pcr amplification of bacterial dna for the rapid diagnosis of infections

BROAD-RANGE PCR AMPLIFICATION OF BACTERIAL DNA IN VARIOUS

CLINICAL SAMPLES FOR THE RAPID DIAGNOSIS OF INFECTIONS

WOON SU LI ANGELINE

DISSERTATION SUBMITTED

IN FULFILMENT OF THE REQUIREMENTS FOR

THE DEGREE

OF

MASTER IN MEDICAL SCIENCE

DEPARTMENT OF MEDICAL MICROBIOLOGY

FACULTY OF MEDICINE

UNIVERSITY OF MALAYA

KUALA LUMPUR

2005/2006

ii

Abstract

The objective of this study was to develop and optimise a broad-range PCR protocol

to detect and allow Gram-typing on bacterial 16S rDNA, and to provide bacterial

identification by sequence analyses without the need for culture in a routine clinical

diagnostic laboratory setting. The alkali-heat wash, boiling, phenol chloroform isoamyl-

alcohol extraction and DNAzol extraction methods were performed on cerebrospinal fluid,

synovial fluid, peritoneal fluid and blood culture bottle sample types. Boiling was found to

be most effective for cerebrospinal fluid, alkali-heat wash for blood culture bottle and

peritoneal fluid, and DNAzol for synovial fluid. The optimised duplex PCR for Pan and

Gram-positive specific PCR detected 10 pg of Staphylococcus aureus DNA while the

Gram-negative specific PCR detected 10 pg of Escherichia coli DNA. Both protocols were

able to Gram-type the 12 pure culture samples tested. The 16S rDNA sequence analyses

provided higher order identification for all 12 samples. The optimised PCR assays were

tested on 233 clinical samples and the molecular results compared with culture. Sensitivity

was found to be at 67.74%, specificity at 95.54%, positive predictive value at 70% and

negative predictive value at 95.1%. Furthermore, 91.8% of the results from the 16S rDNA

PCR assays and culture were in agreement. In conclusion, the broad-range PCR protocols

developed can be applied for use in a routine clinical diagnostic laboratory, and together

with sequencing analysis can enable bacterial identification. However, further work should

be carried out to increase the sensitivity and specificity of the molecular protocols.

iii

Acknowledgements

I would like to extend my appreciation to:

� My supervisors, Professor Dr. Ngeow Yun Fong and Associate Professor Dr. Mary

Anne Tan Jin Ai of the Faculty of Medicine, University of Malaya, for their

recommendations and expert advice.

� Professor Dr. Yap Sook Fan, for allowing me the run of her laboratory facilities.

� Dr Tay Sun Tee and Dr Chia of the Department of Medical Microbiology, UM; and

the staff of the Microbiology Diagnostic Laboratory, UMMC, for providing some of

the materials used in this study.

� The staff at the Department of Medical Microbiology, particularly Mr. Wong, Mr.

Wee and Mr. Cheng for their assistance in sorting out the gremlins in paperwork and

laboratory equipment.

� The Unit Penyelidikan DiTaja for funding this project through the Skim Pasca

Siswazah and Peruntukan Penyelidikan Jangka Pendek (Vot F).

� Fellow students, past and present, at the Molecular Diagnostic Research Laboratory

(MDRL), for their support, ideas, troubleshooting abilities and more importantly,

friendship. Special mention goes to Dr Tetty Aman Nasution, Leila Hilout, Caroline

Wee, Elton Sagim, and Alex Lim.

� Amy, Sook Meng and John, for their encouragement and help in smoothing out the

details. GANBARE!

I dedicate this to my family and Benoit, for keeping me happy and healthy through the late

nights, starvation and general frustrations as I tried to churn out something resembling a

dissertation.

Thank you

>***+(

Woon Su Li Angeline

April 2006

iv

Table of Contents

PAGE

Title Page i

Abstract ii

Acknowledgements iii

Table of Contents iv

List of Figures xiii

List of Tables xviii

List of Symbols and Abbreviations xx

1.0 Introduction 1

1.1 The Diagnosis of Infections 2

1.1.1 The Status Quo 2

1.1.2 Rapid Diagnosis: The Benefits 3

1.1.3 The Hurdle: Drawbacks of Culture Method 4

1.1.4 A Solution: Benefits of Molecular Methods 5

1.2 Broad-range 16S rDNA Amplification and Sequencing 6

1.2.1 Polymerase Chain Reaction 6

1.2.2 Analysis of Amplification Products 9

1.2.3 Analysis of Sequencing Results 9

1.2.4 The 16S ribosomal RNA Gene (16S rDNA) 11

1.2.5 A Broad Outline of the Method 13

v

1.3 Literature Review of 16S rDNA Amplification and Sequencing 14

1.3.1 Used in the Identification of Unknown Etiologic Agents 14

1.3.2 Important Highlights Regarding the 16S rDNA

Broad-range PCR

15

1.3.3 16S rDNA PCR as a Routine Clinical Diagnostic Service 17

1.3.4 16S rDNA PCR in Specific Clinical Conditions 18

1.4 Outline of the Method used in this Study 20

1.5 Objective of the Study 22

2.0 Methodology 23

2.1 Samples 23

2.1.1 Bacterial Stock Culture 23

2.1.2 DNA Samples 23

2.1.3 Culture-Negative Clinical Specimen 24

2.1.4 Clinical Specimens for 16S rDNA Screening 25

2.2 General Methods 25

2.2.1 Preparation of Media and Buffers 25

2.2.2 Sterilisation 25

2.2.3 Workflow and Special Considerations 26

2.3 Extraction Methodology 26

2.3.1 Cell Counting 26

vi

2.3.2 Alkali Heat-Wash Extraction Method 27

2.3.3 Boiling Extraction Method 28

2.3.4 Lysis Buffer and Phenol Chloroform Isoamyl-Alcohol

Extraction Method

28

2.3.5 DNAzol Extraction Method 29

2.3.6 DNA Quantification of Extracted Samples 30

2.4 PCR Primers 30

2.4.1 Designing Primers 30

2.4.2 Manufacturing Primer Oligonucleotides 31

2.4.3 Primer Profile 31

2.5 PCR, Sequencing and Analysis 34

2.5.1 Preparation of PCR Mixtures 34

2.5.2 Gel Electrophoresis of Amplified PCR Products 35

2.5.3 Min Elute PCR Purification Kit Protocol and Sequencing 36

2.5.4 Analysing Sequencing Results 37

2.5.5 Statistical Analyses 37

2.6 Determination of PCR Sensitivity 38

2.7 Determination of PCR Specificity 39

2.8 Screening of Clinical Specimens 40

vii

3.0 Results 43

PHASE I: Optimisation of Protocols

3.1 DNA Extraction 43

3.1.1 Complexity Ranking 44

3.1.2 DNA Amplification Results of Extracted Samples 45

3.1.3 Choosing the Best Extraction Methods 54

3.1.4 Lowest Detection Limit (CFU/ml) of the Extraction Methods 55

3.2 PCR Optimisation 58

3.2.1 Optimisation of Annealing Temperature 58

3.2.2 Optimisation for the Number of PCR Cycles 61

3.2.3 Optimisation of MgCl2 and Taq Polymerase Concentrations 65

3.2.4 Optimisation of Primer Concentration 74

3.2.5 Multiplex Optimisation 82

3.3 Optimisation of PCR Mixtures and Thermal Profiles 83

3.3.1 Gram-positive Specific PCR 83

3.3.2 Pan-bacterial Specific PCR 84

3.3.3 Pan and Gram-positive Specific Duplex PCR 85

3.3.4 Gram-negative Specific PCR 86

3.4 PCR Sensitivity 87

3.5 PCR Specificity 93

viii

3.6 Sequencing and Analyses of Pure Cultures 99

3.6.1 Staphylococcus aureus 99

3.6.2 Enterococcus faecalis 99

3.6.3 Corynebacterium sp. 100

3.6.4 Neisseria gonorrhoeae 100

3.6.5 Haemophilus influenzae 101

3.6.6 Acinetobacter baumanii 101

3.6.7 Klebsiella pneumoniae 101

3.6.8 Enterobacter sp. 102

3.6.9 Escherichia coli 102

3.6.10 Proteus sp. 103

3.6.11 Stenotrophomonas maltophilia 103

3.6.12 Summary of Section 3.6 103

PHASE II: Screening of Clinical Samples

3.7 Collection of Samples 107

3.8 PCR of Clinical Samples 108

3.9 Sequencing of Clinical Samples 110

3.9.1 Clinical Samples that Produced Positive Results by

Culture and 16S rDNA PCR (Refer Table 3.10)

110

3.9.1a Sample C065

(Identified as Enterobacter sp. by Culture)

110

ix

3.9.1b Sample C089, B082, P045 and P063

(Identified as Klebsiella pneumoniae by Culture)

111

3.9.1c Samples P002, P056 and P055

(Identified as Escherichia coli by Culture)

111

3.9.1d Samples P004 and P029

(Identified as Enterococcus sp. by Culture)

112

3.9.1e Samples P007, B078 and B079

(Identified as Acinetobacter baumanii by Culture)

113

3.9.1f Samples C003

(Identified as Streptococcus sp. by Culture)

113

3.9.1g Sample P051

(Identified as Group G Streptococci by Culture)

113

3.9.1h Sample P017

(Identified as Staphylococcus aureus by Culture)

114

3.9.1i Sample P014

(Identified as Pseudomonas aeruginosa by Culture)

114

3.9.1j Sample B080

(Identified as Salmonella enteritidis by Culture)

114

3.9.1k Samples B073 and B074

(Identified as Coagulase-negative Staphylococci

by Culture)

115

3.9.1l Sample B076

(Identified as Gram-negative Rod by Culture)

115

3.9.1m Summary of Section 3.9.1 115

x

3.9.2 Clinical Samples Found Positive by 16S rDNA PCR

but Negative by Culture (Refer Table 3.11)

122

3.9.2a Cerebrospinal Fluid Samples

(C016, C027, C033, C051 and C067)

122

3.9.2b Peritoneal Fluid Sample (P020) 123

3.9.2c Synovial Fluid Samples (S010, S017 and S033) 123

3.9.3 Clinical Samples Found Negative by 16S rDNA PCR

but Positive by Culture

128

3.10 Comparison of the 16S rDNA PCR with Culture 129

3.10.1 Overall Results 129

3.10.2 Breakdown of Results into Sample Types 130

3.10.3 Performance of the 16S rDNA PCR Assay Compared

to Culture

132

4.0 Discussion 134

4.1 Contamination Issues in Broad-range PCR 134

4.2 Extraction Methods 135

4.2.1 Complexity Ranking 135

4.2.2 DNA Amplification of Extracted Samples 136

4.2.3 Boiling Method on CSF Specimen 137

4.2.4 AH Method on BCB and PF Specimen 138

4.2.5 DNAzol and SF Specimen 138

4.2.6 Other Methods 139

xi

4.3 PCR Optimisation 139

4.4 PCR Sensitivity 142

4.5 PCR Specificity 143

4.6 Sequencing 144

4.6.1 Fragment Size 144

4.6.2 Sequencing Results Analyses and Cut-off Points 145

4.6.3 Sequencing Analyses for Pure Culture Samples 146

4.6.4 The Limitations of the 16S rDNA PCR and DNA Sequence

Analyses for the Identification of Bacterial Isolates

150

4.7 PCR on Clinical Samples 151

4.8 Sequencing on Clinical Samples 152

4.8.1 Clinical Samples that Gave Positive Results by Culture and

16S rDNA PCR

152

4.8.2 Clinical Samples Found Positive by 16S rDNA PCR but

Negative by Culture

155

4.8.3 Clinical Specimen Found Negative by 16S rDNA PCR but

Positive by Culture

158

4.9 Comparison of the 16S rDNA Assay with Culture 159

4.10 Limitations of the 16S rDNA PCR and DNA Sequencing Assay

for Use on Clinical Specimens

162

xii

4.11 Significance of Findings 164

4.12 Conclusion 166

Appendices

Appendix A- Lists of Chemicals, Media, Kits and Equipment

Appendix B- Preparation of Media, Stocks and Buffers

Appendix C- Primer Location on the 16S rDNA

Appendix D- Examples of Electropherograms from the DNA

Sequencing of Pure Culture Samples

Appendix E- Table AppE

Appendix F- Examples of Electropherograms from the DNA

Sequencing of PCR-positive Clinical Samples

Appendix G- Calculation of the Number of Escherichia coli

cells detected by DNA amplification in this

study.

References

xiii

List of Figures

PAGE

Figure 1.1 Cycles involved in the Polymerase Chain Reaction (PCR). 7

Figure 1.2 Secondary structure of a 16S rRNA molecule based on the

Escherichia coli structure of Maidak et al.(1994)

12

Figure 1.3 The outline of the 16S rDNA PCR and sequencing method

used in this study.

21

Figure 2.1 A diagram showing the primer annealing positions and

fragment sizes of the PCR products in this study.

33

Figure 2.2 Procedure for the determination of PCR sensitivity in this

study.

38

Figure 2.3 Procedure for the determination of PCR specificity in this

study.

39

Figure 2.4 Procedures used in the screening of the clinical specimens in

this study.

40

Figure 2.5 Diagrams of possible PCR results on agarose gel during

hypothetical clinical screening of specimens.

42

Figure 3.1 Gel electrophoresis of PCR products amplified from DNA

extracted using the alkali heat-wash and boiling methods.

47

xiv


extracted using the phenol chloroform isoamyl-alcohol and

DNAzol methods.

49


extracted by the phenol chloroform isoamyl-alcohol and

DNAzol methods.

53

Figure 3.4 Gel electrophoresis of PCR products using the duplex Pan (nf

and NR) and Gram-positive specific primer (f3p and NR) sets

to determine the lowest detection limit (Colony Forming

Unit/ml) for the alkali heat-wash method on peritoneal fluid.

57

Figure 3.5 Optimisation of the Gram-positive specific PCR using different

annealing temperatures.

60

Figure 3.6 Optimisation of DNA amplification for Gram-positive and

Gram-negative specific primers using 26 cycles of PCR.

62

Figure 3.7 Optimisation of DNA amplification for Gram-positive and

Gram-negative specific primers using 27 and 28 cycles of

PCR.

64

Figure 3.8 Optimisation of DNA amplification for Pan, Gram-positive

and Gram-negative specific primers using 0.6 units of Taq

polymerase and various concentrations of MgCl2.

67

xv

Figure 3.9 Optimisation of DNA amplification for Pan, Gram-positive



69

Figure

3.10

Optimisation of DNA amplification for Pan, Gram-positive



71

Figure

3.11

Optimisation of DNA amplification for Pan and Gram-positive

specific primers using different nf and NR primer

concentrations.

76

Figure

3.12


specific primers using different nf and NR primer

concentrations.

78

Figure

3.13


specific primers using different f3p primer concentrations.

81

Figure

3.14

Gel electrophoresis of DNA products amplified using the Pan

specific primers with different DNA concentrations.

88

Figure

3.15


and Gram-positive specific primers in a duplex PCR with

different Escherichia coli DNA concentrations.

89

xvi

Figure

3.16


and Gram-positive specific primers in a duplex PCR with

different Staphylococcus aureus DNA concentrations.

91

Figure

3.17

Gel electrophoresis of DNA products amplified using the

Gram-negative specific primers in a duplex PCR with different

Escherichia coli DNA concentrations.

92

Figure

3.18


and Gram-positive specific primers with template DNA from

various Gram-positive and Gram-negative organisms.

96

Figure

3.19

Gel electrophoresis of DNA products amplified using the

Gram-negative specific primers with template DNA from

various Gram-positive and Gram-negative organisms.

97

Figure

AppC

The location of the primers used in this study on a higher-order

structure model for Escherichia coli 16S rRNA that was

obtained from Gutell et al. (1994)

Appendix

C

Figure

AppD-1

Electropherogram from the DNA sequencing of 16S rDNA

obtained from the Staphylococcus aureus (PC041) pure culture

sample.

Appendix

D-1

Figure

AppD-2


obtained from the Escherichia coli (PC039) pure culture

sample.

Appendix

D-2

xvii

Figure

AppF-1


obtained from a cerebrospinal fluid sample (C003).

Appendix

F-1

Figure

AppF-2


obtained from a synovial fluid sample (S010).

Appendix

F-2

xviii

List of Tables

PAGE

Table 2.1 Details of the oligonucleotide primers used in the study. 31

Table 3.1 The Complexity Ranking of various DNA extraction methods. 44

Table 3.2 List of DNA extraction methods selected for the different

clinical samples.

54

Table 3.3 The PCR mixture and thermal profile for the Gram-positive

specific DNA amplification.

83

Table 3.4 The PCR mixture and thermal profile for the Pan-bacterial


84

Table 3.5 The PCR mixture and thermal profile for the Pan and Gram-

positive specific primers in a Duplex PCR.

85

Table 3.6 The PCR mixture and thermal profile for the Gram-negative


86

Table 3.7 The list of organisms used in this study confirmed by culture,

Gram-stain, and DNA amplification results.

94

Table 3.8 The results of BLAST and RDP-II SeqMatch analyses on 16S

rDNA sequences obtained from the DNA sequencing of pure

cultures.

104-106

xix

Table 3.9 The number of specimens found positive or negative by culture

and PCR, with division into Gram-positive and Gram-negative

groups.

109

Table 3.10 List of clinical specimens found positive by 16S rDNA PCR and

culture, with results from BLAST and RDP-II analyses.

116-121

Table 3.11 List of clinical specimens found positive by 16S rDNA PCR

assay and negative by culture, with BLAST and RDP-II

analyses.

125-127

Table 3.12 List of clinical samples that produced negative results using 16S

rDNA PCR assay but showed positive culture results.

128

Table 3.13 Results obtained from 16S rDNA broad-range PCR and

sequencing compared with those obtained from cultures in the

233 clinical samples studied.

130

Table 3.14 Results obtained from 16S rDNA broad-range PCR and

sequencing compared with those obtained from culture methods.

131

Table 3.15 Performance of the 16S rDNA PCR assay compared to the

culture results of cerebrospinal fluid (CSF), peritoneal fluid (PF),

synovial fluid (SF) and blood culture bottle (BCB) samples.

132

Table

AppE

The results of Gram-positive (GP), Gram-negative (GN), and

Pan specific primers PCR on the 233 clinical samples studied.

Appendix

E

xx

List of Symbols and Abbreviations

16S rDNA gene coding for 16S rRNA

16S rRNA small-subunit ribosomal RNA

AH Alkali-heat wash extraction method

BCB Blood culture bottle

BLAST Basic Local Alignment Search Tools

bp base pair

°C degree Celcius

CFU Colony Forming Unit

CSF cerebrospinal fluid

DNA Deoxyribonucleic acid

dNTP Deoxyribonucleotide triphosphate

EDTA Disodium ethylenediaminetetraacetic acid

FISH Flourescent in situ hybridization

g gram

µg microgram

ng nanogram

pg picogram

fg femtogram

GN Gram-negative

GP Gram-positive

xxi

ml mililitre

µl microlitre

LB Luria-Bertani

MgCl2 Magnesium chloride

M Molar

mM milimolar

µM micromolar

min minute

MW molecular weight

nm nanometre

N/A not available

NaCl sodium chloride

NaN not any number

NPV negative predictive value

OD optical density

PCIA phenol chloroform isoamyl-alcohol

PCR Polymerase Chain Reaction

PF peritoneal fluid

PPV positive predictive value

psi pounds per square inch

RDP-II Ribosomal Database Project-II

RE restriction endonucleases

xxii

RNA ribonucleic acid

rpm revolutions per minute

rRNA ribosomal RNA

s second

sddH2O sterile double distilled water

SDS sodium dodecyl sulphate

SF synovial fluid

SISA Simple Interactive Statistical Analysis

SPS sodium polyanetholesulfonate

sp. species

Ta annealing temperature

TBE Tris-borate EDTA

TE Tris-EDTA

Tm melting temperature

UM University of Malaya

UMMC University of Malaya Medical Centre

UV ultraviolet

V volt

Introduction

1

1.0 Introduction

It is estimated that there are 4 - 6 x 1030 prokaryotic cells, but less than 1% of all the

bacteria that exists in this world have been cultivated and characterized (Amann et al.,

1995; Torsvik and Øvreås, 2002). In their argument for phylogenetic identification and in

situ detection of microbial cells without cultivation, Amann et al. (1995) offered examples

of well-known but uncultured microorganisms, and discussed the “Great Plate Count

Anomaly”, where a majority of microscopically visualized viable cells do not form visible

colonies on plates.

Fredricks et al. (2005) investigated microbial communities associated with bacterial

vaginosis by using molecular identification without cultivation. Using broad-range 16S

rDNA PCR amplification with clone analysis, bacterium-specific PCR assay, and

fluorescence in situ hybridization (FISH) which were performed directly on vaginal fluid

from subjects with and without bacterial vaginosis, they found that women with bacterial

vaginosis had complex vaginal infections and many newly recognized species not found in

healthy subjects. An understanding of the microflora of an anatomical niche could be useful

in the identification of a “non-native” that may be the cause of disease (Relman, 1999).

In the field of medical microbiology, the usage of molecular methods has brought

about a reassessment of Koch’s Postulates to include sequence-based identification in

determining causation of diseases (Fredricks and Relman, 1996). In addition, the most

Introduction

2

recent taxonomic outline in the Bergey's Manual of Systematic Bacteriology (2nd Edition)

included the use of 16S rDNA sequence analysis to help define a classification that

reflected the phylogeny of prokaryotes (Garrity et al., 2004). And while traditional culture

methods of isolating, growing and identification by morphological structures and

biochemical tests are still the accepted "gold standard" for bacterial identification

(Houpikian and Raoult, 2002), molecular techniques have increased our understanding of

the range and activity of the microorganisms that share our world.

1.1 The Diagnosis of Infections

1.1.1 The Status Quo

Human instincts of self-preservation have led to large efforts dedicated to

identification of microbes once the clinical signs of infection develop. Practically all

available information about the composition and role of microflora has been based on

laboratory cultivated microorganisms. It was once thought that much was known about the

human body – the ecosystem most intimately related to our existence - and the methods

used to obtain that knowledge (Relman, 1999).

This however, was otherwise indicated from the results obtained from the

Unexplained Deaths project coordinated by the Centers for Disease Control (Perkins et al.,

1996). It was reported that unexplained death or critical illnesses occur in 0.5 to 2.0 persons

per 100,000 persons in the United States population every year. The use of broad-range 16s

rDNA Polymerase Chain Reaction (PCR) without the need for bacterial cultivation revealed

that known disease-causing agents were the probable or definite pathogen in some cases.

Furthermore, approaches for the selection and processing of clinical specimens for the

identification of pathogens using molecular methods have not been properly evaluated.

Introduction

3

1.1.2 Rapid Diagnosis: The Benefits

Rapid identification of bacteria in infections may lead to patient isolation and the

reduction of the patient's infectious period, thereby containing the spread of pathogenic

organisms and shortening the period of morbidity (Podzorski and Persing, 1995). Patient

mortality rates have decreased with a shortened turnover time in diagnosis (Doern et al.,

1994). Statistically fewer laboratory studies, imaging procedures, days of intubations and

days in intensive or intermediate-care area have been observed in situations utilising rapid

detection systems, thus, contributing to lower patient distress.

Rapid diagnosis of infections has been shown to be both beneficial to patient well-

being and to those bearing the costs of testing and hospitalization. Barenfanger et al. (1999)

showed that implementation of minor changes in work flow e.g. reducing diagnostic

turnover time by 5 hours, led to savings of $1,750 per patient or over $4 million per year in

a particular hospital. Lower hospitalization costs were also reported by Doern et al. (1994).

It is known that broad-spectrum antibiotic usage leads to susceptibility to

nosocomial infections and interferes with normal microflora. It has also been shown that

these infections incur increased costs in a hospital, not accounting for the loss of work hours

for the patient, the prolonged length of hospital stay, staff hours and laboratory costs (Inan

et al., 2005). Better reliance on narrow spectrum agents that have less effect on microflora

could help reduce the incidence of nosocomial infections (Gould, 1999) and help to lower

the patients’ distress and hospitalization costs. Therefore, a more specific antibiotic therapy

is desirable and can be obtained with rapid reporting of infective agents (Doern et al.,

1994).

Introduction

4

1.1.3 The Hurdle: Drawbacks of Culture Method

Standard microbiological diagnosis depends on the growth of the organism in

culture and may require 12-72 hours for detection (Klausegger et al., 1999). During direct

examination of clinical samples, identification may be limited by the number of organisms

present and the ability of laboratory staff to recognize the pathogen (Tang et al., 1997).

Culturing of microorganisms depends on the ability of the microbe to propagate on

appropriate artificial media. In addition, certain diagnostic tests are difficult to perform as

some bacteria may grow only a few colonies on agar plates (Carroll et al., 2000). As most

patients are usually treated with broad-spectrum antibiotics before identification

(Klausegger et al., 1999), culturing is made even more difficult due to the lower number of

cells present in these samples.

Another drawback of standard culture methods is the limited sample volume

available for culturing. This makes it difficult to culture all pathogens. Clinical specimens

that are obtained at lower volumes such as ocular fluid, cerebrospinal fluid and blood from

infants usually have fewer microbes present; hence, this would lower the possibility of any

detection even further (Carroll et al., 2000).

Microorganisms themselves can pose a problem in standard identification methods

as those that are non-cultivable or extremely fastidious such as Mycobacterium tuberculosis

(Podzorski and Persing, 1995) may delay diagnosis of the infection, thus affecting

treatment.

In addition, some organisms may be hazardous to laboratory personnel. When

dealing with potentially hazardous microorganisms, diagnosis often depends on serologic

detection of a humoral response or culture in expensive biosafety level II-IV facilities.

These organisms can be cultured but require specially trained personnel, special equipment

and expensive containment facilities. If proper precautions are not designed or followed, the

organisms may infect laboratory personnel and cause serious illness or even death.

Introduction

5

Logistics can also be a problem with standard culture methods. In laboratories

working with smaller sample loads, special media for culturing rarely encountered

pathogens may not be readily available or used routinely as they are not economically

feasible to be maintained as the reagents may expire before usage. Nevertheless, the

samples can be sent to referral labs, but these fragile microbes may lose their viability or

become overgrown with other organisms during transit (Tang et al., 1997).

1.1.4 A Solution: Benefits of Molecular Methods

Identification by molecular methods allow for more rapid and accurate identification

of etiologic agents in a much shorter time than traditional methods. For example, a protocol

using real-time PCR to detect and differentiate Gram-positive from Gram-negative bacteria

could yield results in less than 3 hours, inclusive of preparation time (Klaschik et al., 2002).

Such rapid identification would allow for the earlier initiation of a focused antimicrobial

regimen, and decrease the likelihood of disease progression (Doern et al., 1994).

Problems of low sample volumes from ocular fluids, cerebrospinal fluids, and swabs

can be overcome with molecular methods such as PCR. A single PCR reaction tube requires

only a small amount of sample (1-10 µl) for each test.

Molecular techniques have also been used to address issues such as the handling of

hazardous or potentially hazardous material, particularly when working on samples with

unknown etiologic agents. After the initial extraction procedure, only noninfectious

materials such as DNA or RNA are handled. These nucleic acids may be extracted with

commercially available kits and sent frozen to molecular reference facilities. This would be

helpful in situations where the organisms are rare or cannot be identified due to non-

availability of media. If molecular facilities are available, another benefit would be that

primers and probes necessary for the identification of rare organisms may be stored frozen,

Introduction

6

thereby excluding the need for maintaining media with a limited shelf-life. As molecular

techniques are made more readily available, a positive effect would be the lower cost in

clinical testing as well as a more rapid turnover rate (Tang et al., 1997).

1.2 Broad-range 16S rDNA Amplification and Sequencing

Broad-range PCR is one DNA amplification method that can easily be adapted in

routine clinical diagnostic laboratories to produce rapid and specific results. Once set up, it

is relatively simple, does not require much preparation time, and is reproducible, specific

and sensitive when appropriately designed.

The 16S ribosomal RNA gene (16S rDNA) is chosen as the target for broad-range

PCR as the gene sequences (and their gene products, the 16S rRNA) are considered the

most useful of molecular chronometers for the determination of phylogenetic relationships

(Woese, 1987). Aside from determining phylogeny, the 16S rDNA sequences are also

useful for bacterial identification in clinical settings.

1.2.1 Polymerase Chain Reaction

PCR is presently one of the most widely used methods of nucleic acid amplification.

It increases the sensitivity of detection while still retaining high specificity. The high

sequence specificity is due to using two unique and closely spaced synthetic oligonucleotide

primers that must hybridise to the target DNA under stringent conditions. Only then can

exponential amplification occur, in which each cycle theoretically doubles the amount of

target DNA in the presence of a thermostable DNA polymerase (Figure 1.1).

Introduction

7

Figure 1.1: Cycles involved in the Polymerase Chain Reaction (PCR).

Introduction

8

The steps in PCR include repeated cycles of amplifying selected nucleic acid

sequences. Each of the cycle consists of a DNA denaturation step, in which double strands

of DNA are separated; a primer annealing step, in which primers anneal to complementary

target sequences; and an extension reaction step, in which DNA polymerase extends the

sequences between the primers. The steps are repeated for 25-35 cycles. All of these steps

are performed on a programmable thermal cycle.

In the early cycles, initially synthesized strands of new DNA vary in length. As the

primers begin to use the synthesized strands of DNA as templates, the product of

amplification, which are in the form of double-stranded DNA sequences, become short

products. The length of the product is the sum of length of the two primers and the target

DNA sequence in between.

Multiplex PCRs are designed to probe a specimen for different organisms or target

sequences within a single PCR tube. This form of PCR uses a panel of primers that have

similar annealing temperatures, and each of the amplification products must be unique in

size, allowing detection and identification of specific organisms or genes (Podzorski and

Persing, 1995).

Broad-range PCR involves the use of primer pairs that target gene sequences that are

conserved among a broad group of agents. The conserved region should flank sequences

that are sufficiently variable to provide reliable phylogenetic information about an

infectious agent (Relman, 1999).

Introduction

9

1.2.2 Analysis of Amplification Products

One simple method of post-amplification analysis is the use of agarose-gel

electrophoresis followed by ethidium bromide staining. DNA could then be transferred to a

solid phase and probed either by radiolabeling or enzyme-labeling (Podzorski and Persing

(1995).

The DNA could also be purified and sequenced using an automated DNA

sequencing system which is the result of projects involving entire genome sequencing. The

sequencing reactions of automated systems are based on the Sanger-dideoxy procedure, but

uses fluorescent dye-labeled primers for easier detection (Madigan et al., 1997). The

products are separated by electrophoresis and the bands detected by fluorescence

spectroscopy. The results are analysed by computer and an electropherogram is generated,

consisting a colour-coded sequence of the four DNA bases.

