttcaGAGTATTACCATGGAAATGTAT-3' 35

51 N 5'-ctactatacatcttactatactttGAGTATTACCATGGAAATGTAA-3' 14

51 CM 5'-phosphate-TTCCCTAGATATGAAATATTTT-biotin-3'

59 R 5'-cttttcatcttttcatctttcaatTCACATATGTTGTAACTGCACG-3' 37

59 C 5'-tacactttctttctttctttctttTCACATATGTTGTAACTGCACA-3' 12

59 CM 5'-phosphate-AAAATATTTCATATCTAGGGAAWTA-biotin-3'

108 T 5'-ctaactaacaataattaactaacTTGTAGTTATGGGAAGAACAAC-3' 80

108 S 5'-ctataaacatattacattcacatcTTGTAGTTATGGGAAGAACAAG-3' 69

108 N 5'-tcatcaatcaatctttttcactttTTGTAGTTATGGGAAGAACAAA-3' 59

108 CM 5'-phosphate-CTGGGAAAGCATTCCAAAAAAA-biotin-3'

164 I 5'-ctttctatctttctactcaataatGAAATTAAATTACTATAAATGTTTTATTA-3' 94

164 L 5'-ctatctttaaactacaaatctaacGAAATTAAATTACTATAAATGTTTTATTT-3' 100

164 CM 5'-phosphate-TAGGAGGTTCCGTTGTTTATC-biotin-3'

pfdhps 540 K 5'-ctacaaacaaacaaacattatcaaGGAAATCCACATACAATGGATA-3' 28

540 E 5'-ctttaatcctttatcactttatcaGAAATCCACATACAATGGATG-3' 17

540 CM 5'-phosphate-AACTAACAAATTATGATAATCTAG-biotin-3'

581 A 5'-aatctaacaaactcctctaaatacTTGATATTGGATTAGGATTTGC-3' 76

581 G 5'-ctttcaattacaatactcattacaTTGATATTGGATTAGGATTTGG-3' 43

581 CM 5'-phosphate-GAAGAAACATGATCAATCTATTA-biotin-3'

613 A 5'-tacactttaaacttactacactaaGATATTCAAGAAAAAGATTTATTG-3' 95

613 S 5'-aaacaaacttcacatctcaataatGGATATTCAAGAAAAAGATTTATTT-3' 48

613 CM 5'-phosphate-CCCATTGCATGAATGATCAAA-biotin-3'


80

2.3.4.4 Bio-plex Fluorescent Detection

The SNP or species-specific LDR products with microsphere-labelled anti-tag probes

were detected by dual-fluorescence flow cytometry in the Bio-Plex array reader (Bio-

Rad Laboratories, CA). The chamber temperature was set to 37°C as reporter signals

were collected into allele-specific or species-specific classification bins via the Bio-Rad

software, Bio-Plex Manager 3.0 (Figure 2.10).

Figure 2.10 Bio-plex array reader. LDR-FMA Fluorescence signals of the

Plasmodium species and drug resistance SNPs are detected and sorted into

classification bins by the Bio-plex reader.

2.4 SOLID PHASE MICRO-EXTRACTION (SPME)

Solid phase micro-extraction (SPME) is a sensitive and simple method for the

extraction of volatile organic compounds (VOCs) from gaseous or liquid samples. This

technique was used to detect VOCs in the headspace of P. falciparum cultures. The

SPME fibre (SUPELCO™, Sigma Aldrich) is bonded to a plunger inside a protective

needle (Figure 2.11). The fibre was conditioned initially according to the

manufacturer’s instructions (PDMS phase 250°C for 0.5 hr and triple fibre phase 270°C


81

for 1 hr. Before each analysis, the fibre was activated in the injector port of the gas

chromatography (GC) at 250°C for 5 min and repeated after each sampling. The SPME

fibre was introduced into the headspace of the flask by gently pushing the protective

needle through the septum that sealed the sample flask. The plunger was lowered to

expose the adsorbent fibre to the gaseous phase for one hour at 35⁰C. During this time,

equilibrium between the atmosphere and the fibre was achieved, and the volatile and

semi-volatile organic compounds were adsorbed onto the coating of the fibre. After

retracting the fibre and withdrawing the needle, the syringe sampler was taken to the

gas chromatography-mass spectrometry (GC-MS) for desorption and subsequent

analysis of VOCs. Details of VOCs experiments are described in Chapter 7.

Figure 2.11 Solid phase micro-extraction sampler.


82

CHAPTER 3

IN VITRO SENSITIVITY OF

P. FALCIPARUM TO CONVENTIONAL

AND NEW DRUGS IN

PAPUA NEW GUINEA

Chapter 3 In vitro drug sensitivity of PNG field isolates

84

CHAPTER 3. IN VITRO SENSITIVITY OF P.

FALCIPARUM TO NEW AND CONVENTIONAL DRUGS

IN PAPUA NEW GUINEA

3.1 INTRODUCTION

Resistance of P. falciparum to CQ first emerged in PNG in the 1970’s (Saint-Yves

1971; Grimmond et al. 1976; Yung et al. 1976; Han 1978). As these treatment failures

were infrequent and low grade (RI), CQ or amodiaquine (AQ) were initially retained as

recommended therapy for uncomplicated malaria. However, because higher grade (RII

and RIII) in vivo resistance to CQ and AQ became more widespread (Darlow et al.

1981; Dulay et al. 1987; Schuurkamp et al. 1989; Sapak et al. 1991; Trenholme et al.

1993; Al-Yaman et al. 1996), the PNG Health Department added sulfadoxine-

pyrimethamine (SP) in 2000 to improve clinical efficacy (Casey et al. 2004). This

approach provided relatively brief respite. Further in vivo studies (Marfurt et al. 2007)

and a recently-published large-scale comparative efficacy trial (Karunajeewa et al.

2008a) demonstrated that neither CQ-SP nor AQ-SP met WHO criteria for retention as

first-line treatment in PNG (WHO 2006). As a result, the ACT artemether-lumefantrine

replaced these regimens in 2010. An overview of in vitro and treatment outcome studies

conducted in PNG is presented (Table 3.1)

Because of their relative simplicity and low cost compared with in vivo assessment, in

vitro tests of parasite drug sensitivity can serve as an early warning system for the

emergence of drug resistance (WHO 2005). This includes artemisinin and the longer

half-life partner components of ACT (Price et al. 2004; Ekland et al. 2008; Noedl et al.

2008). The antimalarial activity of the partner drug appears especially important for

selection of an appropriate ACT in countries such as PNG (Karunajeewa et al. 2008b),

but there is often a lack of in vitro data to facilitate this choice. In PNG, for example,

the most recent parasite sensitivity data are from the study period 1995 - 1996 for CQ,

AQ and antifolate drugs (Genton et al. 2005). In this study, the in vitro antimalarial

activities of a range of conventional and novel antimalarial drugs was assessed in P.

falciparum isolates collected from Madang Province where malaria transmission is


85

hyperendemic (Cattani et al. 1986; Mueller et al. 2003) and where there has been

evidence of progression of parasite drug resistance (Darlow et al. 1981; Trenholme et

al. 1993; Al-Yaman et al. 1996; Al-Yaman et al. 1997; Casey et al. 2004; Marfurt et al.

2007).


86

Table 3.1 Overview of in vitro drug sensitivity findings in PNG.

IVR = In vitro resistance reported as percentage, where no inhibitory concentrations were available. Reported median or mean IC50s of antimalarials;

chloroquine (CQ), amodiaquine (AQ), quinine (Q), mefloquine (MQ), halofantrine (HF) and Pyrimethamine (PYR), Cycloguanil (CYC); Schizont

Maturation = microtechnique where drug sensitivity was determined by schizont maturation. (Al-Yaman et al. 1996; Reeder et al. 1996; Hombhanje et

al. 1998a; Hombhanje 1998b; Genton et al. 2005; Mita et al. 2006b; Wong et al. 2010)


87

Authors Province Study

Period

Samples

(n)

CQ AQ Q MQ HF PYC CYC Method

Mita et al

2006

East Sepik 2002-2003 57 IVR 82%

Mean

88 to 107nM

- - - - - - Schizont

Maturation

Genton et

al 2005

East Sepik 1994-1995 36 IVR 50% IVR 27% IVR 0% IVR 8% IVR 0% IVR 4% IVR 6% Schizont

Maturation

Hombhanje

1998b

Central 1995-1996 30 IVR 50%

Median

1150nM

- IVR 10%

Median

2760nM

IVR 0%

Median

350nM

IVR 0.7%

Median

1.0nM

- - Schizont

Maturation

Hombhanje

et al 1998a

Central Not stated 21 - - - - Median

1.5nM

- - Schizont

Maturation

al-Yaman

et al 1996

Madang 1990-1993 35 IVR 86% IVR 86% IVR 7% - - - - Schizont

Maturation

Reeder et al

1996

East Sepik 1990-1992 24 - - - - - IVR 38%

IVR 34%

Schizont

Maturation


88

3.2 MATERIALS AND METHODS

3.2.1 Study Site and Sample Collection

The present study was carried out at the PNG Institute of Medical Research, Yagaum

Hospital, Madang, PNG. The study utilised blood samples taken in 2006 and 2007 from

children aged 6 months to 10 years as part of clinical studies conducted at the

Alexishafen Health Centre in Madang Province and at Modilon Hospital in Madang

town. In all cases, informed consent was obtained from the parents or legal guardians

before recruitment and blood sampling. Scientific and ethical approval for each study

was obtained from the Medical Research and Advisory Committee of the Ministry of

Health of PNG. Of the 64 samples collected, 45 (70.3%) were from children recruited

to a randomised trial of uncomplicated malaria (Karunajeewa et al. 2008b). The

remaining 18 samples (29.7%) were from pharmacokinetic studies conducted at

Alexishafen or studies of severe malaria in progress at Modilon Hospital.

3.2.2 In vitro Culture of Parasite Isolates

In vitro culture of P. falciparum isolates from paediatric patients followed similar

methods to those described in section 2.1.3, with modifications to suit field conditions.

After initial diagnosis of P. falciparum infection from a finger-prick blood smear, 4 mL

venous blood were collected into a heparin-containing tube and transported to the

laboratory within 24 hr. After centrifugation, both plasma and buffy coat were removed.

The packed RBC were washed twice in culture medium and blood smears were

prepared for confirmation of P. falciparum mono-infection and quantification of

parasitaemia by microscopy. Parasites were cultured at 37°C using a modified candle

jar method to create a CO2-rich microaerophilic atmosphere (Trager et al. 1976) (Figure

3.1). The composition of the culture medium was also different under field conditions

(Appendix B). Parasites were maintained in type O human RBC from a non-immune

individual at 5% hct in RPMI 1640 media supplemented with neomycin as well as

gentamycin. Since non-immune human plasma was not available, Albumax II (Gibco)

was used in the complete media (Appendix B).


89

Figure 3.1 Candle jar method used for P. falciparum culture in PNG. A container

into which a lit candle is placed prior sealing the airtight lid. The flame burns until

extinguished by O2 deprivation, creating a CO2-rich microaerophilic environment.

3.2.3 Drug Susceptibility Assays

Stock solutions of CQ diphosphate (Sigma Chemicals, St Louis, USA), AQ

dihydrochloride (Sigma), monodesethyl-AQ (dAQ) (Sapec Fine Chemicals, Lugano,

Switzerland), piperaquine tetraphosphate (PQ) (Yick-Vic Chemicals and

Pharmaceuticals, Hong Kong), naphthoquine phosphate (NQ) (ZYF Pharm Chemical,

Shanghai, China), mefloquine hydrochloride (MQ) (Sigma), lumefantrine (LM)

(Novartis Pharma, Basel, Switzerland), dihydroartemisinin (DHA) (Sigma) and

azithromycin (AZ) (Pfizer, NSW, Australia) were prepared as described in Section

2.2.1.

Drug sensitivity was assessed in triplicate in 96-well plates, with each well containing

100 µL drug-containing media and 100 µL parasitised RBC suspension at 0.5 - 1.0%

parasitaemia and a final hct of 1.5% (Section 2.2). With the exception of AZ, which


90

was incubated for 72 hr due to its slower antimalarial activity (Noedl et al. 2006), all

other plates were incubated for 48 hr at 37°C. The plates were then subjected to four

freeze-thaw cycles to achieve complete haemolysis. The haemolysate were kept frozen

until assayed. A modification of a Plasmodium lactate dehydrogenase (pLDH) detection

method was used to assess parasite growth as detailed in Section 2.2.4 (Makler et al.

1993a; Makler et al. 1993b).

3.2.4 Assay Validation

For validation purposes, the pLDH assay was compared to the reference 3H-

hypoxanthine incorporation method (Chulay et al. 1983) using culture-adapted CQ-

sensitive and CQ-resistant strains of P. falciparum 3D7, W2mef and E8B and a panel of

antimalarial drugs. Briefly, two sets of CQ, MQ and DHA drug dilutions in either

complete media or complete media without hypoxanthine as appropriate for the pLDH

and 3H-hypoxanthine assays, respectively. To allow for between-day variability in assay

performance the drug sensitivity of each P. falciparum strain was assessed

simultaneously using the two methods.

3.2.5 Data Analysis

Statistical analyses were performed using GraphPad PRISM version 4.0 (GraphPad

Software, CA) and Microsoft Excel for Windows. The concentration of drug required to

inhibit parasite growth by 50% (IC50) and 90% (IC90) for each antimalarial drug as

measured by pLDH assay were determined by non-linear regression analysis of

logarithmically-transformed dose-response curves using HN NonLin v.1.1, a free tool

for malaria in vitro drug sensitivity analysis (Noedl 2002). Comparisons between the

IC50 values in laboratory-adapted strains obtained by pLDH and 3H-hypoxanthine

incorporation assays were made using regression analysis (Bablok et al. 1988) and the

Bland and Altman method (Bland et al. 1986). One-way analysis of variance (ANOVA)

was used to compare differences between the IC50 values obtained from the three

different measurement time-points of the pLDH reaction. Associations between IC50

and IC90 values of drug pairs for evaluation of in vitro cross resistance were assessed

using Spearman’s rank correlation co-efficient. Because of the number of comparisons,


91

a significant P-value <0.05 was used throughout. Correlations between the IC50s of CQ,

PQ and LM in a subset of the present patients have been reported previously

(Karunajeewa et al. 2008b).

3.3 RESULTS

3.3.1 Comparison of pLDH and Isotopic Assays

The pLDH assay was compared to the reference 3H-hypoxanthine incorporation method

in cultured-adapted P. falciparum (Figure 3.2). There was a significant linear

correlation between the data obtained by the two IC50 assay methods (r2=0.97, n=26;

P=0.001), with a slope and intercept ([95% confidence intervals]) of 1.13 [1.00 to 1.25]

and 7.83 [-3.3 to 18.98] nM, respectively. The Bland-Altman plot showed that the

pLDH assay sometimes significantly underestimated the IC50 at high values and

provided the least reliable estimations at IC50s >200 nM.

3.3.2 Effect of pLDH Reaction Duration on IC50 Values

For simplicity and efficiency, a single endpoint was used to interpret the results of the

pLDH assay; specifically measurement of the OD when substantial colour contrast had

developed during the enzyme reaction, rather than multiple measurements at 30 sec

intervals over 30 min as originally described (Makler et al. 1993a). In laboratory-

adapted P. falciparum, 45 to 60 min of incubation was adequate for visual evaluation of

dye reduction. At this point in the reaction, the colouration in drug-free wells is intense

(purple), reflecting heavy parasite growth, whilst non-parasitised control wells show

minimal colour change (pink) (see Figure 2.6). In field isolates however, the rate of

pLDH dye reduction varied between samples, with some requiring up to 2 hr to produce

maximal contrast.


92

Figure 3.2 Comparison of pLDH and 3H-hypoxanthine incorporation methods for

analysis of antimalarial sensitivity in culture-adapted P. falciparum. Upper panel:

correlation plot of IC50s obtained by both methods, red circles for CQ, open circles for

MQ and triangles for DHA. Lower panel: Bland-Altman plot of difference between the

pLDH and 3H-hypoxanthine incorporation data vs the mean of the two methods.


93

To investigate whether the IC50 values calculated for antimalarial drugs were influenced

by the duration of pLDH incubation, dose-responses curves for six antimalarial agents

assessed against four field isolates were determined from OD measurements at 80, 120

and 180 min, and their respective IC50s compared (Figure 3.3). The majority of isolates

tested produced similar dose-response curves to each respective antimalarial drug over

a 3 hr period (data not shown). In some isolates (e.g. 106 and 112 in Figure 3.3), an

increase in CQ IC50 was observed with reaction time. This increase was due to greater

colour contrast as the reaction proceeded, causing changes in the slope of the dose-

response curve. Overall, there were no significant differences between IC50s calculated

from data measured at 80 to 180 min (n=93; P=0.60). When IC50s were plotted against

pLDH reaction time (Figure 3.4), the general distribution of data points was similar

between groups, with collective median IC50s of 15.7, 15.9 and 16.7 nM at 80, 120 and

180 min, respectively.

3.3.3 Field Application of the pLDH Assay

The in vitro activities of nine antimalarial drugs against P. falciparum isolates from

paediatric patients with uncomplicated malaria were evaluated. Blood samples with

parasitaemia ranged between 0.3 to 14% were included in the drug sensitivity assay.

Samples with inadequate RBC were only screened against 4-aminoquinolines drugs. Of

125 field isolates obtained, 64 (51%) were both cultured successfully and provided

valid data drug sensitivity data by pLDH assay. Loss of isolates reflected mainly

logistic issues with transportation, and laboratory-related problems including power

supply reliability, reagent availability, clotting of blood samples due to inadequate

mixing with anticoagulant and bacterial contamination. Experiments involving LM,

DHA and AZ were only undertaken during the latter part of the study period. The

distribution of IC50s in response to antimalarial drugs is illustrated in Figure 3.5.


94

Figure 3.3 Effect of pLDH reaction time on IC50s in PNG P. falciparum. Four

samples of P. falciparum were tested against six antimalarial drugs; chloroquine (CQ);

piperaquine (PQ); desethyl-amodiaquine (dAQ); amodiaquine (AQ); naphthoquine

(NQ) and mefloquine (MQ). Optical measurements were taken at 80, 120 and 180 min

into the pLDH reaction. IC50s were calculated for each time point for comparison.


95

Figure 3.4 Scatter plot of IC50s determined from three pLDH time points. IC50

values for CQ, PQ, AQ, dAQ and MQ at three different time points were compared in

18 field isolates of P. falciparum. Optical measurements were collected at 80, 120 and

180 min into the pLDH reaction from which IC50s were determined and plotted. The

median for each time point is shown.


96

Figure 3.5 Distribution of 50% inhibitory concentrations (IC50) of antimalarials against PNG P. falciparum isolates.

Piperaquine (PQ), amodiaquine (AQ), desethyl-amodiaquine (dAQ), chloroquine (CQ), naphthoquine (NQ), mefloquine (MQ), dihydroartemisinin

(DHA), lumefantrine (LM) and azithromycin (AZ).


97

3.3.4 Antimalarial Susceptibility of PNG P. falciparum Isolates

The mean IC50 and IC90 values for the nine antimalarial drugs are summarised in Table

3.2. The accepted in vitro resistance threshold for CQ (≥100 nM) is based on the in

vitro response of African isolates obtained from malaria-infected, non-immune

individuals taking CQ prophylaxis and semi-immune patients failing to respond to CQ

treatment (Le Bras et al. 1990; Cremer et al. 1995; Ringwald et al. 1996; Basco et al.

2002). This threshold was obtained using the reference 3H-hypoxanthine incorporation

method but has been employed in many subsequent studies using different techniques

for in vitro drug susceptibility assessment (Attlmayr et al. 2006; Kaddouri et al. 2006;

Mayxay et al. 2007; Nkhoma et al. 2007). Because there was close agreement between

the pLDH and 3H-hypoxanthine methods in the present study at this concentration, a

100 nM cut-point was used, with 82% of isolates tested exhibiting an IC50 above this

level. In vitro resistance thresholds for the other antimalarial drugs tested have not been

established through valid correlative in vivo studies.


98

Table 3.2 In vitro susceptibilities of P. falciparum PNG isolates against 4-

aminoquinolines and other antimalarial drugs. IC50 = 50% inhibitory drug

concentrations and IC90 = 90% inhibitory drug concentrations, CI = confidence interval.

3.3.5 Correlations of in vitro Responses to Nine Antimalarials

Correlations between IC50 values for the panel of antimalarial drugs are shown in Table

3.3. Apart from LM, there were strong associations between the IC50s of 4-

aminoquinoline (CQ, AQ, DAQ and NQ), bisquinoline (PQ) and aryl-aminoalcohol

(MQ) compounds. Although the numbers of isolates tested were low, AZ activity did

not correlate significantly with that of any other drug. The artemisinin derivative DHA

IC50 values showed positive associations with those of the 4-aminoquinoline and related

compounds.

Isolates tested (n)

IC50 (nM) Mean (95% CI)

IC90 (nM) Mean (95% CI)

Chloroquine 63 215 (175 – 254) 431 (382 – 480)

Amodiaquine 64 26.3 (18.8 – 33.7) 54.3 (42.9 – 65.7)

Desethyl-amodiaquine 60 23.1 (19.4 – 26.8) 48.8 (38.7 – 58.8)

Piperaquine 57 15.5 (10.8 – 20.2) 48.8 (30.3 – 67.4)

Naphthoquine 41 10.3 (6.7 – 13.9) 31.0 (21.0 – 41.0)

Mefloquine 58 7.8 (5.8 – 9.8) 21.2 (16.2 – 26.2)

Lumefantrine 25 4.6 (1.1 – 8.0) 12.7 (5.7 – 19.7)

Dihydroartemisinin 30 3.5 (1.9 – 5.1) 11.1 (7.2 – 15.0)

Azithromycin 15 13,895 (6,277 – 21,513)

39,471 (21,300 – 57,642)


99

Table 3.3 Spearman correlation co-efficients for associations between IC50 values.

The number of drug pairs analysed are shown in parentheses. *P<0.05, **P<0.01, ***P<0.001.

Chloroquine Amodiaquine Desethyl-

amodiaquine Piperaquine Naphthoquine Mefloquine Lumefantrine Dihydro-

artemisinin

Amodiaquine 0.46***

(60)

Desethyl-amodiaquine

0.45***

(58)

0.61***

(57)

Piperaquine 0.51***

(54)

0.59***

(53)

0.51***

(55)

Naphthoquine 0.56***

(37)

0.61***

(36)

0.64***

(37)

0.74***

(36)

Mefloquine 0.61***

(54)

0.52***

(57)

0.37**

(52)

0.52***

(48)

0.52**

(32)

Lumefantrine 0.09

(22)

0.18

(24)

0.35

(19)

0.17

(17)

0.25

(7)

0.47*

(23)

Dihydro- artemisinin

0.45*

(27)

0.37*

(29)

0.43*

(24)

0.22

(20)

0.84**

(10)

0.57**

(28)

0.31

(23)

Azithromycin 0.56

(12)

0.12

(13)

0.54

(9)

0.18

(9)

-0.50

(3)

0.24

(12)

-0.12

(12)

-0.29

(12)


100

3.4 DISCUSSION

The high prevalence of in vitro CQ resistance in the present study accords with recent

local molecular and clinical data. A number of genotyping studies have reported near-

fixation of the CQ resistance-associated mutation pfcrt in PNG (Mehlotra et al. 2005;

Carnevale et al. 2007). In addition, the significant rates of in vivo CQ-SP treatment

failure in the Madang area (Marfurt et al. 2007; Karunajeewa et al. 2008b) are also

consistent with the present in vitro findings, although mutations associated with SP

resistance will have contributed (Casey et al. 2004; Mita et al. 2007; Saito-Nakano et

al. 2008).

The IC50s for AQ and its active metabolite dAQ in the present study were much lower

than in previous studies from PNG (Trenholme et al. 1993; Al-Yaman et al. 1996). This

is likely to reflect methodological differences, since microscopic assessment of schizont

maturation produces IC50 values several times higher than those derived from

radioisotope incorporation (Wernsdorfer et al. 1988) and, by implication, from the

pLDH assay. However, consistent with the present IC50 data, a recent study from

neighbouring East Sepik Province found a much lower prevalence of in vitro resistance

to AQ than CQ (Genton et al. 2005).

Clinical studies in PNG have found equivalent high treatment failure rates for AQ-SP

and CQ-SP (Marfurt et al. 2007; Karunajeewa et al. 2008b). However, AQ-SP is used

in younger children (those <19 kg in body weight) than CQ-SP under PNG national

treatment guidelines (PNGDOH 2000). This means that a lack of immunity may offset

relative parasite sensitivity to AQ in this age-group, producing comparable failure rates

to those with CQ-SP in older children. Indeed, AQ is more effective than CQ in African

children of similar age (Brasseur et al. 1999; Oduro et al. 2005; Pradines et al. 2006).

Nevertheless, there may not be a clear relationship between AQ in vitro parasite

sensitivity and clinical outcome (Trenholme et al. 1993; Pradines et al. 2006).

A valid in vitro resistance threshold for PQ remains to be confirmed. An IC50 <100 nM

has been used to identify sensitive strains of P. falciparum by radioisotope uptake

(Deloron et al. 1985; Basco 2003b; Mwai et al. 2009b), while Chinese investigators


101

have reported resistant isolates with IC50 values >300 nM using the schizont maturation

microtechnique (Yang et al. 1999b; Lin et al. 2005). All PQ IC50 values in the present

study were <100 nM. Sixteen of the isolates were from children treated with DHA-PQ

in the recent comparative clinical trial (Karunajeewa et al. 2008b) and one (IC50 19.5

nM) was a late parasitological failure. These various data suggest that further in vivo-in

vitro correlation studies are needed to establish a clinically meaningful resistance

threshold for PQ.