1.2.3 Analysis of Sequencing Results

The Basic Local Alignment Search Tools (BLAST) programs are a set of sequence

comparison algorithms that searches sequence databases and produces an optimal local

alignment to a query (http://www.ncbi.nlm.nih.gov/education/BLASTinfo/similarity.html).

A local alignment includes only the most similar local region(s). Comparisons on BLAST

are made in a pairwise fashion and then given a score to reflect the degree of similarity

[defined as the extent (of similarity) to which nucleotide sequences can be, based on percent

sequence identity (extent in which two nucleotide sequences are invariant)]. The higher the

score, the greater the degree of similarity between a query sequence and the sequence

against which it is compared.

Introduction

10

The Ribosomal Database Project (RDP-II) however, is a more specialised database

containing aligned and annotated rRNA sequences which uses a hierarchical framework

based on new phylogenetically consistent higher-order bacterial taxonomy proposed by

Garity et al. (2004). It is updated monthly and contains 194,696 16S rRNAs as of Release

9.34 (Dec 1, 2005). Two of the tools of the RDP-II are the Classifier and SeqMatch (or

Sequence Match).

The Classifier (http://rdp.cme.msu.edu/classifier/class_help.jsp) gives initial

taxonomic placement using a Naïve Bayesian rRNA classifier whereby each query

sequence is assigned to a set of hierarchical taxa trained on known type strains of 16s rRNA

sequences. It displays the ancestor of current root taxon from the highest to the lowest rank.

A confidence estimate is generated for each assignment and only those defined by the user-

specific confidence threshold are displayed. The Classifier provides probable taxa but not

information such as similarity scores and possible matches with other genus which could

infer overlaps.

SeqMatch (http://rdp.cme.msu.edu/seqmatch/seqmatch_help.jsp) was found to be

more accurate than BLAST at finding closely related rRNA sequences (Cole et al., 2005). It

provides a similarity score which is obtained by dividing the number of unique oligomers

shared between the query and RDP sequences by the lowest number of unique oligos in

either sequence.

Introduction

11

1.2.4 The 16S ribosomal RNA Gene (16S rDNA)

The 16S rDNA is the gene coding for the small-subunit ribosomal RNA (16S rRNA;

Figure 1.2). The gene is located at the 5' terminus of an rrn operon and is followed by the

larger 23S rDNA and the small 5S rDNA. These genes are separated by spacers that may

contain genes for transfer RNA. During translation, the pre-rRNA is folded under the

influence of ribosomal proteins into tertiary and quaternary structures, and these become the

basis for the maturation process. The 5' and 3' flanking region of the rRNA genes are

digested by specific enzymes during maturation, and the resulting RNA and ribosomal

proteins are assembled to form the two ribosomal subunits which then forms one ribosome.

The two ribosomal subunits consist of the small 30S ribosomal subunit containing the 16S

rRNA and 21 proteins, and the larger 50S subunit containing the 23S rRNA, the 5S rRNA

and 32 proteins (Stackebrandt, 2001).

The 16S rRNA and its gene have some unique features that enable it to be used for

the identification of unknown bacteria. The gene itself is universally present among all

cellular life forms and the relatively small size of about 1540 nucleotides makes it an easy

target to analyse. The primary structure of the gene, which comprises an alternating

sequence of invariant regions from the conserved to the highly variable, allows for the

design of primers (in the conserved regions) to flank a variable region (Figure 1.2). Ideally,

the sequences in the variable region should allow for the identification or relatedness of

bacteria. As the function of ribosomes has not changed for about 3.8 billion years i.e. the

rate of change is constant over long periods and among diverse organisms, inferences of

evolutionary distance relatedness can be made (Relman, 1998; Stackebrandt, 2001).

Introduction

12

The database for the 16S rDNA sequences are also more extensive when compared

with other homologous molecules sequenced e.g. 23S rDNA and 5S rRNA, and genes

coding for enzymes or ribosomal proteins. As of February 8th, 2005, a total of 124,165

aligned and annotated bacterial small-subunit rRNA sequences have been deposited in the

RDP (Ribosomal Database Project II at http://rdp.cme.msu.edu/index.jsp) (Cole et al.,

2005).

Figure 1.2: Secondary structure of a 16S rRNA molecule based on the Escherichia coli

structure of Maidak et al. (1994). Highly variable regions are in red; highly conservative

stretches are in green; binding sites of primers used in the PCR of the rDNA are in blue, and

other nucleotides are in black (adapted from Stackebrandt, 2001).

Introduction

13

1.2.5 A Broad Outline of the Method

As mentioned previously, one of the unique features of the 16S rDNA gene is the

sets of conservative nucleotide stretches that are scattered over the genes. The conserved

regions can act as target sites for oligonucleotide primers that allow for PCR amplification

and sequencing. Molecular analysis can be performed on either purified nucleic acid

preparations or on crude extracts of bacterial cells.

The amplified DNA sequences are then determined using the chain termination

method. The statistical introduction of a nucleotide analogue such as dideoxynucleotide

competes with conventional nucleotides and causes base-specific termination of elongation

products. This result in populations of single-stranded DNA fragments of different lengths

sharing a common 5' end i.e. the primer.

The resulting sequences are then aligned using the sequence analysis tools, forming

columns in which homologous nucleotides derived from common positions within the

sequences are arranged. The sequences can be identified as identical or different. Pairwise

similarities or the 100% similarity between a pair of 16S rDNA sequences using different

methods would imply high relatedness or even the identity of the organisms itself. A lower

percentage of similarity would decrease the likelihood of relatedness in the organisms

compared (Stackebrandt, 2001).

Introduction

14

1.3 Literature Review of 16S rDNA Amplification and Sequencing

1.3.1 Used in the Identification of Unknown Etiologic Agents

One of the first uses of the 16S rDNA PCR in the identification of etiologic agents

in infections was in the determination of the agent of bacillary angiomatosis (Relman et al.,

1990). DNA sequences were amplified directly from tissue samples and a previously

uncharacterised rickettsia-like organism was identified. The sequenced fragment showed

that the organism was closely related to Rochalimaea quintana and it has since been named

Bartonella hensalae

Another success was achieved in the investigation of the cause of Whipple’s disease

where 16S rDNA PCR was performed on a small bowel biopsy taken from a patient with

the disease (Wilson et al., 1991). The subsequent sequencing and rRNA sequence search

showed a high similarity to sequences of bacteria of the Rhodococcus, Streptomyces and

Arthrobacter genera and a weak similarity to Mycobacteria. Later, using the same 16S

rDNA and sequencing method, sequences were obtained directly from the infected tissue of

five patients with the disease and more than 90% of the gene sequence determined. The

organism Tropheryma whipplei was then proposed as the etiologic agent of Whipple’s

disease (Relman et al., 1992).

The identification of these two organisms was considered a success as they could

not be cultured during that period in time. In the case of T. whipplei, the organism has since

then been isolated and maintained on human embryonic lung fibroblast monolayers

although it still cannot be cultivated in the absence of living eukaryotic cells (La Scola et

al., 2001). The positive identification of such etiologic agents by culture confirmed the

usefulness of the 16S rDNA broad-range PCR in the determination of unknown organisms.

Introduction

15

1.3.2 Important Highlights Regarding the 16S rDNA Broad-range PCR

Before the PCR was used to investigate the gene coding for the 16S rRNA, the

sequences were obtained from the rRNA itself. Prior knowledge of the rRNA sequences

was required and large amounts of rRNA were needed per reaction. It was difficult to

culture sufficient cells for the extraction of rRNA for processing. The PCR of 16S rDNA

with sequencing overcame the need for obtaining the rRNA. It also eliminated the need to

clone rDNA as cloning is time consuming (Wilson et al., 1990).

The first report on the contiguous sequence information of the entire amplified gene

coding for the 16S rRNA spanning 1.5 kb without the need for subcloning was presented by

Edwards et al. (1989). In this paper, the use of synthetic oligonucleotides in PCR followed

by sequencing provided an almost complete nucleotide sequence of the gene.

The 16S rDNA method has been compared with culture methods in the

identification of bacteria. Seventy-two aerobic Gram-negative bacilli that were

unidentifiable using the computer-assisted replica plating method developed by the Mayo

Clinic in Rochester, USA (but identified by conventional methods) were evaluated using a

commercial 16S rRNA gene sequencing system (MicroSeq; PE Biosystems, California,

USA), a bacterial cellular fatty acid profile system (Sherlock; MIDI, Inc., Del., USA) and a

carbon source utilization system (Microlog; Biolog, Inc., California). The percentage of

identification using the Sherlock, Microlog and MicroSeq methods were 77.8%, 87.5% and

97.2% identified to genus level, and 67.7%, 84.6%, and 89.2% identified to species level

respectively. The MicroSeq system managed to identify all 72 isolates tested to the genus

level and 65 to the species level. The commercial 16S rDNA system showed a more rapid

turnaround time and provided unambiguous bacterial identification compared with the other

two systems (Tang et al., 1998).

Introduction

16

Broad-range 16S rDNA PCR has been particularly useful in the identification of

organisms that were previously undetected using standard culture methods. Using this

technique, a fastidious organism, Bartonella quintana was identified as the etiologic agent

in a case of culture-negative infective endocarditis in Finland (Jalava et al., 1995). It had

never previously been diagnosed in Finland and would not have been suspected if not for

the 16S rDNA PCR findings. This has important implications for laboratory practices e.g.

the need for longer incubation times for selected microbial cultures to enhance detection of

fastidious and slow-growing microbes. Other cases of PCR-detected organisms involved in

culture-negative bacterial endocarditis have also been reported by Goldenberger et al.

(1997) and Wilck et al. (2001). PCR and sequence analysis of the 16S rDNA also helped

identify the first case of community-acquired bacteremia caused by Acinetobacter

radioresistens in an immunodeficient patient, where ambiguous Gram-staining and poor

biochemistry reactivity of blood culture isolates misguided early drug therapy in the patient

(Visca et al., 2001).

Broad-range 16S rDNA PCR was then used in a systematic manner in a population-

based surveillance for unexplained life-threatening infections, the Unexplained Death and

Critical Illness Project, where it was observed that known bacterial pathogens cause some

critical illnesses and deaths that failed to be explained using traditional diagnostic methods.

Among the known bacterial pathogens identified in the previously unexplained cases were

Neisseria meningitidis from cerebrospinal fluid samples, Streptococcus pneumonia from

cerebrospinal and pleural fluid, Stenotrophomonas maltophilia from bone marrow aspirates

and Staphylococcus epidermidis from blood culture material (Nikkari et al., 2002).

Introduction

17

1.3.3 16S rDNA PCR as a Routine Clinical Diagnostic Service

Drancourt et al. (2000) used the 16S rDNA PCR and sequencing method on a range

of environmental and clinical bacteria isolates that were unidentifiable by the BioMérieux

(France) identification strips and extensive phenotypic investigations. Retrospective

analysis found that phenotypic identification failure was due to inappropriate biochemical

profile (58.7%), Gram-staining (11.6%), oxydase and catalase activity (3.6%), and growth

requirements (1.5%). Out of the 177 phenotypically unidentifiable isolates, 159 (89.8%)

were identified to the genus level and 139 (78.5%) were identified to the species level using

the 16S rDNA PCR and sequencing. There were 10.2% of isolates that remained

unidentifiable as it was probably new bacterial species, but phylogenetic position could be

assigned to these organisms. The method was also found to be reproducible in and between

laboratories.

In a four year study conducted at the Turku University Central Hospital (Finland) on

536 clinical samples consisting of body fluids (cerebrospinal, synovial and pleural fluid),

biopsy specimen from tissues and pus samples from abscesses, the results from the 16S

rDNA PCR and sequencing method were compared to those obtained from bacterial culture.

The molecular methods were found to be superior to culture techniques when infections

were caused by bacteria with unusual growth requirement e.g. Bartonella quintana from

heart valves and Ureaplasma urealyticum from amniotic fluid. Also, it was statistically

verified that there was a tendency for the specimens to be culture-negative but PCR-positive

if patients were receiving antimicrobial therapy at the time the sample was taken. Compared

to culture and clinical assessment, the sensitivity of PCR and sequencing in that study was

74.2% and specificity was 98.7-99.6% (Rantakokko-Jalava et al., 2000).

Introduction

18

The broad-range 16S rDNA PCR was also used as a routine diagnostic clinical

microbiological service at a hospital in London where 382 referred paediatric specimens

were tested in a two year period. The specimens consisted of blood samples, cerebrospinal

fluid, tissues, pus, pleural fluids, peritoneal dialysis fluids, bronchoalveolar lavages, blood

culture fluids and others. PCR was the sole evidence for infection in 18.6% of the cases

(Harris and Hartley, 2003).

In a hospital-affiliated laboratory in Marseille, France, 1404 bacterial isolates (0.8%

of the total samples tested in five year period) failed to be phenotypically identified using

conventional culture methods (which included biochemical profiling). The samples were

obtained from patients with various clinical conditions. Each unidentified isolate had 1400

bp of its 16S rDNA gene sequenced. The 16S rDNA sequence analysis identified 11 new

species (those having less than 97% of sequence identity with known bacteria). Of the

samples tested using 16S rDNA PCR and sequencing, 120 were found to be rare (fewer

than 10 published cases) or unique (no published cases associated with humans). Sixteen of

these 16 isolates were previously recognised as environmental, and had never before been

reported in humans (Drancourt et al., 2004).

1.3.4 16S rDNA PCR in Specific Clinical Conditions

Broad-range 16S rDNA PCR and sequencing was used on cerebrospinal fluid

samples (Greisen et al., 1994; Kotilainen et al., 1998) in diagnosis of bacterial meningitis

and was found to be superior to conventional methods when antimicrobials were used

(Schuurman et al., 2004). It was also used on synovial fluids (Wilbrink et al., 1998) to

suggest an association between bacterial infection and inflammatory arthritides (Wilkinson

et al., 1999). The 16S rDNA PCR detected bacterial infection in total knee arthroplasty,

where the molecular method produced less false-negative results when compared with

Introduction

19

standard microbiological assay i.e. out of the 50 samples tested, bacterial infection were

detected in 32 samples using PCR, compared to only 15 samples using standard culture

methods (Mariani et al., 1996).

PCR and sequencing was used to test for presence of 16S rDNA in BACTEC 9240

automated blood culture system (Becton Dickinson Diagnostic Instrument Systems, Sparks,

Md.) to confirm true-positive and true-negative results. True-positive samples were samples

that had a positive signal on the BACTEC system, and had Gram-stained cells and growth

on chocolate agar. True-negatives samples were negative by the BACTEC system, Gram-

stain and growth on agar. Using the MicroSeq 500 PCR kit (PE Biosystems), the instrument

true-positive samples were shown to have 16S rDNA and the true-negative samples were

shown to have no 16S rDNA (Qian et. al., 2001).

Most infections are treated empirically using broad-spectrum antibiotics, and delays

in processing (24 hours to 48 hours) can result using standard culture methods. The 16S

rDNA PCR allows for the detection and differentiation of Gram-positive and Gram-

negative bacteria without the need for cultivation. Early detection enables adequate

treatment of bacterial infection. Differentiation by Gram-stain type using PCR allowed for

the exact classification of 17 microorganisms from intensive care unit cases (Klaschik et al.,

2002), 62 pathogenic species (Klausegger et al., 1999) and organisms in intraocular samples

(Carroll et al., 2000).

Introduction

20

1.4 Outline of the Method used in this Study

An outline of the research protocol used in this project is shown in Figure 1.3. DNA

was extracted via several methods i.e. alkali heat-wash (AH), boiling in buffer, DNAzol

extraction, and phenol chloroform isoamyl-alcohol extraction (PCIA). Extraction was

performed on various culture-negative clinical samples i.e. cerebrospinal fluids (CSF),

synovial fluids (SF), peritoneal fluids (PF) and blood culture bottle (BCB) fluids that were

inoculated with a known microorganism. The results of the extractions were compared and

the best method for each sample type was chosen for further use in experiments.

A primer pair targeting the area in the 16S rRNA gene sequences which is shared

only by bacteria was selected and other primer sets were constructed within sequences in

the 16S rRNA gene to further differentiate bacteria into Gram-negative and Gram-positive

type groups (Carroll et. al., 2000). Primers were designed by aligning the sequences of

various bacteria and finding consensus sequences.

The broad-range PCR protocol was optimized and tested for sensitivity using known

concentrations of extracted bacterial DNA. The protocol was also tested for specificity

using a range of bacterial DNA that was extracted from pure bacterial cultures.

The optimised broad-range PCR protocol was then used to determine the presence

and Gram-type of the bacterial DNA in clinical samples.

The amplified DNA was then sequenced using the fluorescent dye terminator

sequencing system (ABI). Sequencing results were submitted for BLAST and RDP-II to

search for similarity to other sequences for the determination of the species or genus of the

bacteria present. The results obtained by PCR and sequencing were compared to results

using culture techniques (Figure 1.3).

Introduction

21

Figure 1.3: The outline of the 16S rDNA PCR and sequencing method used in this study.

Part I involved designing and optimising various components of the method using known

parameters to determine the experimental limitations. Part II involved using the optimised

conditions to test a range of clinical samples obtained from the Microbiology Diagnostic

Laboratory, University of Malaya Medical Centre.

Part I: Design and Optimization Part II: Screening

Extraction of DNA from clinical specimens

of various types.

Amplification of bacterial 16S rDNA and

differentiation into Gram-positive and

Gram-negative groups.

Sequencing of amplified DNA

BLAST and RDP-II

similarity search on the sequences to determine

species (or genus or group) of the organism.

Comparison of results from 16S rDNA PCR and sequencing with those from culture to

determine clinical sensitivity and

specificity.

Sequencing of amplified DNA from organisms with known identities

BLAST and RDP-II similarity search on the results of the

sequencing of known organisms.

Comparison of results from 16S rDNA and

sequencing with known results from culture method to determine the extent of

matches.

Using 4 methods:

•Alkali heat-wash •Boiling in buffer

•Phenol chloroform isoamyl-alcohol extraction

•DNAzol extraction

Extraction

On spiked culture-negative samples of:

•Cerebrospinal fluids

•Synovial fluids •Peritoneal fluids

•Blood culture bottle fluids

Determination of specificity

and sensitivity

Design of primers for: •Pan-bacterial

•Gram-positive organisms •Gram-negative organisms

Optimization of PCR protocol

Polymerase Chain Reaction

Introduction

22

1.5 Objective of the Study

The main objective of this study is to develop and optimise a broad-range PCR

protocol to detect bacterial 16S rDNA, allowing for differentiation into Gram-stain types,

and to provide identification of bacteria without the need for cultivation. Development and

optimisation of the broad-range PCR was performed on various clinical samples in a routine

clinical diagnostic laboratory.

Specific objectives of this study:

• To evaluate different methods of DNA extraction from various types of clinical samples

for the optimal recovery of DNA and to overcome the presence of amplification

inhibitors.

• To design and optimize a broad-range PCR for use in a clinical setting that will be able

to detect the presence of bacterial DNA and to determine the Gram-stain type of Gram-

positive and Gram-negative bacteria.

• To determine the sensitivity and specificity of the PCR when applied to clinical

samples.

• To study the range of bacterial pathogens causing culture-negative infections by using

broad-range PCR on culture-negative deep body fluids i.e. CSF, PF, SF and venous

blood in BCB samples.

Methodology

23

2.0 Methodology

2.1 Samples

2.1.1 Bacterial Stock Culture

Pure cultures of Staphylococcus aureus and Escherichia coli identified by standard

bacterial testing techniques were obtained from the Diagnostic Microbiology Laboratory,

University of Malaya Medical Centre (UMMC). The pure cultures were used to optimise

and determine the lowest detection limits of DNA extracted using different techniques. The

specimens were obtained from hospitalised patients in the UMMC and were grown on agar

plates. Single colonies were obtained from purified sub-cultured agar plates and inoculated

into tubes containing 1 ml of Luria-Bertani (LB) broth and incubated at 37°C overnight. If

there was bacterial growth, the tubes were kept at 4°C or used immediately. Stock cultures

were re-grown in LB broth every fortnight, after sub-culturing on agar plates for purity.

2.1.2 DNA Samples

The DNA of S. aureus and E. coli were extracted from LB broth cultures using the

phenol chloroform isoamyl-alcohol method (Section 2.3.4). DNA extracts with an OD

reading between the ratios of 1.8-2.0 were used for PCR optimisation, determination of

PCR sensitivity and specificity, and as positive controls for the optimised PCR.

Methodology

24

Pure cultures of Enterococcus faecalis, Corynebacterium sp., Neisseria

gonorrhoeae, Haemophilus influenzae, Acinetobacter baumanii, Klebsiella pneumoniae,

Enterobacter sp., Proteus sp. and Stenotrophonomas maltophilia were obtained from the

Diagnostic Microbiology Laboratory, UMMC. The samples originated from in-patients of

the hospital and were grown on agar plates. About five single colonies were obtained from

purity plates and inoculated into 0.1 ml of LB broth. The DNAzol method of extraction was

performed on the samples using the method in Section 2.3.5. The samples were used to

determine the PCR specificity in this study.

The DNA of the fungus Cryptococcus neoformans was obtained from the

collections of Dr Tay Sun Tee of the Department of Medical Microbiology in the Faculty of

Medicine, University of Malaya (UM). The sample was used as a negative control in

determining PCR specificity in this study.

2.1.3 Culture-Negative Clinical Specimen

Culture-negative clinical specimens were used to evaluate the choice of extraction

methods in this study. The specimens were deep body fluids from hospital in-patients, sent

to the Diagnostic Microbiology Laboratory, UMMC for microbiological diagnosis. The PF

specimen was from a patient with a pleural effusion, the CSF specimen was pooled from

patients diagnosed with suspected meningitis, the SF specimen was from a patient

diagnosed with suspected septic arthritis and the BACTEC blood culture bottle (BCB;

Becton-Dickinson, USA) sample was cultured from a patient suffering from fever of

unknown origin. Samples were collected and used immediately or stored at -20°C until

required for use.

Methodology

25

2.1.4 Clinical Specimens for 16S rDNA Screening

Clinical specimens that were used for 16S rDNA screening consisted of CSF, SF,

PF and BCB samples collected from the Diagnostic Microbiology Laboratory, UMMC. The

collection was at random and selected only on the basis of sample type. Clinical information

on the patients and culture results were obtained from test request and report forms.

For each specimen, 0.1 ml was placed into a 1.5 ml microtube for DNA extraction.

The remaining sample fluid was stored in -20°C until the end of the study. Extraction was

carried out immediately, or within 2 days. Samples that could not be immediately extracted

were stored at -20°C.

2.2 General Methods

2.2.1 Preparation of Media and Buffers

All media and buffers were prepared in sterilised glassware or Schott bottles using

sterile MilliQ (18.2 megaohm/cm) water (sddH2O). Fresh broth powder and chemicals from

commercial companies were used during preparation (Appendix A). The buffers were kept

for 3 months at room temperature and longer if kept at 4°C. The autoclaved media bottles

were kept for one month at room temperature, and at 4°C when opened. Methods for media

and buffer preparation are outlined in Appendix B.

2.2.2 Sterilisation

Media solutions and water were autoclaved at 121°C at 15 psi for 15 minutes.

Pipette tips and microtubes and other plastics were autoclaved at 121°C at 15 psi for 20

minutes. Glasses and Schott bottles were washed with cleaning solution and dried at 80°C

in an oven.

Methodology

26

2.2.3 Workflow and Special Considerations

Several procedures were implemented to minimize carry-over DNA and sample-to-

sample contamination during PCR. Among them are aliquoting reagents, particularly if the

reagents are used in small amounts, the use of positive displacement pipettes, meticulous

laboratory techniques and the use of dedicated equipment (e.g. micropipettes, tips, tubes,

and centrifuge) in specialised areas (e.g. the Class II biological safety cabinet for extraction,

and the Post-PCR room). Proper negative and positive controls were also included in every

experiment and every batch to help detect contamination. A physical separation of pre- and

post- amplification areas and a unidirectional workflow was strictly implemented in the

following manner:-

Reagent preparation (Reagent Room and laminar flow hood in main laboratory) �

PCR Premix (Class II biological safety cabinet, dedicated for PCR only) �

Extraction and DNA template addition (Class II biological safety cabinet,

dedicated for sample manipulation) � DNA amplification (thermal cycler in main

laboratory) � Post-PCR manipulation (in Post-PCR room on separate floor from

main laboratory)

2.3 Extraction Methodology

2.3.1 Cell Counting

A 1 ml volume of E. coli broth culture was transferred into 0.9 ml of sterile LB

broth. Six serial 10-fold dilutions were made and 100 µl of the final three dilutions were

plated on Nutrient Agar. The plates were incubated overnight at 37°C. Colonies were

counted on plates having 30-300 colonies and the colony forming units (CFU) per ml of

each sample was determined using the following formula:

Methodology

27

CFU/ml = __N__

DF x V

With N = the number of colonies counted on the plate; DF = the dilution factor (or the

number of times the sample was diluted), and V = the volume plated in ml (0.1 ml in this

case). This experiment was repeated using S. aureus broth cultures. Known quantities of

CFU/ml in a broth culture were used to determine the best extraction method as well as the

lowest detection limits of the method of choice.

2.3.2 Alkali Heat-Wash Extraction Method

The AH method used in this study was modified from the method proposed by

Kulski and Pryce (1996). To wash the cells, 0.1 ml of the sample and 1.4 ml of alkali wash

solution was placed into a microtube. The lid was closed firmly and the solution mixed by

inversion for 10 minutes in room temperature. The cells were pelleted by centrifugation at

13,000 g for 5 minutes and the supernatant removed. The remaining alkali wash solution

was removed by washing twice with 0.5 ml of 0.5 M Tris-HCl (pH 8.0). At each wash, the

pellet was resuspended in the buffer, and then pelleted again by centrifugation at 13,000 g

for 5 minutes. After the second wash, the pellet was resuspended in 0.1 ml of TE buffer (pH

8.0). The microtube was then placed on the heating block and incubated at 95°C for 25

minutes. The microtube was then removed and placed in -20°C until the lysate was frozen.

The lysate was thawed out by placing the microtube in warm water for 15 minutes. The

freeze/thaw cycle was repeated twice. The lysate was then centrifuged at 13,000 g for 5

minutes and the supernatant transferred into a fresh tube. The supernatant containing DNA

was used immediately or stored at -20°C until use.

Methodology

28

2.3.3 Boiling Extraction Method

A 0.1 ml volume of sample was buffered with 0.4 ml of TE buffer (pH 8.0) and

incubated at 95°C for 25 minutes. The lysate was then frozen at -20°C and then thawed in

warm water for 15 minutes. The freeze/thaw cycle was repeated twice to break down any

remaining cell wall or membrane. The lysate was then centrifuged at 13,000 g for 15

minutes. The supernatant containing DNA was then transferred to a fresh tube and used

immediately or stored at -20°C until use.

2.3.4 Lysis Buffer and Phenol Chloroform Isoamyl-Alcohol Extraction Method

A lysis buffer was added to 0.1 ml of sample in a microtube. The buffer consisted of

146 µl of the buffer TE (10/10 mM), 225 µl of lysozyme (10 µg/ml), 11.5 µl of Proteinase K

(10 µg/ml) and 17.5 µl of 10% SDS. The microtube was then incubated at 65°C for an hour,

and then at 55°C for 3 hours (or 37°C overnight).

An equal volume of phenol (500 µl) was then added to the lysate, and mixed well by

inversion of the microtube. The lysate solution was then centrifuged at 3,500 g for 5

minutes. The resulting aqueous layer was removed carefully and transferred into a fresh

microtube. An equal volume of chloroform-isoamyl-alcohol (24:1) was then added into the

microtube and placed into the centrifuge at 3,500 g for 5 minutes. Again, the aqueous layer

was removed and transferred into a fresh microtube. To precipitate the DNA, 100% ethanol

was added at twice the volume of the aqueous layer and 4 M NaCl at a tenth of the volume.

The microtube was inverted several times to mix and the solution was observed for DNA

precipitation. The microtube was then placed in -20°C overnight or -80°C for 3 hours. The

DNA was pelleted by centrifugation at 13,000 g for 10 minutes and the supernatant

discarded.

Methodology

29

The DNA precipitate was washed using 1 ml of 100% ethanol and then sedimented

by centrifugation at 13,000 g for 10 minutes. The supernatant was discarded. The pelleted

DNA precipitate was then washed again using 1 ml of 70% ethanol and centrifuged as

before. The supernatant was drained from the microtube, and the microtube inverted until

the ethanol had evaporated. The DNA was solubilized using TE buffer (pH 8.0) and used

immediately or kept at -20°C until required.

2.3.5 DNAzol Extraction Method

This method was modified from the Molecular Research Centre protocol for genomic DNA

isolation (found online at http://www.mrcgene.com/dnazol.htm). A 0.1 ml volume of the

sample was placed in a microtube and 0.9 ml of DNAzol was added for cell lysis. The

solution was mixed by inversion for 15-30 seconds and then incubated at 50°C for 15

minutes. The homogenate was then sedimented by centrifugation at 10,000 g for 10

minutes. The resulting viscous supernatant was transferred to a fresh tube. To precipitate the

DNA, 0.5 ml of 100% ethanol was added to the lysate. The sample was mixed by inverting

the tube 5-8 times, making sure that the DNAzol and ethanol mix well to form a

homogenous solution. The microtube was then stored at room temperature for 5 minutes.

DNA was visible as a cloudy precipitate and this was sedimented by centrifugation at 5,000

g for 15 minutes. The supernatant was removed and the precipitated DNA was washed

twice with 1 ml of 70% ethanol. At each wash, the DNA was suspended in ethanol by

inverting the tubes 3-6 times and the DNA sedimented by centrifugation at 5,000 g for 5

minutes before the removal of the supernatant. After the second wash, the microtube was

drained of remaining ethanol and inverted for 1-2 minutes. The DNA was solubilised with

TE buffer (pH 8.0) and used immediately or stored in -20°C until use.

Methodology

30

2.3.6 DNA Quantification of Extracted Samples

DNA concentration for each clinical sample was estimated using the BioPhotometer

(Eppendorf, Hamburg). A 5 µl volume of DNA was diluted into 45 µl of sterile ddH2O to

make a final 1/10 dilution. The absorbance reading for the sample was measured at 260 nm

to estimate the DNA concentration in µg/µl. Protein contamination was measured at 280

nm. DNA purity was measured using absorbance readings at 260/280.

2.4 PCR Primers

2.4.1 Designing Primers

Consensus sequences were determined by aligning the 16S rDNA sequences (≈1500

bp) of various organisms obtained from GenBank (http://www.ncbi.nlm.nih.gov/Genbank/),

using the FastPCR for Windows software v2.4.13 (http://www.biocenter.helsinki.fi/bi/bare-

1_html/oligos.htm) followed by manual alignment. From the aligned sequences, “front” and

“back” end consensus sequences that potentially contained forward and reverse primers

were chosen, with preference on conserved regions flanking variable regions.

The Primo Pro software (http://www.changbioscience.com/primo/primo.html) was

used to select the best primers from the chosen consensus sequences using the following

settings: 5’ primer <1-100>, melting Tm <65°C>, Tm formula <Nearest-N>. From the

many potential primer sequences generated, those that were more than 25 bp in length,

ranked with a lower quality (as defined by FastPCR), formed primer-dimers with existing

primers, and had a non-matching Tm were eliminated from the list. The final primers were

tested for correct matching with target areas by inserting a string of more than 20 Ns

between two primers and performing the search as if it were one sequence on BLAST

(http://www.ncbi.nlm.nih.gov/BLAST/).

Methodology

31

2.4.2 Manufacturing Primer Oligonucleotides

Sequences of primers were synthesised by 1st Base Laboratories Sdn. Bhd

(Selangor, Malaysia). The manufactured oligonucleotides were delivered in lyophilised

form and solubilised with ddH2O to make 100 mM of stock solution which was then diluted

to make a 10 mM of working solution. The primer solutions were aliquoted into small

volumes and kept in -20°C until use.

2.4.3 Primer Profile

Primers nf, NR and f3p (modified) were from Carroll et al. (2000). The primers f4n

and r18n were designed using the method above (Section 2.4.1). Table 2.1 contain details

and sequences of the primers used.

Table 2.1: Details of the oligonucleotide primers used in the study.

Primer

Name Sequence (5'-3')

Length

(bases)

Position

on E.coli

rRNA

sequence

(bases)

Target

area

Fragment

size

f4n AGCAGCCGCGGTAATACGGAGG 22 520-541

Gram-

negative

specific

r18n ACGAGCTGACGACAGCCATGCAG 23 1051-

1073

Gram-

negative

specific

554 bp

nf GGCGGCAKGCCTAAYACATGCAAGT 25 38-62

Pan

bacterial

specific

f3p CCGRCTCTCTGGTCTGTAACTGACGC 26 731-756

Gram-

positive

specific

NR GACGACAGCCATGCASCACCTGT 23 1044-

1066

Pan and

Gram-

positive

specific

336 bp

and

1029 bp

Note: K=G/T; Y=C/T; R=A/G; S=G/C

Methodology

32

The Pan-bacterial specific primers of nf and NR targeted only the 16S rRNA gene

sequence of bacteria. The nf primers contained two degenerate bases and were 25 bases in

length. The sequence of this oligonucleotide was located on the sense strand of the E. coli

16S rRNA sequence between the bases 38 and 62.

The NR primer was also paired with f3p in the Gram-positive specific PCR. The NR

primer had one degenerate base, was 23 bases in length and was located on the antisense

strand of the E.coli rRNA sequence at 1044-1066 bases.

The f3p primer was based on the P2F primer (Carroll et al., 2000). One of the bases

was changed at the 5'-end and 8 other bases were added at the 3'-end. The 8 bases added

were based on the consensus sequence of several Gram-positive organisms. The length of

the primer was 26 bases with the additions. The primer was located on the sense strand of

the E. coli rRNA sequence (with 8 bases mismatched) and had one degenerate base.

The f4n and r18n primers were Gram-negative specific. The f4n primer was 22

bases in length and was located on the sense strand of the E. coli rRNA sequence between

the bases 520 and 541.

The reverse primer r18n was 23 bases in length and was located at positions 1051 to

1073 of the antisense strand of the E. coli rRNA sequence. The r18n and NR primers

overlap by 16 bases. However, when both the primers were examined by BLAST, r18n

gave results that were more specific to Gram-negative organisms.

Methodology

33

The image on which the primer sequences were matched to those on the E. coli

rRNA sequence is shown in Figure AppC (Appendix C). The potential fragment size of

the amplified products was calculated as the distance between the forward and reverse

primers on the E. coli rRNA sequence. The f4n and r18n primers amplified a fragment that

was 554 bp in size, f3p and NR primers produced a fragment of 336 bp in size, and nf and

NR primers produced a fragment of 1029 bp in size. A diagrammatic view of the PCR

primer target areas and the sizes of the fragments produced are shown in Figure 2.1.

Figure 2.1: A diagram showing the primer annealing positions and fragment sizes of the

PCR products in this study.

TARGET AREAS OF PRIMERS

16S rDNA

Pan-bacterial specific PCR product

nf f3p NR

r18n f4n

0 1500 bp

1029 bp

nf NR

38 62 1044 1066 bp

336 bp

f3p NR

731 756 1044 1066 bp

554 bp

f4n r18n

520 541 1051 1073 bp

FRAGMENT SIZES

Forward primer for

duplex PCR

Forward primer for

Gram-negative

specific PCR

Reverse primer for

duplex PCR

Reverse primer for

Gram-negative

specific PCR

DNA fragment

KEY

Gram-positive specific PCR product

Gram-negative specific PCR product

Methodology

34

2.5 PCR, Sequencing and Analysis

2.5.1 Preparation of PCR Mixtures

PCR reagents are sensitive to cycles of freezing and thawing, thus, solutions were

aliquoted in small volumes of 50-100 µl in microtubes. The Taq polymerase (recombinant,

1U/µl; Fermentas) and primers were kept at -20°C until use. The stock solution for the

buffer (10X), MgCl2 (25 mM) and dNTPs (10 mM) were kept at -20°C, but the working

solutions were stored at 4°C for a maximum duration of one week to prevent cycles of

freezing and thawing. Frozen solutions were thawed out slowly on ice and centrifuged

before use. The preparation of the PCR mixture was also performed on ice.

A PCR pre-mix solution was prepared by pipetting the buffer solution, MgCl2,

dNTPs, primers, Taq polymerase, and sddH2O into a thin-walled PCR tube and mixing

thoroughly. Template DNA was then added in an area separate from the PCR pre-mix area.

Negative and positive controls with samples containing appropriate DNA were added in

each batch of reactions. In addition, DNA blanks with no DNA added to the PCR tubes

were included in every PCR batch to ensure no DNA contamination.

Following template addition, the tubes were placed in a thermal cycler with a heated

lid (MJ Research Instrument Inc, USA). The file with the appropriate thermal profile was

selected.

When the PCR assay was completed, the tubes were placed into a post-PCR

container, taken to the post-PCR area, and spun down before gel electrophoresis.

Methodology

35

2.5.2 Gel Electrophoresis of Amplified PCR Products

The PCR amplification products were observed using agarose gel-electrophoresis. A

1.5% agarose-TBE gel was made to which 1 µl of ethidium bromide (10 mg/ml) was added.

The solution was mixed by swirling and poured into the acrylic gel tray with the two ends

taped up to make a reservoir. The 14-well comb was set in place and the gel was left to set

for 30 minutes. When the gel solidified, the comb and tapes were removed and the gel tray

placed in the buffer tank. The gel was submerged to a depth of 2-5 mm by pouring 1x TBE

into the tank.

On a strip of parafilm, 1.5 µl of loading dye was mixed with 9 µl of the PCR

amplified DNA sample. The mixture was then carefully loaded into the well of the gel. The

MassRuler DNA Ladder (Fermentas) was used as a molecular weight marker. Gel

electrophoresis was carried out at 90V for one hour (or until the dye reached 3/4 the length

of the gel).

When the run was complete, the gel tray was removed from the buffer tank and the

gel placed on a UV lightbox. The gel was photographed and documented using Polaroid

667 black and white film.

Methodology

36

2.5.3 Min Elute PCR Purification Kit Protocol and Sequencing

Amplified PCR products were purified using the MinElute PCR Purification Kit

(Qiagen) according to manufacturer’s instructions. Absolute ethanol was added to Buffer

PE before use, following the volume written on the bottle label. All centrifuge steps were at

13,000 g. Buffer PB was added to the PCR mixture in a 5:1 ratio and mixed. The MinElute

column was placed in a 2 ml collection tube. The sample was applied to the MinElute

column and centrifuged for 1 minute to bind DNA. The flow-through was discarded and the

MinElute column placed back into the same tube. To wash, 750 µl Buffer PE was added to

the MinElute column and centrifuged for 1 minute. The flow-through was again discarded

and the MinElute column placed back into the same tube. The column was centrifuged for

an additional minute to remove residual ethanol from the Buffer PE. The MinElute column

was then placed in a clean 1.5 ml centrifuge tube. To elute the DNA, 50 µl of ddH20 with a

pH value of between pH 7.0 and 8.5 (as maximum elution efficiency is achieved at that

range) was added to the centre of the membrane. The column was left to stand for 1 minute

and then centrifuged for another minute. The purified PCR products were stored at 4°C

until sent for sequencing.

The purified PCR products and the appropriate primers were collected by 1st Base

Laboratories Sdn. Bhd representatives within 24 hours. Sequencing results were generated

by the company in 2-3 working days and were initially sent via email. Hardcopies of the

results were sent after a week. Results were obtained as electropherograms and .txt file

formats.

Methodology

37

2.5.4 Analysing Sequencing Results

The DNA sequenced results obtained were analysed using databases freely available

online. Analyses from both BLAST (Altschul et. al., 1997) and the RDP Database Project-

II or RDP-II (Cole et. al., 2005; http://rdp.cme.msu.edu/index.jsp) were used to confirm the

identity of the sequenced DNA.

The sequences were sent for BLAST analysis and the percentage of similarity was

noted. The Nucleotide-nucleotide BLAST (blastn) program was used with the default

option selected i.e. nr database, low complexity filter, a word size of 11 and expected 10.

Identification was refined using the RDP-II tools of the Classifier. When the

sequence was tested on the Classifier using an 80% confidence level, the taxa in which the

organism belongs could be determined with the percentage of probability stated.

Information for the identification of bacteria was further obtained by selecting the

SeqMatch (Sequence Match) "type and non-type" and "type only” option for strains, which

provided a possible organism name and a similarity score (where the highest matching score

from a combination of both groups was considered). The “type” option displayed only

sequences of known type strains. Results from unidentified or uncultured organisms were

generally excluded unless there was a high probability match or no other close matches.

2.5.5 Statistical Analyses

Statistical analyses and comparison of the performance of the 16S rDNA PCR and

sequencing assay against culture methods were performed using Fisher’s Exact Test and the

SISA software (Uitenbroek, 1997).

Methodology

38

2.6 Determination of PCR Sensitivity

To determine the sensitivity or lowest detection limit in of DNA concentration for

the PCR, E. coli was used to represent Gram-negative organisms, and S. aureus was used to

represent Gram-positive organisms. The DNA of each organism was extracted using the

PCIA method, DNA concentration was determined spectrophotometrically. Serial dilutions

to 10 ng, 1 ng, 100 pg, 10 pg, 1 pg of DNA per 5 µl of DNA template solution was carried

out. The DNA template solution was then added to 20 µl of PCR pre-mix to make a total of

25 µl per PCR microtube. PCR was performed using the optimised thermal profile and the

results observed on an agarose gel. The lowest detection limit for PCR is the minimum

amount of DNA template needed to produce an amplified product (Figure 2.2).

10 ng/5 µl 1 ng/5 µl 100 pg/5 µl 10 pg/5 µl 1 pg/5 µl

5 µl 5 µl 5 µl 5 µl 5 µl

PCR tubes with 20 µl of

pre-mix

DNA template


Example of a PCR result

on an agarose gel

Marker Lane 1 Lane 2 Lane 3 Lane 4 Lane 5 DNA blank

10 ng 1 ng 100 pg 10 pg 1 pg DNA DNA DNA DNA DNA

A faint amplified specific band observed in Lane 4 and none in Lane 5 indicates

the lowest detection limit for this PCR is 10 pg.

1/10 dilution

1/10 dilution

1/10

1/10 dilution

1/10

1/10 dilution

1/10

No DNA added

Figure 2.2: Procedure for the determination of PCR sensitivity in this study.

Methodology

39

2.7 Determination of PCR Specificity

For specificity testing of PCR, DNA from a range of organisms was extracted using

the DNAzol method. DNA concentration was determined and 10 ng of DNA from each

sample was then used in each 25 µl PCR mixture. PCR was performed using the optimised

thermal profile and the results observed on an agarose gel. The PCR was considered

specific for a particular microorganism when DNA amplification of a specific product was

obtained (Figure 2.3).

Figure 2.3: Procedure for the determination of PCR specificity in this study.

DNA template from various

known organisms

Organism A Organism B Organism C Organism D

10 ng DNA

10 ng DNA

10 ng DNA

10 ng DNA

PCR tubes with pre-mix


Marker Lane 1 Lane 2 Lane 3 Lane 4 DNA blank

Example of a PCR result on an agarose gel

Amplified specific bands observed in Lanes 1, 2 and 4 and none in Lane 3 indicates

organisms A, B and D contain target DNA specific to this particular PCR.

Methodology

40

2.8 Screening of Clinical Specimens

The clinical specimen was collected and used immediately (or stored at -20°C if

tests could not be performed within the same day). DNA from each specimen was extracted

using the methods found to be most effective for each specimen type (Section 3.1.3).

Procedures for the screening of clinical samples are shown in Figure 2.4.

Figure 2.4: Procedures used in the screening of clinical specimens in this study.

Pan and Gram-Positive Specific Duplex


Gram-Negative Specific Polymerase Chain Reaction

Clinical Specimen

DNA Template

PCR tubes with pre-mix

100 pg Staphylococcus

aureus DNA

100 pg Escherichia

coli DNA

Tube 1

10 ng into each PCR tube

Tube 2 Tube 3 Tube 4

PCR positive results sent

for sequencing

Electropherogram from sequencing

Gram-type obtained

Bacterial identity

obtained

Diagrammatic examples of possible PCR results on agarose gel can be seen in Figure 2.5.

BLAST and

RDP-II search

Extract DNA

Methodology

41

Following OD readings, 10 ng of extracted DNA was added into PCR pre-mixes.

Each sample was placed into four separate PCR tubes, two tubes containing 10 ng of

sample only, another spiked with an additional 100 pg of S. aureus DNA, and another

spiked with 100 pg of E. coli DNA. The tubes containing 10 ng of samples only, and spiked

with S. aureus DNA were used for Pan and Gram-positive specific PCR while the other

tube containing 10 ng of samples only and spiked with E. coli DNA were used for Gram-

negative specific PCR.

Each PCR batch had E. coli and S. aureus DNA as positive or negative control and a

DNA blank with no DNA template added. E. coli DNA was the negative control and S.

aureus DNA was the positive control in the Gram-positive specific PCR and vice-versa for

the Gram-negative specific PCR. All PCR assays were carried out with at least two positive

and negative control tubes to ensure reproducibility in results. However, in the gel photos

shown in the thesis, only one negative, one positive and one DNA blank were shown. Each

test was performed twice.

Diagrammatic examples of possible PCR results on agarose gel can be seen in

Figure 2.5. DNA blank batch controls that were included in each run were expected not to

have any bands. The positive control for Pan and Gram-positive specific PCR (S. aureus

DNA) was expected to have 1029 bp and 336 bp bands, while the negative control (E. coli

DNA) was expected to have only a 1029 bp band. The positive control for Gram-negative

specific PCR (E. coli DNA) was expected to have a 554 bp band and the negative control

(S. aureus DNA) was expected to have no bands. Clinical specimens producing 1029 bp

and 336 bp bands only were considered to have DNA from Gram-positive organisms, while

specimens producing 1029 bp and 554 bp bands are considered to contain DNA from

Gram-negative organisms. If spiked samples produced bands but no bands were observed in

non-spiked samples, the clinical specimens were considered to be negative for the targeted

DNA sequences.

Methodology

42

Samples that were positive in PCR were purified and sent for sequencing. The

results were analysed using BLAST and RDP-II searches and the possible identity of the

organism determined.

Figure 2.5: Diagrams of possible PCR results on agarose gel during hypothetical clinical

screening of specimens.

- 1029 bp

- 554 bp

- 336 bp

Tube 2

Tube 1

Tube 3

Tube 4

GP GN BL

GP GN BL

Marker

- 1029 bp

- 554 bp

- 336 bp

Tube 2

Tube 1

Tube 3

Tube 4

GP GN BL

GP GN BL

Marker

Key:

Tube 1: Clinical specimen DNA only

Tube 2: Clinical specimen spiked with Staphylococcus aureus DNA

Tube 3: Clinical specimen DNA only

Tube 4: Clinical specimen spiked with Esherichia colis DNA

GP: S. aureus DNA

GN: E. coli DNA

BL: No DNA added (blank)

- 1029 bp

- 554 bp

- 336 bp

Tube 2

Tube 1

Tube 3

Tube 4

GP GN BL

GP GN BL

Marker

Pan and Gram-positive specific PCR results

Gram-negative specific PCR results

DNA was

obtained from a

Gram- positive

organism

DNA was

obtained from a

Gram-negative

organism

No DNA

present or

DNAwas

obtained from a

non-bacterial

source.

Results

43

3.0 Results

The results will be presented in two sections. The first section contains results from

Phase I of the study which involved the optimisation of the various methods used. Phase II

contains the results obtained from the screening of the clinical samples in this study.

PHASE I: Optimisation of Protocols

3.1 DNA Extraction

The clinical specimens used in this study were from different sources. Thus,

different methods of extraction were evaluated for each of the specimen types to determine

the most optimal method for use. The methods tested were the AH, boiling, PCIA and

DNAzol methods on culture-negative CSF, SF, PF and BCB samples (Section 2.1.3).

Whole cells of Escherichia coli and Staphylococcus aureus (1x106 CFU/ml) were

separately spiked into 100 µl of each specimen types prior to extraction. The final choice of

extraction method depended on the comparison of the "Complexity Ranking" for each

method (Section 3.1.1) together with the PCR results of the extracted DNA templates

(Section 3.1.2).

Results

44

3.1.1 Complexity Ranking

The complexity ranking (Table 3.1) is a qualitative analysis of several conditions

during extraction i.e. the number of steps involved, the amount of toxic chemicals used, the

skill level needed to conduct the extraction, and the amount of waste (chemicals and

consumables) generated. Each of the conditions was graded as low (+), medium (++) or

high (+++) in complexity.

Table 3.1: The Complexity Ranking of various DNA extraction methods.

Method Name Number

of Steps

Toxic

Chemicals

Skill

Level

Waste

Generation

Boiling 10 (+) + + +

Alkali heat-wash (AH) 18 (++) + + +

DNAzol 17 (++) ++ + ++

Phenol chloroform isoamyl-alcohol (PCIA) 23 (+++) +++ +++ +++

Note: + : low complexity

++ : medium complexity

+++ : high complexity

The boiling method had the lowest overall complexity ranking. It required the least

amount of steps compared to the other methods (10 steps, Section 2.3.3), involved almost

no toxic materials, required a low skill level, and the amount of waste generated was

negligible as everything was carried out in the same tube. In addition, the chemicals used

did not require special disposal aside from the usual biohazard disposal system.

The AH method was similar to the boiling method with regards to the amount of

toxic materials used, the skill level needed to perform the extraction, and the amount of

waste generated. However, the number of steps was increased by an additional eight steps

(Section 2.3.2). Thus, the AH method had the second lowest complexity ranking.

Results

45

The method involving DNAzol had the second highest complexity ranking of the

four. The number of steps involved (17 steps, Section 2.3.5) were almost similar to the AH

method but lesser than the steps needed to perform the PCIA method. Because the main

ingredient of DNAzol was guanidium thiocyanate, which is a mildly hazardous irritant and

requires careful attention when in use, the method was given a higher complexity ranking in

terms of the waste generated. Aside from the care needed in handling the toxic material, the

skill level when using DNAzol was low.

The PCIA method required the most number of steps to perform (23 steps, Section

2.3.4). The amount of toxic materials such as phenol, chloroform, isoamyl alcohol and SDS

used gave this method a high complexity ranking. In addition, the step involving the

removal of the aqueous layer with minimal disturbance to the interphase required a steady

hand and this step had to be carried out slowly and carefully. The amount of waste

generated was also high, and as the chemicals are poisons, they have to be stored and

disposed by University of Malaya contract disposal companies.

In summary, the boiling method had the lowest complexity ranking, followed by the

AH, DNAzol and PCIA methods (Boiling<AH<DNAzol<PCIA).

3.1.2 DNA Amplification Results of Extracted Samples

Figures 3.1 and 3.2 show the products of a Gram-negative specific PCR using DNA

from the experiment in which the AH, boiling, PCIA and DNAzol extraction methods were

evaluated on CSF, BCB, PF, SF and water samples spiked with E. coli cells. A standard

DNA concentration of 10 ng was used in the PCRs. The agarose gel-electrophoresis system

was used to observe the amplified product after PCR. The presence of a distinct band with

the specific molecular weight indicated that a particular extraction method used was

successful in removing PCR inhibitors and producing purified DNA. The MassRuler DNA

Ladder (Fermentas) was used as a molecular weight marker.

Results

46

Alkali heat-wash method of extraction

Lane 1: Cerebrospinal fluid sample, 554 bp band.

Lane 2: Blood culture bottle sample, 554 bp band.

Lane 3: Synovial fluid sample, no amplified product.

Lane 4: Peritoneal fluid sample, 554 bp band.

Lane 5: Water sample, no amplified product.

Lane 6: Massruler DNA ladder (Mix)

Boiling method of extraction


Lane 8: Blood culture bottle sample, no amplified product.

Lane 9: Synovial fluid sample, no amplified product.

Lane 10: Peritoneal fluid sample, no amplified product.

Lane 11: Water sample, no amplified product.

Lane 12: 100 pg Escherichia coli DNA (positive control), 554 bp band.

Results

47

1 2 3 4 5 6 7 8 9 10 11 12

10 kbp

1031 bp

500 bp

554 bp

Figure 3.1: Gel electrophoresis of PCR products amplified from DNA

extracted using the alkali heat-wash and boiling methods. The Gram-

negative specific primer set (f4n and r18n) was used

80 bp

Results

48

Phenol chloroform isoamyl-alcohol method of extraction



Lane 3: Synovial fluid sample, 554 bp band.

Lane 4: Peritoneal fluid sample, 554 bp band.

Lane 5: Water sample, 554 bp band.


DNAzol method of extraction



Lane 9: Synovial fluid sample, 554 bp band.

Lane 10: Peritoneal fluid sample, 554 bp band (faintly visible).

Lane 11: Water sample, 554 bp band.

Lane 12: DNA blank, no amplified product.

Results

49

1 2 3 4 5 6 7 8 9 10 11 12

10 kbp

1031 bp

500 bp

80 bp

554 bp


extracted using the phenol chloroform isoamyl-alcohol and DNAzol

methods. The Gram-negative specific primer set (f4n and r18n) was used.

Results

50

Figure 3.1 shows the results using DNA extracted by the AH and boiling methods.

E. coli were added to each sample prior to extraction, thus, successful DNA amplification

using Gram-negative specific primers would produce a specific 554 bp amplified band. For

the AH method of extraction, the specific 554 bp amplified band was observed in DNA

extracted from the CSF sample (lane 1), the BCB sample (lane 2), and the PF sample (lane

4). The SF (lane 3) and water (lane 5) samples had no amplified product. The boiling

method of extraction had a specific 554 bp band amplified from DNA extracted from the

CSF sample (lane 7) but no amplified products were observed from the BCB (lane 8), SF

(lane 9), PF (lane 10) and water (lane 11) samples.

Figure 3.2 shows the results using DNA extracted by the PCIA and DNAzol

methods. The specific 554 bp product was observed in the CSF (lane 1), SF (lane 3), PF

(lane 4), and water (lane 5) samples extracted by the PCIA method. The BCB sample (lane

2) extracted by PCIA showed no amplified product. The DNAzol method of extraction had

amplifiable DNA of the 554 bp molecular size in samples from CSF (lane 7), SF (lane 9),

PF (lane 10), and water (lane 11). The band in Lane 10 was faintly visible. The BCB sample

(lane 8) showed no amplified product. The positive control for this experiment was the E.

coli DNA template which produced a specific 554 bp band (Fig. 3.1, lane 12). There was no

PCR product in the lane where no DNA was added (Figure 3.2, lane 12).

Results

51

The same DNA protocol was performed using S. aureus cells instead of E. coli cells,

and the DNA was extracted, followed by PCR using the Pan and Gram-positive specific

primers in a duplex PCR. The sample types with positive amplifications were similar when

spiked with S. aureus and with E. coli (e.g. compare the DNA profiles in Figures 3.2 and

3.3).

Figure 3.3 shows the results using DNA extracted by the PCIA and DNAzol

methods. A 1029 bp band (obtained using Pan-specific primers of nf and NR) and a 336 bp

band (obtained using Gram-positive specific primers of f3p and NR) were expected from

positive DNA amplifications. The specific 1029 bp and 336 bp bands were observed in

PCIA-extracted CSF (lane 1) and SF (lane 3) samples, and also in DNAzol-extracted CSF

(lane 7), SF (lane 9), PF (lane 10) and water (lane 11) samples. The PCIA-extracted PF

(lane 4) and water (lane 5) samples had positive amplifications but only the 336 bp band

was observed. BCB samples extracted by both PCIA and DNAzol methods (lanes 2 and 8)

did not produce amplifications. The DNAzol extracted PF samples in lane 10 of Figures 3.2

and 3.3 produced weak bands.

Results

52

Phenol chloroform isoamyl-alcohol method of extraction

Lane 1: Cerebrospinal fluid sample, 1029 bp and 336 bp bands.


Lane 3: Synovial fluid sample, 1029 bp and 336 bp bands.

Lane 4: Peritoneal fluid sample, 336 bp band only.

Lane 5: Water sample, 336 bp band only.


DNAzol method of extraction

Lane 7: Cerebrospinal fluid sample, 1029 bp and 336 bp bands.


Lane 9: Synovial fluid sample, 1029 bp and 336 bp bands.

Lane 10: Peritoneal fluid sample, 1029 bp and 336 bp bands.

Lane 11: Water sample, 1029 bp and 336 bp bands.


Results

53

1 2 3 4 5 6 7 8 9 10 11 12

10 kbp

1031 bp

500 bp

80 bp

1029 bp

336 bp


extracted by the phenol chloroform isoamyl-alcohol and DNAzol methods.

The duplex Pan (nf and NR) and Gram-positive specific primer (f3p and

NR) sets were used.

Results

54

3.1.3 Choosing the Best Extraction Methods

DNA extraction methods for the 4 different sample types were determined using the

Complexity Ranking based on the qualitative analysis of the methods used, as well as the

presence or absence of amplified products from DNA amplification using the extracted

DNA. The DNA extraction methods selected for the different clinical samples are shown in

Table 3.2.

Table 3.2: List of DNA extraction methods selected for the different clinical samples.

Samples Methods chosen for each sample

Cerebrospinal fluid (CSF) Boiling

Blood culture bottle (BCB) Alkali heat-wash (AH)

Synovial fluid (SF) DNAzol

Peritoneal fluid (PF) Alkali heat-wash (AH)

As all the methods were suitable for CSF samples, the decision was made based on

the complexity ranking. The boiling method was chosen as the best method for use on CSF.

For BCB samples, only the AH method was found to be effective for DNA

extraction and removal of inhibitors. The AH method was chosen as the best method to

extract DNA from BCB samples.

SF samples were properly extracted by PCIA and DNAzol methods, and the best

choice among the two was made based on the complexity ranking. The DNAzol method

was therefore chosen as the best method to isolate DNA and remove impurities from the SF

samples.

The DNA in PF samples could be isolated using the AH, PCIA and DNAzol

methods and based on the complexity ranking, the AH method was chosen as the best

method to extract DNA from PF samples.

Results

55

3.1.4 Lowest Detection Limit (CFU/ml) of the Extraction Methods

The lowest detection limit (CFU/ml) of the extraction method is the minimum

number of bacterial cells present in a sample (prior to extraction) that is needed to produce

amplifiable DNA. The detection limit was evaluated using a series of dilutions of S. aureus

and E. coli cells. A series of 1x101 CFU/ml to 1x10

6 CFU/ml of cells were added to the

samples, extracted, and the amplified DNA was observed. Two bands -1029 bp and 336 bp

-are expected from samples containing S. aureus and only the 1029 bp band is expected

from samples containing E. coli.

Figure 3.4 shows the results of DNA amplification using Pan and Gram-positive

specific primers with DNA extracted by the AH method from a spiked PF sample. The

specific 1029 bp and 336 bp amplified bands were present in samples containing 1x106

CFU/ml (lane 1), 1x105 CFU/ml (lane 2), 1x10

4 CFU/ml (lane 3), and 1x10

3 CFU/ml (lane

4) of S. aureus cells. The specific 1029 bp band was observed in samples containing 1x106

CFU/ml (lane 6), 1x105 CFU/ml (lane 7), 1x10

4 CFU/ml (lane 8), and 1x10

3 CFU/ml (lane

9) of E. coli cells. (Note: the 1x101 CFU/ml and 1x10

2 CFU/ml samples did not have any

bands and were excluded from the Figure). There was no amplified product in the lane

containing the DNA blank (lane 10).

Lanes 4 and 9 showed the faintest detectable bands and correspond to a minimum of

1x103 CFU/ml needed for positive DNA amplifications from both Gram-positive (S.

aureus) and Gram-negative (E. coli) organisms. Therefore, the lowest detection limit for the

AH method of extraction on PF was found to be 1x103 CFU/ml.

The boiling method on the CSF sample, the DNAzol method on the SF sample and

the AH method on the BCB sample also showed the lowest detection limit to be 1x103

CFU/ml.

Results

56

Lanes with a dilution series of Staphylococcus aureus added prior to extraction:-

Lane 1: 1x106 CFU/ml, 1029 bp and 336 bp bands.



Lane 4: 1x103 CFU/ml, 1029 bp and 336 bp bands (faintly visible).


Lanes with a dilution series of Escherichia coli added prior to extraction:-

Lane 6: 1x106 CFU/ml, 1029 bp band.

Lane 7: 1x105CFU/ml, 1029 bp band.

Lane 8: 1x104 CFU/ml, 1029 bp band.

Lane 9: 1x103 CFU/ml, 1029 bp band (faintly visible).


Results

57

1 2 3 4 5 6 7 8 9 10

10 kbp

1031 bp

500 bp

80 bp

1029 bp

Results

336 bp

Figure 3.4: Gel electrophoresis of PCR products using the duplex Pan (nf

and NR) and Gram-positive specific primer (f3p and NR) sets to determine

the lowest detection limit (Colony Forming Unit/ml) for the alkali heat-

wash method on peritoneal fluid.

Results

58

3.2 PCR Optimisation

PCR optimisation was carried out by evaluation of a single PCR condition while the

other conditions were kept constant. The presence of a specific amplified band after PCR

indicated successful amplification of the target DNA.

3.2.1 Optimisation of Annealing Temperature

The annealing temperature (Ta) of a PCR reaction is usually 5°C less than the

melting temperature of the primers used and occasionally a compromise was made between

the Ta of the two primers. A difference of less than 5°C between the Tm and Ta results in

stringent conditions that may impair the PCR. Annealing temperatures lower than those

calculated for each PCR may not be stringent enough, thus resulting in the amplification of

non-specific bands.