MQ has not been used previously in PNG. All isolates had MQ IC50 values below the

resistance threshold of 108 nM established recently using in vivo responses, 3H-

hypoxanthine uptake and molecular characteristics including the number of copies of

the P. falciparum multidrug resistance 1 (pfmdr1) gene (Price et al. 2004). This

threshold was also employed in a study of field isolates from Laos which were assessed

using the pLDH method (Mayxay et al. 2007). The present in vitro MQ data are

consistent with the results of a recent molecular survey that reported an absence of

multiple copies of pfmdr1 gene in PNG isolates (Hodel et al. 2008).

Data from this current study are the first characterising the in vitro sensitivity of PNG

isolates to LM and NQ, drugs that have both recently become available as part of ACT

in PNG. A previously published resistance threshold for LM of >150 nM was based on 3H-hypoxanthine uptake studies in African isolates without in vivo correlation (Basco et

al. 1998). None of the PNG isolates had an IC50 value above this level. There are no

equivalent published cut-points for NQ but the median IC50 (10.3 nM) was less than

those reported for isolates from Southern China using the micro-test method (mean 88.5

nM for ‘artesunate-sensitive’ and 119.4 nM for ‘artesunate-resistant’ strains) (Yang et

al. 1999a). The IC50 values for DHA were all below the suggested cut-point of 10.5 nM

derived from 3H-hypoxanthine uptake studies in African isolates without in vivo

correlation (Pradines et al. 1998). The AZ IC50s from the present study (mean 13.9 µM)

are also largely below a previously reported range derived from Thai isolates and the

micro-test technique (mean 29.3 µM) (Noedl et al. 2001).

The positive inter-correlations between IC50 values for 4-aminoquinoline and related


102

compounds have been reported in studies from other countries (Fan et al. 1998; Yang et

al. 1999a; Basco et al. 2003a; Pradines et al. 2006). These findings are consistent with

the observation that pfcrt alleles influence parasite susceptibility to drugs other than CQ

such as MQ (Sidhu et al. 2002; Johnson et al. 2004; Sidhu et al. 2005), but other

mechanisms such as common drug-specific effects on parasite haem polymerase may

be involved (Slater et al. 1992; Dorn et al. 1998). It is also possible that the positive

associations in the present study reflect general parasite fitness rather than shared

resistance determinants, but the lack of significant associations involving LM and AZ,

also reported by others (Noedl et al. 2001; Noedl et al. 2007), are against this. The IC50

values for PQ correlates with CQ, AQ and dAQ in the present study. However, this is

not the case in the African data set (Mwai et al. 2009b), raising questions about

mechanisms of action of PQ. In addition, the African study showed consistent inverse

relationship between LM sensitivities and CQ which has also be reported by others

(Pradines et al. 1999b; Price et al. 2006). These differences in the African and PNG

findings may be due to variations in methodologies (i.e. longer assay time of 84 hr,

adaption of field isolates to long-term culture prior to sensitivity testing) and different

histories of parasite drug exposure. As with most antibiotics with antimalarial activity,

the macrolide AZ is relatively weak and slow-acting, and best used as adjunctive

therapy (Anderson et al. 1995; Noedl et al. 2006; Noedl et al. 2007).

Lumefantrine and MQ are aryl-aminoalcohols with related chemical structures and a

similar mode of action (Peel et al. 1994; Basco et al. 1998; Pradines et al. 2006).

However, a significant correlation was found between the LM IC50s and those of MQ

but not with the other long half-life antimalarial drugs. This observation is in accord

with previous reports (Basco et al. 1998; Pradines et al. 2006) and is also consistent

with the significantly better clinical response to artemether-LM than DHA-PQ in a

recent comparative trial (Karunajeewa et al. 2008b). There were generally weak

associations between DHA IC50s and those of other drugs, consistent with the findings

of others (Basco et al. 2003a; Attlmayr et al. 2005; Pradines et al. 2006; Noedl et al.

2007). There is some evidence that pfcrt status influences the antimalarial activity of the

artemisinin derivatives (Sidhu et al. 2002), but the known association between P.

falciparum sensitivity to these drugs and pfmdr1 mutations and copy number (Sidhu et

al. 2005; Sidhu et al. 2006) does not apply in PNG (Hodel et al. 2008).


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PLDH assessment of P. falciparum drug sensitivity was originally described as a

kinetic assay requiring repeated measurement of absorbance (Makler et al. 1993a). This

method determines the mean Vmax (mOD/min) of pLDH activity reflecting parasite

growth (Makler et al. 1993a; Basco et al. 1995). A recent field study in Malawi

employed a similar single pLDH measurement as used in the present study (Druilhe et

al. 2001; Nkhoma et al. 2007). The IC50s determined by the kinetic approach correlated

positively with those determined by the reference isotopic method (Makler et al. 1993a;

Basco et al. 1995). In the interests of simplicity and efficiency in the field where a

spectrophotometer was not readily accessible, non-kinetic assessment of pLDH activity

was more convenient. The IC50s from this approach correlated well with the isotopic

method although it tended to overestimate the IC50s above 100 nM as shown in the

Bland-Altman analysis.

Unlike culture-adapted strains, P. falciparum isolates from patients varied in their in

vitro growth and consequent pLDH activity. A number of isolates failed to develop over

the 48 hr incubation period, hence little colour contrast was observed between drug-free

controls, antimalarial-dosed and non-parasitised control wells on pLDH assay. Some

isolates developed colour intensities more slowly than others, for which the OD at 180

min into the pLDH reaction was measured. The use of a pre-test was helpful in reducing

reagent wastage and for determining measurement time. This involved first testing the

haemolysate from one drug-free and one non-parasitised well from each sample and

time for colour development prior to running all three 96-well plates.

During validation of the modified pLDH method, efforts were made to ensure

comparability with the reference 3H-hypoxanthine incorporation technique. Factors

underlying between-day variations of in vitro estimates of drug sensitivity include the

time-dependent growth characteristics of the cultures. To minimise such effects on

assay performance, both assays were conducted in parallel and on the same day. In

order to reduce unnecessary transfer and handling of radioactive material, two sets of

drug dilutions were prepared for each method (one lacking hypoxanthine) rather than

taking an aliquot of cell suspension from the isotopic test wells for pLDH assessment,

as has been done previously (Makler et al. 1993a). Two data points showed


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unexpectedly high IC50s by the isotopic method for MQ (Figure 3.2), the influence of

these outliers may be reduced if more samples were examined for this drug. Agreement

between the two methods may be more substantial if the drug dilutions used or

haemolysate were from the same experiment set. Although it is worth noting that

previous reports have only compared correlations and not the agreement between the

two methods (Basco et al. 1995; Delhaes 1999).

The present study provides baseline data at a time when, as a result of the findings of a

large-scale clinical trial (Karunajeewa et al. 2008b), the treatment of uncomplicated

malaria in PNG will change from AQ-SP or CQ-SP to artemether-LM. Ongoing

assessment of in vitro sensitivity using the same techniques will facilitate assessment of

the adequacy of such treatment. Conventional monitoring involves the WHO micro-test

with labour-intensive visual enumeration of schizonts (Al-Yaman et al. 1996;

Hombhanje 1998b). The colourimetric pLDH assay allows prompt semi-automated

generation of parasite growth data from triplicate experiments involving multiple

antimalarial drugs. The IC50 values generated correlate well with those derived using 3H-hypoxanthine incorporation and there is no issue with disposal of radioisotopes, an

important consideration in countries such as PNG. Assays based on pLDH

quantification have been recently introduced for screening patient isolates against

multiple antimalarial drugs in Africa and Asia (Brockman et al. 2004; Kaddouri et al.

2006; Nkhoma et al. 2007). The assay may serve to monitor the possible reversal of CQ

resistance after its official withdrawal in PNG as evident in Malawi (Laufer et al. 2006).

Rational drug policy in countries such as PNG can only benefit from such convenient,

high-throughput in vitro testing, especially if this is done regularly so that emerging

resistance can be identified with relative confidence at an early stage.

This work for the most part has been published in Tropical Medicine and International

Health, titled “In vitro sensitivity of Plasmodium falciparum to conventional and novel

antimalarial drugs in Papua New Guinea”. Work regarding methodology validation has

been published in Malaria Journal, titled “A comparative study of a flow-cytometry-

based assessment of in vitro Plasmodium falciparum drug sensitivity”. A small portion

of data relating to drug sensitivity has been published in The New England Journal of

Medicine, titled “A trial of combination antimalarial therapies in children from PNG”.

CHAPTER 4

CHARACTERISATION OF DRUG

RESISTANT POLYMORPHISMS OF

P. FALCIPARUM USING A NEW

MOLECULAR ASSAY

Chapter 4 Molecular Characterisation of PNG isolates

106

CHAPTER 4. CHARACTERISATION OF DRUG

RESISTANT POLYMORPHISMS OF P. FALCIPARUM

USING A NEW MOLECULAR ASSAY

4.1 INTRODUCTION

Resistance of Plasmodium species to 4-aminoquinolines emerged in PNG in 1976 and

has since spread across the country (Grimmond et al. 1976; Marfurt et al. 2007). In

addition, mass dosing of pyrimethamine in the 1960’s conveyed continuous drug

pressure on the parasite population that led to the selection of resistant mutations. High-

level resistance has been documented both in vivo (Darlow et al. 1980; Marfurt et al.

2007; Karunajeewa et al. 2008b) and in vitro (Reeder et al. 1996; Mita et al. 2006a).

Chloroquine (CQ) or amodiaquine (AQ) monotherapy was retained as first-line

treatment for uncomplicated malaria until 2000 when sulfadoxine/pyrimethamine (SP)

was added to improve clinical efficacy (Casey et al. 2004). Despite initial success, cure

rates have since declined (Marfurt et al. 2007; Karunajeewa et al. 2008b).

Parasite drug resistance is largely assessed in three ways. The reference assessment is

by clinical efficacy trials where treatment outcome is monitored. However, they are

costly, time consuming, and patient recruitment and follow-up are often difficult (WHO

2005). Parasite drug sensitivity can be tested in vitro, but it can be labour intensive

particularly if multiple drugs are to be screened for each sample. With advancing

technology, molecular surveillance of malaria resistance is increasingly valuable as it

overcomes many challenges associated with clinical and in vitro approaches.

Single nucleotide polymorphisms (SNPs) in parasite genes determining drug effects can

underlie resistance. Mutations in the P. falciparum chloroquine transporter (pfcrt) gene,

in particular K76T, is central to determining the phenotype of CQ resistance and in

predicting treatment failure (Fidock et al. 2000; Basco et al. 2002). The pfcrt K76T

mutation is often associated within different amino acid haplotypes (CVIET, CVMNT,

CVMET, or SVMNT residues 72-76), however the roles of these haplotypes is not well


107

defined except that they are reflective of the parasite’s geographic origin (Fidock et al.

2000).

Higher-levels of CQ resistance result from other SNPs and is inversely associated with

the copy number of the multidrug resistance 1 (pfmdr1) gene (Foote et al. 1990; Reed et

al. 2000; Babiker et al. 2001; Pickard et al. 2003). Pfmdr1 gene polymorphisms also

confer resistance to other antimalarials including quinine, mefloquine, lumefantrine and

halofantrine (Cowman et al. 1994; Peel et al. 1994; Reed et al. 2000). Of particular

concern are the results of a pfmdr1 gene allelic replacement study in which various

polymorphisms reduced artemisinin susceptibility in cloned parasite lines (Reed et al.

2000). The study showed pfmdr1 polymorphisms at codons 86, 1034, 1042 and 1246

altered artemisinin susceptibility in D10 and 7G8, originating from PNG and South

America, respectively. This finding has serious implications for future prospect of

artemisinin effectiveness in endemic areas.

Polymorphic changes in the genes encoding dihydrofolate reductase (dhfr) and

dihydropteroate synthetase (dhps) underlie parasite resistance to pyrimethamine

(Cowman et al. 1988; Peterson et al. 1988) and sulfadoxine (Triglia et al. 1994; Triglia

et al. 1999), respectively. The S108N mutation in dhfr is a primary determinant of

pyrimethamine resistance and additional mutations at codons 16, 50, 51, 59, 140 and

164 cause higher-level resistance (Cowman et al. 1988; Peterson et al. 1988). Similarly,

polymorphisms involving S436A/F, A437G, and K540E in the pfdhps gene confer

initial mutation to sulfadoxine. Other genetic alterations such as A581G and S613A will

lead to higher-level resistance (Triglia et al. 1994; Triglia et al. 1999). Almost all

strains of P. falciparum from patients from Madang Province in PNG who fail CQ-SP

treatment carry pfcrt K76T and pfmdr1 N86Y, while pfdhfr C59R and S108N are also

found at moderate/high levels, reflecting the selective pressure from long periods of CQ

and pyrimethamine usage (Casey et al. 2004; Carnevale et al. 2007).

At present, most molecular techniques for SNP analysis are based on PCR restriction

fragment length polymorphism (RFLP), sequence-specific oligonucleotide probe

hybridisation (SSOPH) and direct sequencing. However, most such methods identify a


108

small number of candidate SNPs regarded as primary predictors of clinical resistance

(Ranford-Cartwright et al. 2002). Mutations that are not directly involved in resistance

but which may have compensatory or modulating effects that contribute to the overall

phenotype are often omitted. An approach based on DNA microarray allows parallel

detection of multiple SNPs (Crameri et al. 2007), but remains relatively expensive. An

alternative technique is a post-PCR ligase detection reaction-fluorescent microsphere

assay (LDR-FMA) that enables cost-effective evaluation of 22 SNPs (Carnevale et al.

2007).

In view of the importance of a low-cost system for large-scale monitoring of drug

resistance in developing countries, the present study further expanded this system to

detect an additional 10 different pfmdr1 allelic variants. In addition to assay

development, this new technique has been applied in a study of key drug resistance

mutations in P. falciparum field isolates from clinical studies conducted in PNG. The

prevalence of different allelic variants of the pfcrt, pfdhfr, pfdhps and pfmdr1 genes are

presented. Associations between these mutations and treatment outcome are also

examined.


4.2.1 Field Studies, P. falciparum isolates

The present study utilised a subset of 402 samples for Plasmodium speciation from a

large-scale treatment trial in children aged 6 months to 5 years (mean 36 months) with

uncomplicated malaria (Karunajeewa et al. 2008b) (Australian New Zealand Clinical

Trials Registry ACTRN12605000550606). The study was conducted between 2005 and

2007 in Madang and East Sepik Provinces. Participants were assigned CQ-SP,

artesunate-SP (ART-SP), piperaquine-dihydroartemisinin (PQ-DHA) or artemether-

lumefantrine (AL). Children who had been treated with antimalarial drugs within the

previous 14 days were excluded. The samples used in the present study were those

collected at baseline prior to treatment allocation. Full details of the trial protocol have

been published previously (Karunajeewa et al. 2008b).


109

The number of samples that were assayed for pfcrt, pfdhps and pfdhfr genotypes from

the treatment groups CQ-SP, ART-SP, PQ-DHA and AL were 81, 86, 94 and 90,

respectively (total of 351) and for pfmdr1 were 63, 65, 79 and 72 respectively (total of

279) due to limited sample volume. Efficacy was assessed over 42 days using WHO

definitions (WHO 2003) with correction for re-infections by PCR genotyping

(Karunajeewa et al. 2008b), specifically adequate clinical and parasitological response

(ACPR), early treatment failure (ETF; an inadequate parasitological response and/or

worsening of clinical signs by day 3), late parasitological failures (LPF; emergent

parasitaemia between days 4 and 42), or late clinical failure (LCF; where LPF was

associated with fever). Informed consent was obtained from the parents/guardians

before recruitment. Scientific/ethical approvals for the main study and present sub-

study were obtained from the Medical Research and Advisory Committee of the

Ministry of Health of PNG, the University Hospitals Case Medical Centre and the

University of Western Australia Human Research Ethics Committee.

4.2.2 Genomic DNA

Laboratory-adapted P. falciparum strains including 3D7, Dd2, K1, 7G8 and HB3 were

provided by MR4, American Type Culture Collection. DNA was extracted from 200 µL

whole blood (field samples) or haemolysate (laboratory-adapted strains) using the

QIAmp 96 DNA blood kit or DNeasy Blood and Tissue Kit (Qiagen, CA) under the

manufacturer’s protocol (Section 2.3.1).

4.2.3 Plasmodium Speciation

Detection of Plasmodium species was by amplification of ssu rDNA by a modified

multiplex LDR-FMA (McNamara et al. 2006). Parasite genomic DNA served as

templates for the PCR primers flanking the small-subunit rRNA gene fragment (491-

500 base-pairs). This domain contains sequences conserved within the Plasmodium

genus and those that are species-specific (Section 2.3.2.1). All PCR reactions (25 µL)

were performed using a Peltier Thermal Cycler, PTC-225 (MJ Research, MA)

consisting of 3 µL genomic DNA in a master mix containing 3 pmol of appropriate


110

upstream and downstream primers (Section 2.3.2.1).

To evaluate amplification efficiency, the PCR products were visualised by

electrophoresis on 2% agarose gels stained with SYBR Gold and images were acquired

using a Storm 860 (Section 2.3.3). This was followed by species-specific ligase

detection reaction (LDR) as described previously (Section 2.3.4.1 and Table 2.3). LDR

utilises the ability of DNA ligase to preferentially join adjacent oligonucleotides to the

target PCR amplicon where there is a perfect complementation at the junction during

hybridisation.

The second step involves hybridisation of LDR products with anti-tag oligonucleotides

coupled with Plasmodium species-specific microspheres (Section 2.3.4.3). These

microspheres (Luminex Corporation, TX) are embedded with varying ratios of

red:infra-red fluorochromes and emit unique fluorescent ‘classification’ signatures. The

hybridised mixture is then labelled with a reporter dye (streptavidin-R-phycoerythrin,

Molecular Probes, OR) through binding to the biotin end of the LDR conjugate.

Fluorescent signals are sorted into allele-specific ‘bins’ by the bioplex array reader

(Bio-Rad Laboratories, CA).

4.2.4 Detection of Drug Resistant Polymorphisms

Amplification of target sequences for P. falciparum pfdhps, pfdhfr, pfcrt (Carnevale,

2007) and pfmdr1 were achieved using oligoprimers and conditions described in Table

2.2 and Section 4.3.1.1, respectively. Following PCR, the products were combined in a

multiplexed LDR (Table 2.4 and Section 4.3.1.2). Upstream LDR primers are allele-

specific and contain the complementary base to the SNP of interest at the 3’ end (Figure

4.1). The upstream primers were designed to have unique tag sequences of 24

nucleotides at the 5’ end that enables subsequent identification of specific SNPs.

Downstream LDR primers contain conserved sequence oligonucleotides and were 5’

phosphorylated and 3’ biotinylated.


111

Figure 4.1 Principle of LDR-FMA diagnosis of drug resistant polymorphisms.

Top: Main components in the reaction. Middle: During thermocycling, the LDR primers

hybridise to the PCR products with matching base-pairs. If there is a perfect match

between the junctions of adjacent LDR primers, the gap will be sealed by DNA ligase.

A single base mismatch will not result in ligation. Bottom: LDR products are hybridised

with anti-tag oligonucleotides coupled to microspheres that report signals specific to the

SNPs of interest. This is followed by labelling with streptavidin-R-phycoerythrin

(SAPE) through binding to biotin.


112

During thermocycling, the LDR primers hybridise to PCR products with matching base-

pairs. As a result, the LDR primers specific to the gene and SNP of interest are brought

together in close proximity. If there is a perfect match at the junction of the LDR

upstream and downstream primers, the nick will be sealed by a DNA ligase. A single

base mismatch will not result in ligation. Hence, this step is highly specific (Figure 4.1).

Details of the LDR for pfcrt, pfdhfr, and pfdhps are described in Section 2.3.4.2.

Recipes for PCR and LDR master mix solutions and respective primer sequences are

outlined in Appendix B.

4.2.5 Data Analysis

Statistical analysis was performed using GraphPad PRISM version 4.0 (GraphPad

Software, CA). Fluorescent signals from the field samples were classified positive or

negative for drug susceptibility markers according to thresholds determined by

standardised procedures. Fluorescent signals were first normalised to a mean of 10,000

and SD 1,000 arbitrary units for each codon by subtracting the calculated mean from

every signal within the corresponding codon, then multiplying by 1,000/codon-specific

SD, and finally adding 10,000. The same procedure was applied to fluorescent signals

from culture-adapted strains with known genotypes, thus providing controls within each

SNP assay. Once adjusted, codon-specific cut-points that applied to all control strains

were derived with a value that predicted the highest number of true positives as a

conservative cut-point for distinguishing positive signals from background

fluorescence.

A cut-point of >9600 had 97.5%, 98.8% and 98.6% accuracy for predicting true

positive alleles for codons 540, 581 and 613 in the pfdhps gene in control strains. The

>9600 cut-point also applied to codons 1042 and 1246 in the pfmdr1 gene, while >9800

accurately predicted known alleles at codon 86 in the pfmdr1 gene, codons 51, 59, 108

and 164 in the pfdhfr gene, and in the CVMNK, SVMNT, and CVIET pfcrt haplotypes.

A threshold of >10,000 applied to pfmdr1 codons 184 and 1034. By reversing the

normalisation process, the cut-points were made specific to each drug resistance

marker. A similar approach that uses polar-co-ordinates has also been used to determine

thresholds for the LDR-FMA system (DaRe et al. 2010).


113

Mixed strain infections can be identified when fluorescence signals from both alleles

(i.e. wild type and mutated) from the same codon occur above calculated cut-points.

Previous experiments have shown that strain-specific allele fluorescence signals are in

direct proportion to the ratio of the parasite strain densities within the sample

(Carnevale et al. 2007). Therefore, Day 28 and day 42 post-treatment blood samples

from patients from the clinical trial (Karunajeewa et al. 2008b) that were parasite

negative by both microscopy and PCR were assayed from which very low fluorescence

signals (<200) were found. These observations indicate that multiple P. falciparum

strains and non-falciparum DNA such as that from the human host do not interfere with

SNP detection by LDR-FMA. While haplotypes were assigned based on the dominant

allele signals at each locus, they have masked the presence of a minor clone in the case

of a multiple strain infection. Although multiplicity of infection (MOI) was not

calculated in the analysis of drug resistance haplotypes, efforts were made to exclude

samples showing mixed infection at more than two loci. In addition, previous studies

have shown that multiclonal infections are rare in PNG, with a mean MOI of 1.3 - 1.8

(Felger et al. 1994; Cortes et al. 2004).

Associations between parasite mutations and measures of treatment outcome were

assessed using Fisher’s exact test or ANOVA with Bonferroni post hoc adjustment for

multiple comparisons (SPSS v16.0, Chicago IL).

4.3 RESULTS

4.3.1 Pfmdr1 LDR-FMA Development

4.3.1.1 PCR Optimisation

Pfmdr1 SNPs are clustered in two regions approximately 2000 base-pairs (bp) apart.

Two sets of PCR primers (Integrated DNA Technologies) were designed for the

amplification of pfmdr1 polymorphisms at codons 86 and 184 (a total of 4 alleles)

designated as region 1, and polymorphisms at codons 1034, 1042 and 1246 (a total of 6

alleles) as region 2.


114

Previously designed PCR primers and conditions for pfmdr1 regions 1 and 2

(Carnevale, unpublished) were tested in seven laboratory strains of P. falciparum. This

involved two successive runs of PCRs with the second intended to amplify a target

sequence within the first-run product (i.e. nested PCR). Well defined PCR products of

expected size (~294 bp) were observed for 6 of the 7 control strains from pfmdr1 region

1. The nested 1 amplification of pfmdr1 region 2 was less successful, producing very

light bands. Non-specific amplification including multiple bands and smearing in the

nest 2 reaction was likely due to sub-optimal annealing temperature (TA).

To improve amplification specificity, gradient experiments were employed to select for

the optimal TA. This was tested using genomic DNA from 7G8 (Figure 4.2). PCR

amplification was successful across TA of 40°C to 60°C for region 1. For region 2

however, specificity increased when TA was >48°C. Since 56°C was the optimal TA for

the PCR amplification of other drug resistant genes (pfcrt, pfdhfr and pfdhps), it was

used for pfmdr1 for further validation.

The necessity of a nested PCR was assessed. Firstly, PCR products from the pfmdr1

region 2 nest 1 were used as a template for the nest 2 primers. Secondly, the region 2

nest 2 primers were used directly with genomic DNA. Multiple PCR product bands and

smearing resulted when nest 1 products were used (data not shown). However, nest 2

primers used directly with genomic DNA resulted in well defined bands of ~694bp,

which negated the need for a nested PCR for pfmdr1 region 2.

Despite acceptable PCR amplification, the products (required for subsequent LDR-

FMA) produced high background fluorescent intensities (FI), particularly for alleles

86Y/N and 1034S/C. The HB3 strain carries the pfmdr1 allele 86N (wild type);

however, FI for both 86N and 86Y were high at 18168 and 17758, respectively.

Similarly, in Dd2 which carries the 1034S allele, FI of 25537 and 13628 were obtained

for 1034S and 1034C, respectively. Ideally, the FI of the negative allele should be

<1500, as observed in other LDR-FMA assays (Carnevale et al. 2007). This high

background was suggestive of cross-reactivity or non-specific binding. Closer

examination of the oligonucleotide sequences of respective PCR and LDR primers


115

revealed an overlap of 19 bp. This may have caused partial amplification of the PCR

primers against LDR probes and contributed to the high background signals.

With the aim of enhancing the LDR-FMA FI specificity, new PCR primers were

designed (Table 4.1). Forward and reverse complementary oligonucleotides sequences

were selected from the P. falciparum genome (Genebank accession #X56851).