Optimisation of the annealing temperature for the Gram-positive specific PCR is

shown in Figure 3.5. The Ta tested was at 61, 62, 63 and 64°C. Each set contained

templates with standard amounts of S. aureus DNA as the positive control, E. coli DNA as

the negative control and a DNA blank where no template DNA was added.

The negative control with E. coli DNA (lanes 1, 4, 8 and 11) and the DNA blanks

(lanes 3, 6, 10 and 13) did not yield any products. The PCR mixtures containing S. aureus

template DNA showed amplification of the 336 bp product (lanes 2, 5, 9 and 12). Results

for comparison of annealing temperatures were mostly similar, with Ta=64°C having the

faintest bands. The Ta at 63°C was chosen as the Ta for the Gram-positive specific PCR as

a distinct amplified product was observed.

The annealing temperatures for the other DNA amplification protocols were

evaluated in a similar way. The Ta at 63°C also gave the most optimal results for the Gram-

negative specific primers.

Results

59

Annealing temperature, Ta=61°C

Lane 1: 100 pg of E. coli DNA (negative control), no amplified product.

Lane 2: 100 pg of S. aureus DNA (positive control), 336 bp band.













Lane 12: 100 pg of S. aureus DNA (positive control), 336 bp band (faintly visible).


Results

60

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

336 bp

Figure 3.5: Optimisation of the Gram-positive specific PCR using

different annealing temperatures. DNA from Staphylococcus aureus and

Escherichia coli were used as positive and negative controls respectively.

Results

61

3.2.2 Optimisation for the Number of PCR Cycles

The number of PCR cycles was initially carried out using 30 cycles. The Gram-

negative specific PCR, however, constantly produced a 554 bp amplified product in the

DNA blank despite increasing the stringency of other conditions. This non-specific

amplification was corrected by progressively reducing the number of cycles in the thermal

profile until it was only 26 cycles. Decreasing the cycle number to 26 for the Gram-positive

specific PCR was counter-productive as no bands appeared in the positive control, despite

being present after 30 cycles. For that reason, PCR involving Gram-positive and Gram-

negative specific primers in monoplex were initially optimised using different cycles, 26,

27, and 28 cycles, (Figures 3.6 and 3.7) to prepare for multiplex optimisation. Each set of

reactions had 3 tubes, each respectively containing DNA template in standard amounts of S.

aureus and E. coli DNA and a DNA blank.

In Figures 3.6 and 3.7, the Gram-negative specific PCR produced a 554 bp

amplified product in each reaction containing E. coli DNA as positive control (Figure 3.6,

lane 5; Figure 3.7, lanes 4 and 11), and none from reactions containing the negative control

of S. aureus DNA (Figure 3.6, lane 6; Figure 3.7, lanes 5 and 12) or the DNA blanks

(Figure 3.6, lane 7; Figure 3.7, lanes 6 and 13). Likewise, the Gram-positive specific PCR

produced a 336 bp amplicon in each reaction containing S. aureus DNA as positive control

(Figure 3.6, lane 3; Figure 3.7, lanes 2 and 9), and none in reactions containing the negative

control of E. coli DNA (Figure 3.6, lane 2; Figure 3.7, lanes 1 and 8) or the DNA blanks

(Figure 3.6, lane 4; Figure 3.7, lanes 3 and 10). However, the 336 bp bands obtained in the

PCRs at 26 (Figure 3.6, lane 3) and 27 (Figure 3.7, lane 2) cycles were faint in intensity.

When DNA amplification using the Gram-positive and Gram-negative primers was

carried out for 28 cycles, both the 336 bp band (Figure 3.7, Lane 9) and 554 bp band

(Figure 3.7, lane 11) were distinctly observed. Thus, the 28 cycle reaction was considered

the most optimal number of cycles.

Results

62

1 2 3 4 5 6 7

10 kbp

1031 bp

500 bp

80 bp

554 bp

336 bp

Figure 3.6: Optimisation of DNA amplification for Gram-positive and Gram-

negative specific primers using 26 cycles of PCR. DNA from Escherichia coli

and Staphylococcus aureus were used as controls.

Lane 1: Massruler DNA ladder (Mix).

Gram-positive specific primers

Lane 2: 100 pg E. coli DNA (negative control), no amplified product.

Lane 3: 100 pg S. aureus DNA (positive control), 336 bp band (faintly visible).


Gram-negative specific primers

Lane 5: 100 pg E. coli DNA (positive control), 554 bp band.

Lane 6: 100 pg S. aureus DNA (negative control), no amplified product.


Results

Results

63

27 cycles of PCR



Lane 2: 100 pg of S. aureus DNA (positive control), 336 bp band (faintly visible).



Lane 4: 100 pg of E. coli DNA (positive control), 554 bp band.

Lane 5: 100 pg of S. aureus DNA (negative control), no amplified product.



28 cycles of PCR






Lane 11: 100 pg of E. coli DNA (positive control), 554 bp band.

Lane 12: 100 pg of S. aureus DNA (negative control), no amplified product.


Results

64

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

554 bp

336 bp

Figure 3.7: Optimisation of DNA amplification for Gram-positive and

Gram-negative specific primers using 27 and 28 cycles of PCR. DNA from

Escherichia coli and Staphylococcus aureus were used as controls.

Results

65

3.2.3 Optimisation of MgCl2 and Taq Polymerase Concentrations

The MgCl2 and Taq polymerase concentrations were evaluated simultaneously. In

Figures 3.8, 3.9 and 3.10, a multiplex PCR, containing Pan, Gram-positive and Gram-

negative specific primers, was optimised for MgCl2 and Taq polymerase concentrations. A

series of Taq polymerase at 0.6, 0.8 and 1.0 Units were compared against a series of MgCl2

concentrations of 1.6, 2.0, 2.4 and 2.8 mM. Each of the evaluation sets consisted of E. coli,

and S. aureus DNA as controls and a DNA blank. The expected results are a 554 bp and a

1029 bp band for reactions containing E. coli DNA, and a 336 bp and 1029 bp band for

reactions containing S. aureus DNA.

However, a 554 bp band appeared in reactions containing S. aureus (Figures 3.8,

lanes 2, 5, 9 and 12; Figure 3.9, lanes 2, 5, and 12; and Figure 3.10, lanes 5, 9, and 12). No

bands were observed in the DNA blanks where no DNA template were added (Figures 3.8-

3.10, lanes 3, 6, 10 and 13).

Figure 3.8 shows the results of DNA amplifications of the multiplex PCR using 0.6

units of Taq polymerase and various concentrations of MgCl2. In DNA amplifications using

2.4 (lanes 8 and 9) and 2.8 mM (lanes 11 and 12) of MgCl2, the 1029 bp bands were absent,

but the 554 bp band was present in lanes containing E. coli DNA (lanes 8 and 11), and the

336 bp band faintly visible in lanes containing S. aureus DNA (lanes 9 and 12).

Amplifications using 1.6 mM of MgCl2 with E. coli DNA showed distinct 1029 bp and 554

bp bands (lane 1), but the amplification using S. aureus DNA showed faintly visible 1029

bp and 336 bp bands (lane 2). The amplifications using 2.0 mM of MgCl2 produced the

1029 bp and 554 bp bands in the lane containing E. coli DNA(lane 4), and the 1029 bp and

336 bp bands in the lane containing S. aureus DNA(lane 5), but all the bands were faint in

intensity.

Results

66

1.6 mM MgCl2

Lane 1: 100 pg of E. coli DNA, 1029 bp and 554 bp bands.

Lane 2: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands (faintly visible).


2.0 mM MgCl2

Lane 4: 100 pg of E. coli DNA, 1029 bp and 554 bp bands (faintly visible).

Lane 5: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands (faintly visible).



2.4 mM MgCl2

Lane 8: 100 pg of E. coli DNA, 554 bp band.

Lane 9: 100 pg of S. aureus DNA, 554 bp and 336 bp bands (faintly visible).


2.8 mM MgCl2




Results

67

Figure 3.8: Optimisation of DNA amplification protocols for Pan, Gram-

positive and Gram-negative specific primers using 0.6 units of Taq

polymerase and various concentrations of MgCl2. DNA from Escherichia

coli and Staphylococcus aureus were used as controls.

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

554 bp

336 bp

1029 bp

Results

68

1.6 mM MgCl2


Lane 2: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands.


2.0 mM MgCl2


Lane 5: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands.



2.4 mM MgCl2


Lane 9: 100 pg of S. aureus DNA, no amplified product.


2.8 mM MgCl2




Results

69





1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

554 bp

336 bp

1029 bp

Results

70

1.6 mM MgCl2 Lane 1: 100 pg of E. coli DNA, no amplified product. Lane 2: 100 pg of S. aureus DNA, no amplified product. Lane 3: DNA blank, no amplified product. 2.0 mM MgCl2 Lane 4: 100 pg of E. coli DNA, ≈3000 bp, 1029 bp and 554 bp bands. Lane 5: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands. Lane 6: DNA blank, no amplified product. Lane 7: Massruler DNA ladder (Mix) 2.4 mM MgCl2 Lane 8: 100 pg of E. coli DNA, 1029 bp and 554 bp bands (faintly visible). Lane 9: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands. Lane 10: DNA blank, no amplified product. 2.8 mM MgCl2 Lane 11: 100 pg of E. coli DNA, 1029 bp and 554 bp bands. Lane 12: 100 pg of S. aureus DNA, 1029 bp, 554 bp and 336 bp bands. Lane 13: DNA blank, no amplified product.

Results

71





1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

554 bp 336 bp

1029 bp

Results

72

Figure 3.9 shows the results of DNA amplifications of the multiplex PCR using 0.8

units of Taq polymerase and various concentrations of MgCl2. Amplifications using 1.6

(lanes 1 and 2) and 2.0 mM (lanes 4 and 5) of MgCl2 had the expected 1029 bp and 554 bp

bands in lanes containing E. coli DNA (lanes 1 and 4), and the 1029 bp and 336 bp bands in

lanes containing S. aureus DNA (lanes 2 and 5). For the amplifications using 2.4 mM of

MgCl2, the 1029 bp and 554 bp bands were present in the lane containing E. coli DNA (lane

8) but no bands were amplified in the lane containing S. aureus DNA(lane 9). For the

amplifications using 2.8 mM of MgCl2, the 336 bp band was only faintly visible in the lane

containing the S. aureus DNA (lane 12), and the 554 bp band was strongly amplified in the

lane containing E. coli DNA (lane 11), but the expected 1029 bp band was not present in

both lanes.

Figure 3.10 shows the results of DNA amplifications of the multiplex PCR using

1.0 units of Taq polymerase and various concentrations of MgCl2. No amplified products

were obtained when 1.6 mM of MgCl2 was used (lanes 1 and 2). Amplifications using 2.0

mM MgCl2 had distinct 1029 bp and 554 bp bands in the lane containing E. coli DNA (lane

4), but a 3000+ bp non-specific band was also present. The lane containing S. aureus DNA

for the 2.0 mM MgCl2 concentration had 1029 bp and 336 bp bands (lane 5). The S. aureus

DNA template obtained 1029 bp and 336 bp bands using 2.4 mM of MgCl2 (lane 9), but the

amplification using E. coli template had 1029 bp and 554 bp bands that were faint in

intensity (lane 8). The 2.8 mM MgCl2 amplification had visible 1029 bp and 554 bp bands

in the lane containing E. coli DNA (lane 11), and 1029 bp and 336 bp bands in the lane

containing S. aureus DNA (lane 12).

Results

73

Thus, on analysis of the protocols using different Taq polymerase and MgCl2

concentrations, there were three reaction sets that produced distinct amplified bands, the

reactions containing 1.6 mM (Figure 3.9, lanes 1 and 2) and 2.0 mM (Figure 3.9, lanes 4

and 5) MgCl2 with 0.8 Units of Taq polymerase, and the reactions containing 2.8 mM

MgCl2 with 1.0 Unit of Taq polymerase (Figure 3.10, lanes 12 and 13). The set containing

1.0 Unit of Taq polymerase (Figure 3.10, lanes 12 and 13) used more consumables

compared to the 0.8 Unit sets (Figure 3.9) and had a similar outcome, thus, the 1.0 unit

concentration was not chosen for future experiments due to the higher costs. From the

remaining two sets, the PCR protocol requiring 1.6 mM of MgCl2 was not considered as it

had a slight smearing in the lane containing E. coli DNA (Figure 3.9, lane 1).

Thus, the 2.0 mM MgCl2 and 0.8 Units of Taq polymerase (Figure 3.9, lanes 4 and

5) were selected as the optimal concentrations to be used for the Pan, Gram-positive and

Gram-negative specific multiplex, and also in the duplex of Pan and Gram-positive specific

primers. This optimisation strategy was repeated in determining the Taq polymerase and

MgCl2 concentrations in the other PCR reactions.

Results

74

3.2.4 Optimisation of Primer Concentration

The concentrations of the various primers in the Pan and Gram-positive specific

duplex PCR were determined by first varying the concentrations of the nf and NR primers,

followed by the concentration of the f3p primer. Each set of reactions contained the DNA

templates of S. aureus and E. coli DNA as positive and negative controls. In addition, a

DNA blank with no addition of DNA was included to check for DNA contamination. The

expected results were a 1029 bp band and a 336 bp band in lanes from PCR reactions

containing S. aureus DNA. Lanes with E. coli DNA were expected to amplify only the 1029

bp Pan specific amplified product.

Figures 3.11 and 3.12 show the results from DNA amplifications using varying

concentrations of nf and NR primers. The Pan and Gram-positive specific duplex PCR

produced a 1029 bp amplified product in each reaction containing E. coli DNA (Figures

3.11 and 3.12, lanes 1, 4, 8, and 11). The expected 1029 bp and 336 bp bands were present

in lanes containing S. aureus (Figures 3.11 and 3.12, lanes 2, 5, 9, and 12). However, the

1029 bp band amplified from S. aureus DNA in lanes 2 and 12 of Figure 3.11 were faint in

intensity. All lanes with the DNA blanks did not show any amplified bands (Figures 3.11

and 3.12, lanes 3, 6, 10 and 13).

Results from all eight optimisation reactions showed the expected bands but with

varying intensities of the amplified DNA. A non-specific band of 700+ bp was present in

the lanes amplified with S. aureus DNA (Figures 3.11 and 3.12, lanes 2, 5, 9 and 12). This

non-specific band was not present when the Pan (Figure 3.14, Lanes 7-11) and Gram-

positive (Figure 3.7, lane 9) specific primers were in monoplex reactions.

Results

75

0.1 µM nf, 0.2 µM NR Lane 1: 100 pg of E. coli DNA, 1029 bp band. Lane 2: 100 pg of S. aureus DNA, 1029 bp (faintly visible) and 336 bp bands. Lane 3: DNA blank, no amplified product. 0.1 µM nf, 0.4 µM NR Lane 4: 100 pg of E. coli DNA, 1029 bp band. Lane 5: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 6: DNA blank, no amplified product. Lane 7: Massruler DNA ladder (Mix) 0.2 µM nf, 0.2 µM NR Lane 8: 100 pg of E. coli DNA, 1029 bp band. Lane 9: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 10: DNA blank, no amplified product. 0.2 µM nf, 0.3 µM NR Lane 11: 100 pg of E. coli DNA, 1029 bp band. Lane 12: 100 pg of S. aureus DNA, 1029 bp (faintly visible) and 336 bp bands. Lane 13: DNA blank, no amplified product.

Results

76

Results

Figure 3.11: Optimisation of DNA amplification for Pan and Gram-

positive specific primers using different nf and NR primer concentrations.

DNA from Escherichia coli and Staphylococcus aureus were used as

controls.

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

336 bp

1029 bp Non-specific band

Results

77

0.2 µM nf, 0.4 µM NR Lane 1: 100 pg of E. coli DNA, 1029 bp band. Lane 2: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 3: DNA blank, no amplified product. 0.3 µM nf, 0.2 µM NR Lane 4: 100 pg of E. coli DNA, 1029 bp band. Lane 5: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 6: DNA blank, no amplified product. Lane 7: Massruler DNA ladder (Mix) 0.3 µM nf, 0.3 µM NR Lane 8: 100 pg of E. coli DNA, 1029 bp band. Lane 9: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 10: DNA blank, no amplified product. 0.3 µM nf, 0.4 µM NR Lane 11: 100 pg of E. coli DNA, 1029 bp band. Lane 12: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 13: DNA blank, no amplified product.

Results

78

Results


positive specific primers using different nf and NR primer concentrations.

DNA from Escherichia coli and Staphylococcus aureus were used as

controls.

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

336 bp

1029 bp

Non-specific band

Results

79

The 0.2 µM nf and 0.4 µM NR primer concentration set (Figure 3.12, lanes 1 and 2)

was chosen as it had the most distinct 336 bp band, and the 1029 bp band in the lane

containing E. coli and S. aureus DNA were almost equal in intensity and had the least

amount of smearing.

Next, an attempt was made to remove the presence of the 700+ non-specific band by

comparing a series of concentrations of f3p primers (Figure 3.13) with the primer

concentrations for nf and NR at 0.2 µM and 0.4 µM respectively.

Figure 3.13 shows the results from DNA amplifications using varying

concentrations of the f3p primer. The Pan and Gram-positive specific duplex PCR produced

a 1029 bp amplified product in each reaction containing E. coli DNA (lanes 1, 4, 8, and 11)

and the expected 1029 bp and 336 bp bands in lanes containing S. aureus DNA (lanes 2, 5,

9, and 12). All lanes containing the DNA blanks did not show any amplified bands (lanes 3,

6, 10 and 13). The sets containing S. aureus DNA with 0.2 µM (lane 5), 0.3 µM (lane 9),

and 0.4 µM (lane 12) of f3p still amplified the 700+ bp non-specific band. The non-specific

band was not present in the reaction containing 0.1 µM of f3p (lane 2). In addition, the 1029

bp amplified product was distinct when the f3p primer was used at 0.1 µM (lanes 1 and 2).

The primer concentrations chosen for nf, p3f and NR in the Pan and Gram-positive

specific duplex were 0.2 µM, 0.1 µM and 0.4 µM respectively. Determination for primer

concentrations in other reactions was conducted in a similar manner.

Results

80

0.1 µM f3p Lane 1: 100 pg of E. coli DNA, 1029 bp band. Lane 2: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 3: DNA blank, no amplified product. 0.2 µM f3p Lane 4: 100 pg of E. coli DNA, 1029 bp band. Lane 5: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 6: DNA blank, no amplified product. Lane 7: Massruler DNA ladder (Mix) 0.3 µM f3p Lane 8: 100 pg of E. coli DNA, 1029 bp band. Lane 9: 100 pg of S. aureus DNA, 1029 bp and 336 bp bands. Lane 10: DNA blank, no amplified product. 0.4 µM f3p Lane 11: 100 pg of E. coli DNA, 1029 bp band. Lane 12: 100 pg of S. aureus DNA, 1029 bp (faintly visible) and 336 bp bands. Lane 13: DNA blank, no amplified product.

Results

81


positive specific primers using different f3p primer concentrations. DNA

from Escherichia coli and Staphylococcus aureus were used as controls.

1 2 3 4 5 6 7 8 9 10 11 12 13

10 kbp

1031 bp

500 bp

80 bp

336 bp

1029 bp

Non-specific band

Results

82

3.2.5 Multiplex Optimisation

The PCR reactions were at first set up as single PCR reactions with just one primer

pair per reaction. The conditions of each of the monoplexes were adjusted to be as similar

as possible, in order to make manipulation easier when converted to multiplex. The primers

of the Pan, Gram-positive and Gram-negative specific PCR reactions were then added

together in stages to form a multiplex.

Only the Pan and Gram-positive specific primers were successfully included in a

duplex PCR reaction. Attempts at including the Gram-negative primers into a multiplex

with the other primers failed, as the PCR using S. aureus (a Gram-positive organism) DNA

constantly produced the 554 bp bands in areas targeted by Gram-negative primers (e.g.

Figures 3.8, lanes 2, 5, 9 and 12; Figure 3.9, lanes 2, 5, and 12; and Figure 3.10, lanes 5, 9,

and 12). Despite making the conditions more stringent, this non-specific amplification was

still present.

Because the results were not specific in the multiplex, the Gram-negative specific

primers were separated from the Gram-positive and Pan specific primers. When attempting

to include the Gram-negative and Pan specific primers into the same reaction, non-specific

amplification occurred.

To determine the Gram-typing for bacteria, both the duplex of Pan and Gram-

positive specific reactions and a monoplex of Gram-negative reaction were run concurrently

in separate tubes.

Results

83

3.3 Optimisation of PCR Mixtures and Thermal Profiles

3.3.1 Gram-positive Specific PCR

The optimized monoplex for the Gram-positive specific DNA amplification consists

of 10x buffer, 200 µM dNTPs, 0.2 µM each of primers NR and f3p, 1.5 mM MgCl2, 0.5

Units Taq polymerase, 100 pg DNA template, and sterile double-distilled water to make up

a total volume of 25 µl per reaction tube (Table 3.3). The reaction was subjected to an

initial denaturation cycle at 94°C for 5 min; 26 cycles of denaturation at 94°C for 30s,

annealing at 63°C for 30s and extension at 72°C for 1 min 20s. A further extension of 72°C

for 4 min was then carried out (Table 3.3). The thermal cycler was programmed to be at

20°C for 2 hours after DNA amplification was completed. The PCR tubes were removed

and kept at 4°C before the 2 hour time interval ended.

Table 3.3: The PCR mixture and thermal profile for the Gram-positive specific DNA

amplification.

PCR mixture for Gram-positive specific DNA

amplification

Thermal profile for Gram-positive specific DNA

amplification

Components Final Conc. Temp Time Cyling

10X buffer 1x 94°C 5 min 1 x

dNTPs 200 µM 94°C 30s

Primer NR 0.2 µM 63°C 30s

Primer f3p 0.2 µM 72°C 1 min 20s

26x

MgCl2 1.5 mM 72°C 4 min 1x

Taq polymerase 0.5 Units 20°C 2 hours 1x

Total Vol 25 µl

Results

84

3.3.2 Pan-bacterial Specific PCR

The optimized monoplex for the Pan-bacterial specific DNA amplification (Table

3.4) consists of 10x buffer, 200 µM dNTPs, 0.4 µM each of primers NR and nf, 1.5 mM

MgCl2, 1 Unit Taq polymerase, 100 pg DNA template, and sterile double-distilled water to

make up a total volume of 25 µl per reaction tube (Table 3.4) The reaction was subjected to

an initial denaturation cycle at 94°C for 5 min; 26 cycles denaturation at 94°C for 30s,

annealing at 63°C for 30s and extension at 72°C for 1 min 20s. A further extension of 72°C

for 4 min was then carried out (Table 3.4).

Table 3.4: The PCR mixture and thermal profile for the Pan-bacterial specific DNA

amplification.

PCR mixture for Pan specific DNA amplification

Thermal profile for Pan specific DNA amplification





Primer nf 0.4 µM 72°C 1 min 20s

26x


Taq polymerase 1 Unit 20°C 2 hours 1x

Total Vol 25 µl

Results

85

3.3.3 Pan and Gram-positive Specific Duplex PCR

The optimized duplex PCR for the Pan and Gram-positive specific DNA

amplification consists of 10x buffer, 200 µM dNTPs, 0.4 µM primer NR, 0.1 µM primer

f3p, 0.2 µM primer nf, 2.0 mM MgCl2, 0.8 Units Taq polymerase, 100 pg DNA template,

and sterile double-distilled water to make up a total volume of 25 µl per reaction tube

(Table 3.5). The reaction was subjected to an initial denaturation cycle at 94°C for 5 min;

26 cycles of denaturation at 94°C for 30s, annealing at 63°C for 30s and extension at 72°C

for 1 min 20s. A further extension of 72°C for 4 min was then carried out (Table 3.5).

Table 3.5: The PCR mixture and thermal profile for the Pan and Gram-positive specific primers in a Duplex PCR.

PCR mixture for Pan and Gram-positive specific primers (Duplex PCR)

Thermal profile for Pan and Gram-positive specific primers (Duplex PCR)





Primer f3p 0.1 µM 72°C 1 min 20s

26x

Primer nf 0.2 µM 72°C 4 min 1x

MgCl2 2.0 mM 20°C 2 hours 1x

Taq polymerase 0.8 Unit

Total Vol 25 µl

Results

86

3.3.4 Gram-negative Specific PCR

The optimized monoplex for the Gram-negative specific DNA amplification

consists of 10x buffer, 200 µM dNTPs, 0.1 µM each of primers r18n and f4n, 1.5 mM

MgCl2, 0.5 Units Taq polymerase, 100 pg DNA template, and sterile double-distilled water

to make up a total volume of 25 µl per reaction tube (Table 3.6). The reaction was

subjected to an initial denaturation cycle at 94°C for 5 min; 26 cycles of denaturation at

94°C for 30s, annealing at 63°C for 30s and extension at 72°C for 1 min 20s. A further

extension of 72°C for 4 min was then carried out (Table 3.6).

Table 3.6: The PCR mixture and thermal profile for the Gram-negative specific DNA

amplification.

PCR mixture for Gram-negative specific DNA

amplification

Thermal profile for Gram-negative specific DNA

amplification




Primer r18n 0.1 µM 63°C 30s

Primer f4n 0.1 µM 72°C 1 min 20s

26x


Taq polymerase 0.5 Unit 20°C 2 hours 1x

Total Vol 25 µl

Results

87

3.4 PCR Sensitivity

The sensitivity of each of the PCR reactions was determined by subjecting each of

them to a series of increasingly diluted DNA templates during DNA amplification. The

minimum template concentration needed to produce an amplified product was considered to

be the lowest detection limit of the PCR. Both E. coli and S. aureus DNA were separately

used as templates, to represent Gram-negative and Gram-positive organisms respectively.

Figure 3.14 shows the results of DNA amplification using the Pan specific primers.

A specific 1029 bp band was expected and this was observed in the lanes containing 10 ng

(lane 1), 1 ng (lane 2), 100 pg (lane 3), 10 pg (lane 4) and 1 pg (lane 5) of E. coli DNA, and

lanes containing 10 ng (lane 7), 1 ng (lane 8), 100 pg (lane 9), 10 pg (lane 10) and 1 pg

(lane 11) of S. aureus DNA. DNA amplification using 1 pg of DNA (lanes 5 and 11)

produced faint bands. No bands were observed in lane 12, where DNA template was not

added (DNA blank). The lowest detection limit was 1 pg of both E. coli and S. aureus DNA

for the Pan specific PCR.

Figure 3.15 shows the results of DNA amplification using the Pan and Gram-

positive specific primers in a duplex with different E. coli DNA concentrations. A specific

1029 bp band was expected and this was observed in the lanes containing 10 ng (lane 1), 1

ng (lane 2), 100 pg (lane 3), and 10 pg (lane 4) of E. coli DNA. DNA amplification using

10 pg of DNA (lane 4) produced a faint band. No bands were observed in lanes containing 1

pg (lane 6), 100 fg (lane 7), 10 fg (lane 8) and in the DNA blank (lane 9). The lowest

detection limit was 10 pg of E. coli DNA for the Pan and Gram-positive specific duplex

PCR.

Results

88

Results

Figure 3.14: Gel electrophoresis of DNA products amplified using the Pan

specific primers with different DNA concentrations.

Escherichia coli DNA

Lane 1: 10 ng, 1029 bp band.


Lane 3: 100 pg, 1029 bp band.


Lane 5: 1 pg, 1029 bp band (faintly visible).


Staphylococcus aureus DNA







1 2 3 4 5 6 7 8 9 10 11 12

10 kbp

1031 bp

500 bp

80 bp

1029 bp

Results

89

Results


and Gram-positive specific primers in a duplex PCR with different

Escherichia coli DNA concentrations.

Lane 1: Massruler DNA ladder (Mix).

E. coli DNA





Lane 6: 1 pg, no amplified product.

Lane 7: 100 fg, no amplified product.



1 2 3 4 5 6 7 8 9

10 kbp

1031 bp

500 bp

80 bp

1029 bp

Results

90


positive specific primers in a duplex with S. aureus DNA. Specific 1029 bp and 335 bp

bands were expected and this was observed in the lanes containing 10 ng (lane 2) and 1 ng

(lane 3) of S. aureus DNA. DNA amplification using 100 pg (lane 4) and 10 pg (lane 5) of

DNA only had the 336 bp band. No bands were observed in lanes containing 1 pg (lane 6)

and in the DNA blank (lane 7). The lowest detection limit was 10 pg of S. aureus DNA for

the Gram-positive specific primers and 1 ng for the Pan specific primers in the duplex PCR.

Figure 3.17 shows the results of DNA amplification using the Gram-negative

specific primers with different E. coli DNA concentrations. A specific 554 bp band was

expected and this was observed in the lanes containing 10 ng (lane 2), 1 ng (lane 3), 100 pg

(lane 4), and 10 pg (lane 5) of E. coli DNA. No bands were observed in lanes containing 1

pg (lane 6), 100 fg (lane 7), 10 fg (lane 8) and in the DNA blank (lane 9). The lowest

detection limit was 10 pg of E. coli DNA for the Gram-negative specific monoplex PCR.

Results

91

Results


and Gram-positive specific primers in a duplex PCR with different

Staphylococcus aureus DNA concentrations.


S. aureus DNA

Lane 2: 10 ng, 1029 bp and 336 bp bands.

Lane 3: 1 ng, 1029 bp and 336 bp bands.

Lane 4: 100 pg, 336 bp band only.

Lane 5: 10 pg, 336 bp band only.



1 2 3 4 5 6 7

10 kbp

1031 bp

500 bp

80 bp

336 bp

1029 bp

Results

92

Results

Figure 3.17: Gel electrophoresis of DNA products amplified using the

Gram-negative specific primers with different Escherichia coli DNA

concentrations.


E. coli DNA









1 2 3 4 5 6 7 8 9

10 kbp

1031 bp

500 bp

80 bp

554 bp

Results

93

3.5 PCR Specificity

The PCR specificity in this study not only referred to the ability of the particular

PCR to amplify the proper target sequence, but also to its ability to infer the Gram-type of

the organism tested. In addition, DNA amplification should not occur with the negative

control DNA. DNA was extracted from a range of pure culture organisms of different

Gram-types (Table 3.7) and was used to test the specificity of the different PCRs. The list

of Gram-positive organisms includes two aerobic cocci - Staphylococcus aureus and

Enterococcus faecalis; and the aerobic rod of a Corynebacterium sp. The list of Gram-

negative organisms includes the aerobic cocci of Neisseria gonorrhoeae; the aerobic,

fastidious, glucose-nonfermenting rods of Haemophilus influenzae and Acinetobacter

baumanii; the glucose-fermenting, Enterobacteriaceae rods of Klebsiella pneumoniae,

Enterobacter sp., Escherichia coli, and Proteus sp.; and the glucose-nonfermenting rods of

Stenotrophonomas maltophilia. A fungal organism, Cryptococcus neoformans, was also

evaluated as a negative control (Table 3.7).