Amplification of pfmdr1 regions 1 and 2 using the new primers have proven successful

in control strains. Figure 4.3 illustrates well-defined amplicons of expected sizes from

both pfmdr1 regions in all control strains.

Table 4.1 Primer sequences and thermocycling conditions for pfmdr1 assays.

Initial and optimised conditions for the PCR amplification of pfmdr1 regions 1 and 2 (in

parentheses) are shown.

Set

Gene (region)

PCR Primer Sequence

pfmdr1(1) 754 forward 1048 reverse

5’-GTGTTTGGTGTAATATTAAAG-3’

5’-CAAACGTGCATTTTTTATTAATG-3’

pfmdr1(2) Nest 1 3439 forward 4489 reverse

5’-GATCCAAGTTTTTTAATACAGG-3’

5’-TTAGGTTCTCTTAATAATGCAC-3’

Initial

pfmdr1(2) Nest 2 3570 forward 4264 reverse

5’-TATTGTAAATGCAGCTTTATGG-3’

5’-CACTAACTATTGAAAATAAGTTTC-3’


5’-TGTATGTGCTGTATTATCAG-3’

5’-CTTATTACATATGACACCACA-3’

Optimised


5’-TAGAAGATTATTTCTGTAATTTG-3’

5’-CAATGTTGCATCTTCTCTTCCA-3’


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Figure 4.2 PCR amplification of pfmdr1 regions 1 and 2 in 7G8 over a temperature

gradient. PCR products of expected sizes (294 bp and 694 bp) were observed from

regions 1 and 2, respectively over a range of annealing temperature (TA). Specificity

was enhanced at TA >48°C for the region 2 reaction.


117

Figure 4.3 Gel scan of PCR products generated using new pfmdr1 primers.

PCR products of expected sizes (438 bp and 812 bp) were generated using new pfmdr1

primers. DNA ladder (HyperLadder™ IV, Bioline, London, UK) band size = 100 bp.

Upper: PCR amplicons of pfmdr1 region 1 from laboratory-adapted strains HB3, Dd2,

K1, 3D7, 7G8, empty, PNG 1917, Bk; water blank. Lower: PCR amplicons of pfmdr1

region 2 from control strains HB3, Dd2, K1, 3D7, 7G8, PNG1905, PNG1917 and water

blank.


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Preliminary LDR-FMA data generated by using new PCR primers showed enhanced

clarity between known positive and negative alleles. A noticeable reduction in

background FI was evident in the HB3 strain, a carrier of the 86N allele. In this

example, signals correspond to 86Y and 86N alleles were 17758 and 18168 using initial

primers, compared with 5457 and 14393 using modified primers, respectively.

The effect of the number of PCR cycles in reducing background FI was also

investigated. DNA from control strains were subjected to PCR using 10, 15, 20, 25, 30,

35 and 40 amplification cycles. As expected, higher number of cycles produced more

PCR products in both regions (Figure 4.4). The optimal number of PCR cycles ranged

from 30 to 40 for pfmdr1 regions 1 and 2 (Figure 4.4).

Optimised pfmdr1 PCR conditions are summarised in Tables 4.2 and 4.3. For pfmdr1

region 1, the reaction begins by preheating at 95°C for 2 min, followed by 32 cycles of

94°C for 30 sec, annealing at 56°C for 30 sec, 72°C for 30 sec, followed by final

extension at 72°C for 4 min. Thermocycling conditions for the amplification of the

pfmdr1 region 2 were similar to that of region 1 except for a longer extension time at

72°C for 1 min and repeated for 40 cycles.

4.3.1.2 LDR Optimisation

Each allele-specific LDR primer was designed with a unique 24-bases tag sequence

added to its 5’ end. These tag sequences are complementary to the anti-tag sequences

that are bound to microspheres and each emits a distinctive classification code (Table

4.4).


119

Figure 4.4 Effect of PCR cycles on pfmdr1 amplification.

PCR amplification of pfmdr1 regions 1 (upper) and region 2 (lower) by different

number of cycles.


120

Table 4.2 Optimised PCR conditions for pfmdr1 region 1. Table 4.3 Optimised PCR conditions for pfmdr1 region 2.

PCR: pfmdr1 region 1

Volume (µL)

Cycling Program

Sterile distilled water 19.6 95°C – 2 min

10 x PCR Buffer 2.5 94°C – 30 sec

2.5mM dNTPs 2.0 56°C – 30 sec

72°C – 30 sec Forward primer (10pmol/µL) pfmdr1

(region 1) 681

0.3

X 32 cycles

72°C – 4 min Reverse primer (10pmol/µL) pfmdr1

(region 1) 1119

0.3

10°C

Mac Taq 0.3

Total volume per well 25.0

PCR: pfmdr1 region 2

Volume (µL)

Cycling Program


10 x PCR Buffer 2.5 94°C – 30 sec

2.5mM dNTPs 2.0 56°C – 30 sec

72°C – 1 min Forward primer (10pmol/µL) pfmdr1 (region 2) 3499

0.3

X 40 cycles

72°C – 4 min Reverse primer (10pmol/µL) pfmdr1 (region 2) 4311

0.3

10°C

Mac Taq 0.3



121

Table 4.4 LDR primers for P. falciparum pfmdr1 molecular markers. aLowercase

nucleotides represent tag sequences added to the 5’ ends of each allele-specific LDR

primer. bID, microsphere fluorescence identification. Luminex microsphere sets are

synthesised to exhibit unique fluorescence. Each microsphere set is coupled to different

anti-tag sequences that are complementary to allele-specific tag sequences. cCom,

common (conserved) sequence primer positioned immediately downstream from the

allele-specific primer.

Gene

LDR Primer

Sequencesa

IDb

pfmdr1 region 1

86N

86Y

Com86

184Y

184F

Com184

5'tacactttctttctttctttctttTTGGTGTAATATTAAAGAACATGA-3’

5'atcatacatacatacaaatctacaTTGGTGTAATATTAAAGAACATGT-3’ 5’phosphate-ATTTAGGTGATGATATTAATCCTA-biotin-3’

5'tcaaaatctcaaatactcaaatcaGCCAGTTCCTTTTTAGGTTTATA-3’ 5'ctacaaacaaacaaacattatcaaGCCAGTTCCTTTTTAGGTTTATT-3’

5’phosphate-TATTTGGTCATTAATAAAAAATGCA-biotin-3’

10 12 -

18 28 -

pfmdr1 region 2

1034S

1034C

Com1034

1042N

1042D

Com1042

1246D

1246Y

Com1246

5'ttacctttatacctttctttttacATGCAGCTTTATGGGGATTCA-3’ 5'caatttcatcattcattcatttcaATGCAGCTTTATGGGGATTCT-3’ 5’phosphate-GTCAAAGCGCTCAATTATTTATT-biotin-3’

5'cttttcatcttttcatctttcaatCCAAACCAATAGGCAAAACTATT-3’ 5'ctttttcaatcactttcaattcatCAAACCAATAGGCAAAACTATC-3’

5’phosphate-AATAAATAATTGAGCGCTTTGAC-biotin-3’ 5'tcatcaatcaatctttttcactttAATATATGTGATTATAACTTAAGAG-3’

5'tcataatctcaacaatctttctttTAATATATGTGATTATAACTTAAGAT-3’ 5’phosphate-ATCTTAGAAACTTATTTTCAATAG-biotin-3’

30 35 -

37 54 -

59 68 -

A series of comprehensive experiments were set up to optimise pfmdr1 LDR

conditions. To test whether annealing temperature would improve signal clarity, parallel

LDR with TA at 58°C, 60°C and 62°C were performed. FI ratios between positive and

negative alleles were compared in control strains for different annealing temperatures

(Appendix C). For pfmdr1 region 1, 60°C produced the best clarity as higher

temperature dampened the FI for positive alleles. The opposite was observed in the

LDR for pfmdr1 region 2 in which higher TA enhanced signal contrast. Further


122

investigation for region 2 using annealing conditions at 62°C, 63°C, 64°C and 65°C,

indicated 65°C was optimal.

Secondly, the effect of PCR amplicon concentration on FI was investigated in P.

falciparum strains HB3, K1 and 7G8. Briefly, PCR products from pfmdr1 region 1,

region 2 and regions 1 plus 2 together, were subjected to LDR undiluted, diluted 1:2,

1:5, 1:10 and 1:100 in sterile distilled water. Although signal clarity was improved at

some dilutions, no consistent trend was found. In addition, DNA yield from field

samples would likely be lower than those derived from cultured parasites, hence

standardised dilutions may not be applicable.

Optimised LDR for pfmdr1 involves two separate reactions for each region. For pfmdr1

region 1, the reaction mixture was initially heated at 95°C for 1 min, followed by 32

cycles of denaturation at 95°C for 15 sec and annealing/ligation at 60°C for 2 min

(Table 4.5). Similar thermocycling conditions were used for LDR of pfmdr1 region 2,

with the exception of the final step performed at 65°C for 2 min (Table 4.6).

4.3.1.3 Optimised LDR-FMA for pfmdr1 and Multiplexed Detection of SNPs in pfdhfr,

pfdhps and pfcrt genes

The first step of the optimised LDR-FMA involves PCR amplification of the pfmdr1

gene from genomic DNA extracts. Briefly, sample DNA was centrifuged (3000 rpm for

30 sec) and 3 µL was combined with PCR master mix (25 µL/well) for pfmdr1 regions

1 and 2. The plate was sealed using Microseal® ‘A’ film (Bio-Rad, USA) and

centrifuged prior to PCR. Following PCR, the products were subjected to two separate

LDR for both pfmdr1 regions due to different TA requirements. LDR master mixes (14

µL/well) were prepared (Appendix B) and combined with 1 µL of PCR product from

corresponding regions. The plates were firmly sealed (sealing film B-1212-5, Denville

Scientific Inc), centrifuged and subjected to thermocycling (Table 4.5 and 4.6) in a

PTC-225 Peltier Thermal Cycler (MJ Research, Iowa). On completion, 2.5 µL of LDR

products from each pfmdr1 regions 1 and 2 were combined into 60 µL of pre-warmed

hybridisation solution (Appendix B) containing microspheres from each


123

Table 4.5 Optimised LDR conditions for pfmdr1 region 1. Table 4.6 Optimised LDR conditions for pfmdr1 region 2.

LDR: pfmdr1 region 1 Volume (µL) Cycling Program


Taq Ligase Buffer 1.5 95°C – 15 sec

Com86 0.2 60°C – 2 min

Com184 0.2 x 32 cycles of steps 2 and 3 only

86Ytag12 0.2

86Ntag10 0.2

184Ytag18 0.2

184Ftag28 0.2

Taq DNA Ligase 0.1

PCR product (region 1) 1


LDR: pfmdr1 region 2 Volume (µL) Cycling Program


Taq Ligase Buffer 1.5 95°C – 15 sec

Com1034 0.2 65°C – 2 min

Com1042 0.2 x 32 cycles of steps 2 and 3 only

Com1246 0.2

1034Stag30 0.2

1034Ctag35 0.2

1042Dtag54 0.2

1042Ntag37 0.2

1246Dtag59 0.2

1246Ytag68 0.2

Taq DNA Ligase 0.1

PCR product (region 2) 1



124

allelic set (total of 10 alleles). From this point on, the LDR products (5 µL) from pfcrt,

pfdhfr, and pfdhps genes can be multiplexed into a single well with the hybridisation

solution provided that it contains microspheres from their respective allelic set (total of

18 alleles). Hybridisation, reporter dye labelling and fluorescent signal measurement

were performed as described previously (Sections 2.3.4).

Further validation and application of the new LDR-FMA for pfmdr1 SNP screening of

culture-adapted and patient isolates of P. falciparum are described in the subsequent

section. Positive thresholds for each allele were established as detailed in Section 4.2.5.

4.3.2 Assay Validation

4.3.2.1 Comparison between LDR-FMA and RFLP speciation

Plasmodium speciation using LDR-FMA and the reference RFLP method were

compared in 374 samples. The sensitivity and specificity of LDR-FMA compared to the

reference RFLP method for P. falciparum speciation were 96.6% and 100%,

respectively. Concordances between the two methods are presented in Table 4.7. There

were high concordances for the diagnosis of P. falciparum (97%), P. vivax (90%) and

P. malariae (98%). 11 of 12 cases that were P. falciparum negative by LDR-FMA,

exhibited strong P. vivax fluorescent signals (>20,000), yet they have been classified as

P. falciparum positive by the RFLP approach. The remaining case proved to be a non-

falciparum mixed infection by the LDR-FMA characterised by strong positive signals

(23,145) for P. malariae and weak positive (667) for P. vivax. However, it was

classified as a P. falciparum mono-infection by the RFLP method. The LDR-FMA

method identified a total of 10 cases of P. malariae infections compared with 3 cases by

RFLP.

4.3.2.2 Inter-assay concordance

If a sample is positive for P. falciparum by LDR-FMA then the pfcrt, pfdhps, pfdhfr and

pfmdr1 genes should also be detectable. There were 304 samples in which speciation

and all four specific gene assays were performed using LDR-FMA. In 241 (79%), each

of the pfcrt, pfdhps, pfdhfr and pfmdr1 genes were identified. For discordant samples,


125

the pfdhps and pfdhfr assays were more often PCR negative in the amplification of

Plasmodium genome.

Table 4.7 Concordance between RFLP and LDR-FMA diagnosis of Plasmodium

species in PNG field samples.

P. falciparum

LDR (+)

LDR (-)

Total

RFLP & LDR-FMA Concordance

RFLP (+) 362 12 374

RFLP (-) 0 0 0

Total 362 12 374 96.8%

P. vivax

RFLP (+) 17 15 32

RFLP (-) 23 319 342

Total 40 334 374 89.8%

P. malariae

RFLP (+) 2 1 3

RFLP (-) 8 363 371

Total 10 364 374 97.6%

4.3.2.3 Identification of drug resistance alleles

The specificities of the pfcrt, pfdhfr and pfdhps assays have been reported previously

with 100% concordance with haplotypes from a variety of laboratory-adapted strains

(Carnevale et al. 2007). The specificities of the pfmdr1 LDR-FMA probes are shown in

Table 4.8. The results for the pfmdr1-specific LDR-FMAs show that allele-specific

background median fluorescence intensity (MFI) signals ranged from 168 to 6,464 and

positive allele-specific signals ranged from 1421 to 22,008. Strain-specific LDR-FMA

results were 100% concordant with published haplotypes (Mehlotra et al. 2008).


126

4.3.3 Field Application of the LDR-FMA

4.3.3.1 Speciation and drug resistance genes in PNG field isolates

In 402 samples with microscopy-confirmed P. falciparum, the Plasmodium species

LDR-FMA identified 28 patients with P. vivax co-infections and 13 with P. malariae

co-infections. No P. ovale co-infections were found. The maximum median FI obtained

for field isolates and thresholds used to determine the presence of an allele are shown in

Table 4.9.

Table 4.8 LDR-FMA evaluation of pfmdr1 SNPs in laboratory-adapted P.

falciparum strains. The fluorescence signal is expressed as median fluorescence

intensity (MFI) units. Boldfacing indicates positive allele-specific signals. apfmdr1

haplotypes for P. falciparum strains are for 3D7, NYSND; for 7G8, NFCDY; for Dd2,

YYSND; for HB3, NFSDD; K1, YYSND.

Fluorescence signal for the Pfmdr1a gene, codon and allele:

86 184 1034 1042 1246

Y N Y F S C D N D Y

3D7 2657 15306 17956 6464 21903 5568 225 21182 5243 327

7G8 1724 11351 1869 21092 1475 16556 6022 436 746 1421

Dd2 12684 3418 15465 5891 22008 5061 234 18333 4357 359

HB3 555 6381 530 10036 17881 1555 8238 271 2686 168

K1 19971 3482 17393 6055 21501 4519 199 18265 3476 543


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4.3.3.2 Prevalence of polymorphic alleles in pfcrt, pfmdr1, pfdhfr and pfdhps

Overall, 9 mutant alleles were detected. These were at pfmdr1 codons N86Y (91%),

Y184F (2%), N1042D (2%), D1246Y (4%), pfcrt codons C72S and K76T (both 92%),

pfdhfr codons C59R (93%), S108N (95%) and pfdhps codon K540E (1.5%) (Figure

4.5). The pfcrt haplotype SVMNT was found to be at fixation in the sample (92%), with

only 7% of P. falciparum strains retaining the CQ-sensitive haplotype CVMNK. Two

children were infected with mixed strains carrying CVIET and SVMNT mutations. The

majority of the P. falciparum isolates carried the CQ resistance-associated YYSND

(93%) haplotype of the pfmdr1 gene (Figure 4.6).

One patient was infected with an isolate carrying a single pfdhfr S108N mutation.

However, most children (97%) had parasites with double mutations in the NRNI

haplotype corresponding to amino acids at codons 51, 59, 108 and 164. A few isolates

(3%) retained the wild haplotype NCSI. No isolates carried the pfdhfr I164L allele. The

pfdhps haplotype KAA which harbours a single mutation at codon 613 was

predominant (98%). Four isolates carried the pfdhps K540E mutation.

When the isolates with completely defined haplotypes were assessed for multiple-gene

mutations, it was found that 88% (100/113) of children were infected with P.

falciparum carrying quintuple mutations across the pfcrt, pfdhfr, pfmdr1 and pfdhps

genes characterised by the respective haplotypes SVMNT+NRNI+YYSND+KAA. Four

patients (one per treatment group) were infected with parasites carrying the six-fold

mutated haplotype SVMNT+NRNI+YYSND+EAA. One of these patients was treated

with PQ-DHA and had a LPF, whilst the other three had P. falciparum ACPR. Table

4.10 details the number of P. falciparum isolates with multiple combinations of

mutations across drug resistance genes.


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Table 4.9 Fluorescence detection thresholds and maxima for P. falciparum pfdhps,

pfdhfr, pfcrt and pfmdr1 in PNG field samples. *Alleles not detected in the field

isolates.

Gene and allele Fluorescence intensity signal

dhps Threshold Maximum

540K 20,400

540E

1213

9,774

581A 21,876

581S*

1940

-

613A 21,403

613S*

2374

-

dhfr

51I* -

51N

4147

23,429

59R 23,368

59C

6087

23,490

108T* -

108S 16,258

108N

3348

22,198

164I 19,695

164L*

3914

-

pfcrt

CVIET * -

CVMNK 20,657

SVMNT

4791

22,523

pfmdr1

86Y 21,994

86N

6722

18,189

184Y 21,145

184F

7899

20,412

1034S 25,792

1034C*

11166

-

1042D 10,973

1042N

2836

23,200

1246D 9,921

1246Y

1410

3,174


129

Figure 4.5 Prevalence of pfcrt, pfmdr1, pfdhfr, pfdhps alleles in P. falciparum-

infected individuals from the Madang and East Sepik Provinces, PNG.

Figure 4.6 Frequency distributions of pfcrt, pfdhps, pfdhfr, pfmdr1 haplotypes in P.

falciparum-infected individuals from PNG field sites. The number of samples

demonstrating complete haplotype for each gene were 376, 254, 273 and 195,

respectively.


130

Table 4.10 Occurrence of P. falciparum isolates carrying multiple mutations across

4 genes associated with drug resistance. Wild-type alleles of pfcrt, pfdhfr, and pfmdr1

are indicated by boldfacing. Allele mutations are underlined. Pfcrt haplotypes

CVMNK, CVIET and SVMNT correspond to codons 72 to 76. Pfdhfr haplotypes

NCSI, NRNI and NCNI correspond to codons 51_59_108_164. Pfmdr1 haplotypes

NYSND, YYSND and NFSDD correspond to codons 86_184_1034_1042_1246.

pfcrt

pfdhfr

Double gene mutation

(pfcrt+pfdhfr only)*

Triple gene mutation (+pfmdr1)

NYSND YYSND NFSDD

NCSI 1 0 1 0

CVMNK with NRN I 14 1 1 0

NCNI* 0 0 0 0

NCSI 0 0 0 0

CVIET with NRNI 1^ 0 1^ 0

NCNI*

NCSI 2 0 2 1

SVMNT with NRNI 114 3 100^^ 3

NCNI 1 0 0 0

*Only assayed for pfcrt and pfdhfr due to inadequate sample volume.

^Sample with P. falciparum carrying both CVIET and SVMNT mutations.

^^Four of these isolates were also carrying the 540E mutation, whilst all other P.

falciparum sampled carried 540K allele of the pfdhps gene.

4.3.3.3 Parasite drug resistance mutations and treatment outcome

In evaluating the association of parasite genes with treatment outcome, the mean

number of parasite mutations in ACPR, ETF, LPF and LCF groups in 351 P.

falciparum cases was compared. Overall, there were 308 cases of ACPR, 3 cases of

ETF (one from CQ-SP; two from ART-SP), 3 cases of LCF (one case each from CQ-

SP, PQ-DHA and AL) and 37 cases of LPF (eleven from CQ-SP; twelve from ART-SP;

twelve from PQ-DHA and two from AL). There were 4 mutations in 41.6%, with 0.6%,

6.8%, 16%, 27.1%, 7.1%, 0.9% carrying no mutation and single, double, triple,


131

quintuple and sextuple mutations, respectively. There was no significant difference

between the mean number of mutations within the ACPR group (mean 3.3 [95% CI 3.1-

3.4]) and those in the ETF, LCF, LPF groups (means 2.3 [0-6.1], 3.0 [0.5-5.5] and 3.4

[3.0-3.8], respectively, P>0.05 in each case). For the purposes of subsequent analyses,

ETF, LCF and LPF were grouped as treatment failure.

The polymorphisms pfdhfr N51I, C59R, S108N and pfdhps K540E did not predict

treatment failure in 81 children allocated CQ-SP and in 86 allocated ART-SP (P>0.05).

In analyses of pfmdr1 N86Y, Y184F, N1042D and pfcrt K76T, pfmdr1 D1246Y was a

significant predictor of treatment failure in 79 children treated with PQ-DHA therapy;

40% (4 of 10) of such children carried D1246Y strains while only 3 of 69 (4%) who

responded to treatment harboured parasites with this mutation (P=0.004). In none of the

other three groups was there a significant association between the presence of D1246Y

and treatment failure (P≥0.10). Similar analyses did not reveal any associations

between haplotypes of pfcrt, pfdhfr and pfdhps and treatment failure.

4.4 DISCUSSION

The consequences of past antimalarial treatment policies in PNG were evident in these

data. Only 7% of the parasites carried the wild-type pfcrt CVMNK (codons 72 to 76)

associated with a CQ-sensitive phenotype. The high prevalence of the resistant K76T

polymorphism concurred with studies conducted between 2000 and 2005 in Madang

and East Sepik Provinces (Casey et al. 2004; Mehlotra et al. 2005; Schoepflin et al.

2008). The SVMNT haplotype (codons 72 to 76) is at fixation in the PNG parasite

population with an increase in prevalence from 83% from the early 1990s to 92.3% in

2003 - 2005 (Mehlotra et al. 2001; Marfurt et al. 2008; Schoepflin et al. 2008). As well

as being associated with CQ resistance, a transfection study has shown that parasites

carrying the SVMNT haplotype has reduced sensitivity to AQ and its metabolite (Sidhu

et al. 2002). Since AQ is recommended in place of CQ for treatment of malaria in PNG

children <19 kg (PNGDOH 2000), this may have implications for the most vulnerable

patients.

Another CQ-resistant haplotype, CVIET (codons 72 to 76) found commonly in Africa


132

and South-East Asia (Lim et al. 2003; Keen et al. 2007; Nsobya et al. 2007; Yang et al.

2007) was detected in two isolates as a mixed infection with the SVMNT strain,

confirming its recent emergence in PNG (DaRe et al. 2007). Differences between the

pfcrt intronic microsatellite diversity haplotypes of the SVMNT and CVIET parasites

from the province adjacent to Madang suggest that they have been imported (DaRe et

al. 2007), presumably by economic migrants from near-by Asian countries (Mehlotra et

al. 2001; Mehlotra et al. 2005; Mehlotra et al. 2008).

Although assessed in limited numbers of isolates (n=195) due to inadequate sample

volume, the CQ-sensitive pfmdr1 NYSND (codons 86_184_1034_1042_1246) was

present in 5.1%. Most others carried the N86Y polymorphism with the YYSND

haplotype (codons 86_184_1034_1042_1246) associated with CQ resistance. These

results reflect an increase of this haplotype since the mid 1990s (Mehlotra et al. 2005;

Mehlotra et al. 2008). It was also observed that four isolates (2%) carried the double

point mutations Y184F and N1042D, which confirmed the recent emergence of these

pfmdr1 polymorphisms in PNG (Marfurt et al. 2008). Although none of the four

patients with parasites carrying the pfmdr1 NFSDD haplotype (codons

86_184_1034_1042_1246) were assigned to the AL treatment group in this study. In a

Nigerian paediatric study (Happi et al. 2008), the presence of these SNPs with the wild-

type 86N allele was significantly associated with AL treatment failure. Since

introduction of this treatment in PNG is imminent, monitoring changes in the NFSDD

pfmdr1 haplotype should be a high priority.

It was found that signal intensities for the pfmdr1 1246 alleles were relatively weak

even in the controls. This was unlikely to reflect poor PCR amplification, as signal

intensities for codons 1034 and 1042 derived from the same region were unaffected.

Poor hybridisation with the LDR probe is possible. The D1246Y allele, present in 12%

of isolates in association with the wild-type allele 1246D, has not been previously

detected in PNG (Marfurt et al. 2008; Mehlotra et al. 2008). A recent African study

observed an increased prevalence of pfmdr1 N86Y and D1246Y alleles post AQ

exposure (Nawaz et al. 2009), but sporadic mutations at the 1246 codon have also been

documented in Thailand (Rungsihirunrat et al. 2009) and it may also have been

imported into PNG (Mehlotra et al. 2005). Both D1246Y and N86Y have been


133

associated with diminished in vitro sensitivity to CQ and AQ (Reed et al. 2000; Pickard

et al. 2003).

The concomitant occurrence of pfmdr1 N86Y and pfcrt K76T mutations was observed

in many isolates, with increased frequency compared to a decade earlier (Mehlotra et al.

2008). Concurrent mutations may reflect the involvement of CQ pressure in selecting

for the predominant pfmdr1 YYSND haplotype. This hypothesis was supported by the

selection of pfmdr1 N86Y allele after CQ and AQ therapy (Duraisingh et al. 1997;

Djimde et al. 2001). Concurrent mutations in pfcrt K76T, and pfdhfr C59R and S108N

were observed in 92.7% of the PNG isolates. Of those with pfmdr1 genotyping, 88.5%

also harboured N86Y mutations. Parasites with multiple mutations were more common

than found in another study conducted several years earlier in the same region

(Schoepflin et al. 2008).

The pfmdr1 haplotypes NFCDD, NFSND, and YFSND haplotypes (codons

86_184_1034_1042_1246) were not found in PNG isolates as found in those from

Thailand (Pickard et al. 2003), or the NFCDY and NFSDY haplotypes found in Brazil

and Colombia (Mehlotra et al. 2008). In vitro studies by Sá et al. showed 7G8 and

hybrid crosses with its pfmdr1 haplotype (NFCDY) resulted in higher 50% growth

inhibitory concentrations (IC50s) for AQ and its metabolite (Sá et al. 2009). However,

the “CDY” (i.e. S1034C, N1042D, D1246Y) mutation of the pfmdr1 gene has not been

detected in PNG. Collective polymorphisms in the 3’ coding region (N86Y and Y184F)

can confer resistance to quinine, mefloquine and halofantrine and modulate parasite

sensitivity to artemisinin drugs (Reed et al. 2000), and are found in South America,

Africa and Asia. Their geographical distribution suggests the requirement of drug

pressure for their maintenance and spread (Foote et al. 1990), as may occur with the

future use of ACTs in PNG. However, the frequency of the wild-type 86N may increase

with adoption of ACT as has been seen in African studies (Dokomajilar et al. 2006;

Humphreys et al. 2007).

This study demonstrated that 97% of the present isolates carried both the C59R and

S108N SNPs which constitute the major pfdhfr resistance alleles. Since the prevalence


134

of this double mutant in East Sepik Province was 72% - 91% in 2001 - 2003 (Mita et al.

2006b; Carnevale et al. 2007), this suggests that there has been continuing consistent

selection pressure for alleles conferring pyrimethamine resistance in northern PNG.

Carnevale et al. noted that a number of isolates from this area carried a single mutation

at codon 108 with the NCNI (n=13) and NCTI (n=1) haplotypes (Carnevale et al.

2007). In the present study, only one isolate had a single pfdhfr mutation with the NCNI

haplotype (codons 51_59_108_164) and, consistent with Marfurt et al. (Marfurt et al.

2008), the S108T mutant that was reported to be present in PNG in 1996 (Reeder et al.

1996) was not detected in the current study.

In the evaluation of pfdhps polymorphisms at codons 540, 581 and 613, only wild-type

alleles at loci 581 and 613 were detected. Four isolates were found to carry the K540E

variant first detected in studies in East Sepik and Simbu Provinces in 2002 - 2004 (Mita

et al. 2006b; Marfurt et al. 2008). Most of the present isolates (98.4%) carried the KAA

haplotype and 1.6% carried the EAA haplotype. SNPs at codons 436 and 437 were not

evaluated, as the respective LDR probes were unavailable at the time of study.

The lack of association between well known mutations (pfcrt K76T, pfdhfr S108N,

pfdhfr C59R, pfmdr1 N86Y) and treatment failure is largely due to fixation levels of

these mutations in Madang Province. Although carriers of multiple mutations were

more often observed in treatment failure cases, this did not reach statistical significance.

In the present study there was limited statistical power because of the relatively small

number of treatment failures (43 of 351), but the high baseline number of mutations per

isolate and the emergence of immunity in this age group in a high transmission setting

may also have attenuated the relationship. Although pfdhfr K540E has been shown to

predict SP treatment failure (Talisuna et al. 2004; Bacon et al. 2009), there was a low

prevalence of this allele in the isolates and it was unrelated to outcome. These data are

consistent with those of Marfurt et al. who showed that pfcrt K76T, and pfdhfr C59R

and S108N, did not predict treatment failure after CQ/SP treatment in a region north-

west of Madang (Marfurt et al. 2008), reflecting fixation of these mutations in PNG.

Interestingly, the association between pfmdr1 D1246Y allele with PQ-DHA and overall

treatment failure highlights the increasingly recognised role of this transporter gene in


135

modulating resistance to antimalarial drugs from different classes (Cowman et al. 1994;

Peel et al. 1994; Reed et al. 2000).

A novel approach to determine presence or absence of mutations using the LDR-FMA

system was adopted. Determination of signal positivity proved challenging. Initially,

allele-specific thresholds that have been established previously were applied for the

pfcrt, pfdhfr and pfdhps alleles (Carnevale et al. 2007). However, a number of samples

were plainly mis-classified when compared by visual discrimination via 2-dimensional

and 3-dimensional modelling. Various statistical models were tested but, in the absence

of valid malaria-negative samples, it was found that bimodal and gamma distributions

were inappropriate. Subsequent use of allelic signal ratios within each codon appeared

robust when applied to controls with known haplotypes, especially in cases where

strong positive signals were accompanied by high background. However, this approach

was based on the assumption of single strain infections, which can only be

circumvented by establishing a specific threshold. It was found that, through

normalisation of the data, application of gene-specific cut-points from the control

strains, and reversing the process to obtain codon-specific cut-offs, prediction of

positivity was relatively accurate. Unless better resolution of positive from negative

signal is possible, this method or related approaches (DaRe et al. 2010) can be adopted

for future LDR-FMA studies.

The multiplex LDR-FMA technique proved a cost-effective tool for epidemiologic

studies. Taking into consideration the reagents required for each step (DNA extraction,

plasticware, PCR and LDR primers, and Fleximap microspheres), the total cost per

sample for the analysis of 28 SNPs was AUD $4.14 ($0.15 per SNP), with over 60% of

the cost due to DNA extraction. This amounts to less than half the expense of the

recently-described microarray SNP detection approach (Crameri et al. 2007). However,

as with other expensive equipments in the PNG settings, maintenance of the bioplex

array reader and shipment of reagents maybe costly. Compared to PCR-based

approaches that have been used to evaluate polymorphisms in the pfdhfr, pfdhps, pfcrt

and pfmdr1 genes, most of which involve DNA probe hybridisation and post-PCR

RFLP methods (Duraisingh et al. 1998; Casey et al. 2004; Alifrangis et al. 2005; Farcas


136

et al. 2006; Veiga et al. 2006), the LDR-FMA system offers greater efficiency and

objectivity when analysing multiple mutations. Given these considerations and the

increase in key parasite mutations in resource-poor malaria-endemic countries such as

PNG, the LDR-FMA SNP assay represents an excellent tool for molecular surveillance.

The present LDR-FMA platform enables assessment of 18 SNPs in the pfcrt, pfdhps

and pfdhfr genes in a single-tube multiplex assay, a task that is beyond the capabilities

of existing real-time PCR and RFLP methodology. The inclusion of 10 additional SNPs

in the pfmdr1 gene can be easily accommodated through modified microsphere set

selection with all 28 SNPs having their own unique classification codes. Monitoring the

spread of resistance to CQ, sulfadoxine and pyrimethamine using this or equivalent

methodology is a high priority in countries such as PNG where these drugs are still

used. In addition, there will be an increasing need for monitoring pfmdr1 SNPs since

polymorphisms encompass diverse effects on parasite sensitivity to a range of

antimalarial drugs including those used in artemisinin-based combination therapy (Reed

et al. 2000).

This work has been published in Antimicrobial Agents and Chemotherapy, titled

“Molecular Assessment of Plasmodium falciparum Resistance to Antimalarial Drugs in

Papua New Guinea Using an Extended Ligase Detection Reaction Fluorescent

Microsphere Assay”.

CHAPTER 5

ANTIMALARIAL PROPERTIES OF

DESBUTYL-LUMEFANTRINE

Chapter 5 Antimalarial Properties of Desbutyl-Lumefantrine

138

CHAPTER 5. ANTIMALARIAL PROPERTIES OF

DESBUTYL-LUMEFANTRINE

5.1 INTRODUCTION

Desbutyl-lumfantrine (DBL), formerly known as desbutyl-benflumetol is a 2,3-

benzindene compound with antimalarial activity. Although previously considered only

a putative metabolite of lumefantrine because of a lack of supportive pharmacokinetic

data (Samal et al. 2005; Starzengruber et al. 2007), recent analytical developments have

enabled the reliable detection of relatively low concentrations of DBL in samples of

plasma from small numbers of patients treated with conventional doses of artemether-

lumefantrine combination therapy (McGready et al. 2006; Hatz et al. 2008; Ntale et al.

2008). The ratio of maximum plasma concentration (Cmax) of the parent compound to

that of the metabolite in this situation has varied substantially, from 6 (Ntale et al.

2008) to >270 (Hatz et al. 2008).

DBL is more potent in vitro against chloroquine (CQ)-resistant P. falciparum and P.

vivax field isolates than lumefantrine (Noedl et al. 2001; Kyavar et al. 2006;

Starzengruber et al. 2008). There is evidence of in vitro synergy between lumefantrine

and DBL against P. falciparum, but at ratios (999:1 and 995:5) that were presumably

selected at a time when plasma concentrations of DBL were assumed to be very much

lower than those of the parent compound (Starzengruber et al. 2007; Starzengruber et

al. 2008). Interactions between DBL and artemisinin were assessed in a study of

schizont maturation in Thai P. vivax field isolates in which antagonism was found at

low concentrations and apparent synergy at much higher concentrations (Kyavar et al.

2006). A subsequent similar field study confirmed concentration-dependent synergy in

strains of P. falciparum (Muller et al. 2008).

Because of its relative in vitro potency and evidence of low cardiac toxicity (Traebert et

al. 2004), DBL has been suggested as an antimalarial drug in its own right

(Starzengruber et al. 2007). There is, however, a need for further assessment of its

interactions with other antimalarial drugs, especially lumefantrine and the artemisinin

derivatives, in strains of P. falciparum of differing drug sensitivities. In addition, and


139

given that artemether-lumefantrine is recommended as first-line treatment for

uncomplicated malaria (WHO 2009), there is also a need to confirm the relative plasma

concentrations of lumefantrine and DBL together with their therapeutic implications.

The present chapter reports on in vitro antimalarial activity of DBL in comparison to

lumefantrine and CQ in CQ-resistant and CQ-sensitive laboratory-adapted strains of P.

falciparum. It also provides a comprehensive evaluation of DBL interaction with DHA

and lumefantrine across 17 combination-ratios. Plasma levels of DBL and lumefantrine

in 127 clinical samples and their relationship with artemether-lumefantrine treatment

outcome are also presented.


5.2.1 Parasite Cultures

The laboratory-adapted P. falciparum strains 3D7 (CQ-sensitive) and W2mef (CQ-

resistant) were cultured as described previously (Section 2.1.3) (Trager et al. 1976;

Scheibel et al. 1979).

5.2.2 Antimalarial Drugs

Stock solutions of CQ diphosphate, piperaquine tetraphosphate (PQ), mefloquine

hydrochloride (MQ), lumefantrine, DBL and dihydroartemisinin (DHA) were prepared

as described in Section 2.2.1. Stocks and working standards of lumefantrine and DBL

were sonicated for 90 sec in an ultrasonic waterbath in pre-warmed media to facilitate

dissolution. On the day of assay, aliquots were thawed and further diluted in RPMI to a

working standard, and further two-fold serial dilutions in complete RPMI (without

hypoxanthine) at double assay concentrations were prepared for CQ (25 - 1600 nM),

PQ (6.25 - 400 nM), MQ (0.78 - 200 nM), DHA (0.78 - 51.2 nM), and lumefantrine and

DBL (3.12 - 400 nM).


140

5.2.3 In vitro Drug Susceptibility

Drug susceptibility was tested in triplicate as described in Section 2.2. To each well of a

96-well plate was added 100 µL of dosed or drug-free media without hypoxanthine, 90

µL of RBC suspension (final 0.5% parasitaemia, 1.5% hct) and 10 µL of 5 mg/ml 3H-

labelled hypoxanthine. After 48 hr incubation, the plates were harvested and processed

as detailed in Section 2.2.5.

5.2.4 Drug Interaction Studies

The traditional checkerboard method (Berenbaum 1978; Canfield et al. 1995; Hassan

Alin et al. 1999) and a recently described fixed-ratio approach (Fivelman et al. 2004)

were used to develop the following assay. Solutions (5 µM) of each drug were used to

prepare 17 fixed molar combination ratios in 12-well plates. The molar ratios tested for

lumefantrine:DBL and DHA:DBL are detailed in Table 5.1. Two hundred microlitres of

each drug combination were dispensed into row H of a 96-well plate. Rows A to G

were filled with 100 µL of media without hypoxanthine. Preparations of one drug alone

were assayed in triplicate, and other combination ratios in duplicates. Two-fold serial

dilutions were performed using an electronic multichannel pipette (Labnet excel, Fisher

Biotec, Australia) from rows H to B. Drug-free control wells were included (row A).

All wells contained a final volume of 200 µL including 3H-labelled hypoxanthine, were

standardised to 1.5% parasitaemia at 1.5% hct and were incubated for 48 hr and

processed as described previously (Section 2.2.5).

Table 5.1 Drug combination ratios for isobologram assays. Molar ratios and drug

concentrations of desbutyl-lumefantrine (DBL) paired with either lumefantrine (LM) or

dihydroartemisinin (DHA) are shown. Within-well concentration shown in the table is

that of the prepared drug combination. Further two-fold serial dilutions of each

combination were performed to give six additional tests at lower doses. For simplicity,

drug concentrations are displayed only for the first assay well (i.e. the one containing

the highest concentration of drugs) for a given combination.


141

Drug Combination

Molar Ratio Within-well assay concentration (nM) DBL LM DHA

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

1:0

0:1

1:1

1:3

1:10

1:30

1:100

1:300

1:1000

1:3000

3000:1

1000:1

300:1

100:1

30:1

10:1

3:1

100

0

100

33.3

10

3.33

1

0.33

0.1

0.033

100

100

100

100

100

100

100

0

400

400

400

400

400

400

400

400

400

0.133

0.4

1.33

4

13.33

40

133.3

0

100

100

100

100

100

100

100

100

100

.033

0.1

0.33

1

3.33

10

33.3

5.2.5 Study Site and Sample Collection

Plasma concentrations of DBL and lumefantrine were measured in samples taken from

children participating in an intervention trial carried out in the Madang Province of

Papua New Guinea (PNG) (Karunajeewa et al. 2008b). Children aged 0.5 to 5 years and

with uncomplicated falciparum or vivax malaria were randomised to one of four

treatments, one of which was artemether-lumefantrine (Coartem®, Novartis Pharma,

Basel, Switzerland) at a dose of 10 mg/kg lumefantrine twice daily for three days (total

dose of 60 mg/kg). Scientific and ethical approval was obtained from the Medical

Research and Advisory Committee of the Ministry of Health of PNG and informed

consent was obtained from the parents or legal guardians before recruitment and blood

sampling. A venous blood sample was taken at 7 day post-treatment for drug assay

since this is regarded as a useful surrogate marker of the area under the plasma

concentration-time curve and the time above the minimal inhibitory concentration for

long-acting antimalarial drugs (Price et al. 2007). Whole blood was centrifuged on site

and separated plasma was stored at -80°C until analysis. For the purposes of the present


142

study, therapeutic response was considered to be either an adequate parasitologic and

clinical response (ACPR) or treatment failure (early treatment failure, late parasitologic

failure or late clinical failure) during a follow-up of 42 days without PCR correction for

reinfection (WHO 2003; Karunajeewa et al. 2008b).

5.2.6 Liquid Chromatography and Mass Spectrometry

Lumefantrine was analysed using a validated high performance liquid chromatography

method (Mansor et al. 1996). Plasma samples of 1.0 mL were spiked with atovaquone

as an internal standard and mixed with 7 mL of hexane:diethylether (70:30). After

centrifugation, the organic layer was separated, evaporated and reconstituted with 200

µL methanol:acetic acid (98:2). Aliquots of 15 µL were injected onto a Phenomenex

C6-phenyl 4.6 x 150 mm column (Phenomenex, CA, USA). A mobile phase of

acetonitrile:0.05 M phosphate buffer at pH=2.0 (62:38) with 0.03 M sodium perchlorate

was pumped at 1 mL/min. Lumefantrine and atovaquone were measured at 335 nm and

quantified using Chemstation Software (Version 9, Agilent Technology, Waldbronn,

Germany). The linear range for lumefantrine was 20 - 20,000 ng/mL. Inter-day

variability was 4.94%, 4.93%, 7.16% and 11.23% and intraday variability 2.83%,

4.41%, 4.11%, 9.55% for 20,000, 2000, 200 and 20 ng/mL respectively.

DBL was analysed using a validated ultra high-performance liquid chromatography-

tandem mass spectrometry (UPLC-LCMS-MS) method using a hexyl-analogue as an

internal standard (IS). To facilitate protein precipitation, 40 µL of a 0.1 M ZnSO4 was

added to 20 µL sample and briefly vortexed. A 200 µL aliquot of acetonitrile containing

the internal standard was added before the sample was centrifuged and 10 µL of the

supernatant was injected onto a 2795/Quattro Premier XE UPLC-MS/MSWaters Corp,

MA) using a Waters XTerra MS C18, 2.5 x 50 mm 3.5 µm column. Gradient elution

was performed using aqueous 2 mM ammonium acetate/0.1% formic acid and

methanolic 2 mM ammonium acetate/0.1% formic acid as mobile phases at 0.4

mL/min. Transitions were monitored using positive electrospray ionisation with

multiple-reaction monitoring for DBL and the IS which were m/z 472.1/346.0 and

500.1/346.0, respectively. The linear range for DBL was 0.5 - 100 ng/mL with the

lower end taken as the limit of quantitation. Inter-day variability was 3.36%, 3.47%,


143

9.98% and 6.74% and intraday variability 2.47%, 3.46%, 8.16% and 3.48% for 50, 10,

1 and 0.5 ng/mL, respectively. When matrix effects were assessed, between-subject

variability was 3.37%, 4.47% and 9.43% at 50, 10 and 1 ng/mL, respectively.

5.2.7 Statistical Analysis

Drug susceptibility and interactions were analysed by non-linear regression of

logarithmically-transformed concentrations. The concentration that inhibited 50%

parasite growth (IC50) was determined for each drug, as was the concentration that

inhibited 99% of growth (IC99). The fractional inhibitory concentrations (FICs)

representing the concentration of each drug alone or in combination resulting in 50%

inhibition were used to construct isobolograms (Berenbaum 1978). Two analytical

approaches were employed (Davis et al. 2006). First, the sum of fractional inhibitory

concentrations (ΣFICs) was calculated using the formula (IC50 of A in a mixture

resulting in a 50% inhibition/IC50 of A alone) + (IC50 of B in a mixture resulting in a

50% inhibition/IC50 of B alone) (Berenbaum 1978). The combination has an indifferent

interaction when the ΣFIC is close to 1.0. A ΣFIC of <1 indicates synergy with data

points forming a concave isobole beneath the line of additivity (Figure 1.22). A ΣFIC of

>1 indicates antagonism as represented by a convex isobole (Berenbaum 1978; Chawira

et al. 1987; Fivelman et al. 2004; Davis et al. 2006). Second, the function (y = 1 - x/(x

+ (1-x)*exp(-I))) (Brueckner et al. 1991; Canfield et al. 1995) was fitted to the data

where y is the IC50 of drug A combined with drug B; x is the IC50 of drug B when

combined with drug A, and I is the interaction value. Positive I values indicate synergy,

negative values antagonism and values close to zero an indifferent interaction. Values

of I and FIC were considered significantly different from no interaction if both 95%

confidence intervals (CIs) of the estimates did not span zero and unity, respectively

(Davis et al. 2006).


144

5.3 RESULTS

5.3.1 In vitro Antimalarial Potency of DBL

The geometric mean IC50 and 95% CIs for DBL, lumefantrine and other drugs are

shown in Table 5.2. W2mef had, as expected, a higher CQ IC50 than 3D7 but there were

no other strain-specific differences. Consistent with the IC50 data, the geometric mean

IC99 values for DBL against 3D7 and W2mef were 78 and 56 nM, respectively, and, for

lumefantrine, 239 and 226 nM. Based on both the IC50 and IC99 values, the in vitro

activity of DBL was at least 3 times that of lumefantrine regardless of CQ sensitivity

(Figure 5.1).

Table 5.2 In vitro sensitivity of laboratory-adapted P. falciparum to desbutyl-

lumefantrine and other antimalarial drugs. IC50 values are geometric means. Data

represent at least six experiments performed in triplicate.

3D7 IC50 (nM) 95% CI

W2mef IC50 (nM) 95% CI

Chloroquine 29.6 15.3 - 57.5 171.4 144.4 - 203.4

Lumefantrine 65.2 42.3 - 100.8 55.5 40.6 - 75.7

Desbutyl-lumefantrine

9.0 5.7 - 14.4 9.5 7.5 - 11.9

Piperaquine 16.9 13.4 - 21.3 17.4 11.8 - 25.6

Dihydroartemisinin 4.2 2.5 - 7.0 3.1 1.8 - 5.3


145

Figure 5.1 In vitro susceptibility of laboratory strains of P. falciparum to

chloroquine, desbutyl-lumefantrine and lumefantrine.


146

5.3.2 DBL Interaction with Conventional Antimalarials

Isobolographic analysis of DBL and lumefantrine combinations showed no interaction

in both laboratory-adapted strains (see Table 5.3 and Figure 5.2). Drug interactions

between DBL and dihydroartemisinin were mildly synergistic as assessed from both I

and ΣFIC.

Table 5.3 In vitro efficacy of antimalarial drug combinations against P. falciparum

clones 3D7 and W2mef as assessed by isobolographic analysis. Data are the

interaction factor (I) and the summed fractional inhibitory concentration (ΣFIC) with

95% confidence intervals. The assessment of interaction is based on both I and ΣFIC

data (see text).

I (95% CI) ΣFIC (95% CI) Interaction

3D7

DBL-lumefantrine 0.41 (-0.24 to 1.05) 0.99 (0.93 to 1.05) Indifferent

DBL-dihydroartemisinin 0.99 (0.71 to 1.28) 0.92 (0.87 to 0.98) Mildly synergistic

W2mef

DBL-lumefantrine 0.79 (0.02 to 1.56) 1.06 (0.97 to 1.14) Indifferent

DBL-dihydroartemisinin 0.92 (0.73 to 1.10) 0.94 (0.90 to 0.99) Mildly synergistic


147

Figure 5.2 Isobolograms illustrating interactions between desbutyl-lumefantrine

with conventional antimalarials. Isobolograms showing effect of desbutyl-

lumefantrine in combination with lumefantrine against P. falciparum 3D7 (top left),

W2mef (top right). Effect of desbutyl-lumefantrine in combination with

dihydroartemisinin against P. falciparum 3D7 (bottom left) and W2mef (bottom right).

The isoboles are representative of three or four experiments in which each of the 17

drug ratios was tested in duplicate. Degree of interaction (I) with 95% CI are

represented by red and dotted lines, respectively.


148

5.3.3 DBL Plasma Levels on Day 7 Post-Treatment

DBL and lumefantrine were quantified in 94 available day 7 plasma samples from the

127 children with falciparum malaria recruited to the artemether-lumefantrine arm of

the intervention trial (Karunajeewa et al. 2008b). The mean (range) DBL concentrations

were 15.5 (0.6 - 58.2) ng/mL or 31.9 (1.3 - 123.1) nM – all children had a plasma

concentration above the 0.5 ng/mL lower limit of quantitation. For lumefantrine, the

mean (range) plasma concentration was 370 (26 - 1,720) ng/mL or 699 (49 - 3,251) nM.

The lumefantrine:DBL ratio ranged from 7.0 and 123.0 with a mean of 27.4.

5.3.4 Influence of DBL Plasma Levels on Clinical Outcome

The relationship between plasma lumefantrine and DBL concentrations, and treatment

outcome at 42 days is shown in Figure 5.3. The mean plasma concentrations of

lumefantrine in those children who failed treatment were lower than in those with an

ACPR, but this difference was not significant (P=0.22). In the case of DBL, there was a

similar result but at borderline significance (P=0.053). There was no difference in the

case of the lumefantrine:DBL ratio (P=0.97).


149

Figure 5.3 Boxplots summarising day 7 plasma levels of lumefantrine and

desbutyl-lumefantrine. Plasma lumefantrine (left panel) and desbutyl-lumefantrine

(right panel) concentrations in children who had an adequate clinical and parasitological

response (ACPR) or who failed treatment with artemether-lumefantrine


150

5.4 DISCUSSION

The present observations confirm and extend previous published data relating to in vitro

and in vivo aspects of the antimalarial activity of DBL. The two laboratory-adapted

strains of P. falciparum were more sensitive in vitro to DBL than lumefantrine,

consistent with previous studies using field isolates (Noedl et al. 2001; Starzengruber et

al. 2007; Starzengruber et al. 2008). This effect was independent of CQ sensitivity. The

lack of in vitro interaction between DBL and lumefantrine appears to contradict

previous reports of synergy in field isolates of P. falciparum using limited numbers of

drug combinations (Starzengruber et al. 2007; Starzengruber et al. 2008). However, the

synergy between DBL and DHA observed using a comprehensive method of

isobolographic assessment parallels data from studies of field isolates of P. vivax

(Kyavar et al. 2006) and P. falciparum (Muller et al. 2008). Both lumefantrine and

DBL were detected at mean concentrations that were well above the IC99 for both

laboratory-adapted strains of P. falciparum in day 7 plasma of children treated with

artemether-lumefantrine for uncomplicated malaria. The day 7 plasma DBL was a

stronger predictor of subsequent therapeutic outcome than plasma lumefantrine or the

plasma lumefantrine:DBL ratio. These various observations have potential clinical

implications.