Pan specific primers should amplify a 1029 bp band in all bacteria but not in non-

bacterial organisms. Gram-negative specific primers should amplify a 554 bp band from

Gram-negative organisms only, and Gram-positive specific primers should amplify only a

336 bp band from Gram-positive organisms. If a 554 bp band was amplified from the

Gram-negative specific PCR, and only a 1029 bp band was amplified using the Pan specific

primers in the duplex PCR (with no 336 bp band amplified), it is expected that the DNA

template was from a Gram-negative organism. Likewise, if 1029 bp and 336 bp bands were

amplified by the Pan and Gram-positive specific PCR and no band was obtained by the

Gram-negative specific PCR, it is expected that the DNA template was from a Gram-

positive organism.

Table 3.7: The list of organisms used in this study confirmed by culture, Gram-stain, and DNA amplification results.



Pan specific primers

1 PC 041

Staphylococcus aureus √ X √ Gram-type

positive

2 PC 022

Enterococcus faecalis √ X √ Gram-type

positive

3 PC 024

Corynebacterium sp.

Aerobic, Gram-positive rods X X √

Bacterial, possible Gram-type positive

4 PC 021

Neisseria gonorrhoeae

Aerobic, Gram-negative cocci X √ √ Gram-type

negative

5 PC 017

Haemophilus influenzae X √ √ Gram-type

negative

6 PC 032

Acinetobacter baumannii X √ √ Gram-type

negative

7 PC 018

Klebsiella pneumoniae X √ √ Gram-type

negative

8 PC 014 Enterobacter sp. X √ √ Gram-type

negative

9 PC 039 Escherichia coli X √ √ Gram-type

negative

10 PC 015 Proteus sp. X √ √ Gram-type

negative

11 PC 016

Stenotrophomonas maltophila

Glucose-nonfermenting, Gram-negative rods

X √ √ Gram-type negative

12 PC 046

Cryptococcus neoformans Fungi X X X Non-bacterial

Note: √ - indicates the presence of a PCR product, X - indicates the absence of a PCR product

Presence of PCR product using:

Gram-type by DNA

amplification

Aerobic, Gram-positive cocci

Aerobic, fastidious, glucose-nonfermenting, Gram-negative rods

Glucose-fermenting, Gram-negative, Enterobacteriaceae rods

No. Lab No. Organism Name Gram-type by

culture

94

Results

95


positive specific primers on DNA obtained from the various organisms. The 1029 bp Pan

specific band was observed in all the lanes containing bacteria (lanes 1-6 and 8-12), but not

in the lane containing fungal DNA (lane 13). The 336 bp Gram-positive specific band was

observed in the lanes containing S. aureus DNA (lane 1, faintly visible) and E. faecalis

(lane 2). DNA from the Gram-positive Corynebacterium sp. bacteria did not produce a 336

bp band. DNA from all the Gram-negative bacteria and from Cyptococcus neoformans also

did not produce the 336 bp band (lanes 4-13). The DNA blank, where no DNA was added

produced no bands (lane 14).

Figure 3.19 shows the results of DNA amplification using the Gram-negative

specific primers on DNA from the same range of organisms. The expected 554 bp specific

band was observed in lanes containing Gram-negative organisms (lanes 4-6 and 8-12). The

lanes containing DNA from Gram-positive organisms (lanes 1-3) and the fungal organism

(lane 13) had no amplified products. The DNA blank, where no DNA was added produced

no bands (lane 14).

The results of the PCR amplifications in Figures 2.18 and 2.19 are shown in Table

3.7. The DNA from the Gram-positive S. aureus (No. 1) and E. faecalis (No. 2) were

amplified by Pan and Gram-positive specific primers, but not by Gram-negative specific

primers. This inferred that the organisms in the pure culture were Gram-type positive, and

this concurred with the Gram-stain. The DNA from the aerobic, Gram-positive rod of

Corynebacterium sp. (No. 3) was not amplified by Gram-negative or Gram-positive

primers, but was amplifiable by Pan specific primers. The Gram-type of the organism could

not be positively determined by PCR, but the DNA likely originated from a bacterial

organism and was possibly a Gram-positive organism, as no DNA was amplified from the

Gram-negative specific PCR.

Results

96

10 kbp

1031 bp

500 bp

80 bp

336 bp

1029 bp

Figure 3.18: Gel electrophoresis of DNA products amplified using the Pan and

Gram-positive specific primers with template DNA from various Gram-positive and

Gram-negative organisms.

Lane 1: Staphylococcus aureus DNA, 1029 bp and 336 bp bands (faintly visible).

Lane 2: Enterococcus faecalis DNA, 1029 bp and 336 bp bands.

Lane 3: Corynebacterium sp. DNA, 1029 bp band only.

Lane 4: Neisseria gonorrhoeae DNA, 1029 bp band.

Lane 5: Haemophilus influenzae DNA, 1029 bp band.

Lane 6: Acinetobacter baumannii DNA, 1029 bp band.


Lane 8: Klebsiella pneumoniae DNA, 1029 bp band.

Lane 9: Enterobacter sp. DNA, 1029 bp band.

Lane 10: Escherichia coli DNA, 1029 bp band.

Lane 11: Proteus sp. DNA, 1029 bp band.

Lane 12: Stenotrophomonas maltophila DNA, 1029 bp band.

Lane 13: Cryptococcus neoformans DNA, no amplified product.


1 2 3 4 5 6 7 8 9 10 11 12 13 14

Results

97

10 kbp

1031 bp

500 bp

80 bp

554 bp

Figure 3.19: Gel electrophoresis of DNA products amplified using the Gram-

negative specific primers with template DNA from various Gram-positive and

Gram-negative organisms.

Lane 1: Staphylococcus aureus DNA, no amplified product.

Lane 2: Enterococcus faecalis DNA, no amplified product.

Lane 3: Corynebacterium sp. DNA, no amplified product.

Lane 4: Neisseria gonorrhoeae DNA, 554 bp band.

Lane 5: Haemophilus influenzae DNA, 554 bp band.

Lane 6: Acinetobacter baumannii DNA, 554 bp band.


Lane 8: Klebsiella pneumoniae DNA, 554 bp band.

Lane 9: Enterobacter sp. DNA, 554 bp band.

Lane 10: Escherichia coli DNA, 554 bp band.

Lane 11: Proteus sp. DNA, 554 bp band.

Lane 12: Stenotrophomonas maltophila DNA, 554 bp band.

Lane 13: Cryptococcus neoformans DNA, no amplified product.


1 2 3 4 5 6 7 8 9 10 11 12 13 14

Results

98

The DNA from the Gram-negative organisms of N. gonorrhoeae (No. 4), H.

influenzae (No. 5), A. baumanii (No. 6), K. pneumoniae (No. 7), Enterobacter sp. (No. 8),

E. coli (No. 9), Proteus sp. (No. 10), and S. maltophilia (No. 11) were found to be

amplifiable by Gram-negative and Pan specific primers, but not by Gram-positive primers

(Table 3.7). The results inferred that all these organisms were Gram-type negative, and this

concurred with the Gram-stain of the culture type.

The DNA from the negative control fungal organism of C. neoformans (No 12) did

not have any amplification from the Gram-negative specific PCR, and the Pan and Gram-

positive specific duplex. The results inferred that the organism was not of bacterial origin

and this concurred with the results of the culture type.

To summarize, the duplex PCR of Pan and Gram-positive specific primers and the

monoplex of Gram-negative specific primers were able to Gram-type the DNA extracted

from the pure culture samples in the study, except for one out of the 12 samples tested.

Specificity was high for the Pan-bacterial specific primers, with all the samples being

correctly identified. The Gram-positive specific primers were not able to correctly amplify

one Gram-positive organism – Corynebacterium sp. The PCR protocol should be repeated

with another pure culture of a Corynebacterium sp. to confirm PCR specificity. Gram-

negative specific primers amplified all DNA isolated from Gram-negative bacteria.

Results

99

3.6 Sequencing and Analyses of Pure Cultures

Sequencing was performed using pure cultures obtained from the Diagnostic

Microbiology Laboratory, UMMC (Section 2.1.2). The objective was to determine if

bacterial identification by analyses of sequencing results (Section 2.5.4) matched the

culture results, or to what extent they differed. As the sequencing initially involved the use

of DNA from known organisms (the pure culture samples), this gave baseline information

that was later useful when working with DNA from unknown organisms. Examples of

electropherograms from DNA sequencing of PCR products from pure culture samples can

be found in Appendix D. Results of BLAST and RDP-II SeqMatch analyses on the 16S

rDNA PCR sequences obtained from pure cultures are shown in Table 3.8 at the end of this

section.

3.6.1 Staphylococcus aureus

The DNA from the pure culture of Staphylococcus aureus (PC041) was found to

have a 99.7% similarity match with either S. aureus, or S. croceolyticus after a 293 bp

sequence was studied using BLAST analysis. Using the Classifier, the sequence was found

to belong 100% to the order Bacillales, with an 86% chance of belonging to the genus

Staphylococcus. Both the type options in SeqMatch showed a high clustering of results

within the species S. aureus. It is very likely then, that the DNA sequences found within

PC041 is that of Staphylococcus aureus.

3.6.2 Enterococcus faecalis

The sequenced 287 bp DNA from the Enterococcus faecalis (PC022) culture was

studied using BLAST analysis and found to be 99.7% similar to DNA from Enterococcus

Results

100

faecalis. The RDP-II Classifier found it to be probably (92%) of the genus Enterococcus

and definitely (100%) of the Order Lactobacillales. SeqMatch results showed only E.

faecalis as a possible organism with a similarity score of 0.965 but type-only analysis

included other species types but with a score below 0.920. Therefore, because of the high

clustering of the species in BLAST and RDP-II (type and non-type) analysis, it is very

likely that the DNA found in PC022 is that of E. faecalis. Identity by sequencing is similar

to that by culture.

3.6.3 Corynebacterium sp.

PC024 was found to be Corynebacterium sp. by culture. The sequenced DNA 740

bp fragment studied using BLAST analysis matched those of Corynebacterium jeikeium

with a 99.5% similarity. The RDP-II Classifier concurred with this analysis and the

sequence was found to be 100% in agreement with the genus Corynebacterium. The

similarity score using the SeqMatch was a little lower as it was only 0.908 for the species

Corynebacterium jeikeium. However, a high clustering of results for that species and a more

than 99% match using BLAST shows that DNA from PC024 is likely from C. jeikeium. The

result by sequencing provides identification to the species level.

3.6.4 Neisseria gonorrhoeae

The DNA from PC021 showed an across the board similarity with the species

Neisseria gonorrhoeae. It had a 100% similarity when the 484 bp sequence was studied

using BLAST analysis, and 1.000 similarity match using the RDP-II. It also had a full

match with the genus Neisseria. The organism was clearly identified by sequencing analysis

as N. gonorrhoeae and matches the identity obtained via culture.

Results

101

3.6.5 Haemophilus influenzae

The DNA from the Haemophilus influenzae culture (PC017) also showed an across

the board full match with BLAST and SeqMatch. However, the 498 bp sequence only had a

full match with the family Pasteurellaceae and a partial match (93%) to the genus

Haemophilus. Despite that, the full match identifies the DNA as belonging to the species H.

influenzae. The result is therefore similar to those determined by culture.

3.6.6 Acinetobacter baumanii

PC032 was identified as Acinetobacter baumanii by culture methods. Results from

BLAST analysis of the 506 bp sequenced showed a 100% similarity with either A.

baumanii or A. calcoaceticus. Classification using the RDP-II tool also showed a highly

probable (100%) match to the genus Acinetobacter. However, while SeqMatch showed a

0.992 match with A. baumanii and A. calcoaceticus, analysis using type strains only

included other species names belonging to the same genus but with a similarity score below

0.911, including the type strain of A. baumanii at 0.865. The clustering of results and

matches above 99% shows that PC032 is either A. baumanii or A. calcoaceticus.

3.6.7 Klebsiella pneumoniae

The DNA of Klebsiella pneumoniae (PC018) was sequenced and the 486 bp product

analysed by BLAST was found to be 100% similar to K. pneumoniae and Enterobacter

dissolvens. When analysed using the RDP-II Classifier, the sequence was shown to belong

100% to the genus Klebsiella. SeqMatch showed a 0.998 similarity score to K. pneumoniae

or E. dissolvens. PC018 is likely to be either K. pneumoniae or E. dissolvens.

Results

102

3.6.8 Enterobacter sp.

PC014 was identified as Enterobacter sp. by culture. When 504 bp of the sequenced

DNA from this sample was analysed by BLAST, it was found to have a 100% similarity

with several different types of species from the genus Enterobacter, namely Enterobacter

cancerogenus, E. aerogenes, E. ludwigii, E. intermedius (now belonging to the genus

Kluyvera), and E. agglomerans (now of the genus Pantoea), and a match to Kluyvera

cryocrescens. Classification on the RDP-II showed a full match with the family

Enterobacteriaceae and 94% match with the genus Enterobacter. Type and non-type

SeqMatch showed a full sequence match with E. cancerogenus, E. aerogenes and P.

agglomerans. Type-only SeqMatch showed similar results for the former two species along

with K. cryocrescens. PC014 is very likely from Enterobacter sp. as it showed a closer

match to the genus Enterobacter during classification, but P. agglomerans and K.

cryocrescens could not be excluded from the final diagnosis.

3.6.9 Escherichia coli

A similar situation was encountered with the culture Escherichia coli (PC039)

which showed full match with the family Enterobacteriaceae but only an 83% match with

the genus Escherichia. BLAST analysis of the 506 bp submitted showed a 100% similarity

with E. coli, E. fergusonii, Shigella boydii, S. flexneri., S. sonnei and Photorhabdus

luminescens. Type and non-type SeqMatch showed similar results at a 0.972 with S. boydii

showing 0.974. Analysis of type strains only had E. coli giving a score of 0.947 and S.

flexneri showing 0.972. The identity of the organism in PC039 could not be conclusively

determined by sequencing analysis.

Results

103

3.6.10 Proteus sp.

The DNA from the sample found to be Proteus sp. (PC015) was sequenced and

analysed and the 502 bp obtained was found to have a 99.8% similarity with Proteus

mirabilis and P. vulgaris. The Classifier concurred with this analysis and found a 100%

match with the genus Proteus. Sequence match had similar results with a score of 0.986 for

each species type. Therefore, the sample is of the genus Proteus and is either P. mirabilis or

P. vulgaris.

3.6.11 Stenotrophomonas maltophilia

The culture Stenotrophomonas maltophilia (PC016) was fully matched in sequence

analysis. The 501 bp sequence matched the genus Stenotrophomonas at 100%. PC016 is

therefore that of S. maltophilia and the result is similar to the culture results.

3.6.12 Summary of Section 3.6

There was some difficulty speciating the family Enterobacteriaceae e.g. those

identified by culture as Escherichia coli, Enterobacter sp., Klebsiella pneumoniae and

Proteus sp. Of the 12 clinical isolates identified by standard bacterial methods used in the

routine diagnostic laboratory, nine were similarly identified by DNA sequencing analysis.

The remaining three were identified to the family level with the species identified by culture

(E. coli, K. pneumoniae and Enterobacter sp.) included as high probability sequence

matches.

Table 3.8: The results of BLAST and RDP-II SeqMatch analyses on 16S rDNA sequences obtained from the DNA sequencing of pure cultures.

Staphylococcus aureus

Staphylococcus croceolyticus

Enterococcus faecalis 0.913

Enterococcus haemoperoxidus 0.920

Desemzia incerta 0.916

Enterococcus moraviensis 0.916

Enterococcus dispar 0.913

3 PC024 740 Corynebacterium

sp. Corynebacterium jeikeium 99.5 Corynebacterium

jeikeium 0.908 Corynebacterium jeikeium 0.908 Corynebacterium

jeikeium

4 PC021 484 Neisseria

gonorrhoeae Neisseria gonorrhoeae 100.0 Neisseria

gonorrhoeae 1.000 Neisseria gonorrhoeae 1.000 Neisseria

gonorrhoeae

No Culture ResultsBLAST Results

Organism Name % similarity

Lab No

PC041

RDP-II Sequence MatchPossible Organism

Type & Non-type Similarity Score Type only Similarity

Score

Staphylococcus aureus0.929

Enterococcus faecalis 2

Staphylococcus aureus subsp. aureus

Staphylococcus aureus0.953Staphylococcus

aureus1 99.7

0.965

293

Enterococcus faecalis

Enterococcus faecalis 99.7

5 Haemophilus influenzae

Haemophilus influenzae

Enterococcus faecalis287

498

PC022

100.0 Haemophilus influenzae 1.000 Haemophilus

influenzae 0.960 Haemophilus influenzae

bp

PC017

104


Acinetobacter baumannii 0.865

Acinetobacter calcoaceticus 0.992

Acinetobacter lwoffii 0.911

Acinetobacter ursingii 0.901

Acinetobacter radioresistens 0.875

Klebsiella pneumoniae



Enterobacter dissolvens



Enterobacter cancerogenus, E. aerogenes, E. ludwigii, E. agglomerans, E. intermedius

Enterobacter cancerogenus


Kluyvera cryocrescens

Enterobacter aerogenes


Pantoea agglomerans

Pantoea agglomerans


No Lab No bp Culture Results

1.000

BLAST Results RDP-II Sequence Match%

similarity Type & Non-type

Acinetobacter baumannii

Acinetobacter calcoaceticus

Possible OrganismSimilarity Score Type only Similarity

ScoreOrganism Name

7 100.0PC018

0.992

Klebsiella pneumoniae 0.998



100.06

Enterobacter sp.PC014 100.0504 1.000

Enterobacter sp., Kluyvera cryocrescens or Pantoea agglomerans

Acinetobacter sp.

Klebsiella pneumoniae or Enterobacter dissolvens

0.998

Acinetobacter baumanii

8

PC032 506

486

105


Escherichia coli Escherichia coli 0.972

Escherichia fergusonii

Escherichia fergusonii 0.972

Shigella boydii Shigella boydii 0.974

Shigella flexneri Shigella flexneri 0.972

Shigella sonnei Shigella sonnei 0.972

Photorhabdus luminescens

Photorhabdus luminescens 0.972

Proteus mirabilis Proteus mirabilis Proteus mirabilis 0.986

Proteus vulgaris Proteus vulgaris Proteus vulgaris 0.918

11 PC016 501 Stenotrophomonas

maltophilia Stenotrophomonas maltophilia 100 Stenotrophomonas

maltophilia 1.000 Stenotrophomonas maltophilia 0.992 Stenotrophomonas

maltophilia


Organism Name % similarity Type & Non-type Similarity

Score Type only Similarity Score

Escherichia coli, Shigella sp. or Photorhabdus luminescens

Escherichia coli 0.947

Shigella flexneri 0.972

No Lab No bp Culture Results

BLAST Results

Proteus sp.0.986

Escherichia coli

99.8Proteus sp. PC015

506 100PC039

10 502

9

106

Results

107

PHASE II: Screening of Clinical Samples

3.7 Collection of Samples

Different types of clinical specimens were collected from the Microbiological

Diagnostic Laboratory, UMMC to determine the ability of the optimised broad-range PCR

in determining the presence of bacterial DNA.

Four different clinical sample types were collected i.e. CSF, PF, SF, and the

peripheral venous blood in BCB samples (Section 2.1.4). Both culture-positive and culture-

negative samples from patients suspected of having bacterial infections were collected over

a 2 year period between July, 2002 and August 2004. Patient information on the test request

forms such as name, age, registration number, laboratory sample number as well as possible

diagnosis and current treatment (if any) were documented.

DNA was extracted from the clinical specimens, and used for broad-range PCR to

determine Gram-type. The PCR products from DNA amplification were also sequenced,

and the resulting sequences aligned with those in public databases in order to determine the

identity of organisms present in the specimens.

Results

108

3.8 PCR on Clinical Samples

A short explanation on the determination of Gram-type by PCR can be found in

Section 3.5. The full results of Gram-positive (GP), Gram-negative (GN) and Pan specific

PCR on the 233 clinical samples used in this study are presented in Appendix E. The

culture results and the Gram-type of the organisms identified by culture were listed and

compared against the typing results by PCR. Samples with no organisms isolated by culture

were listed in the Gram-type as N/A (not available). A summary of the results in Appendix

E can be found in Table 3.9.

Gram-typing by PCR matched those by culture and full concordance was observed

in the following situations:-

i) When both culture and PCR results were positive e.g. a culture-positive sample

that was identified as Escherichia coli had DNA which was amplified by Gram-

negative specific and Pan-specific primers.

ii) When both culture and PCR results were negative e.g. samples that did not show

any results by culture also did not undergo DNA amplification.

iii) When organisms identified as Gram-positive by staining had DNA amplified by

Gram-positive specific and Pan-specific primers, and when those identified as

Gram-negative by staining had DNA amplified by Gram-negative specific and

Pan-specific primers.

Gram-typing by PCR did not match culture results in cases when culture negative

samples had amplifiable DNA or when culture-positive samples failed to produce

amplifiable DNA.

Results

109

In Table 3.9, 11 of the PCR-positive results were typed as Gram-positive, while 19

were typed as Gram-negative. Of the 11 PCR Gram-positive specific samples, four were

culture-negative; while 5 out of 19 of the PCR Gram-negative specific samples were

culture-negative. The Pan-specific PCR samples made up the total of samples found

positive for Gram-positive and Gram-negative specific PCR. Seven of the 14 of the Gram-

positive organisms isolated by culture could not be amplified by PCR, while three of the 17

Gram-negative organisms were not detectable by PCR.

Table 3.9: The number of specimens found positive or negative by culture and PCR, with

division into Gram-positive and Gram-negative groups.

PCR-positive Culture results Gram-positive

specific Gram-negative

specific Pan-specific

PCR-negative specimen

Total for

culture

Gram-positive culture-positive

samples 7 0 7 7 14

Gram-negative culture-positive

samples 0 14 14 3 17

Culture-negative samples 4 5 9 193 202

Total for PCR 11 19 30 203 233

Note: The numbers in the column with the double-lines were disregarded from the total.

The numbers in the Pan-specific column are the total numbers from the Gram-positive

specific and Gram-negative specific column.

Results

110

3.9 Sequencing of Clinical Samples

The PCR products from clinical samples that had amplifiable DNA (Section 3.8)

were purified and sequenced (Section 2.5.3) and the results analysed according to the

method in Section 2.5.4. Examples of electropherograms from the DNA sequencing of PCR

products from clinical samples are presented in Appendix F and the results of the analyses

are presented below.

3.9.1 Clinical Samples That Produced Positive Results by Culture and 16S rDNA

PCR (Refer Table 3.10)

3.9.1a Sample C065 (Identified as Enterobacter sp. by Culture)

Sample C065 was identified as Enterobacter sp. by culture. When the 479 bp

sequenced DNA from this sample was analysed by BLAST, it was found to have a 100%

similarity with several different types of species from the genus Enterobacter i.e.

Enterobacter cancerogenus, E. aerogenes, E. ludwigii, E. intermedius (now belonging to

the genus Kluyvera), and E. agglomerans (now of the genus Pantoea), and Kluyvera

cryocrescens. Classification on the RDP-II showed a full match with the family

Enterobacteriaceae and 96% match with the genus Enterobacter. Type and non-type

SeqMatch showed a full sequence match with E. cancerogenus, E. aerogenes and P.

agglomerans. Type-only SeqMatch showed similar results for the former two species along

with K. cryocrescens. Sequence from C065 is very likely from Enterobacter sp. as it

showed a closer match to the genus Enterobacter during classification, although P.

agglomerans and K. cryocrescens could not be excluded from the final diagnosis. Results

using sequencing are considered similar to that of culture.

Results

111

3.9.1b Samples C089, B082, P045 and P063

(Identified as Klebsiella pneumoniae by Culture)

Samples C089 and B082 which were identified by culture as Klebsiella pneumoniae,

were sequenced and the resulting 504 bp product analysed. The sequence was found to be

100% similar to K. pneumoniae and Enterobacter dissolvens by BLAST analysis. When

analysed using the RDP-II Classifier, the sequence was shown to belong partially (99% for

C089 and 97% for B082) to the genus Klebsiella. SeqMatch showed a 0.996 similarity

score to K. pneumoniae or E. dissolvens for C089 and a full match for B082. The sequences

from C089 and B082 were probably from K. pneumoniae based on the result of the

Classifier, but E. dissolvens could not be excluded from the final analysis. Thus, sequencing

analysis supports those of culture.

In comparison, the DNA from P045 (501 bp) and P063 (479 bp) which were

identified by culture as K. pneumoniae and Klebsiella sp. respectively, were found to have a

complete match when using BLAST and RDP-II analysis. The Classifier agrees with this

result and the sequence matches the genus Klebsiella completely. Thus, sequencing results

are similar to those obtained by culture.

3.9.1c Samples P002, P056 and P055 (Identified as Escherichia coli by Culture)

The DNA acquired from P002 and P056 (identified as Escherichia coli by culture)

were sent for BLAST analysis. The 506 bp and 503 bp products (for P002 and P056

respectively) submitted showed 100% similarity with E. coli, E. fergusonii, Shigella boydii,

S. flexneri, and Photorhabdus luminescens. Type and non-type SeqMatch showed 1.000

similarity scores with the addition of the species S. sonnei. Analysis of type strains only had

S. flexneri showing a full similarity score. The RDP-II classifier showed a full match to the

genus Escherichia. It is to be noted that based on the Bergey’s taxonomy, the Shigella spp.

Results

112

listed from this search were all considered to belong to the genus Escherichia. Considering

the similarity with the results from the pure culture samples (refer Section 3.6.9), samples

P002 and P056 possibly contains E. coli, although the other species could not be excluded

in the final analysis.

The sample P055 had rather similar results to P002 and P056 in which the 506 bp

when analysed with BLAST had 100% similarity to the same species listed above. The

Classifier showed only an 81% match to the genus Escherichia. The sequence had a 0.974

similarity score with S. boydii with SeqMatch and 0.974 score for the other organisms

(similar to those found for the previous paragraph). Type strain only subset showed a 0.972

and 0.947 score for S. flexneri and E. coli respectively. Based on the similarity of results

with that of the pure culture analysis (Section 3.6.9), the sample P055 possibly contains E.

coli but the other species could not be excluded in the final analysis.

3.9.1d Samples P004 and P029 (Identified as Enterococcus sp. by Culture)

Samples P004 and P029 were both identified as Enterococcus sp. by culture. DNA

sequenced from both samples (261 bp) was found to have a 100% similarity with

Enterococcus faecalis, E. saccharolyticus and Lactobacillus plantarum. The former two

also had 1.000 similarity scores when tested by SeqMatch with E. moraviensis showing a

0.961 similarity score as a type species. The sample from P004 showed a 99% match to the

genus Enterococcus but P029 showed a full match. Both samples are more likely to contain

DNA from Enterococcus sp. The results of sequencing analysis support those of culture.

Results

113

3.9.1e Samples P007, B078 and B079

(Identified as Acinetobacter baumanii by Culture)

Samples from P007 (502 bp), B078 and B079 (504 bp) which were all identified as

Acinetobacter baumanii by culture, were analysed and found to have high similarities with

A. baumanii and A. calcoaceticus (99.8, 99.8 and 100% respectively). This high match to

the two species was similar when tested with SeqMatch, with a similarity score of 0.986 for

P007 and B078, and 1.000 for B079. The Classifier found all samples to have a full match

to the genus Acinetobacter. A similar result was found in the pure culture analysis (Section

3.6.6). The samples P007, B078 and B079 are therefore either A. baumanii or A.

calcoaceticus.

3.9.1f Sample C003 (Identified as Streptococcus sp. by Culture)

Sample C003 was found to be Streptococcus sp. by culture methods. When the 207

bp sequence obtained was sent for BLAST analysis, the sequence was found to have a

99.5% homology with S. agalactiae and S. difficilis. Similar results were obtained by RDP-

II SeqMatch analysis with a similarity score of 0.915 only. The Classifier found the

sequence in question to be probably 85% from the genus Streptococcus. The DNA from

C003 is probably that of S. agalactiae or S. difficilis.

3.9.1g Sample P051 (Identified as Group G Streptococci by Culture)

Sample P051 was identified as a group G Streptococci by culture methods. BLAST

analysis and SeqMatch of the 279 bp sequence consistently showed a full match to the

species Streptococcus dysgalactiae. The Classifier also agreed with this by showing a full

match with the genus Streptococcus. The organism found in P051 is very likely S.

dysgalactiae. The results by sequencing provide identification to the species level.

Results

114

3.9.1h Sample P017 (Identified as Staphylococcus aureus by Culture)

Sample P017 was identified as Staphylococcus aureus by culture methods. BLAST

analysis showed that the 281 bp submitted for sequencing had a 100% similarity to S.

aureus, S. croceolyticus or S. haemolyticus. The sequence had a 1.000 similarity score with

the former two using SeqMatch analysis. The classifier showed a high but not full

probability of the sequence belonging to the genus Staphylococcus (99%). P017 is possibly

S. aureus, S. croceolyticus or S. haemolyticus but is more likely to be S. aureus due to the

high clustering of the species during the search.

3.9.1i Sample P014 (Identified as Pseudomonas aeruginosa by Culture)

The sample P014 was identified as Pseudomonas aeruginosa by culture methods.

When the 416 bp sequence product was analysed by BLAST, it was found to be 100%

similar with Citrobacter freundii, C. youngae, C. werkmanii and C. braakii. SeqMatch

analysis showed similar results with 1.000 scores but showed C. murliniae instead of C.

youngae. The Classifier identified the sequence as belonging fully to the family

Enterobacteriaceae and only partially (65%) to the genus Citrobacter. The sequence

analysis showed that P014 is probably Citrobacter sp., which does not agree with the result

obtained by culture.

3.9.1j Sample B080 (Identified as Salmonella enteritidis by Culture)

Salmonella enteritidis was identified from the sample B080. BLAST analysis of the

729 bp sequence product showed a 100% similarity with serovar S. typhimurium. SeqMatch

showed a similarly high score of 1.000 while the Classifier placed the sequence fully among

the genus Salmonella. The DNA in the sample B080 likely belongs to serovar S.

typhimurium.

Results

115

3.9.1k Samples B073 and B074

(Identified as Coagulase-negative Staphylococci by Culture)

Samples B073 and B074 were both identified as coagulase-negative Staphylococci

by culture methods. BLAST analysis of the 281 bp sequence obtained from both showed

full similarity with Staphylococcus caprae, S. epidermidis, S. capitis, and S. saccharolyticus

which are all coagulase-negative Staphylococci. SeqMatch on the RDP-II showed similar

results. The Classifier identified the sequences as belonging to the genus Staphylococcus.

The DNA from both samples probably belongs to Staphylococcus sp. and is likely one of

the four organisms listed. Results are considered similar to those by culture.

3.9.1l Sample B076 (Identified as Gram-negative Rod by Culture)

The sample B076 could only be identified as having a Gram-negative rod by culture

methods. BLAST analysis of the 502 bp sequence showed a 100% homology to the species

Escherichia coli and Shigella boydii. Results were replicated in SeqMatch. The Classifier

found the sequence to match fully with the family Enterobacteriaceae and only 97% of the

genus Escherichia. The organism in B076 is either E. coli or S. boydii.

3.9.1m Summary of Section 3.9.1

To sum up the results of sequence analyses from this section, nine samples could be

identified to genus level (P004, P029, P007, B078, B079, C003, P017, B073, and B074),

four to species level (P045, P063, P051, and B080), and seven to family level (C065, C089,

B082, P002, P056, P055, and B076) and all of these were in agreement with culture results.

Only one (P014) out of the 21 PCR and culture-positive samples was not in agreement.

Table 3.10 : List of clinical specimens found positive by 16S rDNA PCR and culture, with results from BLAST and RDP-II analyses.

Streptococcus agalactiae

Streptococcus agalactiae

Streptococcus difficilis

Streptococcus difficilis

Enterobacter aerogenesEnterobacter intermediusEnterobacter ludwigiiEnterobacter cancerogenusEnterobacter agglomeransKluyvera cryocrescensPantoea agglomeransKlebsiella pneumoniae






Culture Results

Streptococcus sp.

Enterobacter sp.


Type & Non-type Similarity Score Type only

1.000

Pantoea agglomerans

0.915


479 1.000

RDP-II Sequence MatchPossible OrganismSimilarity

Score

BLAST Results


Streptococcus agalactiae 0.915

Streptococcus agalactiae or Streptococcus difficilis

No bpLab No.

2 C065 100.0



1 C003 207 99.5

504 0.9963 C089 100.0 0.996

Enterobacter sp., Kluyvera cryocrescens or Pantoea agglomerans




116


Escherichia coli Escherichia coliEscherichia fergusonii


Shigella boydii Shigella boydiiShigella flexneri Shigella flexneri

Photorhabdus luminescensShigella sonnei



Enterococcus saccharolyticusLactobacillus plantarumAcinetobacter baumanii




Citrobacter freundii



Citrobacter youngae

Citrobacter murliniae

Citrobacter murliniae

Citrobacter werkmanii



Citrobacter braakii

Citrobacter braakii

Citrobacter braakii


Pseudomonas aeruginosa

bpBLAST Results RDP-II Sequence Match


Type & Non-type


No Lab No. Similarity


Culture Results

Escherichia coli

Possible Organism

1.000

416

261P0045

4 P002 505


100.0


0.961

6 P007 502 99.8

100.0 Enterococcus saccharolyticus

1.000 Enterococcus moraviensisEnterococcus sp.

Enterococcus sp. or Lactobacillus plantarum

7 P014 100.0 1.000 1.000

Acinetobacter baumanii or Acinetobacter calcoaceticus

0.986 Acinetobacter baumanii 0.986

Citrobacter sp.

117





Staphylococcus aureusStaphylococcus saprophyticusStaphylococcus haemolyticusStaphylococcus cohniiStaphylococcus gallinarum



Enterococcus saccharolyticusLactobacillus plantarum

10 P045 501 Klebsiella pneumoniae

Klebsiella pneumoniae 100.0 Klebsiella

pneumoniae 1.000 Klebsiella pneumoniae 1.000 Klebsiella

pneumoniae

Enterococcus sp.

Group G Streptococci

Culture Results


279

No Lab No. bp

BLAST Results RDP-II Sequence MatchPossible Organism

Streptococcus dysgalactiaeP05111

261P0299

8 P017 281

Staphylococcus haemolyticus


100.0



1.000 0.975 Staphylococcus sp.

Enterococcus sp. or Lactobacillus plantarum

0.961Enterococcus moraviensis1.000

Enterococcus saccharolyticus

100.0

Streptococcus dysgalactiae 100.0 Streptococcus

dysgalactiae 1.000 Streptococcus dysgalactiae 0.982

118




Escherichia coli Shigella boydii 0.974Escherichia fergusonii Escherichia coli

Shigella boydii Escherichia fergusonii

Shigella flexneri Shigella sonnei

Shigella flexneriPhotorhabdus luminescens

Escherichia coli Escherichia coliEscherichia fergusonii


Shigella boydii Shigella boydii

Shigella flexneri Shigella flexneri

Shigella sonneiPhotorhabdus luminescens

14 P063 479 Klebsiella sp. Klebsiella pneumoniae 100.0 Klebsiella

pneumoniae 1.000 Klebsiella pneumoniae 1.000 Klebsiella

pneumoniae

Culture Results

Escherichia coli

No Lab No. bp

BLAST Results



0.972

Escherichia coli

12 P055 506


100.0

Shigella flexneri

Escherichia coli

0.972

0.947


13 P056 503 100.0 1.000


Escherichia coli 0.973


119




Staphylococcus caprae



Staphylococcus epidermidis



Staphylococcus capitis



Staphylococcus saccharolyticus















Escherichia coli Escherichia coli

Shigella boydii Shigella boydiiAcinetobacter baumannii




Coagulase-negative Staphylococci

Coagulase-negative Staphylococci

Gram negative rod

Acinetobacter baumanii504

Lab No. bp

BLAST ResultsCulture Results Possible OrganismNo

100.015 B073 281 1.000 1.000

Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus capitis or Staphylococcus saccharolyticus

RDP-II Sequence Match

17 B076 100.0

1.00016 B074 281 100.0

502

0.986

1.000

Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus capitis or Staphylococcus saccharolyticus

1.000 Shigella dysenteriae 0.943 Escherichia coli or

Shigella boydii



18 B078 99.8

120








Salmonella typhimurium 0.964

Salmonella typhi 0.973







Culture Results


Salmonella enteritidis


No Lab No. bp

BLAST Results RDP-II Sequence MatchPossible Organism

1.000

1.000

20 B080 729 Salmonella typhimurium 100.0

21 B082 504

1.000

1.000

19 B079 504 100.0



100.0


Salmonella typhimurium

Salmonella typhimurium 1.000

121

Results

122

3.9.2 Clinical Samples Found Positive by 16S rDNA PCR but Negative by Culture

(Refer Table 3.11)

3.9.2a Cerebrospinal Fluid Samples (C016, C027, C033, C051 and C067)

DNA was amplified in sample C016 and the 283 bp sequence was sent for BLAST

analysis and found to have a 99.6% similarity with many organisms of the genus

Brevibacillus i.e. Brevibacillus agri, B. parabrevis, B. formosus, B. limnophilus, B. brevis,

B. centrosporus, and B. choshinensis. SeqMatch found similar results but with a similarity

score of 0.971. The Classifier agreed with the results found and the sequence was fully

matched to the genus Brevibacillus. DNA from this sample is likely from Brevibacillus sp.

C027 produced a 504 bp sequence that showed a 100% similarity to that of

Acinetobacter baumanii and A. calcoaceticus. The result was similar by SeqMatch but with

a similarity score of 0.994. The Classifier showed the sequence to have a 100% match to the

genus Acinetobacter. The DNA from this sample is likely from A. baumanii or A.

calcoaceticus.

The 224 bp sequence from the sample C033 yielded a 100% homology with

sequences from Bacillus sp., Planococcus sp. and Planomicrobium sp. SeqMatch showed a

closer match to the sequence from Bacillus infernus with a 0.995 similarity score. The

Classifier could only classify the sequence fully to the class Bacilli and partially (at 36%) to

the genus Bacillus. The DNA from this sample is likely from Bacillus infernus, Bacillus sp.,

Planococcus sp. or Planomicrobium sp.

Results

123

The 284 bp sequence from sample C051 was shown to have a 99.6% similarity with

Oceanobacillus iheyensis via BLAST analysis, and a 0.975 score to the same organism via

SeqMatch. The Classifier showed a full match to the class Bacilli and a partial match to the

genus Virgibacillus, to which O. iheyensis belongs. The DNA amplified is likely from

Oceanobacillus iheyensis or a similar organism.

Sample C067 had DNA amplified and the resulting 478 bp sequence was 100%

similar to Brevundimonas aurantiaca and Caulobacter henricii by BLAST analysis. The

results were similar with SeqMatch with a 1.000 similarity score. The Classifier showed a

99% match to the genus Brevundimonas. The DNA in this sample is likely from B.

aurantiaca or C. henricii.

3.9.2b Peritoneal Fluid Sample (P020)

Sample P020 produced a 479 bp sequence that had 100% similarity (by BLAST)

and a 1.000 similarity score (by SeqMatch) with Acinetobacter rhizosphaerae, A. baumanii

and A. calcoaceticus. The Classifier matched the sequence to the genus Acinetobacter. The

DNA from this sample is likely from Acinetobacter sp.

3.9.2C Synovial Fluid Samples (S010, S017 and S033)

A 506 bp sequence was obtained from the sample S010 which showed a 99.8%

similarity to an uncultured Sphingomonadaceae bacterium when analysed with BLAST.

The same result was obtained from SeqMatch with a 0.986 similarity score. Type-only

analysis showed a 0.978 similarity to Sphingomonas sanguinis. Classification showed a

100% match with the genus Sphingomonas. DNA from this sample is likely from

Sphingomonas sanguinis.

Results

124

Sample S017 provided a 279 bp sequence that showed 100% similarity with

Streptococcus constellatus, S. intermedius and S. anginosus with BLAST analysis and a full

similarity score with SeqMatch. The Classifier agreed with this result as it showed a 100%

match to the genus Streptococcus. DNA from this sample is likely from Streptococcus sp.

The 506 bp sequence obtained from S033 showed a full match with Acinetobacter

baumanii and A. calcoaceticus when analysed by BLAST. By SeqMatch, the similarity

score was 0.988. The Classifier showed a 100% match to the genus Acinetobacter. DNA

from this sample is likely from A. baumanii or A. calcoaceticus.

Table 3.11: List of clinical specimens found positive by 16S rDNA PCR assay and negative by culture, with BLAST and RDP-II analyses.

Brevibacillus agri Brevibacillus agriBrevibacillus parabrevis

Brevibacillus parabrevis

Brevibacillus formosus

Brevibacillus formosus

Brevibacillus limnophilus

Brevibacillus limnophilus

Brevibacillus brevis Brevibacillus brevisBrevibacillus centrosporus

Brevibacillus centrosporus

Brevibacillus choshinensis

Brevibacillus choshinensis





Brevundimonas aurantiaca

Brevundimonas aurantiaca

Caulobacter henricii Caulobacter henricii

0.971

0.994

Oceanobacillus iheyensis

1.000

Oceanobacillus iheyensis 0.975

99.6

99.6

100.0


BLAST Results

Organism Name % similarity Type only Similarity

ScoreType & Non-type Similarity Score

No bpLab No.

1 C016 283

2 C027 504 100.0

3 C051 284

4 C067 478 Brevundimonas aurantiaca 1.000

Brevibacillus sp.


Virgibacillus marismortui 0.906

Brevibacillus reuszeri 0.946


Oceanobacillus iheyensis

Brevundimonas aurantiaca or Caulobacter henricii

125


Bacillus drentensisBacillus circulansBacillus eolicusBacillus niaciniBacillus fumarioliBacillus firmusBacillus macroidesBacillus muralisBacillus methanolicusBacillus coagulans Planococcus citreusPlanococcus rifitiensisPlanococcus maritimusPlanomicrobium chinensePlanococcus psychrotoleratusPlanomicrobium okeanokoites

Bacillus infernus 0.995

No Lab No. bp

BLAST Results


0.9955

Possible OrganismType & Non-type Similarity



C033 100.0 Bacillus infernus224

Bacillus infernus, Bacillus sp., Planococcus sp. or Planomicrobium sp.

126


Acinetobacter rhizosphaerae

Acinetobacter rhizosphaerae





7 S010 506Uncultured Sphingomonadaceae bacterium

99.8Uncultured Sphingomonadaceae bacterium

0.986 Sphingomonas sanguinis 0.978 Sphingomonas

sanguinis

Streptococcus constellatus

Streptococcus constellatus

Streptococcus intermedius


Streptococcus anginosus

Streptococcus anginosus





No Lab No. bp

BLAST Results


Possible OrganismType & Non-type Similarity



6 P020 479 100.0 1.000 Acintobacter sp.1.000


8 S017 279

100.0

0.875 Streptococcus sp.1.000100.0

9 506


S033 0.988Acinetobacter baumannii0.988


127

Results

128

3.9.3 Clinical Samples Found Negative by 16S rDNA PCR but Positive by Culture.

The 16S rDNA PCR assay did not amplify DNA from 10 samples that showed

viable cultures as can be seen in Table 3.12. Four of the samples (C090, P030, P048 and

P069) were shown to be Staphylococcus aureus by culture. Bacillus sp. was isolated by

culture in two BCB samples (B077 and B081) and Enterococcus sp. in a CSF sample

(C048). The other three samples, P042, P052 and P066, were found by culture to contain

Pseudomonas aeruginosa, Acinetobacter baumanii and Escherichia coli respectively.

Gram-positive organisms made up most of the samples that grew viable cultures but

did not produce amplified DNA. Seven of the samples were Gram-positive, and the

remaining three were Gram-negative. Of the 10 clinical specimens that were positive by

culture but negative by 16S rDNA PCR, six of the samples were PF specimen, 2 were CSF

specimen and 2 others were from BCB.

Table 3.12: List of clinical samples that produced negative results using 16S rDNA PCR

assay but showed positive culture results.

No. Lab No. Specimen type Culture Results Gram-type 1 C 048 Cerebrospinal fluid Enterococcus sp. Positive 2 C 090 Cerebrospinal fluid Staphylococcus aureus Positive 3 P 030 Peritoneal fluid Staphylococcus aureus Positive 4 P 042 Peritoneal fluid Pseudomonas aeruginosa Negative 5 P 048 Peritoneal fluid Staphylococcus aureus Positive 6 P 052 Peritoneal fluid Acinetobacter baumanii Negative 7 P 066 Peritoneal fluid Escherichia coli Negative 8 P 069 Peritoneal fluid Staphylococcus aureus Positive 9 B 077 BACTEC fluid Bacillus sp. Positive 10 B 081 BACTEC fluid Bacillus sp. Positive

Results

129

3.10 Comparison of the 16S rDNA PCR with Culture

3.10.1 Overall Results

Results from PCR, sequencing and consequent sequencing analysis (hereby

collectively referred to as 16S rDNA PCR) were compared with those from culture and

collated into four major groups (Table 3.13). The groups consist of samples positive for

both 16S rDNA PCR and culture results, samples positive for 16S rDNA PCR but negative

for culture, samples negative for 16S rDNA PCR but positive for culture and samples

negative for both 16S rDNA PCR and culture. A positive sample for 16S rDNA PCR refers

to successful amplification of the specific target sequence from the extracted DNA sample.

Culture results refer to results obtained using standard microbiological methods and clinical

diagnosis. A positive sample for culture refers to the growth of a bacterial organism in

media and the successful isolation and identification of that organism.

When the 16S rDNA PCR results of 233 clinical samples were compared with the

results obtained by culture, it was found that 21 samples were both culture and 16S rDNA

PCR positive. Of the 21 samples, twenty were found to be fully concordant i.e. the Gram-

typing by PCR and the identification by sequencing and BLAST analysis were similar to

that obtained by culture. However, one of the samples was discordant (Section 3.9.1i) i.e.

the Gram-typing was similar by PCR and culture, but the identification of the organism by

sequencing and BLAST analysis differed from that by culture methods. There were nine

samples found to be positive by 16S rDNA PCR but negative by culture results. Ten of the

culture-positive samples were negative by 16S rDNA PCR. A major portion of the samples

(193 samples) were found to be both culture and 16S rDNA PCR negative. The 16S rDNA

PCR gave positive results for a total of 30 samples out of 233 and negative results for 203

samples. Total culture-positives number at 31 samples, while there was a total of 193

culture-negative samples (Table 3.13).

Results

130

Table 3.13: Results obtained from 16S rDNA broad-range PCR and sequencing compared

with those obtained from cultures in the 233 clinical samples studied.

Culture + Culture -

Concordant 20 Discordant 1

Total PCR positives PCR +

21

9

30

Total PCR negatives PCR -

10

193

203

Total culture positives

31

Total culture negatives

202

233

3.10.2 Breakdown of Results into Sample Types

The overall results was broken down into four other groups comprising the different

sample types used in this study as can be seen in Table 3.14.

CSF samples accounted for three of the 16S rDNA PCR and culture-positive

samples. Of the eight 16S rDNA PCR-positive samples, five were culture-negatives. Of the

71 16S rDNA PCR-negative samples, two were culture-positives and the remaining 69 were

culture-negative. Of the 79 CSF samples collected, 5 were culture positive and 74 were

culture-negative.

A total of 64 PF samples were collected. The 16S rDNA PCR-positive samples

numbered at 12 while there were 51 samples that were 16S rDNA PCR-negative. Of the

16S rDNA PCR-positives, one sample was culture-negative. Of the 16S rDNA PCR-

negatives, six were culture-positive and 45 were culture-negative. In total, there were 18

culture-positive PF samples and 46 culture-negative samples.

Results

131

There were no culture-positive samples in the SF sampling. Of the 42 culture-

negative samples collected, three were found to be positive by 16S rDNA PCR while the

remainder was found to be negative.

The BCB samples had seven that were both 16S rDNA PCR and culture-positive.

There were no 16S rDNA PCR-positives that were culture-negative. A total of 42 PCR

negatives were found, two of them positive by culture. Of the 49 BACTEC samples, nine

were culture positive and the rest were culture negative.

Table 3.14: Results obtained from 16S rDNA broad-range PCR and sequencing compared

with those obtained from culture methods. The samples consist of cerebrospinal fluid

(CSF), peritoneal fluid (PF), synovial fluid (SF) and blood culture bottle (BCB) samples.

Culture + Culture -

PCR + 3 5 8

PCR - 2 69 71 Cerebrospinal fluid 5 74 79 Culture + Culture -

PCR + 11 1 12 PCR - 6 45 51 Peritoneal fluid

17 46 63 Culture + Culture -

PCR + 0 3 3 PCR - 0 39 39 Synovial fluid

0 42 42 Culture + Culture -

PCR + 7 0 7 PCR - 2 40 42 Blood Culture Bottle

9 40 49

Results

132

3.10.3 Performance of the 16S rDNA PCR Assay Compared to Culture

The results from Sections 3.10.1 and 3.10.2 were entered into the Simple Interactive

Statistical Analysis (SISA) software that was available online

(http://home.clara.net/sisa/diagnos.htm) and the effectiveness and predictive accuracy of the

16S rDNA PCR assay was compared to those by culture methods. The performance results

are shown in Table 3.15.

Table 3.15: Performance of the 16S rDNA PCR assay compared to the culture results of

cerebrospinal fluid (CSF), peritoneal fluid (PF), synovial fluid (SF) and blood culture bottle

(BCB) samples.

Sample type Number of samples

Sensitivity (%)

Specificity (%)

Positive predictive

value, PPV (%)

Negative predictive

value, NPV (%)

Cerebrospinal fluid 79 60 93.24 37.5 97.2 Peritoneal fluid 63 64.71 97.83 91.7 88.2

Synovial fluid 42 *NaN (0/0) 92.86 0 100

BACTEC fluid 49 77.78 100 100 95.2 All samples 233 67.74 95.54 70 95.1

* NaN: not any number

The 16S rDNA PCR was shown to have 60% sensitivity and 93.24% specificity

when used on CSF samples. The positive predictive value (PPV) and negative predictive

value (NPV) of the assay on CSF samples were 37.5% and 97.2% respectively.

Specificity of the assay was higher in PF samples at 97.83%, and the sensitivity was

at 64.71%. The PPV of the assay on PF samples was 91.75 % and the NPV was 88.2%.

Results

133

SF samples provided unusual results. The sensitivity of the assay could not be

determined accurately as results showed NaN (0/0) and the PPV was at zero. The specificity

and NPV of the assay on synovial fluid samples were 92.86% and 100% respectively.

The 16S rDNA PCR assay showed the best results on BCB samples, with sensitivity

at 77.78%, specificity at 100%, PPV at 100% and NPV at 95.2%.

The performance of the assay on all 233 samples of varying types was 67.74%

sensitivity, 95.54% specificity, 70% PPV and 95.1% NPV.

The assay had better specificity (above 92%) than sensitivity (ranging from 60-

78%). The PPV varied depending on the sample types but the NPV of the assays were

generally high.

Discussion

134

4.0 Discussion

4.1 Contamination Issues in Broad-range PCR

Broad-range rDNA PCR is prone to experimental contaminants, as shown by Tanner

et al. (1998), where they found that rDNA from different environmental settings correlate

with experimental contaminants, particularly in extraction of DNA from low-biomass

samples, as there is a minimal dilution of the contaminant DNA with the sample DNA.

They also reported that the Taq polymerase and the amplification buffer were not

responsible for the contamination and the source of contamination was more likely the salt

and buffers, lysozyme, and proteinase K used during extraction.

Carroll et al. (1999) found it necessary to eliminate contaminating bacterial DNA

from Taq DNA polymerase by using Restriction Endonucleases (RE) Digestion. Meier et

al. (1993) used 8-methoxypsoralen as an additive to reduce DNA contaminants. However,

using a real-time 16S rDNA PCR, Corless et al. (2000) reported that the commonly used

methods for eliminating false-positives such as UV irradiation, 8-methoxypsoralen facilitate

by UV, and DNase and RE led to a 4-log, 5-log and 1.66-log reduction in PCR sensitivity

respectively. They reported it was difficult to determine the source of contaminating DNA,

and surmised that it was likely from the water, plastics and reagents. They concluded that it

was not possible to eliminate contaminating DNA for broad-range 16S rDNA PCR without

some decrease in sensitivity.

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With these issues in mind, it was decided that good laboratory practices, dedicated

material, filtered tips, and a strict separation of pre- and post- PCR areas (Burkardt, 2000;

Millar et al., 2002) would be implemented to avoid false-positives in this study (Section

2.2.3). The inclusion of positive and negative controls (Figures 2.4 and 2.5) helped in

detecting false-positive or false-negative results.

4.2 Extraction Methods

Optimal extraction methods are important as they affect downstream applications

such as PCR and sequencing (Aoyagi, 2001). There are many kinds of extraction methods,

each suitable for different specimen types. It is advantageous to avoid hazardous solutions,

multiple centrifugations, multiple steps and special equipment if possible, and select a

protocol that is robust, fits the choice of specimen and removes PCR inhibition (Greenfield

and White, 1993).

4.2.1 Complexity Ranking

The qualitative Complexity Ranking analysis (Section 3.1.1) was implemented on

the range of methods tested, from the simple (boiling) to the difficult (PCIA). This

comparison was performed as the lowest detection levels of the various methods may be

similar (Section 3.1.4), thus there was a need to determine if the method was suitable

enough to be used in routine diagnostics i.e. with high throughput of samples, the need for

rapid results, and must be easily performed.

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The number of steps was one of the criteria ranked, as an increase in steps

performed could lead to a higher probability of contamination and errors, and would need

extra time to complete. The presence of toxic chemicals was also considered as the material

could be hazardous to laboratory workers. The skill level needed to perform the methods

was also evaluated as methods requiring a skilled manipulation could be prone to errors,

require extensive training, and cause difficulties in standardisation. The extent of waste

generation was also ranked as it could affect the overall cost of the laboratory that requires

the waste to be disposed safely.

4.2.2 DNA Amplification of Extracted Samples

Four extraction methods, the AH, boiling, PCIA and the DNAzol method were

compared using CSF, PF, SF and BCB samples (Section 3.1.2). All samples started with

the same initial volume of 100 µl prior to extraction.

The AH method was successful in extracting bacterial DNA from CSF, BCB, and

PF samples but not in SF or water samples (Figure 3.1). It was possible that inhibitory

substances in SF were not completely removed using this method. It was doubtful that the

water samples contained inhibitory substances, thus the lack of amplification could be due

to the loss of bacterial cells during the washing steps.

The boiling method was successful in extracting bacterial DNA only from CSF but

not from BCB, PF, SF or water samples (Figure 3.1). The BCB, PF and SF samples

possibly contained inhibitors that were not completely diluted by the buffer. The bacterial

DNA in the water sample was either lost during the final centrifugation or was totally lysed

during heating.

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The PCIA method extracted DNA from all samples except the BCB sample (Figure

3.2). It was possibly the presence of a PCR inhibitor, sodium polyanetholesulfonate (SPS),

in the BCB sample could not be completely removed by the PCIA method (Fredricks and

Relman, 1998). It must be noted that the PCR using Pan and Gram-positive specific primers

produced only the Gram-positive specific bands from PF and water samples (Figure 3.3). It

is possible that some inhibitors were not completely removed during the extraction.

A similar situation occurred with DNAzol extracted samples (Figures 3.2 and 3.3).

The BCB sample did not show any amplification, possibly due to the presence of SPS, but

the DNA in other samples was successfully extracted using DNAzol.

4.2.3 Boiling Method on CSF Specimen

The boiling extraction method was the method of choice for CSF specimens in this

study (Section 3.1.3). The method initially involved heating the sample without the addition

of buffer or other steps, and this caused inhibition during the PCR. This inhibition was

overcome by the addition of the TE buffer prior to extraction, and the freezing and thawing

steps after heating (Section 2.3.3). The boiling method is a rapid method which was

comparable to the other methods tested in this study (Section 3.1.4).

CSF samples extracted via the boiling method has been said to be refractory to

amplification (Greenfield and White, 1993), but this was not the case in this study as

determined by positive controls spiked into each clinical specimen (Section 3.1.2). The

boiling method worked better on CSF samples compared to other sample types, possibly

due to the low number of nucleated cells.

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4.2.4 AH Method on BCB and PF Specimen

The AH extraction method was the method of choice for BCB and PF specimens

used in this study (Section 3.1.3). This simple and effective method involves a simple alkali

wash and heat lysis, and provides DNA templates suitable for use in PCR, particularly those

obtained from mycobacterium and blood samples (Kulski and Pryce, 1996).

In a study carried out by Millar et al. (2000), the AH method was found to be the

only method that completely removed PCR inhibitors and inherent DNA from virgin

BacT/Alert aerobic, anaerobic and paediatric blood culture bottles. The main PCR inhibitor

in BCB samples was the additive SPS, which had similar properties to DNA that enables it

to co-purify during extraction (Fredricks and Relman, 1998). This would explain why DNA

templates extracted from BCB samples using the boiling, PCIA and DNAzol methods did

not produce amplified products.

The AH extraction method was chosen for PF as it was the most simple and

effective method compared to PCIA and DNAzol. The boiling method did not produce

DNA that was amplifiable by PCR.

4.2.5 DNAzol and SF Specimen

DNAzol is a ready-to-use chemical that consists of guanidine thiocyanate and a

proprietary detergent that hydrolyses RNA and allows the selective precipitation of DNA

from cells. The method requires fewer steps and is simpler than PCIA, involves the use of a

mild irritant which is less toxic than phenol, and produces pure DNA (Chomczynski et al.,

1997). It is these properties and a lower complexity ranking compared to PCIA, which

makes DNAzol extraction the method of choice for the SF specimens used in this study

(Section 3.1.3). The boiling and AH methods did not sufficiently remove the proteins

present in SF.

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4.2.6 Other Methods

The PCIA method, while often considered as the standard in DNA extraction

methods (Sambrook et al. 1989) was not the preferred method in this study. This was

mostly because the PCIA method involved the use of phenol, which is highly toxic. As the

protocols in this study were designed for use in a routine diagnostic laboratory, it was

preferable to use simpler methods suitable for low volume samples and high throughput

conditions. Also, the PCIA method was not as sensitive according to some researchers

(Rantakokko-Jalava and Jalava, 2002) as their protocol could only detect Streptococcus

pyogenes at more than 200,000 CFU and Haemophilus influenzae at 20,000 CFU.

Commercial kits were not used as there have been reports of contaminating material

(Evans et al., 2003; van der zee et al., 2002) that could be detected using the broad-range

16S rDNA method, thereby causing false-positives. In addition, commercial kits can be

expensive and increase the cost of laboratory tests.

4.3 PCR Optimisation

During PCR optimisation, certain conditions were observed that should be noted as

it can affect the overall results and performance of the assay.

The annealing temperatures for the primers used in this study were found to be

optimal at 63°C (Section 3.2.1). The expected annealing temperature for each primer was

approximately 5°C less than the melting temperatures and is as follows; NR=61.3°C,

nf=62.9°C, f3p= 65.1°C, f4n= 63.3°C, and r18n= 63.1°C. Therefore, the optimised

annealing temperature was the best match to the expected temperature of the f4n and r18n

primers, which is used for Gram-negative specific PCR; and the nf primer, which is part of

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the Pan-specific PCR primer set. Annealing temperature conditions were of low stringency

for f3p (Gram-positive specific primer) and stringent for NR (used for Pan and Gram-

positive specific PCR).

During optimisation of PCR for cycle times, 28 cycles were found to be optimal in

producing products in the Gram-positive specific PCR (Figure 3.7, lane 9). For Gram-

negative specific PCR however, 26 cycles of PCR were sufficient (Figure 3.6, lane 5).

Attempts were made to standardise the cycle times in order to run samples either in the

same tube or at the same time (to reduce waiting time and usage of the thermal cycler).

Eventually, a 26 cycle amplification procedure was selected as it was able to

produce amplifications in the Gram-positive specific PCR in a multiplex (Figure 3.16).

This allowed for a single thermal profile (and thermal cycler and test run) to be used on

several tubes of the same sample (Figure 2.4).

During optimisation for MgCl2 and Taq polymerase concentrations, it was observed

that a 554 bp Gram-negative specific band appeared in multiplex reactions containing

Gram-positive organism DNA (S. aureus) despite using Gram-negative specific primers

(Figure 3.8, lanes 2, 5, 9 and 12; Figure 3.9, lanes 2, 5 and 12; Figure 3.10, lanes 5, 9

and 12). This non-specific amplification had been reported in a paper using broad-range

PCR for Gram-typing (Klausegger et al., 1998) and implies a lack of specificity with low

stringency conditions. This was rectified by separating Gram-negative primers from Gram-

positive primers in subsequent amplification reactions.

During primer optimisation of f3p (Gram-positive specific) primer concentrations, a

non-specific 700+ bp band was observed (Figure 3.13, lanes 5, 9 and 12) that was not

present in the monoplex Gram-positive specific PCR (Figure 3.5, lanes 2, 5, 9 and 12). The

presence of this band in low stringency conditions could possibly be caused by mispriming

of 8 bases (5’-CTGGTCTG-3’) in the f3p primer to an area in the 16S rRNA (290-297 bp

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141

on the E. coli rRNA sequence) that is not the f3p target site (Figure AppC). The resulting

amplification product from this mispriming would be 784 bp in size and this fits the profile

of the non-specific band. This situation was rectified by increasing the stringency of the

Gram-positive specific PCR.

When multiplexing Pan, Gram-positive and Gram-negative primers, only Pan and

Gram-positive specific primers (nf, p3f and NR) were included in a duplex (Section 3.2.5).