When artemether-lumefantrine is administered to patients with malaria, plasma

lumefantrine concentrations rise after each of the six doses given over 3 days and then

decline with an elimination half-life of around 4 days (Ezzet et al. 1998). There are, as

yet, no equivalent pharmacokinetic data for DBL. The day 7 plasma concentrations

from this study show that both plasma lumefantrine and DBL concentrations remain

above the IC99 in most patients for at least three parasite life cycles. Even if there were

synergy between lumefantrine and DBL at these concentrations as found by others

(Starzengruber et al. 2007; Starzengruber et al. 2008), its relevance at this stage in

treatment is unclear as initial parasite clearance had occurred in all patients allocated

this therapy in the trial (Karunajeewa et al. 2008b) and the presence of one or other

compound at a concentration >IC99 should inhibit low-level (sub-microscopic) parasite

replication. In addition, the variable day 7 lumefantrine:DBL ratios in PNG children,

which are consistent with the marked apparent between-dose variability in lumefantrine


151

bioavailability (Ezzet et al. 1998; van Agtmael et al. 1998), would lead to inconsistent

interactions. Indeed, the data relating day 7 lumefantrine and DBL concentrations to

therapeutic outcome suggest that DBL has a stronger role than the parent compound in

suppressing recrudescence and/or preventing reinfection. This may reflect the fact that,

even at relatively low plasma concentrations, DBL has more potent antimalarial activity

than lumefantrine as exemplified by the present in vitro sensitivity data. The fact that

the lumefantrine:DBL ratio had no relationship with outcome is unlikely to translate

into a clinically important synergistic interaction.

Initial parasite clearance is considered due primarily to the artemisinin component of

ACT and, conversely, its prolongation is taken as evidence of artemisinin resistance

(Dondorp et al. 2010). It is, however, possible that the longer half-life partner and

interactions between the component drugs enhance the relatively rapid parasiticidal

effects of artemisinin derivatives. Synergy between artemether and lumefantrine has

been reported (Hassan Alin et al. 1999) and the present data and those of others

(Kyavar et al. 2006; Muller et al. 2008) suggest a similar interaction for DBL/DHA.

However, the clinical importance of such effects is unclear. The synergy observed in

the present study was mild. The relatively short half-lives of artemether and its active

metabolite DHA (1 - 2 hr) (Ezzet et al. 1998; Ezzet et al. 2000) limit the time-window

for such effects. Interactions can be antagonistic, such as that between artemisinin and

DBL at some concentrations (Kyavar et al. 2006) and between DHA and 4-

aminoquininolines and related drugs (Davis et al. 2006). The fact that a range of

different ACTs show equal efficacy (Sinclair et al. 2009) suggests that acute effects on

the parasite other than those from the artemisinin drug are minor.

According to the manufacturer, DBL is a degradation product of lumefantrine, and

Coartem® tablets contain <0.1% of DBL both at the time of manufacture, and at the

end of the expiry date (H. Gruninger, personal communication, Novartis Pharma). The

occurrence of such low relative concentrations of DBL in pure lumefantrine powder

was confirmed by UPLC-LCMS/MS (unpublished data), and excluded

DBL:lumefantrine at 1:10000 from the drug interaction analysis as a result. Although a

small amount of DBL is present at the time of Coartem® administration, it is


152

quantitatively far below the level detected in plasma. Thus, this exogenous contribution

is insufficient to influence the plasma DBL concentrations in the present study, with the

corollary that DBL is a true metabolite.

The present study confirms that DBL has potential as an antimalarial drug in its own

right. Its in vitro potency relative to the parent compound, its synergy with DHA, and

the positive relationship between day 7 plasma concentrations and ACPR suggest that it

could be a useful alternative to lumefantrine as part of ACT. Although the presence of

DBL at parasiticidal concentrations during conventional artemether-lumefantrine

therapy suggest that it is as safe as lumefantrine, further pharmacokinetic and safety

assessment after DBL administration would be required to facilitate the development of

optimal dose regimens. In contrast to N-desbutyl-halofantrine, the active metabolite of

halofantrine (Traebert et al. 2005), preliminary in vitro cardiotoxicity studies have not

raised any significant concerns (Traebert et al. 2004).

This work has been published in full in Antimicrobial Agents and Chemotherapy, titled

“Desbutyl-lumefantrine is a metabolite of lumefantrine with potent in vitro antimalarial

activity that may influence artemether-lumefantrine treatment outcome”.

CHAPTER 6

STATINS AND FIBRATES:

LIPID-MODIFYING DRUGS AS

ANTIMALARIALS

Chapter 6 Statins and Fibrates as Antimalarials

154

CHAPTER 6. STATINS AND FIBRATES: LIPID-

MODIFYING DRUGS AS ANTIMALARIALS

6.1 INTRODUCTION

The increase in non-communicable diseases of affluence in developing countries such

as PNG may see a significant shift from heavy use of anti-infective agents to therapies

for cardiovascular risk factor reduction (Martin et al. 1981; Iser et al. 1993; Hodge et

al. 1996; Lindeberg et al. 1997; Kende 2001; Lesley et al. 2001; Yamauchi et al. 2001;

Yamauchi et al. 2005). Drugs used for one indication can sometimes have wider

application and there is evidence that some cardiovascular therapies such as the anti-

diabetic drug rosiglitazone (Boggild et al. 2009) could have antimalarial properties.

This is of particular interest given the recent emergence of P. falciparum resistant to

artemisinin (Wongsrichanalai et al. 2008; Carrara et al. 2009; Dondorp et al. 2010).

Statins and fibrates are distinct classes of lipid-modifying drugs that reduce morbidity

and mortality associated with cardiovascular disease. This chapter investigates the

potential of these two groups of agents as novel antimalarials.

6.1.1 Statins as Lipid-lowering and Antimicrobial Agents

Statins are well tolerated and widely used for reducing cardiovascular morbidity and

mortality (Wilt et al. 2004; Thavendiranathan et al. 2006). They inhibit 3-hydroxy-3-

methylglutaryl coenzyme A (HMG-CoA) reductase (Figure 1.19), a key enzyme in

cholesterol biosynthesis, which consequently lower serum concentrations of low-

density lipoprotein–cholesterol. There has been interest in alternative applications of

statins, with studies demonstrating their abilities to inhibit the growth of bacteria

(Catron et al. 2004), yeasts (Song et al. 2003), and protozoa (Chen et al. 1990; Urbina

1993; Andersson et al. 1996; Montalvetti 2000). The first study of their antimalarial

effects found that lovastatin and simvastatin inhibited in vitro intra-erythrocytic

development of P. falciparum (Grellier et al. 1994). More recently, the in vitro

susceptibilities of P. falciparum to six statins revealed atorvastatin had the greatest

activity (Pradines et al. 2007). Despite these encouraging findings, neither simvastatin

nor atorvastatin in high doses improved the outcome in Plasmodium berghei-infected


155

mice (Bienvenu et al. 2008; Kobbe et al. 2008) and there was no effect on parasitaemia

(Bienvenu et al. 2008). However, no study to date has included the most-potent statin in

clinical use, rosuvastatin (Soran et al. 2008). In addition, despite the demonstration of

in vitro synergy between mevastatin and the glycoprotein inhibitor tunicamycin against

P. falciparum (Naik 2001), the interaction between statins and conventional

antimalarial drugs has not been evaluated. Therefore, the relative in vitro antimalarial

activity of rosuvastatin and atorvastain, against P. falciparum and the in vitro

interactions between statins and both chloroquine (CQ) and dihydroartemisinin (DHA)

are presented in this chapter.

6.1.2 Fibrates as Potential Antimalarial Drugs

Fibrates such as gemfibrozil and fenofibrate are agonists of peroxisome proliferator-

activated receptor alpha (PPARα). Although active via a different pathway to that of the

statins, fibrates exhibit potent lipid-modifying properties (Derosa et al. 2009). They

have well-characterised pharmacokinetic and pharmacodynamic profiles. An early

study on the effect of plasma free fatty acid concentrations and temperature on

parasitaemia in P. berghei-infected mice employed clofibrate as a lipid-lowering agent

(McQuistion 1979). Although not a primary interest of the study, clofibrate directly

inhibited the development of parasitaemia. However, the authors did not extend these

observations and no other subsequent study has examined the role of fibrates in the

treatment of malaria. It is possible that Plasmodium species have PPARα-like motifs

which could mediate such fibrate antimalarial effects.

There is further indirect evidence of a link between fibrates and malaria. In a

biochemical assay, Ehrhardt et al. assessed the in vitro influence of fibrates on P-

glycoprotein activity. Of gemfibrozil, fenofibric acid, clofibrate and fenofibrate, the

latter drug was the only member of the class to inhibit P-glycoprotein mediated

transport (Ehrhardt et al. 2004). A P-glycoprotein homologue 1 in P. falciparum has

been implicated in CQ and mefloquine resistance (Reed et al. 2000) and it is possible

that fenofibrate may decrease drug efflux mediated by this protein and thus reverse

resistance. Fibrates exhibit pleotropic effects that could also modify the effects of


156

malaria infection. An example of this is the attenuation of brain tissue injury associated

with inflammation (Bordet et al. 2006) and vascular occlusion (Guo et al. 2009). In a

murine influenza study, where severe systemic disease is thought to arise through

overproduction of proinflammatory cytokines, treatment with gemfibrozil doubled

survival compared to vehicle-treated mice (Budd et al. 2007). Similar host

inflammatory responses have been proposed for malaria pathology, particularly in coma

and other clinical manifestations associated with cerebral malaria (Clark et al. 2005;

Clark et al. 2008; Clark et al. 2009).

In the present study, the direct antimalarial activity of gemfibrozil, clofibrate,

fenofibrate, and its metabolite fenofibric acid against P. falciparum are investigated. In

vitro interactions between these fibrates and both CQ and DHA are also examined.


6.2.1 In vitro Parasite Growth Inhibition

The laboratory-adapted P. falciparum strains 3D7 (Africa; CQ-sensitive), E8B (Brazil;

CQ-resistant), K1 (Thailand; CQ-resistant), W2mef and Dd2 (Indochina; CQ-resistant)

were maintained as previously described (Section 2.1). Stock solutions of CQ

diphosphate (Sigma Chemicals, St Louis, USA), atorvastatin (Waterstonetech, Carmel,

IN), rosuvastatin (Waterstonetech, Carmel, IN), fenofibrate (Sigma), clofibrate (Sigma),

gemfibrozil (Sigma-Aldrich) and fenofibric acid (Tyger Scientific Inc, NJ, USA) were

prepared in distilled water (CQ) and DMSO (statins and fibrates).

Serial dilutions of each drug were prepared in RPMI and added in triplicate to 96-well

plates with final concentrations of 12.5 to 1600 nM (CQ), 0.3 to 200 µM (atorvastatin)

and 0.6 to 400 µM (rosuvastatin, pravastatin and simvastatin), 6.2 to 800 µM

(gemfibrozil, clofibrate, fenofibrate) and 39 to 5000 nM (fenofibric acid). Synchronous

parasite suspensions (≥90% rings) were adjusted to 1.0% for non-isotopic and 0.5%

parasitaemia for isotopic assays and a final hct of 1.5% in the drug-parasite mixture.

Following 48 hr incubation, parasite growth was measured initially by a modification of

the pLDH assay as described previously (Section 2.2.4) (Makler et al. 1993a) and


157

subsequently by the 3H-hypoxanthine incorporation assay (Section 2.2.5) (Desjardin

1979). IC50s and IC90s were determined by non-linear regression analysis (Graphpad

Prism 4.0).

6.2.2 Drug Interaction Studies

A modified fixed-ratio isobologram method was used to assess drug interactions

(Fivelman et al. 2004). Inhibition assays using 3H-hypoxanthine incorporation (Section

2.) were first carried out to determine individual IC50s for statins, fibrates, CQ and

DHA (Desjardin 1979). These were used to establish test concentration ranges in the

combination assays. A total of six and eleven solutions containing fixed-ratios of

conventional antimalarials with statins and fibrates, respectively, were prepared as

shown in Table 6.1. The FICs of each drug in each combination determined from dose-

response curves were used to construct isobolograms from which the sum of each FIC

was calculated (Berenbaum 1978).


158

Table 6.1 Interaction ratios of statins, fibrates and conventional antimalarials.

Molar ratios and drug concentrations of atorvastatin or fibrates (gemfibrozil, fenofibrate

or fenofibric acid) paired with either chloroquine (CQ) or dihydroartemisinin (DHA)

are shown. Each within-well concentration shown is that of the prepared drug

combination. Further two-fold serial dilutions of each combination were performed to

give six additional tests at lower doses. For simplicity, drug concentrations are

displayed only for the first assay well (i.e. contains the highest concentration of drugs)

for a given combination. *Fenofibric acid concentrations are in nmol.

Drug pair Ratio Top concentrations within a combination

Statin/Fibrate (µM) CQ (nM) DHA (nM)

Atorvastatin-antimalarials

5:0

0:5

4:1

3:2

2:3

1:4

200

0

160

120

80

40

0

200

40

80

120

160

0

60

12

24

36

48

Fibrates-antimalarials

Gemfibrozil

Fenofibrate

Fenofibric acid*

1:0

0:1

1:1

1:3

1:30

1:300

1:3000

3:1

30:1

300:1

3000:1

1600

0

1600

533.3

53.3

5.33

0.533

1600

1600

1600

1600

2500*

0

2500

833.3

83.3

8.33

0.833

2500

2500

2500

2500

0

1600

1600

1600

1600

1600

1600

533.3

53.3

5.33

0.53

0

100

100

100

100

100

100

33.3

3.33

0.33

0.033

6.2.3 Dosed Plasma Bioassay

Due to the possibility that active metabolites and other in vivo factors might contribute

to enhanced antimalarial activity of fenofibrate and atorvastatin, such as those observed

for atorvaquone (Butcher et al. 2003; Edstein et al. 2005), bioassays were performed.

For atorvastatin bioassay, a pre-treatment venous blood sample was taken from a


159

healthy volunteer who was then given atorvastatin 80 mg (Lipitor™, Pfizer, NY) once

daily for 4 consecutive days. A second venous blood sample drawn 3 hr after the last

dose at the time of the predicted maximal plasma concentration (Cilla et al. 1996). The

samples were centrifuged promptly and aliquots of separated plasma stored at -20°C.

Aliquots of pre- and post-treatment plasma were used for atorvastatin assay using

HPLC (Nirogi et al. 2006).

For fenofibrate bioassay, a pre-treatment blood sample was taken from a healthy

volunteer who was then given fenofibrate at 145 mg (Lipidil ™, Solvay

Pharmaceuticals) once daily for 6 consecutive days. A second blood sample was drawn

on day 6 at the time of the predicted maximal plasma concentration of fenofibric acid at

steady state (i.e. 4 hr after the final dose) (Keating et al. 2002). The heparinised blood

samples were centrifuged promptly and aliquots of separated plasma were stored at -

20°C. Plasma fenofibric acid levels from pre- and post-treatment samples were

measured, after extraction in hexane/chloroform/isopropanol, (18:80:2, v/v/v), by

validated high performance liquid chromatography assay with tandem mass

spectrometric detection and 2-(2,4,5-trichlorophenoxy)-propionic acid as internal

standard (Laboratoires Fournier S.A., Daix, France) (Zhu et al. 2010). Approval for

these procedures was obtained from the South Metropolitan Area Health Service

Human Research Ethics Committee.

A modified microdilution isotopic technique (Desjardin 1979; Kotecka et al. 2003) was

used to determine the antimalarial activities of pre- and post-treatment plasma. For

atorvastatin bioassay, pre- and post-treatment plasma were spiked with CQ

(concentration range, 3.9 to 250 nM), and DHA (0.9 to 60 nM), or an equivalent

volume of drug-free RPMI. For fenofibrate bioassay, the drug levels in the post-

treatment plasma and inhibitory properties from preliminary in vitro data indicated that

these were adequate for a direct assessment using two-fold serial dilutions in drug-free

RPMI without the need to spike with an active antimalarial drug. In triplicate

experiments, aliquots of 100 µL of plasma were added to 90 µL of parasite suspension

(1% parasitaemia, 1.5% hct) and 10 µL of 3H-hypoxantine (0.5 µCi) in 96-well plates,


160

and the mixture was incubated, harvested and counted (Karl et al. 2009).

6.3 RESULTS

6.3.1 In vitro Antimalarial Activities of Statins

The in vitro inhibitory effects of atorvastatin, rosuvastatin, simvastatin, pravastatin and

CQ are summarised in Table 6.2. All statins showed antimalarial activity, but

atorvastatin was more potent than rosuvastatin. The IC50 and IC90 values for each statin

did not differ between CQ-sensitive and CQ-resistant strains and were well above those

for CQ, even against CQ-resistant strains. Simvastatin and pravastatin were weak

against P. falciparum (IC50>200 µM).

6.3.2 In vitro Antimalarial Activities of Fibrates

The in vitro inhibitory effects of gemfibrozil, clofibrate, fenofibrate, fenofibric acid and

CQ are summarised in Table 6.3. All fibrates showed antimalarial activity but

fenofibric acid was most potent. With the exception of gemfibrozil, the IC50 values of

other fibrates did not differ between CQ-sensitive and CQ-resistant strains and were

well above those for CQ.


161

Table 6.2 In vitro activities of statins against CQ-sensitive and CQ-resistant strains of P. falciparum. The means (and 95% CIs) shown are from

at least four independent triplicate experiments. *Inhibitory concentrations for chloroquine are in nanomoles. Data from CQ-resistant strains Dd2 and

E8B were similar and have been pooled

Strain Atorvastatin Rosuvastatin Pravastatin Simvastatin Chloroquine

IC50 (µM) IC90 (µM) IC50 (µM) IC90 (µM) IC50 (µM) IC50 (µM) IC50 (nM)

3D7 25 (16 - 39) 68 (38 - 121) 80 (47 - 137) 205 (113 - 373) >200 >200 30 (23 - 29)

Dd2/E8B 17 (8 - 37) 39 (24 - 62) 80 (37 - 174) 232 (133 - 403) >200 >200 271 (138 - 533)


162

Table 6.3 In vitro activities of fibrates against CQ-sensitive and CQ-resistant strains of P. falciparum. Data represent at least six experiments

performed in triplicate. *Inhibitory concentrations for chloroquine and fenofibric acid are in nanomoles.

3D7 IC50 (µM) IC90 (µM)

W2mef IC50 (µM) IC90 (µM)

Clofibrate 184 (98 - 345) 441 (264 - 736) 256 (197 - 332) 708 (514 - 976)

Gemfibrozil 311 (245 - 395) 541 (446 - 657) 245 (181 - 332) 511 (445 - 587)

Fenofibrate 69 (54 - 88) 228 (171 - 304) 72 (65 - 80) 178 (152 - 210)

Fenofibric acid 152 (109 - 212)* 250 (191 - 326)* 1120 (916 - 1369)* 2436 (1866 - 3179)*

Chloroquine 23 (15 - 34)* 48 (23 - 99)* 230 (202 - 261)* 495 (334 - 732)*


163

Figure 6.1 In vitro susceptibility of laboratory strains of P. falciparum to cholesterol-lowering drugs and chloroquine.


164

6.3.3 Interaction of Atorvastatin with Conventional Antim alarials

The potential use of atorvastatin as a partner drug with conventional antimalarials was

investigated by means of isobolograms. In vitro interactions between atorvastatin with

CQ and DHA are shown in Figure 6.2. The interaction was indifferent in each case with

a mean ΣFIC [95% confidence interval] of 1.05 [0.97 to 1.14] for atorvastatin-CQ and

1.08 [0.99 to 1.17] for atorvastatin-DHA.

6.3.4 Interaction of Fibrates with Conventional Antimalar ials

There were no synergistic combinations identified from the drug interaction studies

involving fibrates, CQ, DHA and atorvastatin. For fenofibric acid-CQ there was no

interaction present for 3D7 but antagonism for W2mef. In the case of gemfibrozil-CQ

against 3D7 there was antagonism and indifferent interaction in W2mef. The remaining

combinations including that for fenofibric acid-atorvastatin showed indifferent

interactions.


165

Figure 6.2 Interaction between atorvastatin and conventional antimalarials.

Isoboles showing the FICs of atorvastatin plotted against those for CQ (left-hand panel)

and DHA (right-hand panel). The isoboles are representative of three independent

experiments in which each of the 6 drug ratios was tested in duplicate. The degree of

interaction (I) with 95% CI is represented by grey and dotted lines, respectively.


166

Table 6.4 In vitro efficacy of fibrates and antimalarial drug combinations.

Fenofibrate, fenofibric acid and gemfibrozil in combination with CQ, DHA and

atorvastatin were assessed against P. falciparum clones 3D7, W2mef and Dd2 using

isobolographic analysis. Data are the interaction factor (I) and the summed fractional

inhibitory concentration (ΣFIC) with 95% CIs. The assessment of interaction is based

on both I and ΣFIC data (see text). Interaction between fenofibrate-dihydroartemisinin

was not determined.

I (95% CI) ΣFIC (95% CI) Interaction

3D7

Fenofibric acid-chloroquine 0.23 (-0.06 to 0.51) 0.99 (0.95 to 1.02) Indifferent

Fenofibric acid-dihydroartemisinin -0.26 (1.02 to 0.50) 1.11 (0.99 to 1.21) Indifferent

Fenofibric acid-atorvastatin -0.33 (-1.92 to 1.26) 1.19 (1.02 to 1.35) Indifferent

Fenofibrate-chloroquine -0.67 (-1.40 to 0.05) 1.08 (0.98 to (1.12) Indifferent

Gemfibrozil-chloroquine -1.53 (-2.44 to -0.62) 1.12 (1.01 to 1.23) Antagonistic

Gemfibrozil-dihydroartemisinin -1.34 (-3.34 to 0.66) 1.20 (0.95 to 1.45) Indifferent

W2mef/Dd2

Fenofibric acid-chloroquine -1.07 (-2.08 to -0.07) 1.19 (1.02 to 1.36) Antagonistic

Fenofibric acid-dihydroartemisinin -0.48 (-1.31 to 0.36) 1.11 (1.02 to 1.21) Indifferent

Fenofibric acid-atorvastatin -0.81 (-1.52 to -0.09) 1.08 (0.96 to 1.19) Indifferent

Fenofibrate-chloroquine -0.41 (-1.01 to 0.19) 1.01 (0.93 to 1.10) Indifferent

Gemfibrozil-chloroquine -0.55 (-1.80 to 0.73) 1.19 (0.99 to 1.40) Indifferent

Gemfibrozil-dihydroartemisinin -0.25 (-2.10 to 1.61) 1.15 (0.95 to 1.40) Indifferent


167

6.3.5 Bioassay of Atorvastatin

The ability of atorvastatin-containing plasma to inhibit P. falciparum in vitro was

assessed by bioassay. Plasma atorvastatin concentrations in the healthy volunteer were

undetectable at pre-treatment and were 118 µg/L (0.1 µM) post-treatment. Neither pre-

nor post-treatment plasma inhibited growth of 3D7 (Figure 6.3). The 3D7 IC50s for CQ

alone, CQ plus pre-treatment plasma, and CQ plus post-treatment plasma were similar

(20.5 nM, 20.5 nM, and 20.4 nM, respectively), as were those for DHA alone, DHA

plus pre-treatment plasma, and DHA plus post-treatment plasma (12.7 nM, 20.1 nM,

and 19.2 nM, respectively).

6.3.6 Bioassay of Fenofibric Acid

The antimalarial activity of fenofibric acid generated in vivo as a result of fenofibrate

dosing was assessed by bioassay (Figure 6.4). Plasma fenofibric acid concentrations in

the healthy volunteer were undetectable at pre-treatment and were 13.0 mg/L post-

treatment (i.e. plasma fenofibric acid concentration 40,816 nM). Post-treatment plasma

inhibited growth of 3D7 at dilutions between 8 to 1024-fold.


168

Figure 6.3 Atorvastatin bioassay. Dose response of laboratory-adapted P. falciparum

subjected to conventional antimalarials with pre- and post- Lipitor™ (atorvastatin)

treatment plasma. No significant differences were indicated in response to pre- and

post-treatment plasma added to chloroquine (CQ) (top) and to dihydroartemisinin

(DHA) (bottom).


169

Figure 6.4 Fenofibrate bioassay. Growth response of laboratory-adapted 3D7 to two-

fold dilutions of plasma pre- and post-treatment of Lipidil ™ (fenofibrate). Data points

were obtained from three independent bioassays performed in triplicate.


170

6.3.7 BLAST Analysis for PPAR-like Region in Plasmodium

To elucidate possible mechanisms underlying the activity of fenofibric acid against

malaria parasites, similarity searches were conducted between mRNA and protein

sequences of human PPARα and P. falciparum using basic local alignment search tool

(BLAST, NCBI). Nucleic acid alignments between human and Plasmodium mRNA

produced 102 blast hits of short sequences (<40 bp). One hit had non-random matches

(expected value (E) <0.02) identified as a region encoding for a P. falciparum 3D7

conserved Plasmodium protein, however its function is unknown.

Comparisons between the human PPARα protein (NP_001001928.1) and reference

proteins for P. falciparum taxid (5833) resulted in three blast hits (Figure 6.5).

Although the alignment scores were <40 for all three sequences, two were located at the

PPARα DNA binding domain and one at the ligand binding domain. The latter,

identified as a conserved Plasmodium protein (XP_001350490.2) is of particular

interest since it aligns with both the ligand binding site and the heterodimer interface,

with 17% coverage of the human PPARα protein sequence.

In addition, the same Plasmodium protein was one of five hits with other

apicomplexans in comparison with the human PPARα protein. There were two hits

from Babesia bovis showing 22 and 27% coverage of the human protein sequence (E =

1.4 and 1.9), and two from Toxoplasma gondii with 11 and 17% sequence coverage.

The region (959-1030) of the Plasmodium protein identified as Plasmodium 1 in Figure

6.5, showed similarity with hypothetical proteins in other Plasmodium species including

P. knowlesi, P. vivax, P. yoelii, P. chabaudi and P. berghei. It also weakly aligned with

the PPARα protein sequence from Rhesus Macaque, Common Chimpanzee, Guinea pig

and human.

6.3.8 BLAST Analysis for ABC-1 transporter in P. falciparum

Proteins within the ATP-binding cassette sub-family A member (ABC-1) mediate

cholesterol and lipid transport, are within the same superfamily of ATP-binding cassette


171

(ABC) transporters as the multidrug resistant P-glycoprotein. Nucleic acid alignments

between human and Plasmodium mRNA produced 103 blast hits of short sequences (up

to 50 bp). Similarity searches between reference protein sequences of human ABC-1

and P. falciparum revealed the presence of a parasite homolog of this lipid efflux pump.

There were 49 protein alignment hits, 13 of the P. falciparum nucleotide sequences

spanned across two regions (900 to 1116 and 1927 to 2110) with a coverage up to 19%

(E <0.006) of the human ABC-1 query sequence (Figure 6.6). Two significant

alignments were found in the P. falciparum ABC transporter protein (XP_001350233.1)

and the P. falciparum multi-drug resistance protein 2 (XP_001348629.1) with E values

of 8-16and 1-12, respectively.


172

Figure 6.5 Distribution of Plasmodium BLAST hit sequences on human PPARα. Protein-protein alignments between human PPARα (468bp) and

P. falciparum was analysed by BLAST. Three P. falciparum protein sequences (green) have 10-17% coverage of the human PPARα sequence (grey).

These specific hits span over the PPARα DNA binding (blue) and ligand binding (red) domains. Plasmodium 1: conserved Plasmodium protein (E =

0.18) (XP_001350490.2), Plasmodium 2: erythrocyte membrane protein, PfEMP1 (E = 1.6) (XP_001349513.1), Plasmodium 3: conserved

Plasmodium protein (E = 8.4) (XP_001349690.1).


173

Figure 6.6 Distribution of P. falciparum BLAST hit sequence on human ABC-1. Protein-protein alignments between human ABC-1 (2261 bp)

and P. falciparum was analysed by BLAST. Thirteen of forty-nine P. falciparum sequences from the reference nucleotide database aligned at the same

two regions (green) with an overall of 10-19% coverage of the human ABC-1 protein sequence (grey). These specific hits spanned over the ABC-1

conserved domains (CD, in red). Two significant alignments were the P. falciparum ABC transporter protein (E = 8-16) (XP_001350233.1), P.

falciparum multi-drug resistance protein 2 (E = 1-12) (XP_001348629.1), both have alignment scores of 50 to 200.


174

6.4 DISCUSSION

The present data confirm that atorvastatin inhibits the growth of P. falciparum in vitro

(Grellier et al. 1994; Pradines et al. 2007). Consistent with previous findings (Pradines

et al. 2007), pravastatin and simvastatin had minimal activity against P. falciparum.

The antimalarial activity of atorvastatin is greater than that of rosuvastatin, but the

atorvastatin IC50 (17 to 25µM; Table 6.2) is approximately 100 times above that

achievable in plasma with repeated maximal (80 mg) doses (0.1 to 0.3 µM) (Borek-

Dohalsky et al. 2006). As might have been predicted from this observation, and

consistent with the hypothesis that the metabolism of atorvastatin does not generate

compounds with antimalarial activity, the bioassay showed that therapeutic plasma

concentrations had no inhibitory effect against cultured P. falciparum. In addition, there

was no synergy with conventional antimalarial drugs.

The ability of the malaria parasite to synthesise cholesterol de novo (i.e. via the

mevalonate pathway) appears limited (Vial et al. 1984; Wunderlich et al. 1991), and the

presence of an HMG-CoA homolog was not revealed by BLASTX analysis of the P.

falciparum sequence with other protozoan HMG-CoA protein sequences (Pradines et

al. 2007). These observations and the greater antimalarial potency of atorvastatin versus

rosuvastatin (the reverse of their ability to inhibit cholesterol synthesis in humans

(Jones et al. 2003)) suggest an alternative, albeit low-potency, mechanism of

antimalarial action to inhibition of HMG-CoA reductase.

The present study demonstrates that gemfibrozil, fenofibrate and clofibrate have weak

activity relative to conventional antimalarial drugs in vitro. Nonetheless, their IC50s are

similar to antibiotics that are used for malaria prophylaxis and adjunctive therapy

(Nakornchai et al. 2006). This activity may have accounted for the lower infection rate

in the clofibrate-treated group of animals observed previously (McQuistion 1979),

although the inflammation modulating effects of clofibrate may have also contributed.

Fenofibric acid, the major metabolite of fenofibrate in vivo (Kirchgassler et al. 1998),

has greatest activity at nM media concentrations similar to those of conventional agents.

As might have been predicted from this observation, and consistent with the hypothesis

that the metabolism of fenofibrate would generate sufficient fenofibric acid with


175

antimalarial activity, the bioassay showed that therapeutic plasma concentrations (13

mg/L or 40,816 nM) had inhibitory effect against cultured P. falciparum with IC90s of

CQ-sensitive and resistant strains at 250 nM and 2436 nM, respectively.

An inhibitory effect was also observed in pre-treatment plasma against P. falciparum.

Plasma from healthy individuals can interfere with parasite survival via complement-

mediated cell lysis. Non-heat treated sera was shown to reduce parasite growth as much

as 25% compared to heat-treated control (Teja-Isavadharm et al. 2004). Therefore, heat

inactivation of pooled human plasma is required to reduce this growth inhibitory

activity prior supplementation in culture medium (Appendix B). Plasma fenofibric acid

is stable for up to 8 hr at room temperature (Dubey et al. 2010); however, its stability in

plasma at 50°C is unknown. Therefore, to minimise the risk of drug degradation,

plasma samples in the bioassays were not heat-treated. This may explain the apparent

dose-response of pre-treatment plasma against the parasite. Treatment of bioassay

plasma with non-heat approaches such as the use of Affingel Protein-A may reduce this

inhibition by removal of human immunoglobulin G (Teja-Isavadharm et al. 2004).

For a drug to be clinically useful, the plasma concentration achievable in vivo should be

a number of magnitudes higher than the in vitro inhibitory concentration. The steady-

state maximum plasma concentration for fenofibric acid is approximately 25.5 mg/L

(i.e. 80 µM) (Miller et al. 1998), whilst the maximum plasma concentration of

fenofibric acid is in the range 3 – 15 mg/L (9.4 – 47 µM) after an oral dose of

fenofibrate of 100 or 200 mg (Bhavesh et al. 2009) with levels >0.4 mg/L (>1.2 µM)

sustained over 2 days. The plasma fenofibric acid level available with repeated

therapeutic doses is approximately 100 times more than that required to inhibit 50% of

cultured P. falciparum. A newer formulation of micronised fenofibrate may further

enhance bioavailability (Keating et al. 2002).

Although its mode of action remains to be elucidated, fenofibric acid may act by

interfering with P-glycoprotein (Ehrhardt et al. 2004) and ABC-1 mediated transport,

and/or via a putative PPARα-like protein. BLAST analysis revealed partial similarities

between a conserved Plasmodium protein sequence and that of the PPARα ligand


176

binding domain in humans. Despite the low alignments score, there may be sufficient

similarities at key amino acid positions for the tertiary protein conformation to interact

with fenofibric acid, resulting in subsequent metabolic interference. In human and

murine cells, fenofibric acid interferes with the expression of ABC-1 (Jaye et al. 2003;

Arakawa et al. 2005), thus altering lipid accumulation. Fenofibric acid effects on the

Plasmodium ABC-1 homolog may disturb the development of P. falciparum by similar

mechanisms, depriving the growing parasite of lipid components of membranes and

other cellular structures.

In conclusion, this study confirmed statins to have antimalarial properties but at a

concentration higher than that achieved by therapeutic doses (Borek-Dohalsky et al.

2006). In addition, even at supra-therapeutic doses, no synergy with CQ or DHA was

observed. Although atorvastatin has been shown to prevent cytoadherence of P.

falciparum to endothelial cells in co-culture models (Taoufiq et al. 2011), outcome data

from animal models of severe malaria showed no protection (Bienvenu et al. 2008;

Kobbe et al. 2008). These in vivo studies together with the present in vitro findings and

do not support calls for clinical trials of statins as adjuvant antimalarial therapy

(Bienvenu et al. 2008).

The present experiments also revealed fenofibric acid to be the most active lipid-

modifying agent against P. falciparum in vitro. The favourable pharmacokinetics of

fenofibrate (Miller et al. 1998; Bhavesh et al. 2009) along with the high antimalarial in

vitro activity of its major metabolite fenofibric acid warrants confirmatory in vivo

investigation of this promising therapeutic application.

The statin component of this work has been published in Antimicrobial Agents and

Chemotherapy, titled “Statins as potential antimalarial drugs: Low relative potency and

lack of synergy with conventional antimalarial drugs”. The fenofibrate component is

undergoing review for a patent.

CHAPTER 7

DETECTION OF VOLATILE ORGANIC

COMPOUNDS OF PLASMODIUM

FALCIPARUM IN VITRO

Chapter 7 Volatile Organic Compounds

178

CHAPTER 7. CHARACTERISATION OF VOLATILE

ORGANIC COMPOUNDS OF P. FALCIPARUM IN VITRO

7.1 INTRODUCTION

The detection of viable parasite forms is an essential requirement for malaria diagnosis

and subsequent monitoring of the response to antimalarial therapy. For diagnosis,

microscopic examination of a peripheral blood smear remains the investigation of

choice in a wide variety of clinical situations. However, the sensitivity of microscopy is

limited even when expert microscopists view high quality slides. In addition, the

diagnosis may be missed in cases of severe falciparum malaria in which the majority of

parasites are sequestered within the microvasculature of major organs (Coltel et al.

2004; Safeukui et al. 2008) or in the placenta in infected expectant mothers (Duffy

2007; Goyal et al. 2009). Antigen detection kits can be used where reliable microscopy

is unavailable but they have even lower sensitivity and specificity (Section 1.6). PCR

increases diagnostic sensitivity but its timely availability is limited largely to

specialised laboratories in developed countries. In addition, the sensitivity of PCR

(down to 1 parasite/µL) means that even a child weighing only 15 kg and with a

circulating blood volume of approximately 1 litre who is PCR-negative may still

harbour up to a million malaria parasites. The monitoring of the response to antimalarial

therapy in individual patients depends on the availability of serial blood smears

complemented by PCR where available. Antigen detection methods cannot be used

because of the persistence of antigen after parasite clearance, while PCR does not

differentiate between DNA from viable and non-viable parasites.

There is a need for the development of alternative diagnostic tests that detect viable

parasites before and after treatment with greater specificity and sensitivity than

currently available methods. The human breath contains a large number of volatile

organic compounds (VOCs) derived from the blood by passive diffusion in the lungs

(Phillips et al. 1992c). VOCs in the breath are directly related to concentrations in blood

and other tissues as they flow from compartments with higher vapour pressure to those

with lower pressure (Phillips 1992b). Breath tests have been used to assist in the early

diagnosis of conditions such as heart disease, rheumatoid arthritis and lung cancer


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(Gordon et al. 1985; Humad et al. 1988; Weitz et al. 1991) as they detect increased

VOCs released as a result of disease-specific cellular injury. More recently, exogenous

VOCs produced by microorganisms such as Mycobacterium tuberculosis have been

found in the breath of infected patients (Phillips et al. 2007). Plasmodium species may,

in the same way, produce a characteristic VOCs ‘fingerprint’ that can facilitate

diagnosis and therapeutic monitoring. In the case of P. falciparum and perhaps P. vivax

(Anstey et al. 2007), the cytoadherence of mature parasite forms in the pulmonary

microvasculature may facilitate detection of Plasmodium-specific VOCs in breath

samples. The cause of altered consciousness in severe malaria remains unknown. VOCs

are used as general anaesthetics in clinical practice (Soukup et al. 2009) and it is

possible that coma complicating malaria may result from elaboration of VOCs by

malaria parasites in the cerebral microcirculation that have anaesthetic properties. In

any case, malaria may, through indirect pathogenic tissue effects such as oxidative

stress, alter the VOCs content of human breath in ways that are characteristic of the

infection.

A number of extraction techniques are used for the capture and analysis of VOCs from

human breath and the microbial culture atmosphere (Phillips 1997; Lechner et al.

2005a; Syhre et al. 2008; Martin et al. 2010; Risticevic et al. 2010). Sampling and

sample preparation involve pre-concentrating the analytes of interest by purge and trap,

headspace, liquid-liquid or solid phase extractions. These conventional techniques

consist of multiple labour-intensive procedures and/or require organic solvents. Solid

phase micro-extraction (SPME) is an adsorption/desorption technique that circumvents

most of the drawbacks to sample preparation (Risticevic et al. 2010). SPME can be

used to concentrate volatile and non-volatile compounds in liquid samples or headspace

without the use of solvents with sensitivities down to parts per trillion (Risticevic et al.

2010), where the target compounds are subsequently separated and quantified by gas

chromatography-mass spectrometry (GC-MS).

This chapter outlines the design and optimisation of a P. falciparum culture-sampling

system suitable for VOCs headspace capture and analysis. Mass spectra of VOCs

emitted by P. falciparum in vitro using GC-MS are also reported. Identification and


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evaluation of these chemical finger-prints may have useful indications for diagnosis and

may yield insights into the metabolism and pathogenicity of P. falciparum.


7.2.1 Parasites

The laboratory-adapted P. falciparum strains 3D7 (chloroquine-sensitive) and W2mef

(chloroquine-resistant) were maintained in RPMI 1640 HEPES as previously described

(Section 2.1). Once the parasitaemia was >5%, synchronous cultures at the trophozoite

stage were transferred into custom-designed containers (Section 7.3.1) at 1% hct and

purged with a mixture of 1% O2 and 5% CO2 in nitrogen at 5 psi for 4 sec and 30 sec

for prototypes 1 and 2, respectively. Subsequent optimisation used 5% O2 and 5% CO2

in nitrogen at 15 psi for 40 sec in the prototype 2 culture-sampling apparatus. The

volume of media required to sustain high parasitaemia was calculated using the

formula: volume of media (mL)/24hr = 0.005 x (µL RBC pellet) x (% parasitaemia)

(Radfar et al. 2009). This equation takes into account the nutrient requirements for non-

parasitised as well as parasitised RBC. A control was set up with non-infected RBC

using similar conditions and incubated for 24 hr at 37°C.

7.2.2 Solid Phase Micro-Extraction (SPME)

After incubation, samples were double-contained and transported to the School of

Biomedical, Biomolecular and Chemical Sciences (UWA) for extraction and analysis.

Volatile and semi-volatile compounds within the headspace of non-parasitised control

and malaria cultures were pre-concentrated onto a polydimethylsiloxane (PDMS, 100

µM) coated SPME fibre (SUPELCO, Bellefonte, PA, USA, #57300-U or portable field

sampler #504823) for 1 hr in a heated waterbath (Section 2.4). In subsequent

experiments, a triple fibre, 50/30 µM Divinylbenzene/Carboxen/PDMS StableFlex

fibre™ (SUPELCO, Bellefonte, PA, USA, #57328-U) was also used. After sampling

was completed, the fibre was retracted and the SPME holder was manually loaded onto

the GC injector port where VOCs were desorbed for 5 min in splitless mode for 2 min.


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7.2.3 Solvent Extraction

Supernatants from 3D7 and W2mef cultures at high parasitaemia (5% to 13.2%) were

pooled together (100 mL and 150 mL, respectively). Cell pellets of each strain were

lysed by sonication (Microson™ ultrasonic cell disruptor, Misonix Inc, NY) for 30 sec

and diluted with distilled water prior to extraction. The aqueous supernatant was

transferred into a separation funnel and partitioned 3 times with ⅓ volume of an organic

solvent (hexane, dichloromethane or ethyl acetate). The procedure involved gentle

swirl-mixing with occasional depressurisation via the outlet valve of the funnel. After

repositioning the funnel to the retort stand, the aqueous and organic phases gradually

separated (Figure 7.1)

7.2.4 Thermal Desorption: Purge and Trap

For purge and trap extraction, non-parasitised control and P. falciparum infected RBC

were cultured in prototype 2 containers (Figure 7.2). Air was drawn through the side

inlets containing a loosely fitted cap and through the flask over the surface of the

samples and the VOCs were trapped using a Tenax™ trap (200 mg, SUPELCO,

Bellefonte, PA, USA). The headspace was collected for 1 hr at an airflow rate of 1.5

L/min using a portable air sampling pump (224-PCXR8, SKC Inc.) The trap was

inserted into a short path thermal desorption injector (TD-2, Scientific Instrument

Services, Inc.) and desorbed for 5 min at 200°C using a flow of helium (2 mL/min) into

the GC-MS injection port that was also set at 200°C. The desorbed VOCs were

collected on the column during the desorption process by cooling a small section of the

capillary column with an ethanol/dry ice bath (-20°C to -40°C). The column was then

equilibrated to 35°C and the temperature program on the GC-MS was started. The

compounds were separated using a 30 m × 0.25 mm i.d., 0.25 µm BPX-5 column

(SGE), which was set at 35°C for 2 min and increased at 7°C/min until 250°C, and held

for 10 min. The mass spectrometer was set to record between 45 and 400 amu.


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Figure 7.1 Extraction of VOCs from culture supernatant by an organic solvent.

The aqueous phase was set aside whilst the organic phase was collected into a clean,

acetone-rinsed flask. The aqueous phase was subjected to repeated extraction into an

organic solvent (a). The organic phase was then extracted against distilled water and

collected into a conical flask followed by drying over anhydrous magnesium sulphate.

After filtration (Whatman™ filter papers) (b), the extract was transferred into a round

bottom flask where the solvent was evaporated under reduced pressure by means of a

rotary evaporator (Rotavapor-R, Buchi Labortechnik, Flawil, Switzerland) (c). For

analysis by GC-MS, extracts were evaporated to dryness under nitrogen (d) and

resuspended in 100 µL of the extraction solvent.


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Figure 7.2 Purge and trap set-up for thermal desorption. The prototype 2 sampling

apparatus was kept warm (37°C) using a waterbath heated with a hotplate/magnetic

stirrer. A stirrer bar was used to equilibrate the temperature in the waterbath which was

measured with a thermometer. Air was drawn at a steady rate by vacuum through the

flask for 1 hr through a loose inlet cap (C). The headspace VOCs were passed through

an adsorptive trap (Tenax™) (B) fitted between Teflon tubing (A) where the VOCs were

retained.

7.2.5 Gas Chromatography and Mass Spectrometry

SPME and solvent extracted samples were subjected to GC-MS (Shimadzu GCMS-

QP2010, Kyoto, Japan). The separation of emitted components was achieved using a 30

m × 0.25 mm i.d., 0.1 µm Rt-Stabilwax (Restek, Bellefonte, PA) column in splitless

injection mode with ultra-high purity helium as the carrier gas at a constant flow rate of

1 mL/min. The initial oven temperature was set to 35°C and held for 5 min then ramped

at 7°C/min to 250°C at which compounds were desorbed. The desorption time for

SPME was 5 min, while for solvent injections 1 µL was injected. The ion source was

set at 200°C, and the spectrometer was set to record between 45 and 400 amu (Flematti


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et al. 2009).

7.2.6 Data Analysis

Data collection and mass spectra generation were performed using the GC-MS Real

Time Analysis software and Postrun application (GCMSsolution, version 2.40

Shimadzu Corporation). For compound identification, mass fragments of the target

molecule were screened interactively against commercial Mass Spectral Libraries

(NIST05, NIST05s, Gaithersburg, MD).

7.3 RESULTS

7.3.1 Malaria VOCs Assay Development

7.3.1.1 Design of culture-capture apparatus

Preliminary studies employed T25 flasks coupled with a rubber stopper with two inlets

for the culture and capture of headspace atmosphere (Skinner-Adams T, data

unpublished). However, the use of plastic containers and rubber introduces organic

contaminants which may interfere with the assay. Therefore, custom-designed glass

flasks were created for the in vitro capture of headspace VOCs experiments.

The prototype 1 sampling unit for VOCs analysis consisted of a 250 mL conical flask

modified with a B-40 joint (Figure 7.3). The flask was fitted with an custom built

aluminium stopper coupled with a delrin-polymer holder that served as the SPME

holder. A small machined section at the base of the delrin holder allowed the placement

of a polytetrafluoroethylene (PTFE) septum above a small opening in the metal stopper,

which was pierced during SPME sampling. The prototype 1 container allowed the

culture of 18 mL of parasite-cell-medium suspension. The culture flask and metal

stopper were autoclave-sterilised prior to use.

To maximise parasite mass and VOCs yield, a second design was proposed featuring a

shallow container with a large base-area (Figure 7.2 and Figure 7.4). The prototype 2


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sampling units were custom-made and equipped with two Duran screw thread tube

connections (GL14, Vel, Leuven, Belgium) useful for purge and trap, and SPME

sampling. A B-24 joint with a fitted glass stopper improved access to the parasite

cultures and media changing. This was particularly important during the optimisation

phase of the study in which parasite growth was monitored daily by microscopic

examination of blood smears. The new design allowed a larger volume set-up (50 mL)

of parasite-cell-media suspension. Cultures of high parasitaemia (>20%) were achieved

under the conditions specified in Section 7.2.1, as facilitated by the maximised

air/medium contact surface available for gas-exchange in the new design.

Figure 7.3 Prototype 1 culture-capture apparatus with SPME. The prototype 1

design consisted of a conical flask modified with a B-40 joint that served as a receptacle

for an aluminium stopper. A delrin polymer SPME holder was screwed into the

aluminium stopper and between the mating surfaces, a syringe piercable PTFE septum

was placed to seal the sample before analysis.


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Figure 7.4 Design and dimensions of culture container (prototype 2) for headspace

capture. The wide-base (154 cm2) and shallow design maximises culture efficiency

and total parasite yield. The B-24 joint allows for easy access during RPMI addition

and parasite sampling. Two side inlets facilitate the ease of low-oxygen gas-

replacement and act as an access point for ‘purge and trap’ procedures and SPME of the

headspace atmosphere.

7.3.1.2 Optimisation of culture conditions

Headspace capture requires an enclosed culture system, where the atmosphere within

the culture container must be optimised for parasite growth. The gas mixture of 1% O2

and 5% CO2 in nitrogen used for routine cultures (i.e. in a 28.4 L Nalgene dessicator)

was suboptimal to sustain P. falciparum growth in the custom-designed containers. On

macroscopic examination, RBC became much darker post incubation, likely attributable

to inadequate oxygenation. A series of down-sized, volume vs duration of gas injection

experiments were conducted with an oxygen monitor to determine optimal gas balance

(data not shown). Although conditions for normal parasite replication were achieved,

optimal growth was subsequently attained with a new gas mixture of 5% O2, and 5%

CO2 in nitrogen (Mlambo et al. 2007). This gas composition allowed complete

replacement of the air within the vessel with an atmosphere that is more suited for P.

falciparum culture. This adaptation negated the need to find the intricate balance of gas-

purging duration to lower the O2 content in the air as previously performed.


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Routine in vitro culture of P. falciparum usually maintains a maximum of 5%

parasitaemia at 5% hct. Prototype 2 container was more suitable for malaria culture than

its predecessor. The initial period for VOCs capture was over 48 hr (i.e. one parasite life

cycle), however, the system must remain enclosed during this time without the required

media changes. This approach produced stressed parasites as indicated by the presence

of gametocytes by microscopy. Therefore, subsequent capture experiments were set-up

over the later 24 hr of the developmental cycle where there is maximal parasite

metabolic activity. Synchronised P. falciparum were cultured at high parasitaemia and

pooled into prototype 2 containers at the trophozoite stage (>20% parasitaemia at 1%

hct). To promote liberation of VOCs from the parasite-media matrix to the headspace,

sample containers were incubated in a shaking incubator at slow rotation (40 rpm) for

24 hr.

7.3.2 Analysis of VOCs

This part of the present study employed a number of extraction approaches to capture

and analyse VOCs from the culture samples. Headspace VOCs were extracted by

SPME (PDMS and combined Carboxen/DVB/PDMS phases) and purge and trap

coupled with thermal desorption. Direct immersion of the SPME fibre, and traditional

extractions with organic solvents with various polarities were used to extract VOCs

trapped in the culture supernatant and cell lysate matrix. Overall, mass spectra of over

100 different compounds were detected in the headspace, supernatant and cell lysates of

both non-parasitised control and P. falciparum cultures (Appendix E). Most masses

represent hydrocarbons such as alkanes and alkenes, alcohols, benzene-derivatives and

organic acids. Table 7.1 presents a selection of commonly observed compounds in the

samples. Although minor differences in compound quantities were detected on

occasions, no unique biomarker for P. falciparum was identified. Similarities between

VOCs liberated from non-parasitised control and infected samples are demonstrated in

the chromatograms from various extraction methods (Figure 7.5).


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Table 7.1 VOCs detected in culture headspace.