Gram-negative primers (f4n and r18n) were performed in a separate reaction due to failure

to reduce non-specific priming when in a multiplex (as mentioned above). This difficulty

could have been encountered by other researchers, whose broad-range Gram-negative PCR

were typically in monoplex reactions (Klausegger et al., 1998; Carroll et al., 2000).

The mispriming of Gram-negative specific primers could be due to an inherent bias

in template annealing in multiplex or multitemplate amplifications (Suzuki and Giovannoni,

1996; Polz and Cavanaugh, 1998) in which the ratio of the initial template and the product

of amplification is skewed. This inherent bias could be aided by primer quality, whereby

primers with better amplification efficiency could lead to preferential amplification of the

template. As mentioned above, the final annealing temperature in the thermal profile

matches closely with the expected annealing temperature of the Gram-negative specific

primers. Furthermore, the primer quality (implying amplification efficiency as determined

by the FastPCR software, Section 2.4.1) of each of the primers is as follows: NR is 61, nf is

64, f3p is 71, f4n is 86 and r18n is 100, with a higher score indicating better amplification

efficiency. It can be surmised that the non-specific amplifications involving the Gram-

negative specific primers (f4n and r18n) were caused by the low stringency conditions

present in the multiplex (e.g. higher concentrations of Taq polymerase, and dNTPs), the

optimal annealing temperature for the primer set, and the high amplification efficiency of

these primers compared to the others.

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4.4 PCR Sensitivity

Results from PCR sensitivity tests (Section 3.4) showed that the lowest detection

limit for both the duplex Pan and Gram-positive specific PCR and the monoplex Gram-

negative specific PCR was 10 pg for E. coli and S. aureus DNA. The Pan-specific primer

set had a lowest detection limit of 1 ng in the duplex PCR but was 1 pg for both E. coli and

S. aureus in a monoplex PCR.

Calculations (Appendix G) show that approximately 1965 copies of the E. coli

genome are present in 10 pg of the template. This would mean that 197 genomes are present

in 1 pg of the template. The lowest detection limits for extraction methods (Section 3.1.4)

was 1000 CFU/ml or 5 CFU per reaction (as each PCR reaction use 5 µl of template

solution). Therefore, approximately 5 to 1965 CFU can be detected per reaction.

Comparatively, Klausegger et al. (1999) could detect 10 CFU of E. coli per reaction

and 1000 CFU of S. aureus per reaction, using pure culture templates and a 50 cycle PCR.

Harris and Hartley (2003) detected 10-100 CFU E. coli per reaction and 100-1000 CFU of

S. aureus per reaction which was then improved to 10-100 CFU of S. aureus per reaction

after changing methods of extraction. Schuurman et al. (2004) detected 100-200 CFU/ml

per CSF sample. Meanwhile, Carroll et al. (2000) detected 100 fg to 1pg on intraocular

fluid using a nested broad-range PCR and Wilkinson et al. (1999) detected 1 fg to 10 pg of

bacterial DNA per reaction on joint fluid using nested broad-range PCR.

The results from this study are comparable to the other studies, considering that the

numbers of cycles during amplification were lower and nested PCR was not utilized.

However, the sensitivity may be improved by using different methods of extraction or by

reducing the stringency in the PCR.

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4.5 PCR Specificity

The PCR primers used in this study were found to be quite specific when tested on

pure cultures (Section 3.5). Only one out of 12 of the cultures tested gave unusual results.

The Pan specific PCR produced amplifications on all bacterial cultures but the fungal

Cryptococcus neoformans sample produced no amplification as expected. The Gram-

negative specific PCR produced amplifications from all Gram-negative organisms but none

from Gram-positive organisms. The Gram-positive specific PCR produced amplifications

from all Gram-positive organisms except for Corynebacterium sp., and did not produce

amplifications from Gram-negative organisms.

To determine why the Gram-positive specific primers did not produce any

amplification from Corynebacterium sp., the Gram-positive specific primer (f3p) was

evaluated on BLAST (Section 2.5.4) using the “Search for short, nearly exact matches” tool

limited by an entrez query for “Corynebacterium jeikeium”. A match was found, thus a

target area matching the f3p primer is available on the organism. This implies that the lack

of amplified products was due to reasons other than a lack of f3p primer target area on this

particular organism. The16S rDNA broadrange PCR can be biased and DNA from different

species contain segments outside the template region that could inhibit PCR to different

degrees (Hansen et al., 1998). Also, the amount of bias depended on the position of primer

sites and could be overcome by using two different primer sets. It is possible that the

amplification on the Gram-positive specific primer site was inhibited by segments outside

the template region in Corynebacterium sp.

This confirms the need for separating the Gram-negative specific PCR from the Pan

and Gram-positive specific PCR, as it could be used to confirm or support the results of the

other test. There is a need for more pure culture samples to be tested on the various PCRs

used in the study.

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4.6 Sequencing

4.6.1 Fragment Size

According to Hugenholtz et al. (1998), sequences less than 500 nucleotides long are

sufficient for placement in a phylogenetic tree (thereby implying identity of organism) if the

sequences are closely related and there was more than a 90% identity with homologous

nucleotides, but in cases of novel sequences where less than 85% of the identity are similar,

500 nucleotides are not suitable for placement. Harris and Hartley (2003) sequenced only a

320 bp hypervariable region at the 5’ end of the 16S rDNA, which was used as sole

evidence of pathogenic infection in 71 out of 382 paediatric specimens tested at the Great

Ormond Street Hospital for Children (London). Rantakokko-Jalava et al. (2000) found that

sequences 164-484 bp in length was sufficient for sole evidence of diagnosis in 11 out of

459 patients hospitalised for various illnesses at the Turku University Central Hospital

(Finland). Tang et al. (1998) used the first 527 bp of the 16S rDNA to obtain genus

information on 72 unusual (i.e. unidentifiable by an in-house method) aerobic Gram-

negative bacilli isolates tested at the Mayo Clinic (Rochester, USA) and species information

on 67 of the isolates.

In this study, the usable sequencing results from the pure culture samples were 260 -

506 bp in length and placed at the 520-1073 bp region of the Escherichia coli 16S rDNA,

which is the middle third region of the 16S rDNA. Shorter sequences were preferred as it is

costlier to sequence DNA more than 600 bases in length. Analyses of the sequences

obtained from pure culture samples showed that the short fragments were suitable to

determine the identity of most organisms to genus level (Section 3.6 and 4.6.3). Therefore,

based on the pure culture sequencing results, the short fragment was deemed adequate for

use in identifying the 16S rDNA of organisms to the genus level.

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4.6.2 Sequencing Results Analyses and Cut-off Points

In order to determine the organism identity of the sequences obtained, it is important

that there is a standard cut-off point for identification to species or genus level during

comparison of the query sequence with sequences in the database.

Drancourt et al. (2000) sets the cut-off point for identification to species level at 16S

rDNA similarity from 99-100%, identification to genus level at 97-99% similarity with

sequences in GenBank, and a less than 97% similarity as a failure to designate genus.

Harris and Hartley (2003) noted that not all bacterial species have representatives in

database and that a difference of more than 1% could reflect either an incomplete database

or indicate a novel species. Also, they noted that some phenotypically distinct species can

share up to 100% identity in 16S rDNA sequence e.g. Escherichia coli and Shigella sonnei;

Bacillus antracis and Bacillus cereus, while some strains of the same species vary in 16S

rDNA by more than 10%. Their criteria for species identification was a 98-100% similarity

to more than one GenBank sequences of the same species or for tight clustering with

members of one species in an in-house database and genus identification was set at more

than 95% similarity to more than one species in GenBank sequences of the same species or

for tight clustering with members of one species in an in-house database.

Other researchers consider the highest scoring match as definitive of sequence

identity (Qian et al., 2001; Schuurman et al., 2004).

In this study, species identity on BLAST was considered to be a 99-100% similarity

to sequences in GenBank and genus identity as a 97-99% similarity to database sequences

with a highest scoring match and clustering of hits taken into consideration. The Harris and

Hartley (2003) definition of identity to more than one GenBank sequences of the same

species was not considered as even a single hit provided by the search could be indicative of

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146

a species match. This however, could cause a problem if the single sequence provided was

possibly an error in submission (Lactobacillus plantarum in Section 4.8.1)

The Classifier was useful in identifying the higher order taxa of the query sequence.

The highest similarity scores found using SeqMatch were considered if it was in agreement

with BLAST and clustering of results, as the similarity score using SeqMatch were often

lower than the 99-100% similarity determined by BLAST. If the RDP-II was not used in

conjunction with BLAST, sequence identity would be considered as the highest score from

“Type and Non-Type” and “Type strain only” searches on SeqMatch, clustering of results

to a particular species or genus, and probability of the organism belonging to a particular

taxa using the Classifier.

Overall, BLAST gives information about other species aside from bacterial and this

could give information about possible contamination, but can also complicate the search.

The RDP-II is annotated and contain only rRNA sequences, allowing for better searches but

no cut-off point has been determined as yet, with only highest scores and clustering patterns

to guide. Both BLAST and RDP-II were qualitatively compared in this study but where

BLAST gives only a general overview of taxonomic placement and the RDP-II gives a

more specific identification, both tools work well in conjunction with the other to provide

useful information on the whole.

4.6.3 Sequencing Analyses for Pure Culture Samples

The DNA from pure culture samples were sent for sequencing and the results

analysed using the BLAST and RDP-II programs. The names of the organisms obtained

were then investigated further to determine the extent of match to the culture results.

The Staphylococcus aureus pure culture (Section 3.6.1) was identified as either

Staphylococcus aureus or S. croceolyticus by BLAST. Biochemically, S. croceolyticus

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147

could be easily ruled out by a coagulase test as it tests negative; whereas S. aureus is a

coagulase-positive organism, indicating that a mistake in the identification from culture

results is not possible. A BLAST search using the full S. croceolyticus 16S rRNA gene

found that the sequence was not similar to the S. aureus sequence and a similarity match

possibly occurred because the query sequence was relatively short (293 bp). The S.

croceolyticus (GenBank AY953148) which showed up on the BLAST search was from an

unpublished data and was a new coagulase-negative species isolated from otic infections

(Dajcs et al., 2005). If the Harris and Hartley (2003) cut-off point for sequence

identification were to be used (in which species identification was a 98-100% similarity to

more than one GenBank sequences of the same species; Section 4.6.2), S. croceolyticus

could be excluded as there was only one similarity hit on this species using the BLAST

search. Furthermore, a high clustering of results on S. aureus using SeqMatch indicates that

the organism was of the species S. aureus.

The Acinetobacter baumanii pure culture sample (Section 3.6.6) was found to be

either A. baumanii or A. calcoaceticus. Both species are often referred to as the A.

calcoaceticus- A. baumanii complex, as biochemically they are both glucose-acidifying and

are difficult to be differentiated from each other. Reports of infection caused by A.

baumanii does not necessarily test for the specific organism, rather, it is presumptive as it

could be any of the glucose acidifying organisms in the complex; and also, delineation of

species within this genus is still the subject of research e.g. A. calcoaceticus subsp.

anitratus was not formally accepted by taxonomists and has been found to be A. baumanii

(Bergogne-Bérézin and Towner, 1996). Whether there is a misidentification of the organism

prior to sequencing and submission to the database, or a name change that was not updated,

A. baumanii and A. calcoaceticus could not be differentiated using sequencing and

identification could only be carried out to the genus (or complex) level.

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The Klebsiella pneumoniae culture (Section 3.6.7) had a 100% similarity with K.

pneumoniae as well as Enterobacter dissolvens. These two species can be differentiated

biochemically by the motility test in which K. pneumoniae is found to be non-motile

(Farmer et al., 1985a). A BLAST search using a full E. dissolvens 16S rDNA gene

(296079) from GenBank matched 98.8% with K. pneumoniae which would imply that both

species were from the same genus. High clustering in both BLAST and RDP-II analyses

indicate that the organism is K. pneumoniae but E. dissolvens could not be excluded without

further tests.

The Enterobacter sp. pure culture was found to have matches to organisms of the

same genus as well as others of the genus Kluyvera and Pantoea (Section 3.6.8). Kluyvera

intermedius was formerly of the genus Enterobacter (Pavan et al., 2005) as was Pantoea

agglomerans which had a long history of name changes according to the List of Prokaryotic

Names with Standing in Nomenclature (http://www.bacterio.cict.fr/; last update Nov 10,

2005). Heterogenous biochemical reactions make identification difficult among the

enterobacters e.g. K. cryocrescens can be differentiated from others in the genus Kluyvera

by a negative Voges-Proskauer (VP) test but K. intermedius is VP positive and can not be

differentiated from other enterobacters (Farmer et al., 1985a). The organism was considered

to be an Enterobacter sp.

The Escherichia coli pure culture (Section 3.6.9) showed matches to E. coli, E.

fergusonii, Shigella boydii, S. flexneri, S. sonnei and Photorhabdus luminescens. E. coli and

Shigella sp. are biochemically quite similar and often referred to as the E. coli-Shigella

complex. The complex is difficult to classify by 16S rRNA studies (Christensen et al.,

1998) and DNA hybridisation studies found them to be so similar as to be same species

evolutionary speaking; but the two different genera were maintained because the Shigella

sp. causes bacillary dysentery (Farmer et al., 1985a). E. fergusonii can be differentiated

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149

biochemically from E. coli as the former can ferment adonitol, cellubiose and D-Arabitol.

However, a BLAST search using an E. fergusonii sequence found high similarity of more

than 99% among various Shigella sp. and E. coli and thus cannot be differentiated using the

16S rDNA PCR and sequencing (Farmer et al., 1985b). Photorhabdus luminescens is

biochemically and molecularly (by DNA hybridisation with similarity of 20%) distinct from

E. coli, has a weak bioluminescence and is an insect pathogen that has been isolated from

humans (Peel et al., 1999). However, a BLAST of the P. luminescens (GenBank

AY444555) 16S rRNA sequence found that it only differed from S. sonnei in 2 bases and

from E. coli in 3 bases out of 1439 bases. This suggested that E. coli could not be

adequately identified using the DNA sequence analysis, and final identification would

depend on the clinical and biochemical examination of the samples.

The Proteus sp. pure culture (Section 3.6.10) showed matches to Proteus mirabilis

or P. vulgaris. The two sequences could be differentiated using the spot indole test whereby

P. mirabilis is indole-negative and P. vulgaris is indole-positive (Bale et al., 1985).

However, a full sequence BLAST test of sequences from the two organisms found only

minor differences which made it difficult to differentiate by the sequences in the database.

Organisms whose query sequences had high sequence match and clustering and did

not share results with other species were Enterococcus faecalis (Section 3.6.2),

Corynebacterium sp. (Section 3.6.3) which was identified as Corynebacterium jeikeium,

Neisseria gonorrhoeae (Section 3.6.4), Haemophilus influenzae (Section 3.6.5), and

Stenotrophomonas maltophilia (Section 3.6.11)

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4.6.4 The Limitations of the 16S rDNA PCR and DNA Sequence Analyses for the

Identification of Bacterial Isolates

The determination of the 16S rDNA sequence does not necessarily lead to species

identification as shown in the case of the Enterobacteriaceae, particularly for

phenotypically and taxonomically closely related organisms like Escherichia coli-Shigella

species, and Klebsiella-Enterobacter species (Section 4.6.3). The method may be more

appropriate for the determination of inter- or intragenomic relationship than for speciation

(Fox et al., 1992). It has been said that identical 16S rDNA genes can be found in bacteria

with highly divergent genomes and geophysiologies (Jaspers and Overmann, 2004). DNA-

DNA reassociation has been reported to be superior to 16S rDNA sequencing as some taxa

show a higher level of rRNA variability and some with little variability (Stackerbrandt and

Goebel, 1994).

The difficulty in speciation using 16S rDNA sequence analysis may be caused by

interoperon variation within a strain, strain-to-strain variation within a species, inadequate

taxon delineation, sequencing or other laboratory errors. These may cause ambiguous

results as the accuracy of the sequence depends upon the proper characterization of a strain.

(Clayton et al., 1995; Janda and Abbott, 2002)

Previously, the 16S rRNA gene was thought to be stable but comparative sequence

analyses reveal fragment inaccuracies of short segments containing an abnormally high

number of non-random base variations in the bacterial rDNA of some species, which were

believed to be caused by lateral gene transfer (Wang and Zhang, 2000).

These limitations mean that the 16S rDNA gene analysis alone is insufficient and

there must be efforts to analyse more than one set of genes in a multilocus analysis during

delineation of related species (Hanage et al., 2005). A small number of carefully selected

bacterial gene sequences, such as the recN (a recombination and repair protein-encoding

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gene), thdF (the gene that encodes for the thiophene oxidation enxyme) and rpoA (the gene

that encodes the RNA polymerase α-subunit), can be equal or superior to DNA-DNA

hybridization for determining relatedness (Zeigler, 2003).

4.7 PCR on Clinical Samples

In this section, the Gram-typing by PCR (Section 3.8) is discussed and the overall

assay results will be further elaborated in Section 4.9.

The Pan-specific PCR detected some culture-negative samples as PCR-positive and

failed to detect some culture-positive samples. However, all samples positive in the Pan-

specific PCR could be amplified by either Gram-positive or Gram-negative primers as well,

indicating that the Pan-specific primers are specific for both Gram types.

From the total number of PCR-positive samples, 11 out of 30 (36.7%) were typed as

Gram-positive organisms while the remaining 19 (63.3%) were typed as Gram-negative

organisms. By culture, 14 out of 31 samples (45.2%) were found to be Gram-positive

organisms while the remaining 17 (54.8%) of samples were Gram-negative. In culture-

positive samples, there was complete agreement between the Gram-types obtained by PCR

and by culture.

However, PCR was negative in three of 17 (17.6%) samples that grew a Gram-

positive organism and in seven of 14 (50%) of samples that yielded Gram-negative

organisms. This implies that the Gram-positive organisms were not as efficiently detected

by the PCR techniques as compared to Gram-negative organisms. One possible reason

could be the differences in the cell wall structure among the two Gram-types, the Gram-

positive cell wall being more difficult to lyse to release DNA for amplification. DNA

extraction by mechanical disruption had been suggested as a method to improve the

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sensitivity of PCR detection of Gram-positive bacteria (Rantokokko-Jalava et al., 2000;

Harris and Hartley, 2003).

Culture was negative in four of 11 (36.4%) samples amplified in the Gram-positive

PCR compared to five of 19 (26.3%) amplified in the Gram-negative PCR, suggesting that

possible false PCR-positives are more likely with the Gram-positive PCR. However,

application of the Fisher exact test showed that the difference is not significant.

4.8 Sequencing on Clinical Samples

4.8.1 Clinical Samples that Gave Positive Results by Culture and 16S rDNA PCR.

As previously mentioned, those from the family Enterobacteriaceae (Escherichia

coli, Klebsiella pneumoniae and Enterobacter sp.) were difficult to be differentiated using

the 16S rDNA sequencing analysis (Section 3.6). Analyses of the sequencing results of

some of the clinical samples showed results similar to those of pure culture DNA

sequencing analysis (Section 4.6.3) and could not be elaborated further. Among them were

culture-identified Escherichia coli (P002, P056, P055; Section 3.9.1c) that were confirmed

by 16S sequencing analysis as the Shigella-Escherichia coli complex; the Gram-negative

rod in the sample B076 was identified as either Shigella boydii or E. coli (Section 3.9.1l);

the culture-identified Enterobacter sp. (C065; Section 3.9.1a) that was linked to

Enterobacter sp., Pantoea agglomerans and Kluyvera cryocrescens; and the culture-

identified Klebsiella pneumoniae samples of C089 and B082 could not be differentiated

between K. pneumoniae and Enterobacter dissolvens (Section 3.9.1b). However, the K.

pneumoniae identified by culture in samples P045 and P063 were found to be definite K.

pneumoniae by sequencing analysis (Section 3.9.1b). Other samples with similar

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explanations to those mentioned in Section 4.6.3 were samples P007, B078 and B079

(Section 3.9.1c) which were identified as either Acinetobacter baumanii or A.

calcoaceticus; and sample P017 which was culture-identified as Staphylococcus aureus but

could not be differentiated from S. croceolyticus and S. haemolyticus, both of which were

coagulase-negative Staphylococci (Section 3.9.1h).

Group G Streptococci were isolated by culture in sample P051 (Section 3.9.1g) and

identified as Streptococcus dysgalactiae, which is indeed a member of that group.

Sequencing analyses could speciate the microorganism present in this sample.

The culture-identified Streptococcus sp. (C003; Section 3.9.1f) was found to be

either Streptococcus dysgalactiae or S. difficilis. The two species could not be resolved

further using this method as they were reported to have a high genetic similarity i.e. 100%

for 16S rRNA genes despite having biochemical differences (Kawamura et al., 2005).

However, compared to the routine laboratory culture diagnosis, the sequence analyses

managed to identify down to only two probable species names. There was an agreement

with culture results in the sample, with sequencing providing a narrower target for

identification.

The samples P004 and P029 (Section 3.9.1d) were found by culture methods to

contain Enterococcus sp. but sequencing analyses identified the 16S rDNA as belonging to

Enterococcus faecalis, E. saccharolyticus and Lactobacillus plantarum. The E. faecalis and

E. saccharolyticus were able to be differentiated into species lines using 16S rDNA analysis

(Monstein et al., 1998) but could not be resolved in this study. L. plantarum could be easily

be differentiated via molecular means (Moreira et al., 2005) and thus should not show up in

the search. Further investigation using the GenBank database showed that only one L.

plantarum strain was found by the similarity search, i.e. strain PFK2 (GenBank DQ295035;

Sequence ID: S000627085) which had its genus wrongly listed as Enterococcus.

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Interestingly, the full sequence of the L. plantarum PFK2 is similar to the E. faecalis PFK3

sequence (GenBank DQ295036; Sequence ID: S000627086) and both strains were from

unpublished data by similar authors (Dan et al., 2005). Further checks on BLAST using

sequences from other strains of L. plantarum available on the database showed that it could

be differentiated quite clearly from members of the genus Enterococcus. It is possible that

there was a mistake in the database, and therefore the sequencing identification should read

as Enterococcus sp. which is in agreement with that of culture.

The organisms in samples B073 and B074 (Section 3.9.1k) were culture-identified

as coagulase-negative Staphylococci, and DNA amplified from the samples were similar to

those of Staphylococcus caprae, S. epidermidis, S. capitis, and S. saccharolyticus, all of

which are coagulase-negative Staphylococci. The members of this group could not be

resolved further into individual species in other studies, where the analysis of the HSP60

gene instead of the 16S rDNA was suggested (Kwok et al., 1999). The rpoB gene was also

suggested to speciate Staphylococci, but the 16S rDNA sequencing and analyses still

remain suitable for higher classification above the genus level (Drancourt and Raoult,

2002).

The DNA amplified from sample B080 was found to be similar to those of

Salmonella typhimurium instead of the culture-identified S. enteritidis (Section 3.9.1j).

Both species are heterotypic synonyms of Salmonella enterica subsp. enterica (ex

Kauffman and Edwards 1952) Le Minor and Popoff 1987, subsp. nov. according to the List

of Prokaryotic Names with Standing in Nomenclature (http://www.bacterio.cict.fr/). The

genus has a long history, which is not yet resolved with regards to nomenclature (Tindall et

al., 2005) and thus, the GenBank database would have several naming systems co-existing,

causing discrepancies during similarity searches. However, there was an agreement in

identification down to genus level.

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Pseudomonas aeruginosa was isolated by culture from the sample P014 but

sequencing analysis did not agree and instead, identified the amplified DNA as belonging to

Citrobacter sp. (Section 3.9.1i). The two organisms are easily differentiated by biochemical

or molecular methods. Possible reasons for the misidentification (either by culture or

sequencing analyses) is; that Citrobacter sp. was dismissed as a contaminant and not noted

in the test work-sheet, or the P. aeruginosa contaminated the sample plate but was not

present in the original specimen collected from the patient. There was no indication (by

literature) that both organisms had similar 16S rDNA, nor was there evidence of

contamination during PCR according to the controls.

4.8.2 Clinical Samples Found Positive by 16S rDNA PCR but Negative by Culture

This section will discuss the samples that had amplifiable 16S rDNA targets despite

being found negative for growth by culture methods (Section 3.9.2). The target sequences

were identified as belonging to certain organisms by analyses of the sequencing results.

The DNA amplified from the sample C016 was identified by sequencing analysis as

Brevibacillus sp. Organisms from this genus had been isolated before from ‘sterilised’ milk,

water-borne illnesses, pharmaceutical manufacturing plants and blood; with no

characteristic profile as yet for the genus (Logan et al., 2002). It is possible for this

organism to be found in CSF but it is more likely to be an environmental contaminant.

The C027 and S033 samples yielded DNA that was identified as Acinetobacter

baumanii or A. calcoaceticus, which has been discussed previously (Section 4.6.3). In

neonatal meningitis, Acinetobacter sp. is a possible pathogen; in adults this is unlikely

unless the patient has special predisposing factors. The sample C027 was obtained from a

male patient, 50 years of age, and the CSF sample was noted to be bloody. Patient history

and information about prior antibiotic treatment could not be ascertained.

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The DNA amplified from P020 was also identified as Acinetobacter baumanii or A.

calcoaceticus but with the addition of similarity hits on A. rhizophaerae (GenBank

AY364536) which was not validly published at the time of submission of entry (2003), nor

was it available on the List of Prokaryotic Names with Standing in Nomenclature

(http://www.bacterio.cict.fr/) as of the end of 2005. It could not be determined if A.

rhizophaerae was a possible lab contaminant or if it has clinical implications. However,

there was evidence that P020 was obtained from a patient who was treated with antibiotics

prior to sample collection.

The DNA from C033 showed similarity with sequences from the genus Planococcus

and Planomicrobium which were related to the genus Bacillus. The former two were

usually isolated from marine water, and seafood (fresh or processed) and reportedly isolated

from a traditional Korean fermented food (Yoon et al., 2001). There was also similarity to

Bacillus infernus, which is a strict anaerobe isolated from deep below the land surface

(Boone et al., 1995). As yet, there are no reports on whether it has been isolated from

clinical samples, or even as a common lab contaminant; thus, taking into consideration the

short sequence sent for search (224 bp) it was likely that the target DNA was obtained from

an organism somewhat similar to Bacillus but has not been described, is a PCR-based

chimera, or simply a contaminant DNA.

The sequences obtained from sample C051 was identified as Oceanobacillus

iheyensis which is a deep-sea, halotolerant, alkaphilic species which grew at salinities

between 0-21% (w/v) NaCl at pH 7.5 (Lu et al., 2001). No clinical cases have as yet been

accorded to this organism but it was found to be comparatively close to B. subtilis using

16S rDNA sequence analyses. It is possible that the DNA from this sample was from B.

subtilis but is an unreported strain or a chimera.

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157

Sequences from Brevundimonas aurantiaca or Caulobacter henricii were found to

be similar to those amplified from the sample C067. The two species are closely related as

some species from the genus Brevundimonas fall within the Caulobacter cluster. Both

species are also usually found in fresh or marine water and the genera have not as yet been

fully described (Sly et al., 1999). The clinical significance of either of these samples could

not be determined.

The DNA amplified from the S010 sample had sequences that matched those of

Sphingomonas sanguinis. This organism has been isolated from clinical samples but its

causative role in infections is uncertain (Takeuchi et al., 2001).

The sample S017 yielded DNA that had similarities with sequences from the species

Streptococcus constellatus, S. intermedius and S. anginosus, all of which can be found

within the S. milleri group. The S. milleri group were known to cause abscesses and were

found in the central nervous system, CSF, brain abscesses, respiratory tracts,

gastrointestinal tracts, abdominal pelvic sites, genitourinary sites, skin, soft tissue and bones

as well as blood cultures and is very likely to be the organism responsible (Whiley et al.,

1992) for the infection in S017. The species in the group can be differentiated

phenotypically (Whiley et al., 1990) and by 16S rDNA PCR (Clarridge et al., 2001) but not

by the sequences amplified in this study.

The following are several aspects to consider when analysing the results discussed

in this section. It is possible for easily isolated organisms to be culture-negative (e.g.

Acinetobacter baumanii), and then found in the sample by using 16S rDNA PCR

(Drancourt et al., 2000). In most cases, it is not known if the DNA was from an infection or

from a laboratory contaminant (Nikkari et al., 2001). Also, researchers are constantly

finding new species never before isolated from humans using 16S rDNA (Drancourt et al.,

2004), where some of the organisms found were initially isolated from extreme conditions

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(Eckburg et al., 2003). Although some of the organisms identified by 16S rDNA analysis

are not previously recognized as human pathogens, in immunocompomised patients, it is

possible that they can cause an infection. For these reasons, it is possible that PCR and

sequencing analyses were able to identify cause of infection in the samples above.

Possible reasons for the failure of culture include (i) patients could have undergone

antibiotic treatment with or without the knowledge of the doctor treating him/her at UMMC

(patients could have sought treatment elsewhere and this would not have been documented),

(ii) bacterial cells causing the infection could have degraded due to activity in the bodily

fluids, (iii) the non-viable cells would not have grown on culture but can be detected using

the molecular methods in this study, (iv) there was inhibition in the bodily fluids that could

have been inhibitory to culture but not to PCR and sequencing, and (v) routine hospital

diagnostic laboratories are not equipped to detect some of these organisms.

4.8.3 Clinical Specimen Found Negative by 16S rDNA PCR but Positive by Culture

The organisms that could not be detected by 16S rDNA PCR but were positive by

culture (Section 3.9.3) were bacteria that are commonly isolated in routine laboratories, e.g.

Staphylococcus aureus, Bacillus sp., Enterococcus sp., Pseudomonas aeruginosa,

Acinetobacter baumanii, and Escherichia coli. With the exception of P. aeruginosa, all of

these samples were identified by 16S rDNA sequencing analysis in this study (Sections

4.6.3, 4.8.1 and 4.8.2).

Of the culture-positive samples tested in this study, two out of five (40%) from CSF

samples could not be identified by PCR, while six out of 17 (35.3%) and two out of 9

(22.2%) of PF and BCB samples respectively could not be identified by PCR.

The reasons for the high number of PCR-negative culture-positive CSF samples

could be: (i) the crude boiling method used to extract DNA from CSF is not sufficiently

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effective, (ii) as CSF samples are only available in small volumes, a much smaller volume

was used for DNA extraction than for other specimen types, (iii) the number of CSF

samples examined was small, (iv) CSF contains proteins that degrade DNA at a higher rate

than proteins in other specimen types.

Generally, molecular methods fail to detect organisms in culture-positive specimens

when: (i) the target DNA has been degraded, (ii) there are low numbers of DNA copies in

the sample, and (iii) the extraction method used does not efficiently release DNA from cells

and remove inhibitors of DNA amplification.