Compound Intensity Relative abundance (%)

1-Hexanol, 2-ethyl-* 23,423,000 66

Heptane, 2,2,4,6,6-pentamethyl- 2,665,000 7.5

Benzene, 1,3-bis(1,1-dimethylethyl)- 2,532,000 7.1

Decane 1,794,000 5.1

1-Dodecanol 3,7,11-trimethyl- 1,005,000 2.8

Cyclohexanone 893,000 2.5

1-Octen-3-ol 649,000 1.8

Octane, 3,3-dimethyl- 634,000 1.8

Decane, 3,7-dimethyl- 334,000 0.9

Decane, 5,6-dipropyl- 298,000 0.8

2,4-Dimethyl-1-heptene 290,000 0.8

2,2,4,4-Tetramethyloctane 273,000 0.8

Decane, 3,7-dimethyl- 271,000 0.8

Undecane 218,000 0.6

Nonane, 4-methyl- 213,000 0.6

*Suspected organic contaminant.


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Figure 7.5 Chromatograms of VOCs in the headspace of cultured P. falciparum.

GC-MS total ion chromatograms; black line: VOCs detected in non-parasitised control;

pink line: VOCs detected in culture-adapted P. falciparum. Data collected from (a)

solid phase micro-extraction (SPME); (b) SPME-triple fibre; (c) purge and trap thermal

desorption; (d) solvent (dichloromethane) extraction of culture supernatant.


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7.4 DISCUSSION

Despite substantial attempts following a step-wise approach, the present in vitro study

revealed no specific patterns of VOCs released by P. falciparum cultures. Various

forms of solvent extractions (hexane, dichloromethane, ethylacetate) of supernatants

and cell lysates showed minimal differences compared to control non-parasitised

cultures. When used with a pre-concentration device such as SPME, GC-MS has

sufficient sensitivity in the low ppt range (Chambers et al. 2009; Chambers et al. 2010).

Despite this sensitivity, data from SPME using conventional (PDMS) and triple fibre

(PDMS+divinylbenzene+carbowax) revealed production of a variety of VOCs in

cultured P. falciparum but no unique compounds were identified. Thermal desorption

of purge and trap samples also showed no significant differences with a similar VOCs

profile to that observed with SPME, suggesting that both techniques were detecting the

majority of released VOCs.

Previous studies of VOCs generated by other infectious agents have shown positive

associations between VOCs liberated in vitro and those detected in the breath from

patients. This in vitro vs in vivo relationship is exemplified by studies of respiratory

infections with Aspergillus fumigatus (Syhre et al. 2008; Preti et al. 2009; Chambers et

al. 2010) and pulmonary tuberculosis (Phillips et al. 2007). There were, however, a

number of important differences between these studies and the present series of

experiments. Firstly, bacterial and fungal colonies are cultured on solid medium. Any

VOCs produced by bacteria and fungi are released directly into the culture headspace.

By contrast, P. falciparum are enveloped by two extra layers, being within RBC that

settle at the bottom of liquid medium in the culture plate. The possibility of loss of

VOCs of malarial origin in cell membranes and the culture medium prompted repeated

extractions of supernatant and cell lysate using various organic solvents. No obvious

differences between malaria and control cultures were found in these experiments.

Secondly, the biomass of bacteria and fungi in vitro assessed from colony-forming units

(cfu), viable bacterial or fungal cells per visible colony is much greater than that of P.

falciparum in a typical culture. The number cfu per visible colony is substantially

higher than the number of malaria parasites in a comparable volume of RBC. For


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Mycobacterium tuberculosis culture, an inoculum of 0.5 mL of a 1.0 McFarland

standard contains 1.5 x 108 cfu) (Phillips et al. 2007) compared to a 50 mL P.

falciparum culture of 20% parasitaemia at 1% hct which contains approximately 1.1 x

107 parasitised cells. In addition, the greater biomass for bacteria housed within a

smaller culture vessel (1 mL headspace) considerably increases the concentration and

thus likelihood of VOCs detection compared with the larger headspace (500 mL) of an

intra-erythrocytic parasite culture.

The analysis of VOCs released from in vitro malaria cultures presented a substantial

challenge because of the fastidious nature of P. falciparum in culture including

microaerophilic requirements, daily medium changes and the need for a closed-system

for headspace capture. Although the use of glass culture-capture apparatus minimised

the presence of contaminants related to the use of plastics, a number of external VOCs

were present. Compounds such as diethy-phthalate and ethylhexanol (Appendix E) may

have been derived from bis-2-ethyl-hexyl-phthalate, a common additive to plastics

which renders the plastic more flexible. Siloxane derivatives were also prevalent such

as decamethyl-cyclopentasiloxane and dimethyl-silanediol, and were most likely

derived from the PDMS coating of the SPME fibre or the GC column stationary phase.

A number of different gas mixtures have been used to support malaria culture.

Atmospheres with combinations of 0.5 to 21% O2 mixed with 1 to 7% CO2 diluted in

nitrogen and microbial gas sachets have been employed (Trager et al. 1976; Mirovsky

1989; Taylor-Robinson 1998; Onda et al. 1999; Radfar et al. 2009). High oxygen

concentrations are considered to cause deleterious effects on parasites and reduce yields

(Scheibel et al. 1979), however this has been debated (Radfar et al. 2009). A mixture of

5% O2 with 5% CO2 in nitrogen supports malaria growth better than 5% CO2 with 95%

air (Cohen et al. 1969), although both mixtures have been successful (Miyagami et al.

1985; Mirovsky 1989; Flores et al. 1997; Onda et al. 1999; Radfar et al. 2009).

Therefore, although gas composition is an important consideration, it should not be

singled out as the determining factor for successful cultures, particularly for high

parasitaemias. In addition to the use of premixed gas, the transition from 5% hct for

routine P. falciparum culture to a lower hct (1%) proved an important modification to


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support high parasitaemia for the VOCs experiments. An appropriate ratio of medium

to cell pellet volume prevents parasite toxicity and helps maintain viability (Radfar et

al. 2009).

As SPME is based on attaining equilibrium in the sample or headspace, the GC-MS

chromatographs may not directly correspond to the actual composition of the detected

compounds. Quantitative information would require inclusion of a calibration curve for

each component (Gorecki et al. 1997). The aim of the study was, however, to

investigate the qualitative capacity of SPME to extract and simultaneously concentrate

VOCs released at both low and high quantities thus enabling comparisons of GC-MS

profiles of different samples under similar experimental conditions.

There were slight inter-assay differences in relative abundance and retention time of

VOCs between controls and P. falciparum samples. The difference in relative

abundance probably reflects differences in metabolic requirements of batches of RBC

and intra-erythrocytic parasites. The minor differences in retention time were probably

due to use of the instrument for unrelated interspersed experiments with resulting shifts

in calibration. However, these differences were minor, inconsistent and did not underlie

unique signals or chemical patterns.

Although VOCs may be more readily detected in vivo in respiratory diseases (Gordon et

al. 1985; Chambers et al. 2009; Preti et al. 2009; Chapman et al. 2010), VOCs

generated as part of host response to a systemic disease may also serve as biomarkers.

Examples include increased production of pentane and carbon disulfide in the breath of

patients with schizophrenia (Phillips et al. 1993). Nevertheless, their specificity remains

questionable, as breath carbon disulfide has been detected in both smokers and non-

smokers (Phillips 1992a) and has been linked with myocardial infarction (Weitz et al.

1991). An assessment of a characteristic VOCs fingerprint in the context of malaria

(including severe and non-severe cases) was beyond the scope of the present in vitro

experiments.

The present study used optimised experimental conditions to enable the capture,

extraction and analysis of VOCs liberated from P. falciparum cultures. Even at high


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parasitaemia, VOCs unique to P. falciparum cultures were not detected using solvent

extraction, purge and trap-thermal desorption, or by SPME. GC-MS data revealed a

variety of VOCs but no unique malarial finger-prints. Future in vivo studies analysing

the breath of patients with severe malaria may yet reveal specific clinically-useful

volatile biomarkers. The in vivo parasite biomass is substantially greater than

achievable in vitro and there may be VOCs generated as a specific in vivo response to

the disease.


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CHAPTER 8

CONCLUDING DISCUSSION

Chapter 8 Concluding Discussion

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CHAPTER 8. CONCLUDING DISCUSSION

8.1 OVERVIEW

With new national treatment regimens being introduced in PNG, this thesis presents a

timely assessment of the in vitro and genetic aspects underlying treatment efficacy in

PNG children with falciparum malaria. Through the implementation of two high-

throughput resistance surveillance techniques (pLDH and LDR-FMA), valuable

baseline data were obtained prior to the adoption of artemether-lumefantrine (AL) as

first-line treatment in PNG 2011. In addition, studies in this thesis explore novel

antimalarial agents that could become useful partners with artemisinin derivatives for

the treatment of uncomplicated falciparum malaria. The detection of P. falciparum-

specific volatile organic compounds (VOCs) in breath/other samples as a way of

enhancing diagnosis and therapeutic monitoring was also explored but this technique

does not appear to be a viable alternative to conventional methodologies for parasite

detection and enumeration.

8.1.1 Major Findings and Contributions

i. Most of the PNG isolates of P. falciparum tested (n=64) were resistant to

chloroquine (CQ) but not to other ACT partner drugs (lumefantrine (LM),

piperaquine (PQ), mefloquine (MQ) and naphthoquine (NQ)).

ii. In PNG P. falciparum isolates, strong associations were observed between their

in vitro responses to 4-aminoquinolines (CQ, amodiaquine (AQ) and NQ),

bisquinoline (PQ) and aryl-aminoalcohol (MQ) compounds suggesting cross-

resistance, but LM IC50s only correlated with that of MQ.

iii. There was fixation of pfcrt K76T, pfdhfr C59R and S108N, and pfmdr1

mutations in PNG isolates of P. falciparum (n=402). Multiple mutations were

frequent with 88% of isolates possessing quintuple mutations.


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iv. The pfmdr1 D1246Y mutation was associated with PCR-corrected day 42 in

vivo treatment failure in children allocated dihydroartemisinin (DHA) plus PQ

(P=0.004).

v. A non-isotopic semi-automated, high-throughput drug assay (using pLDH) was

implemented for the first time in PNG. The assay can be adapted to a basic

laboratory setting and facilitates serial assessment of local parasite sensitivity so

that emerging resistance can be identified.

vi. A novel extension of a multiplex, high-throughput ligase detection reaction-

fluorescence microsphere assay (LDR-FMA) was developed and implemented

for the screening of pfmdr1 mutations in PNG P. falciparum isolates.

vii. Desbutyl-lumefantrine (DBL) was found to be several folds more potent than its

parent compound against reference strains of P. falciparum and was mildly

synergistic with DHA.

viii. Mean plasma DBL concentrations were lower in children who failed AL

treatment than in those with an adequate clinical and parasitological response

(ACPR; P=0.053 vs P>0.22 for plasma LM and plasma LM:DBL ratio).

ix. Atorvastatin was more active than rosuvastatin, pravastatin and simvastatin

against culture-adapted P. falciparum, although it had weak activity (mean IC50

≥17 µM) and an indifferent interaction with CQ and DHA.

x. Fenofibric acid was the most potent lipid-modifying drug against CQ-sensitive

and resistant P. falciparum (mean IC50s 152 and 1120 nM, respectively). As

confirmed by the bioassay, the plasma fenofibric acid level available with

therapeutic dosing was 100 times that required to inhibit growth of P.

falciparum by 50%.

xi. A culture-capture apparatus for P. falciparum headspace VOCs was developed.


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Even at relatively high parasitaemia (>20%), in vitro parasite VOCs production

was undetectable, possibly due to loss of VOCs in the components of the

experimental system including erythrocytic forms and/or insufficient parasite

biomass.

The following sections highlight the major findings of the studies in this thesis and

discuss their relevance to the understanding of parasite resistance and their potential

applications. The first section examines the in vitro and genetic aspects of resistance in

PNG isolates of P. falciparum and considers their contribution to the prediction of

treatment efficacy. Limitations of these studies are also discussed. The second section

examines three different classes of agents as novel antimalarial treatments. The

screening of headspace biomarkers of P. falciparum cultures and insights into possible

underlying mechanisms of cerebral malaria and potential drug targets are also

discussed. Lastly, this chapter outlines directions for future research.

8.2 THE ROLE OF IN VITRO RESISTANCE AND PARASITE

GENETIC MUTATIONS IN TREATMENT OUTCOME

The results presented in this thesis provided timely baseline data on in vitro (Chapter 3)

and genetic (Chapter 4) aspects on drug resistance of P. falciparum isolated from

Madang children, prior to the change of national treatment policy from CQ-sulfadoxine

pyrimethamine (SP) to AL in 2011. In vitro drug sensitivity profiles of 64 isolates to

nine conventional (CQ, AQ, dAQ, DHA) and relatively novel (NQ, PQ, MQ, LM, AZ)

antimalarials were obtained. As expected from a history of heavy 4-aminoquinoline

usage, the majority (82%) of isolates were resistant to CQ in concordance with previous

PNG in vitro studies (Hombhanje 1998b; Mita et al. 2006a). The high level of in vitro

resistance was also consistent with near-fixation of the CQ resistance-associated pfcrt

allele as revealed by subsequent genotyping of parasite DNA (Chapter 4).

Strong associations were noted between the IC50s of 4-aminoquinoline (CQ, AQ, DAQ

and NQ), bisquinoline (PQ), and aryl aminoalcohol (MQ) compounds suggesting cross-

resistance, as observed in other countries (Fan et al. 1998; Basco et al. 2003a; Pradines

et al. 2006). These findings are consistent with the observation that pfcrt and pfmdr1


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alleles influence parasite susceptibility to drugs other than CQ such as MQ (Sidhu et al.

2002; Johnson et al. 2004; Mita et al. 2006a). LM and NQ have recently become

available in PNG as part of ACTs. In vitro sensitivities of PNG field isolates to both of

these drugs are described for the first time and could be used as a baseline for future

monitoring of resistance to these agents.

Since microscopic assessment of parasite response to drug exposure is time-consuming

and laborious, a validated high-throughput enzyme method (pLDH) was modified and

implemented in the field laboratory setting (Chapter 3). This approach allowed for

testing of multiple antimalarial drugs in triplicate with relative ease. The non-isotopic

semi-automated nature of the pLDH assay facilitated convenient serial assessment of

local parasite sensitivity so that emerging resistance could be identified with relative

confidence at an early stage. Although the pLDH assay was readily adaptable in this

setting, its relative high cost (AUD $30/plate, assaying four drugs in triplicate)

compared to microscopy limits its use for routine screening. Alternative non-isotopic

growth detection methods such as Sybr Green staining for DNA, although non-specific

to Plasmodium, are much more affordable and would be more likely to be employed for

future routine sensitivity testing in PNG (Karl et al. 2009).

Surveillance for parasite drug resistance mutations is becoming an established tool in

predicting treatment effectiveness, especially as it overcomes the challenges and costs

associated with in vivo testing. To investigate underlying molecular mechanisms, a

post-PCR, multiplexed ligase detection reaction-fluorescent microsphere assay (LDR-

FMA) was used to detect relevant single nucleotide polymorphisms (SNPs) in P.

falciparum drug resistance genes (Chapter 4). This technique enables simultaneous

identification of 18 SNPs in pfcrt, pfdhfr and pfdhps (Carnevale et al. 2007), and was

extended for the purposes of the present studies to screen for 10 allelic variants in

pfmdr1. The method is cost-effective (the analysis of 28 SNPs per sample cost AUD

$4.14), has a high output format suitable for large-scale epidemiological studies and

extends current PCR-based methods.

Molecular findings from the studies in this thesis are consistent with previous heavy use


200

of 4-aminoquinolines and SP in PNG (Chapter 4). Field isolates collected from children

with falciparum malaria showed a fixation of pfcrt 76T, pfdhfr 59R and 108N and

pfmdr1 mutations (>90%), consistent with previous PNG studies (Carnevale et al. 2007;

Mita et al. 2006a; Mita et al. 2006b; Schoepflin et al. 2008). A high prevalence of

multiple mutations across these genes was noted, with majority of the isolates (88%)

harbouring a quintuple mutation SVMNT+NRNI+KAA+Y YSND in codons 72-76 for

pfcrt, 51, 59, 108, 164 for pfdhfr, 540, 581, 613 for pfdhps, and 86, 184, 1034, 1042,

1246 for pfmdr1.

In determining underlying molecular factors that may influence in vivo outcomes, the

presence of the pfmdr1 1246Y mutation was associated with treatment failure in all

treatment groups combined (i.e. CQ-SP, artesunate-SP, PQ-DHA and AL) and in the

PQ-DHA group in particular. However, the association between pfmdr1 1246Y and

treatment failure is likely to be location specific. Parasite mutations are largely selected

by drug pressure exerted over a period of time with genetic haplotypes reflecting

parasite lineage and type of treatment employed in the region (Wongsrichanalai et al.

2002; Mita et al. 2007; Plowe 2009). Although the present findings relating to pfmdr1

1246Y may not be generalisable to other countries even within Oceania, they may

inform future surveillance strategies in epidemiologically similar areas. This situation

also pertains to PNG. A Peruvian study has shown that the P. falciparum SNPs pfdhfr

164L and pfdhps 540E predict SP treatment failure (Bacon et al. 2009). Despite the

previous widespread use of SP, these two mutations are rare in PNG in the present and

other studies (Carnevale et al. 2007; Mita et al. 2007) but the Peruvian experience

would support active surveillance for these parasite mutations if SP remains part of

nationally recommended treatment regimens. Although the pfmdr1 haplotype NFSDD

was found in only four isolates, it has been associated with AL treatment failure in

Africa (Happi et al. 2008). Therefore, monitoring changes in the pfmdr1 gene should be

of high priority due to the recent introduction of this treatment in PNG.

8.2.1 Limitations of PNG field studies

The assessment of the relationship between parasite in vitro drug sensitivity and clinical

outcome was limited by a restricted number of isolates available for testing. Overall,


201

there were 40 isolates with in vitro drug sensitivity profiles from children allocated

randomly to one of the four treatment arms in the large comparative trial (Karunajeewa

et al., 2008). Sixteen were from children treated with DHA-PQ and eight were from

subjects who received each of CQ-SP, artesunate-SP and AL. Unfortunately, the in

vitro component of the trial started when most children had been recruited while a

number of isolates that were successfully tested in vitro were from children who were

excluded post-hoc from the trial because of protocol violations.

There were only three cases of treatment failure in this in vitro-in vivo dataset. Of these,

two were late parasitological failures (PCR-confirmed recrudescences on day 28 and or

day 42) in the CQ-SP group, and one in the DHA-PQ group. The CQ IC50s of isolates

from the CQ-SP treatment failures were 197 and 126 nM, within the range obtained for

successfully-treated children in the same group and for all isolates tested (Table 3.2).

Therefore, in vitro CQ sensitivity alone is unlikely to be a useful predictor of treatment

outcome in the PNG setting, especially when in vitro CQ resistance is at fixation. For

the single DHA-PQ treatment failure, the PQ IC50 was 19.5 nM. Subsequent molecular

analysis revealed that all three parasite isolates possessed the pfcrt K76T allele and the

pfdhfr N51 R59 N108 I164 double mutation. Albeit in small numbers in this subset, the

presence of pfcrt and pfdhfr (markers for 4-aminoquinoline and pyrimethamine

resistance) in association with treatment failure is consistent with previous findings

(Cowman et al. 1988; Peterson et al. 1991; Casey et al. 2004).

Although the measurement of IC50s provides an acceptable indicator of drug sensitivity

trends in parasite populations, an isolate showing in vitro resistance may not equate to

treatment failure and vice versa (Wongsrichanalai et al. 2002; Ekland et al. 2008). This

is mainly attributed to host immunity and other in vivo factors. Pharmacokinetic profiles

are required to confirm that an adequate drug concentration has been achieved to

substantiate true resistance and treatment failure. Although these data are available

through the main clinical trial, the very low number of children with in vitro drug

sensitivity data that failed treatment limited their application.

Despite these limitations, in vitro drug susceptibility testing remains an important part


202

of the monitoring of resistance in the ACT era. The emergence of parasite resistance to

individual drugs employed in ACTs may not be clinically apparent due to the

effectiveness of the partner drug (Laufer et al. 2007). Although candidate molecular

markers for artemisinin resistance have been proposed (Price et al. 1999; Jambou et al.

2005; Uhlemann 2005), these cannot be validated unless true clinical resistance to

artemisinin drugs occurs. Therefore, in vitro drug assays are at the front-line of

surveillance for resistance to artemisinin derivatives and ACTs.

8.3 UNCONVENTIONAL AND NOVEL ANTIMALARIAL

AGENTS

There is a pressing need for new drugs and drug combinations that facilitate prompt

resolution of the symptoms of malarial infection, improve treatment success rates, and

limit the development of parasite resistance. To address this need, the studies in this

thesis have been directed towards identifying a number of novel antimalarial drugs.

These include DBL, a metabolite of an ACT partner-drug, and two classes of lipid-

modifying drugs, statins (i.e. atorvastatin, rosuvastatin, pravstatin, simvastatin) and

fibrates (i.e. fenofibrate, fenofibric acid, gemfibrozil and clofibrate). Their antimalarial

activities and possible therapeutic implementation are discussed in the following

section.

8.3.1 Desbutyl-lumefantrine and its Potential Implementation

With the recent change to AL as first-line treatment for uncomplicated malaria in PNG,

it seems relevant to investigate the antimalarial activity of related drugs (Chapter 5).

Despite speculation that DBL is not a metabolite of LM (Starzengruber et al. 2007;

Starzengruber et al. 2008) and consistent with other reports (Ntale et al. 2008; Hodel et

al. 2009), data from this study confirmed that DBL is indeed a metabolite, being present

in significant concentrations in the plasma of children after AL treatment. The superior

antimalarial activity of DBL (mean IC50 9 nM) to LM (mean IC50 55 nM) reported in

this thesis (Table 5.2) is consistent with previous reports using field isolates (Noedl et

al. 2001; Starzengruber et al. 2008). In addition to its potent activity against P.

falciparum, DBL also effectively inhibits P. vivax (Pirker-Krassnig et al. 2004). This


203

broad-spectrum activity makes DBL a useful candidate for implementation in the field,

as co-endemicity of these two major Plasmodium species is common in Asia, the

Middle East and Oceania (Mehlotra et al. 2000; Dhangadamajhi et al.; Douglas et al.

2011; Wong et al. 2011).

The difference in antimalarial activity between the parent and metabolite is also

consistent with the relationship between plasma LM, plasma DBL and treatment

outcome (Figure 5.3). AL treatment failure cases had significantly lower plasma DBL

concentrations than ACPR cases. Although plasma LM concentrations were also lower

in treatment failure, this did not reach statistical significance. This suggests that DBL

has a stronger role than the parent compound in suppressing recrudescence/and or

reinfection. The in vitro synergy between DBL and DHA (arguably the most potent

antimalarial drug discovered to date) highlights DBL-DHA as a promising novel ACT.

With antimalarial activities greater than their respective parent compounds and pending

detailed pharmacokinetic characterisation, the DBL-DHA formulation may be able to

be given in a simpler dosing regimen than the recommended 6-doses of AL. African

and PNG studies show that the greatest cure rates after AL are when dosing is directly

supervised with fat supplementation given to improve drug absorption (Mutabingwa et

al. 2005; Piola et al. 2005; Karunajeewa et al. 2008b; Schoepflin et al. 2010). Poor

compliance with the number of doses and coadministered fat may lead to sub-curative

drug concentrations and treatment failure, with the likely development of parasite drug

resistance (Wongsrichanalai et al. 2002; White et al. 2009).

The lipophilicity of DBL means that, as with LM (Ezzet et al. 1998), its bioavailability

is likely to be enhanced by concomitant food intake, particularly fat. The fat content of

PNG meals tends to be relatively low, as local diets are typically based on a

carbohydrate staple and vegetables (Iser et al. 1993). Important sources of dietary fat

include oil crops and cooking oil (e.g. peanuts, mature coconuts, palm oil). Given the

abundancy and availability of fresh tuna in coastal PNG where malaria is holoendemic,

consumption of this oily fish should be encouraged as a dietary supplement with AL

dosing to maximise absorption and decrease the chance of recrudescence. Breast-


204

feeding mothers can use breast milk as a fat source if their young children are being

treated with AL. The education of patients and healthcare providers as to the

importance of taking therapy according to the prescribed regimen should increase

understanding and compliance. These considerations would extend to potential ACTs

involving DBL.

8.3.2 Lipid-modifying Agents as Antimalarials

Drugs licensed for other indications can sometimes have antimalarial properties, an

example being lipid-modifying therapy which is becoming affordable even in malaria-

endemic developing countries. Modernisation and lifestyle changes have seen an

increasing need for these agents to reduce cardiovascular diseases, (McMurry et al.

1991; Hodge et al. 1996; Gill 2001). Two classes of commonly used lipid-modifying

drugs, namely fibrates and statins, were tested against P. falciparum (Chapter 6).

The present in vitro drug sensitivity data have confirmed atorvastatin to have the

highest activity of available statins against P. falciparum regardless of strain CQ

sensitivity (Pradines et al. 2007), but at an IC50 well above plasma concentrations after

therapeutic doses in vivo. Although its mechanism of action against P. falciparum

remains unclear, atorvastatin may act via P-glycoprotein (Holtzman et al. 2006), an

efflux protein implicated in 4-aminoquinoline resistance.

Fibrates have different lipid-modifying and possibly antimalarial mechanisms of action

to those of statins. Gemfibrozil and clofibrate proved to have weak antimalarial activity,

whilst fenofibrate in the form of fenofibric acid had a relatively low in vitro IC50,

similar to those of conventional antimalarial drugs (Table 6.3). As evident in the

bioassay (Figure 6.4), plasma fenofibric acid levels generated in vivo after therapeutic

doses of Lipidil™ inhibited cultured P. falciparum (Figure 6.4). Although therapeutic

plasma levels of fenofibric acid after both single and repeated doses are well above the

concentrations required to produce 90% growth inhibition in CQ-resistant P. falciparum

(10-fold and 3-fold, respectively), it should not be used as antimalarial monotherapy but

in partnership with a more rapidly-acting antimalarial agent. The elimination half-life of

fenofibric acid is 20 hr (Bhavesh et al. 2009) which means it is cleared more promptly


205

than most 4-aminoquinolines (Krishna et al. 1996; Tarning et al. 2005; Qu et al. 2010).

Depending on the completeness of the initial parasiticidal effect, this may be

advantageous as an ACT partner drug with a shorter elimination half-life reduces the

time of parasite exposure to subcurative levels thus limiting subsequent selection of

resistant strains (Wongsrichanalai et al. 2002).

Fenofibric acid has indifferent in vitro interactions with DHA (Table 6.4) when

assessed using two mathematical analyses (Berenbaum 1978; Brueckner et al. 1991).

Visual assessment of isobolographic plots suggests, however, that the equations utilised

by these methods may not accurately characterise drug interactions with the result that

clinically important interactions may be missed. This visual-mathematical discordance

is further discussed in Appendix D.

Although its mode of action remains to be elucidated, fenofibric acid may act by

interfering with P-glycoprotein (Ehrhardt et al. 2004) and ABC-1 mediated transport,

and/or via a putative PPARα-like protein. P-glycoprotein prevents intracellular drug

accumulation which results in a multidrug resistance phenotype in both Plasmodium

and mammalian cells. Evidence from in vitro drug-uptake assays and confocal laser

scanning microscopy have confirmed fenofibrate as an inhibitor of P-glycoprotein

activity with a similar potency to verapamil at 7.1 and 4.7 µM, respectively (Ehrhardt et

al. 2004). Therefore, fenofibrate may reverse CQ resistance and produce synergistic

effects when combined with CQ. However, the present drug-interactions studies

revealed indifferent interactions in both CQ-sensitive and resistant P. falciparum.

Despite the superior antimalarial activity exhibited by fenofibric acid, biochemical data

show that it is neither a substrate nor an inhibitor of human P-glycoprotein (Ehrhardt et

al. 2004). The lack of synergistic interaction or potentiation of CQ by fenofibric acid in

this study supports previous observations (Ehrhardt et al. 2004). Fenofibric acid affects

the expression of ABC-1 lipid transport protein in mammalian cells (Jaye et al. 2003;

Arakawa et al. 2005) and may similarly affect the Plasmodium ABC-1 homolog. This

could inhibit the development of P. falciparum by depriving the growing parasite of

lipid components of membranes and other cellular structures. The relative importance

of the effects of fenofibric acid on the Plasmodium homolog of P-glycoprotein, ABC-1


206

and a putative PPARα-like protein, together with possible interactions between these

effects, cannot be ascertained from the present data.

8.4 A PILOT STUDY OF MALARIA VOCS

The use of a non-invasive breath test for the detection of falciparum malaria would

provide a unique tool for diagnosis and therapeutic monitoring that could be

conveniently carried out at the bed-side. This thesis describes, for the first time, a study

of the potential of P. falciparum cultures to release signature VOCs. In addition to

possibly permitting detection of viable parasites, these in vitro data could provide

insights into the metabolism and pathogenicity of the organism. VOCs are used as

general anaesthetics in clinical practice (Soukup et al. 2009) and it is possible that coma

complicating malaria may result from elaboration of VOCs by malaria parasites in the

cerebral microcirculation that have anaesthetic properties.

Challenges encountered in this proof of concept study began with the determination of a

microenvironment that optimally supports a high parasite yield within a system that also

permits the capture, extraction and analysis of headspace VOCs (Chapter 7). Some

important considerations for the design of the culture-capture apparatus included i) the

width and height of the culture flask, ii) the provision of sealable-access openings and

fittings adapted for VOCs extraction, iii) the parasite stage used and duration of

incubation, iv) the culture gas mixture and purging time, and v) initial parasitaemia and

haematocrit. Once optimised, VOCs were collected and concentrated by SPME, solvent

extraction and thermal desorption. Various steps were also taken to enhance the

liberation of VOCs from the liquid matrix and to attain gas-fibre equilibrium. Despite

substantial efforts to define the optimal conditions for the in vitro capture of P.

falciparum VOCs, GC-MS data revealed the production of a variety of volatile

compounds but no unique malarial finger-prints (Chapter 7).

A major limitation is the P. falciparum biomass achievable within the in vitro system.

Unlike bacterial or fungal colonies that are directly grown on solid medium with direct

exposure to the culture headspace, malaria parasites have little access to the headspace,

being enveloped within phosphobilayered-host cells within a liquid medium. The use of


207

a shaking incubator and the assessment of supernatant and cell lysate for VOCs

revealed minimal difference compared to control. Even with the attainment of a 20%

parasitaemia, the difference in VOCs is dependent on a minority of infected cells versus

the non-infected control cells. A recent publication described means to obtain a

synchronous culture of P. falciparum at 60% parasitaemia (Radfar et al. 2009).

However, the methodological requirements for achieving such high parasite yields are

not compatible with VOCs capture. This includes the need for medium changes at 12 hr

intervals, which would result in the escape of any VOCs produced. The use of large-

base culture containers and a low haematocrit are common key considerations noted in

this and other studies (Radfar et al. 2009).

Progress with culture techniques of other protozoans may yet promote novel approaches

to P. falciparum cultivation (Hijjawi et al. 2004; Hijjawi et al. 2010). Recent studies

have reported on the successful propagation of Cryptosporidium hominis, an intra-

cellular Apicomplexan that shares similar life-cycle stages with P. falciparum, in host

cell-free culture (Hijjawi et al. 2010). Such advancements, if possible for Plasmodium,

would bring a new dimension to malaria research.

8.5 CONCLUSION AND FUTURE DIRECTIONS

Despite past efforts to control malaria, resistance of P. falciparum to antimalarial drugs

continues to be a threat to the global community, especially in tropical developing

countries such as PNG. The response has been to change from monotherapy to

combination therapy and, more recently, to the wide deployment of ACTs to ensure

efficacy and retard the spread of parasite resistance (PNGDOH 2000; WHO 2007).

However, P. falciparum drug resistance reflects a complex interplay of parasite and

host factors (Wongsrichanalai et al. 2002; Mackinnon et al. 2010). The development of

novel antimalarials has been slow, despite a surge in research funding in recent years

(McCoy et al. 2009; Kazatchkine 2010; Muller et al. 2010). There remains an urgent

need for novel, effective and affordable antimalarial agents that can be used with

artemisinin derivatives to counter the rapid development of parasite resistance to

conventional drugs.


208

This thesis has contributed to the understanding of the in vitro and genetic aspects

underlying treatment outcome in PNG children. This was achieved via the culture and

testing of parasite sensitivity to antimalarial agents, molecular detection of parasite

mutations and their associations with treatment outcomes. The antimalarial efficacy

findings presented here may become useful for inclusion in the World Antimalarial

Resistance Network (WARN), a global database showcasing collaborative efforts in the

malaria research community to monitor and counter the development of resistance

(Plowe et al. 2007; Sibley et al. 2008; Sibley et al. 2010). Both molecular and in vitro

drug susceptibility profile from this study provided useful baseline data for monitoring

and evaluation of treatment regimens in coastal PNG and supports the need for adoption

of AL as first-line treatment for uncomplicated falciparum malaria.

8.5.1 Directions for Future Research

i. The present studies provide a platform for the continuation of parasite resistance

surveillance through the routine assessment of in vitro drug sensitivity and

molecular markers. The pLDH and LDR-FMA methods established from this

work enable the high-throughput monitoring of changes in parasite drug

sensitivity (particularly in pfmdr1 polymorphisms) under a new wave of ACT

selection. Ongoing assessment using the same techniques will facilitate

assessment of the adequacy of such treatment.

ii. The high in vitro antimalarial activity of fenofibric acid at media concentrations

which can be achieved in vivo may have therapeutic application. Confirmatory

preclinical studies in an animal model (perhaps the well recognised Plasmodium

berghei murine model) would be useful as the next step in assessing the in vivo

efficacy of fenofibric acid.

iii. The present studies have highlighted a number of technical challenges with in

vitro identification of VOCs from the headspace of P. falciparum cultures.

Future in vivo studies analysing the breath of patients with severe malaria may

yet reveal specific, clinically useful volatile biomarkers.

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APPENDICES

Appendix A: Isolate Information

261

APPENDIX A. ISOLATE INFORMATION

P. falciparum Isolate

Source Drug Sensitivity Comments

3D7 Netherlands CQ-sensitive Derived from NF54 isolated in Amsterdam; presumed of African origin, not confirmed

7G8 Brazil CQ-resistant Pyrimethamine-resistant

Derived from IMTM22 (Brazil)

Dd2 Indochina CQ-resistant Pyrimethamine-resistant

MQ-resistant

Derived from W2mef

E8B Australia CQ-resistant MQ-sensitive

Derived from ItG2F6 (Brazil)

HB3 Honduras CQ-sensitive Derived from I/CDC (Honduras)

K1 Thailand CQ-resistant Pyrimethamine-resistant

Kanchanaburi

PNG1905 Australia CQ-resistant Origin not confirmed

PNG1917 Australia CQ-resistant Papua New Guinea isolate

W2mef Indochina CQ-resistant Selected from W2 for resistance to mefloquine

Appendix B: Recipes and Solutions

263

APPENDIX B. RECIPES FOR SOLUTIONS

Culture of P. falciparum

5% Albumax II

� Albumax II (11021-045) (Gibco) 5.5 g

� Milli-Q water 110 mL

Filter sterilise using 0.2 µM membrane (Nalgene Filterware, USA).

Store at -20°C in 10 mL aliquots.

Complete Maintenance Medium (PNG)

� RPMI Medium 1640 powder (31800-089) (Gibco, Auckland, NZ) 5.735 g

� HEPES (Sigma-Aldrich) 4.47 g

� Hypoxanthine (Sigma) 22.5 mg

� 5% Albumax II (see section below) 50 mL

� 5% NaHCO3 (see section below) 21 mL

� Gentamycin sulfate (10mg/mL) (Calbiochem, Darmstadt, Germany) 5 mL

� Neomycin sulfate (10mg/mL) (Calbiochem, Darmstadt, Germany) 5 mL

� Milli-Q-water 500 mL (final)

Adjust to pH 7.3.


Store at 4°C and use within 2 weeks, or supplement with L-glutamine after 2 weeks.


264

Complete Maintenance Medium

� RPMI Medium 1640 (R5886) (Gibco, liquid) 90 mL

� Human plasma (see section below) 10 mL

� L-glutamine solution (see section below) 1 mL

� Hypoxanthine solution (see section below) 1 mL

� Gentamycin (see section below) 100 µL

Store at 4°C and use within 2 weeks, or supplement with L-glutamine after 2 weeks.

Cryoprotective Solution

� Sorbitol (BDH, England) 37.8 g

� NaCl (BDH, Australia) 8.1 g

� Glycerol (BDH, Australia) 350 mL



Store at 4°C.

Gentamycin Stock (50 mg/mL) (PNG)

� Gentamycin sulfate (Calbiochem) 1 g

� Milli-Q-water 20 mL

Protect from light, store at -20°C in 5 mL aliquots

Gentamycin Stock (40 mg/mL)

80 mg/2 mL (Delta West, Pharmacy IV injections).

Store at 4°C.


265

5% Giemsa Stain

� Giemsa stain (BDH, Australia) 0.5 mL

� PBS (pH 7.2) 9 mL

Stain is prepared fresh before use.

Human Plasma Inactivation

O+, A+, AB+ Plasma units (Fremantle Hospital, Transfusion Medicine) were pooled, defibrined and heat inactivated at 56°C in a waterbath as follows:

1. Plasma was added to sterile 500 mL conical flasks containing 1 - 2 cm of autoclaved (2 mm) glass beads, covered and shaken in a waterbath for 2 - 3 hr at 37°C.

2. Pool plasma and heat-inactivate at 56°C in waterbath for 40 min.

3. Use 10 mL of new plasma to make up test CM (100 mL) and test for support of 3D7 strain of P. falciparum cultures for 2 weeks prior use.

4. Store at -20°C.

Human Tonicity Phosphate Buffered Saline (HTPBS)

� NaCl (BDH, Australia) 7 g

� Na2HPO4 (BDH, Australia) 2.85 g

� NaH2PO4 (BDH, Australia) 0.625 g


Adjust to pH 7.3.


Store at 4°C.


266

Hypoxanthine Solution (5 mg/mL)

� Hypoxanthine (Sigma, USA) 0.5 g


Heat in microwave until dissolved.


Store at 4°C.

L-Glutamine Solution (200mM)

� L-glutamine (Sigma) 2.92 g




5% NaHCO3

� NaHCO3 (Sigma-Aldrich, St Louis, Mo, USA) 2.5 g




PBS (6.7mM) for Giemsa Staining

� K2PO4 (BDH, Australia) 0.41 g

� Na2HPO4 (BDH, Australia) 0.65 g


Adjust to pH 7.1.

Filter sterilise using 0.2 µM membrane (Nalgene Filterware, USA) (optional).


267

12% Sodium Chloride (NaCl) Solution


� HTPBS (see section above) 100 mL


Store at 4°C.

1.6% Sodium Chloride (NaCl) Solution




Store at 4°C.

0.9% Sodium Chloride (NaCl) Solution


� Glucose (Sigma) 0.2 g



Store at 4°C.

5% Sorbitol for Synchronisation

� Sorbitol (BDH, England) 5 g



Store at 4°C.


268

LDH Assay

Malstat Solution

� Trizma base (Sigma, Australia) 2.42 g


� Adjust with HCl to pH 9.1

� Triton X-100 (Sigma, Australia) 0.4 mL

� Lithium-L-lactate (Sigma, Australia) 4 g

� APAD (Sigma, Australia) 132 mg

Protect from light and store at 4°C.

Use within one week.

Diaphorase Solution

� Diaphorase (Sigma-Aldrich, USA) 15 mg



Nitro Blue Tetrazolium (NBT) Solution

� NBT chloride monohydrate (Sigma-Aldrich, USA) 15 mg




269

Molecular Assays

2% Agarose Gel

� Agarose I ™ (Amresco, USA) 3 g

� 1 X TBE buffer 150 mL

Melt agarose in buffer before pouring into a large 96-well electrophoresis tray and allow 20 min for gel to set.

2.5mM dNTPs Working Solution

� 100 mM dGTP (Denville Scientific Inc, USA) 25 µL

� 100 mM dATP (Denville Scientific Inc, USA) 25 µL

� 100 mM dCTP (Denville Scientific Inc, USA) 25 µL

� 100 mM dTTP (Denville Scientific Inc, USA) 25 µL

� Nuclease free water 900 µL

1.5 X TMAC Hybrisation Buffer

� 5 M Tetramethyl ammonium chloride (TMAC) (Sigma, USA) 30 mL

� 1 M Tris pH 8.0 (Amresco, USA) 2.5 mL

� 0.5 M EDTA (Amresco, USA) 300 µL

� 20% Sodium dodecyl sulfate (Amresco, USA) 250 µL

� Sterile distilled water 16.95 mL


270

10 x Tris borate (TBE) Buffer

� Tris base 108 g

� Boric acid 55 g

� 0.5M EDTA 40 mL


10 x PCR Buffer

� 1 M Tris pH 8.8 33.5 mL

� 1 M MgSO4 3.4 mL

� 1 M (NH4)2SO4 8.4 mL

� β-mercaptoethanol (14.3 M) 0.35 mL

� Nuclease-free water 4.4 mL

LDR Master Mix – Plasmodium Species

� Nuclease-free water 11.4 µL

� NEBuffer for Taq DNA (10X) (Biolabs, New England) 1.5 µL

� LDR primers for species assay (x 7) (Table 2.3) 0.15 µL/primer

� Taq DNA ligase (Biolabs, New England) 0.05 µL

� PCR product 1 µL


271

LDR Master Mix – Drug Resistance SNPs of pfcrt, pfdhfr, pfdhps genes


� NEBuffer for Taq DNA (10X) (Biolabs, New England) 1.5 µL

� LDR primers for pfcrt, pfdhfr, pfdhps (x 18) (Table 2.4) 0.20 µL/primer

� Taq DNA ligase (Biolabs,New England) 0.10µL

� PCR product 1 µL

PCR Master Mix – Plasmodium Species, pfcrt, pfdhfr, pfdhps


� 10 x PCR buffer 2.5 µL

� 2.5 mM dNTPs 2.0 µL

� Primers –upstream (Section 2.3.2) 0.3 µL/primer

� Primers – downstream (Section 2.3.2) 0.3 µL/primer

� MacTaq (DNA Taq polymerase, M&C Gene Technology, Beijing) 0.3 µL

Keep MacTaq on ice at all times.

SYBR Gold

� Cybergold (Molecular Probes, Eugene, OR) 15 µL

� 1 X TBE Buffer (see section above) 150 mL

Appendix C: LDR Optimisation

272

APPENDIX C. EFFECTS OF LDR ANNEALING TEMPERATURE AND DILUTION


273


274


275


276

Appendix D: Isobologram Analyasis

277

APPENDIX D. ISOBOLOGRAM ANALYSIS

The regression function used by Brueckner et al. is given below:

For determining the relative interaction value, I, this function is suitable when the FIC

values lie in the range [0, 1]. However, when values lie outside this range the fit is quite

poor. This is evident even from a simple visual comparison between the data points and

the regression curve of Figure (left) (denoted by blue circles and red line respectively).

Consequently, only marginal confidence may be attributed to the recovered I value of -

0.305. One straightforward way to improve the regression fit is by first normalising the

FIC values into the range [0, 1]. However, consideration must be given to the nature of

this scaling since it may introduce a bias into the recovered I value.

There are two approaches to applying the normalisation: either scale the data

independently along each axis direction (centre figure), or apply a single scale factor

globally (right figure). The former is done by finding the maximum FIC in each

direction and scaling the corresponding values by that maximum. The latter method

uses the global maximum over all the FICs regardless of axis and scaling all the values

by this factor. In both cases, the resultant values will lie in the unit square hence

suitable for regression using the Brueckner et al. fitting function.

Results of these normalisation methods and their subsequent regression curves are

shown in Figure-centre and right respectively. The original values are denoted as green

points and scaled values as blue circles. Notice that the resultant I values differ slightly

also, but this difference is much less than the difference with the I value found in Figure

(Left).

Appendix D: Isobologram Analyasis

278

Regarding which two approaches is more appropriate, the non-linear regression

function proposed by Brueckner et al should be considered. First of all, its curve has a

line of symmetry along X = Y. Therefore, if values are scaled by different factors in

different directions, then this might destroy any inherent symmetry in the data and

hence reduce the regression fit. This suggests that the second method of scaling all the

FICs by a single global factor is more appropriate. However, a second feature of

Brueckner’s fitting function is that it assumes isobologram start and end points at (0, 1)

and (1, 0) respectively. This is problematic for a global normalisation approach since it

might result in curves terminating before they reach these assumed end points.

In the examples shown in Figures (centre) and (right), the difference in the fitted curves

is negligible as indicated by the proximity of their respective I values. Furthermore, the

regression line still does not appear to capture the data-points lying in the centre of the

plot, away from each of the axes. This is explained by the clustering of data points at

the assumed endpoints of (1,0) and (0,1), that is, eight of the eleven data points lie near

the horizontal and vertical axes with only three in the centre of the plot. Since the least-

squares fitting method used in the Brueckner et al. regression gives equal weight to

every data-point then so long as the fitted curve terminates near (1,0) and (0,1) then the

fit is considered optimal. This suggests that to use Brueckner et al. fitting, it is

important to have sanitised data near the end points which is best offered by scaling the

data independent along each axis.

Appendix D: Isobologram Analysis

279

Figures (left): Isobologram using the raw FIC data Raw FICs, I = -0.305, (Centre) Isobologram using FICs which have been normalised along each

axis independently Scaled FICs (anisotropic), I = -1.088, (Right) Isobologram using FIC data normalised globally, Normalised FICs (isotropic), I = -

0.978.

280

APPENDIX E. VOCS ANAYLSIS

Compounds Common to both P. falciparum Culture and Non-parasitised Control SPME (Triple Fibre)

2,4-Dimethyl-1-heptene p-Trimethylsilyloxyphenyl-(trimethylsilyloxy)trimethylsilyacrylate*

Cyclotetrasiloxane, octamethyl-* Dodecane, 2,6,11-trimethyl-

Heptane, 2,2,4,6,6-pentamethyl- 1-Dodecanol, 3,7,11-trimethyl-

Nonane, 4-methyl- 3-Carene

Octane, 3,3-dimethyl- Furan, 2-pentyl-

Decane Cyclohexanone

Undecane, 3,6-dimethyl- Cyclohexanol

Decane, 3,7-dimethyl- Benzene, 1,3-bis(1,1-dimethylethyl)-

Dodecane 1-Octen-3-ol

1-Octene, 3,7-dimethyl- 1-Hexanol, 2-ethyl-

Decane, 5,6-dipropyl

Notes: Compounds have been identified by comparison of mass spectra with the NIST 2005 mass spectral database. Compounds in italic have been

tentatively identified (<90% match) and may indicate the structural class rather than the actual compound. *Siloxanes possibly derived from coating of

the SPME fibre or the GC column stationary phase (Middleton 1989).

281

Compounds Common to both P. falciparum Culture and Non-parasitised Control SPME (PDMS) Thermal Desorption (Purge and Trap) -

Dodecane Cyclohexanone

Benzene, (1-methylethenyl)- Benzene, 1-ethyl-3-methyl-

Cyclopentasiloxane, decamethyl-* Benzene, 1,2,3-trimethyl-

1-Heptanol, 2,4-diethyl- Decane

Benzene, 1,3-bis(1,1-dimethylethyl)- 1-Hexanol, 2-ethyl-

1-Hexanol, 2-ethyl- Silane, 9H-fluoren-9-yltrimethyl-*

Cyclohexasiloxane, dodecamethyl-* Cyclohexane, 1,2,3-trimethyl- (1.alpha., 2.alpha., 3.beta.)

Benzaldehyde, 2,5-bis[(trimethylsilyl)oxy]- 1-Hexene, 2,5,5-trimethyl-

Silanediol, dimethyl-* 2-Undecene, 6-methyl- (Z)-

Oxime-methoxy-phenyl- Cyclohexane, 1,2-dimethyl- cis-

1-Dodecanol Benzene, 1,3-bis(1,1-dimethylethyl)-

Diethyl Phthalate** Malonic acid, bis(2-trimethylsilylethyl ester)-



the SPME fibre or the GC column stationary phase. **Known contaminants (Middleton 1989).

282

Compounds Common to both P. falciparum Culture and Non-parasitised Control Supernatant Extraction by SPME immersion Supernatant Extraction by Methanol and Sep-Pak

5-O-Methyl-d-gluconic acid dimethylamide Methane, (methylsulfinyl)(methylthio)-

Styrene Dodecane

Cyclohexanone N-Benzyl-2-aminocinnamate, methyl ester

Nonanal Hexadecanoic acid, methyl ester

Benzene, 1,3-bis(1,1-dimethylethyl)- 5-Thiazoleethanol, 4-methyl-

Acetic acid Silane, (2-methoxyethyl)trimethyl-*

1-Hexanol, 2-ethyl- 9-Octadecenoic acid (Z)-, methyl ester

Silanediol, dimethyl-* Octadecanoic acid, butyl ester

Oxime-methoxy-phenyl- n-Hexadecanoic acid

Propanoic acid, 2-methyl-2,2-dimethyl-1-(2-hydroxy-1-methylethyl) propyl ester Androst-2-en-17-one, (5.alpha.)-

Benzoic acid, 2,5-bis(trimethylsiloxy)-, trimethylsilyl ester Benzenesulfonamide, N-butyl-

1-Dodecanol 1H-Purine-2,6-dione, 3,7-dihydro-1,3,7-trimethyl-

Nonanoic acid Prasterone-3-sulfate

4H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl- 1,2-Benzenedicarboxylic acid, diisooctyl ester**

Octasiloxane, 1,1,3,3,5,5,7,7,9,9,11,11,13,13,15,15-hexadecamethyl-* Disiloxane, 1,1,3,3-tetramethyl-1,3-dioctadecyl-

Diethyl Phthalate** Cholest-5-en-3-ol (3.beta)-




283

Compounds Common to both P. falciparum Culture and Non-parasitised Control Dichloromethane (Supernatant) Petrol (Supernatant ) Petrol (Cell Lysate)

Cyclohexanol 4-Heptanol Cholesterol

Hexadecane 3-Heptanol 4-Heptanol

Oxalic acid, butyl 2-ethylhexyl ester 2-Heptanol 3-Heptanol

Octadecane 3,6-Heptanedione 2-Heptanol

Heneicosane Di-sec-butyl ether Nonanal

1-Dodecanol Tetrahydro-1,3-oxazine-2-thione 3,6-Heptanedione

Benzoic acid, 4-ethoxy-, ethyl ester Carbamodithioic acid, diethyl- methyl ester 1-Butoxy-2-ethylhexane

Nonanoic acid Disulfiram Octadecane

1-Tetradecanol 1-Hexadecanol 2,5-Dihydroxyheptane

1-Hexadecanol Behenyl chloride

Tridecanal 7-Oxabicyclo[4.1.0]heptane, 1-methyl-4-(2-methyloxiranyl)-

Pentadecanoic acid, methyl ester

1-Octadecanol Heneicosane

Diethyl Phthalate**

1-Hexadecanol

Tricosane




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