4.9 Comparison of the 16S rDNA Assay with Culture

The total results in Section 3.10.1 were broken down into analyses of sample types

in Section 3.10.2 and the performance of the assay was statistically compared to culture in

Section 3.10.3. There was a 91.8% agreement in results between the 16S rDNA assay and

culture (Section 3.10.1), whereby 21 samples were PCR and culture-positive and 193

samples were PCR and culture-negative (214/233 samples). Overall, the results of both

PCR Gram-typing and identification by DNA sequence analysis were in agreement with

culture results, with the only discrepancy being sample P014 (Section 3.9.1i) where PCR

Gram-typing was in agreement (Gram-negative organism) but sequence identity was not i.e.

instead of Pseudomonas aeruginosa, sequence analysis identified the target sequence to be

from Citrobacter sp. The reason for this discrepancy could be that the sample had a mixed

culture or was contaminated at some stage during investigation.

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Generally, the results show that the 16S rDNA assay was almost at par with the

culture method. Discordant results that were deemed false-positive could have been due to

contaminants or a better detection of DNA by the 16S rDNA method. Either of these two

explanations could be possible but due to certain limitations of this study, follow-up on the

patient samples could not be performed to determine the possible cause of false-positives.

The false-negatives could be more easily explained by the following: as the samples were

collected from the Diagnostic Microbiology Laboratory of UMMC post-culture, DNA

could have already degraded despite efforts to preserve them by freezing or immediate

extraction of DNA. There was also the possibility that the cells were in very low quantities,

enabling growth by culture but losing DNA through the extraction process. Also, there was

the slim possibility that the culture plate itself was contaminated, leading to a positive

culture result despite there being no microbes in the specimen. Inhibition of the PCR was

also considered, but this was unlikely, as each of the samples were spiked by a sample

control.

The overall specificity of the 16S rDNA PCR and sequence analysis was high at

95.54% with a NPV of 95.1%, while the overall sensitivity was 67.74% with a PPV of 70%.

However, different sample types had different scores for sensitivity, specificity, positive

predictive values (PPV) and negative predictive values (NPV). Generally, it was found that

if specificity was high, sensitivity would be slightly sacrificed and vice versa e.g. if steps

were taken to reduce false-positives in terms of contaminants, there is a higher likelihood

that sensitivity would be lowered, and also a more sensitive method such as nested PCR

would have a higher chance of being contaminated.

Of the four sample types, the type that best matches culture results using the16S

rDNA assay was the BCB samples. The specificity was very high at 100% as there were no

culture-negative samples that were PCR-positive. This probably reflects the aseptic

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161

techniques used in blood collection and processing to prevent contamination. The chance

of a positive PCR result being accurate (PPV) was at 100%. The high sensitivity and PPV

could be attributed to the fact that BCB is a culture medium and after incubation, the

bacterial count is generally high enough to support PCR detection. Sensitivity was

acceptable at 77.78% and the probability of the negative results being accurate was at

95.2%, as two out of nine culture-positives were not detectable by PCR. Both of these are

of Bacillus sp. and non-detection could have been due to sedimentation in the bottles, the

lack of viable DNA present, or the target DNA being somehow inhibited, and most likely,

the isolates were laboratory contaminants introduced during culture. Instrument false-

positive (in which the system signalled a positive but was Gram-stain and culture-negative

on chocolate agar) was reportedly at 1.3% but could not be verified in this case (Qian et al.,

2001).

For PF samples, the specificity, sensitivity, PPV and NPV were 97.83%, 64.71%,

91.7 % and 88.2%, respectively. The sensitivity was affected by the inability of the assay to

detect six culture-positive samples by PCR. The organisms that could not be detected by

PCR were Pseudomonas aeruginosa, Staphylococcus aureus, Acinetobacter baumanii and

Escherichia coli, of which the latter three were found to be detectable by this assay

(Sections 3.6.1, 3.6.6 and 3.6.9). These negative PCRs could have been caused by small

bacterial loads vastly diluted in large volumes of peritoneal fluid collected or degradation of

DNA in the samples.

Sensitivity of the CSF samples was low at 60% and the PPV very low at 37.5%,

indicating a high level of false-positives. This is very likely because of the 8 PCR-positive

samples, 5 were not initially detected by culture. The low (60%) sensitivity for CSF

samples indicates that this assay, without further optimization, may not be useful for the

diagnosis of bacterial meningitis. The very low PPV (37.5%) is due to the large number of

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PCR-positives not confirmed by culture (Section 4.8.2). However, except for Acinetobacter,

the other 4 organisms identified by PCR are very likely to be laboratory contaminants.

Hence, the low PPV probably reflects the high risk of false-positives in a very sensitive

DNA amplification assay.

For the SF samples, sensitivity could not be determined as there were no positive

cultures. With culture as the gold standard, all three PCR positive results should be

classified as false-positives but the organisms detected were possible causes of infection in

synovial fluid and the patients’ symptoms and signs suggested bacterial infection. Hence

the results could indicate a higher sensitivity for PCR than culture. The 100% NPV suggests

that the chance of a false-negative PCR is negligible.

4.10 Limitations of the 16S rDNA PCR and DNA Sequencing

Assay for Use on Clinical Specimens

Limitations of the PCR and sequencing assay in this study are inherent problems

present in the PCR method - the bias caused by template annealing during the PCR (Suzuki

and Giovannoni, 1996) and the bias in the template to product ratio in multitemplate PCR

(Polz and Cavanaugh, 1998). This bias could cause a skew in the products and this should

be taken into consideration as there can be more than one organism present in clinical

samples.

Another limitation would be the effect of genome size and the 16S rDNA copy

number on PCR amplification as it is impossible to quantify the number of species

represented if the parameters (of each organism) are unknown (Farrelly et al., 1995; Fogel

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et al., 1999). An infection with a low 16S rDNA copy number could be missed if organisms

from normal flora or other contaminants that have a higher copy number are also present.

The organism detected in a clinical specimen by PCR may not be cause of infection

as the organism amplified could be a by-stander that is present in larger numbers than the

infecting agent and therefore more easily amplified by PCR (Fredricks and Relman, 1996).

Even sterile body fluids like blood of healthy subjects may contain bacterial rDNA of

unknown origins as a result of contamination (Nikkari et al., 2001).

A further limitation of the PCR for diagnosis is its inability to distinguish living

from dead cells (Eckberg et al., 2005). Hence, DNA remaining after a previous or treated

infection may be amplified to give a wrong diagnosis of current infection.

The formation of chimeric sequences in the public database is an especially

worrying limitation of this method (Hugenholtz and Huber, 2003). The frequency of

forming chimeric PCR molecules increases during co-amplification of 16S rDNA from

mixed bacterial genomes or from different rDNA copies in the same organism and the

chimeras are especially abundant if lower amounts of 16S DNA are present during PCR

(Wang and Wang, 1997).

The 16S rDNA assay in this study used an in-house extraction method instead of

kits, thereby requiring different methods for different sample types and indicates

standardisation issues in the future. There were indications that the current extraction

methods used may not be fully releasing DNA especially from Gram-positive cells. A

mechanical disruption method has been recommended (Harris and Hartley, 2003).

The PCR protocols in the study were only able to detect 1,965 genomes in 5 µl of

template DNA (Appendix G). Steps have to be taken to increase the sensitivity of the

broad-range PCR without increasing the rate of detecting false-positives.

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Incidences of mixed cultures, where 16S rDNA sequences from more than one

bacterial species were present in the specimens, were not addressed in this study. Should

mixed cultures be indicated, PCR cloning should be performed and the colonies amplified

and sequenced (Harris and Hartley, 2003).

Also, the efficacy of the PCR in Gram-typing were not tested on organisms with

ambiguous cell wall staining types e.g. organisms of the genus Mycobacterium.

4.11 Significance of Findings

There are two factors to be considered when presenting the significance of the

findings in this study. Firstly, can this method be adopted by laboratories performing

routine clinical diagnostic services? Secondly, if that is not possible, what applications can

the findings be useful in?

The findings show that for this technique to be useful in a clinical laboratory setting,

optimisation and improvements should be carried out in the following areas:

(a) The DNA extraction methods should be better able to break down cellular material

in order to retrieve amplifiable DNA. Preferably, one standard method of DNA

extraction should be established for DNA extraction from the different of sample

sources as this will allow simplicity in protocol. Commercial kits (which are quite

affordable) or mechanical disruption can be investigated to allow for a more

sizeable increase in DNA yield and purity.

(b) The panel of broad-range primers should be increased to include primers specific

for viruses or fungi. Different target areas in addition to the 16S rDNA presently

studied should be investigated to improve the identification of organisms.

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(c) A more rapid method of obtaining or viewing results, for example, Real-Time PCR

can be looked into to allow faster diagnostic tests.

(d) Automated DNA sequencing should be carried out as an "in-house" technique with

dedicated hospital staff to run the service. This will allow more rapid analysis.

(e) Better guidelines for collection of samples and dissemination of results need to be

drawn up. These are extra-laboratory activities would require a different mindset,

training and collaboration of clinicians, particularly in ordering laboratory work on

specimens, or when determining treatment based on the results.

The current broad-range PCR techniques could ideally be a routine tool in clinical

diagnostic laboratories of the future. The existing techniques developed in this study can

still be administered in an ad hoc basis on samples whereby;

(a) Clinical symptoms show clear indication of bacterial infection but culture was

negative by conventional methods. Direct amplification and sequencing from the

samples are possible. Screening of all culture-negative samples could be performed,

and the PCR-positive samples could be further investigated.

(b) Organisms were cultured but could not be identified by standard biochemical tests.

In most cases, save for the Enterobacteriaceae, identification could be performed up

to the genus level. The technique could serve as a screening tool for these

"unidentifiable" cultures and initial identification could be determined.

A limitation of this study is the lack of coordination between the laboratory and the

clinician. This resulted in an inability to address the issues of false-positive and false-

negative results beyond the confines of the laboratory. However, this was only a

preliminary study and the findings are nevertheless significant as they will provide a

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166

framework where future steps can be planned to improve and adapt the techniques for

implementation in a clinical diagnostic laboratory. It is absolutely crucial that consulting

clinicians be involved in the pre-laboratory set up (sample collection to ensure proper

collection and storage before despatch to the laboratories) and in the post-laboratory results

(identification of the organisms and the proper treatment options).

4.12 Conclusion

A broad-range PCR protocol was developed and optimised that was able to detect

bacterial 16S rDNA using Pan-bacterial specific primers, and Gram-type using Gram-

positive and Gram-negative specific primers. Sequencing and sequence analyses of the

amplified DNA were able to provide higher order identification of bacteria without the need

for cultivation. The optimised 16S rDNA PCR and sequencing assay can be applied for use

on various clinical samples in a routine clinical diagnostic laboratory, albeit with

limitations, most notably regarding the sensitivity of the method and issues with analyses

using the public database.

The broad-range 16S rDNA could be prone to contamination, and this was

prevented by good laboratory practices, dedicated material and preparatory areas, and

inclusion of positive and negative controls to detect false-positive and false-negative results.

Extraction methods were chosen using a qualitative complexity ranking of the method and

observation of the results obtained from the DNA amplification of the extracted samples.

The boiling method was found to be effective for CSF samples, AH method for BCB and

PF samples, and DNAzol for SF samples. Commercial kits were not used due to cost and

contamination issues, and the PCIA method was not preferred due to the use of highly toxic

materials, and the high cost of waste removal. The extraction methods developed were

Discussion

167

adequate for this study but a more standardised and sensitive extraction method should be

evaluated and optimised e.g. using mechanical disruption as a method to improve the

sensitivity of PCR detection of Gram-positive bacteria.

The Gram-positive and Gram-negative primer pairs required high-stringency

conditions when placed together in the same reaction. As this affected the sensitivity of the

method, the two primer sets were subsequently separated into separate reactions. The

optimised duplex PCR for Pan and Gram-positive specific PCR detected 10 pg of

Staphylococcus aureus DNA while the Gram-negative specific PCR detected 10 pg of

Escherichia coli DNA. The Gram-positive and Gram-negative specific primers were able to

differentiate 12 pure culture samples with known identities into their respective Gram-

types. Also, the Gram-typing results of PCR-positive clinical samples were in agreement

with the results by culture. Therefore, Gram-typing by PCR was suitable for differentiating

organisms into Gram-type, and the results were available on the same day (about 5 hours

total) or by the next day. This will allow sufficient information to begin preliminary

antibiotic therapy.

A major drawback of the method was using the 16S rDNA analysis to determine

bacterial identification to species level. While the method is sound for higher order

identification, there were problems in resolving the species identity (and on occasion genus

identity) for organisms within the family Enterobacteriaceae and the genus Staphylococcus.

The 16S rDNA analysis was not as useful as phenotypic characterization for common

bacteria like the Staphylococci that are easily classified by coagulase test and Klebsiella-

Enterobacter that are differentiated by motility. These problems are inherent to using this

gene for gene analyses, thereby other genes could be suggested to replace or enhance the

usage of 16S rDNA gene analyses.

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Analyses using the public database were also problematic as anyone could upload

sequences, some of which are unpublished and unverifiable. For adequate understanding of

the results obtained by Gram-typing and bacterial identification, there is a need for an

understanding of prokaryotic taxonomy and clinical microbiology (to evaluate if the sample

is a probable contamination or has clinical implications), which could make the method

difficult as a routine diagnostic assay.

The overall specificity of the 16S rDNA PCR and sequence analyses was high at

95.54% with a NPV of 95.1%, while the overall sensitivity was 67.74% with a PPV of 70%.

The 16S rDNA PCR assays were in agreement with culture results in 91.8% of the samples.

Of the four sample types, the type that best matches culture results using the 16S rDNA

assay was the BCB samples as the BCB is a culture medium and after incubation, the

bacterial count is generally high enough to support PCR detection.

There were no unusual organisms found in culture-negative clinical specimens. The

clinical significance of the DNA found in PCR-positive samples obtained from culture-

negative infections could not be determined. More details on the patient case history should

be obtained in future studies involving the same methods.

The 16S rDNA PCR assay in this study had been found to be useful for rapid Gram-

typing of bacteria in patient samples, but bacterial identification via sequencing and

analyses was not as useful or reliable as expected when used in a routine microbiology

laboratory diagnostic capacity. However, sequencing analyses can be helpful in cases where

other methods fail in identifying the organism, as it provides useful information for

identification to higher order taxa.

Appendices

Appendices

Appendix A- Lists of Chemicals, Media, Kits and Equipment

Chemicals

Trizma hydrochloride, Tris-HCl

Lysozyme

Isoamyl alcohol

Natrium hydroxide, NaOH

Boric acid

Chloroform

Absolute ethanol

Tris base (Molecular Biology Grade)

Agarose LE Grade

Disodium ethylenediaminetetraacetic acid, EDTA

Sodium chloride, NaCl

Buffer-saturated Phenol

Ethidium bromide (10 mg/ml)

Proteinase K

Tri-sodium citrate

Sodium Dodecyl Sulphate, SDS

Sodium acetate

DNAzol Molecular Research Centre, Ohio USA

Merck, Germany

Invitrogen, Ca, USA

BDH Lab, England

Promega, USA.

Univar, Australia

Sigma, USA.

Appendices

Media

Luria-Bertani (LB) broth Gibco BRL, USA

Nutrient agar Media room, UMMC Microbiology Diagnostic Laboratories

Kits

Taq polymerase (recombinant, 1U/µl), supplied with

-10x PCR buffer with (NH4)2SO4 and

-25mM MgCl2

Deoxynucleotide triphosphates, dNTPs

-(dGTP, dATP, dTTP and dCTP)

MassRuler (DNA ladder, Mix)

6x Mass Loading Dye Solution from Fermentas

MinElute PCR Purification Kit Qiagen

Equipment

Buffer tank (Easy-cast Electrophoresis Systems) Owl Scientific Plastics Inc., Cambridge USA

Power supply pack (EC 250-90 EC Apparatus Corporation) Biodiagnostics Sdn Bhd, Malaysia

UV lightbox (Fotoprep Transilluminator) Fotodyne, USA

Polaroid Camera Polaroid, UK

BioPhotometer Eppendorf, Hamburg

Thermal Cycler PTC-100 MJ Research Instrument Inc., USA

Fermentas

Appendices

Appendix B- Preparation of Media, Stocks and Buffers

Luria-Bertani (LB) Broth

Use: 25 g LB broth powder

Add 1L of sddH2O. Measure into 100 or 250 ml Schott Bottles and sterilize by autoclaving.

Store at room temperature for up to 1 month (or 10 days when open).

Alkali Wash Solution

(0.5 M NaOH, 0.05 M sodium citrate/tri-sodium citrate)

Use: 2 g NaOH (MW~ 40.00)

1.47g tri-sodium citrate (MW~294.1)

Add sddH2O to make 100 ml of solution and store at room temperature for up to 3 months.

0.5 M Tris-HCl (pH 8.0)

Use: 7.88g Tris-HCl (MW~157.6)


TE (Tris-EDTA) Buffer (10/10 mM)

(1 M Tris-HCl, 0.5 M EDTA)

Use: 0.3941 g Tris-HCl (MW~ 167.64)

0.9306 g EDTA (MW~372.24)


Appendices

l0% SDS

Use: 1 g SDS

Add 10 ml of sddH2O, mix gently and store at room temperature for up to 3 months.

10 mg/ml Proteinase K

Use: 0.01 g Proteinase K

Add 1 ml of sddH2O. Prepare in 1.5 ml Eppendorf tubes and store at -20°C for 3 months.

10 mg/ml lysozyme

Use: 0.01 g lysozyme

Add 1 ml of sddH2O. Prepare in 1.5 ml Eppendorf tubes and store at -20°C for 3 months.

Chloroform-isoamyl alcohol (24:1)

To every 24 ml of chloroform, add 1 ml of isoamyl alcohol.

4.0M NaCl

Use: 2.338 g NaCl (MW~58.44)

Add 10 ml of sddH2O and store at room temperature for up to 3 months.

70% ethanol

To every 70 ml of ethanol, add 30 ml of sddH2O.

Appendices

TE (Tris-EDTA) buffer pH 8.0

Use: 10 mM Tris-HCl [1 ml of 1M stock, pH 8.0]

1 mM EDTA [200 ul of 0.5M stock, pH 8.0]

Add 100 ml of sddH2O. Filter and store at room temperature for up to 3 months.

1.0 M Tris, pH 8.0

Use: 60.57 g Tris

Add 350 ml of ddH2O. Adjust pH to 8.0 with concentrated HCl. Bring to 500 ml with

ddH2O. Filter and store at room temperature for up to 3 months.

0.5 M EDTA, pH 8.0

Use: 93.05 g EDTA

Add 350 ml of sddH2O. Stir vigorously on a magnetic stirrer and stir vigorously. Adjust the

pH to 8.0 by adding approximately NaOH pellets. Bring to 500 ml with sdd H2O. Filter and

store at room temperature for up to 3 months.

5X TBE (Tris-Borate EDTA) buffer, pH 8.0

(0.45M Tris-borate, 0.01M EDTA in stock)

Use: 54g Tris base

27.5g Boric Acid

Dissolve using 20 ml of 0.5M EDTA (pH 8.0). Add sddH2o to make 1 L. Store at room

temperature for 3 months.

Appendices

Key: Primers

f3p

r18n r18n and NR overlap NR

f4n nf

Figure AppC: The location of the primers used in this study on a higher-order structure model for Escherichia coli 16S rRNA that was obtained from Gutell et al. (1994).

Appendix C- Primer Location on the 16S rRNA

Appendix C

Appendices

Appendix D

Examples of

Electropherograms

from the DNA Sequencing

of Pure Culture Samples

Appendix D- Examples of Electropherograms from the DNA Sequencing of Pure Culture Samples

Figure AppD-1: Electropherogram from the DNA sequencing of 16S rDNA obtained from the Staphylococcus aureus (PC041) pure culture sample.

Appendix D-1

Figure AppD-2: Electropherogram from the DNA sequencing of 16S rDNA obtained from the Enterococcus faecalis (PC022) pure culture sample.

Appendix D-2

Figure AppD-3: Electropherogram from the DNA sequencing of 16S rDNA obtained from the Escherichia coli (PC039) pure culture sample.

Appendix D-3

Appendix D-4

Figure AppD-4: Electropherogram from the DNA sequencing of 16S rDNA obtained from the Haemophilus influenzae (PC017) pure culture sample.

Appendices

Appendix E

Table AppE:

The results of Gram-positive (GP),

Gram-negative (GN),

and Pan specific primers PCR on the

233 clinical samples studied.

Table AppE: The results of Gram-positive (GP), Gram-negative (GN) and Pan specific primers PCR on the 233 clinical samples studied.

Appendix E-1

No.

Culture Results PCR-typing Results*

Organism IdentifiedGram-type GP GN Pan Overall

1 C 001 None N/A No No No None detected2 C 003 Positive Yes No Yes Gram-type positive3 C 004 None N/A No No No None detected4 C 006 None N/A No No No None detected5 C 007 None N/A No No No None detected6 C 008 None N/A No No No None detected7 C 010 None N/A No No No None detected8 C 011 None N/A No No No None detected9 C 012 None N/A No No No None detected10 C 013 None N/A No No No None detected11 C 014 None N/A No No No None detected12 C 015 None N/A No No No None detected13 C 016 None N/A Yes No Yes Gram-type positive14 C 018 None N/A No No No None detected15 C 019 None N/A No No No None detected16 C 020 None N/A No No No None detected17 C 021 None N/A No No No None detected18 C 022 None N/A No No No None detected19 C 024 None N/A No No No None detected20 C 026 None N/A No No No None detected21 C 027 None N/A No Yes Yes Gram-type negative22 C 029 None N/A No No No None detected23 C 031 None N/A No No No None detected24 C 032 None N/A No No No None detected25 C 033 None N/A Yes No Yes Gram-type positive26 C 034 None N/A No No No None detected27 C 035 None N/A No No No None detected28 C 036 None N/A No No No None detected29 C 038 None N/A No No No None detected30 C 039 None N/A No No No None detected31 C 040 None N/A No No No None detected32 C 041 None N/A No No No None detected33 C 042 None N/A No No No None detected34 C 043 None N/A No No No None detected35 C 044 None N/A No No No None detected36 C 045 None N/A No No No None detected37 C 046 None N/A No No No None detected38 C 047 None N/A No No No None detected

Sample Name

Streptococcus sp.

*The Yes/No in this section refers to the presence or absence of amplicons when the PCR reaction contains Gram-positive (GP), Gram-negative (GN) or Pan specific primers. The overall

results refer to the Gram-type of the organism as deduced from the PCR reactions.


Appendix E-2

No.

Culture Results PCR-typing Results

Organism Identified Gram-type GP GN Pan Overall39 C 048 Positive No No No None detected40 C 049 None N/A No No No None detected41 C 050 None N/A No No No None detected42 C 051 None N/A Yes No Yes Gram-type positive43 C 052 None N/A No No No None detected44 C 053 None N/A No No No None detected45 C 054 None N/A No No No None detected46 C 055 None N/A No No No None detected47 C 056 None N/A No No No None detected48 C 057 None N/A No No No None detected49 C 058 None N/A No No No None detected50 C 059 None N/A No No No None detected51 C 060 None N/A No No No None detected52 C 061 None N/A No No No None detected53 C 062 None N/A No No No None detected54 C 063 None N/A No No No None detected55 C 064 None N/A No No No None detected56 C 065 Negative No Yes Yes Gram-type negative57 C 066 None N/A No No No None detected58 C 067 None N/A No Yes Yes Gram-type negative59 C 068 None N/A No No No None detected60 C 069 None N/A No No No None detected61 C 070 None N/A No No No None detected62 C 071 None N/A No No No None detected63 C 072 None N/A No No No None detected64 C 074 None N/A No No No None detected65 C 075 None N/A No No No None detected66 C 076 None N/A No No No None detected67 C 077 None N/A No No No None detected68 C 078 None N/A No No No None detected69 C 079 None N/A No No No None detected70 C 081 None N/A No No No None detected71 C 082 None N/A No No No None detected72 C 083 None N/A No No No None detected73 C 084 None N/A No No No None detected74 C 085 None N/A No No No None detected75 C 086 None N/A No No No None detected76 C 087 None N/A No No No None detected77 C 089 Negative No Yes Yes Gram-type negative78 C 090 Positive No No No None detected79 C 091 None N/A No No No None detected

Sample Name

Enterococcus sp.

Enterobacter sp.

Klebsiella pneumoniaeStaphylococcus aureus


Appendix E-3

No.


Organism Identified Gram-type GP GN Pan Overall80 P 001 None N/A No No No None detected81 P 002 Negative No Yes Yes Gram-type negative82 P 003 None N/A No No No None detected83 P 004 Positive Yes No Yes Gram-type positive84 P 006 None N/A No No No None detected85 P 007 Negative No Yes Yes Gram-type negative86 P 008 None N/A No No No None detected87 P 009 None N/A No No No None detected88 P 010 None N/A No No No None detected89 P 012 None N/A No No No None detected90 P 013 None N/A No No No None detected91 P 014 Negative No Yes Yes Gram-type negative92 P 015 None N/A No No No None detected93 P 017 Positive Yes No Yes Gram-type positive94 P 018 None N/A No No No None detected95 P 019 None N/A No No No None detected96 P 020 None N/A No Yes Yes Gram-type negative97 P 022 None N/A No No No None detected98 P 024 None N/A No No No None detected99 P 025 None N/A No No No None detected

100 P 026 None N/A No No No None detected101 P 027 None N/A No No No None detected102 P 028 None N/A No No No None detected103 P 029 Positive Yes No Yes Gram-type positive104 P 030 Positive No No No None detected105 P 031 None N/A No No No None detected106 P 032 None N/A No No No None detected107 P 033 None N/A No No No None detected108 P 034 None N/A No No No None detected109 P 035 None N/A No No No None detected110 P 036 None N/A No No No None detected111 P 037 None N/A No No No None detected112 P 038 None N/A No No No None detected113 P 040 None N/A No No No None detected114 P 041 None N/A No No No None detected115 P 042 Negative No No No None detected116 P 043 None N/A No No No None detected117 P 044 None N/A No No No None detected118 P 045 Negative No Yes Yes Gram-type negative119 P 046 None N/A No No No None detected120 P 047 None N/A No No No None detected

Sample Name

Escherichia coli

Enterococcus sp.




Enterococcus sp.Staphylococcus aureus




Appendix E-4

No.


Organism Identified Gram-type GP GN Pan Overall121 P 048 Positive No No No None detected122 P 049 None N/A No No No None detected123 P 050 None N/A No No No None detected124 P 051 Group G Streptococci Positive Yes No Yes Gram-type positive125 P 052 Negative No No No None detected126 P 053 None N/A No No No None detected127 P 054 None N/A No No No None detected128 P 055 Negative No Yes Yes Gram-type negative129 P 056 Negative No Yes Yes Gram-type negative130 P 057 None N/A No No No None detected131 P 058 None N/A No No No None detected132 P 059 None N/A No No No None detected133 P 060 None N/A No No No None detected134 P 061 None N/A No No No None detected135 P 062 None N/A No No No None detected136 P 063 Negative No Yes Yes Gram-type negative137 P 064 None N/A No No No None detected138 P 065 None N/A No No No None detected139 P 066 Negative No No No None detected140 P 067 None N/A No No No None detected141 P 068 None N/A No No No None detected142 P 069 Positive No No No None detected143 S 001 None N/A No No No None detected144 S 002 None N/A No No No None detected145 S 003 None N/A No No No None detected146 S 004 None N/A No No No None detected147 S 005 None N/A No No No None detected148 S 006 None N/A No No No None detected149 S 007 None N/A No No No None detected150 S 008 None N/A No No No None detected151 S 009 None N/A No No No None detected152 S 010 None N/A No Yes Yes Gram-type negative153 S 011 None N/A No No No None detected154 S 012 None N/A No No No None detected155 S 013 None N/A No No No None detected156 S 014 None N/A No No No None detected157 S 015 None N/A No No No None detected158 S 016 None N/A No No No None detected159 S 017 None N/A Yes No Yes Gram-type positive160 S 018 None N/A No No No None detected161 S 019 None N/A No No No None detected

Sample Name



Escherichia coliEscherichia coli

Klebsiella sp.

Escherichia coli



Appendix E-5

No.


Organism Identified Gram-type GP GN Pan Overall162 S 020 None N/A No No No None detected163 S 021 None N/A No No No None detected164 S 022 None N/A No No No None detected165 S 023 None N/A No No No None detected166 S 024 None N/A No No No None detected167 S 025 None N/A No No No None detected168 S 026 None N/A No No No None detected169 S 027 None N/A No No No None detected170 S 028 None N/A No No No None detected171 S 029 None N/A No No No None detected172 S 030 None N/A No No No None detected173 S 031 None N/A No No No None detected174 S 032 None N/A No No No None detected175 S 033 None N/A No Yes Yes Gram-type negative176 S 034 None N/A No No No None detected177 S 036 None N/A No No No None detected178 S 037 None N/A No No No None detected179 S 038 None N/A No No No None detected180 S 039 None N/A No No No None detected181 S 041 None N/A No No No None detected182 S 042 None N/A No No No None detected183 S 043 None N/A No No No None detected184 S 044 None N/A No No No None detected185 B 001 None N/A No No No None detected186 B 002 None N/A No No No None detected187 B 003 None N/A No No No None detected188 B 004 None N/A No No No None detected189 B 005 None N/A No No No None detected190 B 006 None N/A No No No None detected191 B 007 None N/A No No No None detected192 B 008 None N/A No No No None detected193 B 009 None N/A No No No None detected194 B 010 None N/A No No No None detected195 B 011 None N/A No No No None detected196 B 012 None N/A No No No None detected197 B 013 None N/A No No No None detected198 B 014 None N/A No No No None detected199 B 015 None N/A No No No None detected200 B 016 None N/A No No No None detected201 B 017 None N/A No No No None detected202 B 018 None N/A No No No None detected

Sample Name


Appendix E-6

No.


Organism Identified Gram-type GP GN Pan Overall203 B 019 None N/A No No No None detected204 B 020 None N/A No No No None detected205 B 021 None N/A No No No None detected206 B 022 None N/A No No No None detected207 B 023 None N/A No No No None detected208 B 024 None N/A No No No None detected209 B 025 None N/A No No No None detected210 B 026 None N/A No No No None detected211 B 027 None N/A No No No None detected212 B 028 None N/A No No No None detected213 B 029 None N/A No No No None detected214 B 030 None N/A No No No None detected215 B 031 None N/A No No No None detected216 B 032 None N/A No No No None detected217 B 033 None N/A No No No None detected218 B 034 None N/A No No No None detected219 B 035 None N/A No No No None detected220 B 036 None N/A No No No None detected221 B 037 None N/A No No No None detected222 B 038 None N/A No No No None detected223 B 039 None N/A No No No None detected224 B 040 None N/A No No No None detected

225 B 073 Positive Yes No Yes Gram-type positive

226 B 074 Positive Yes No Yes Gram-type positive227 B 076 Gram-negative rod Negative No Yes Yes Gram-type negative228 B 077 Positive No No No None detected229 B 078 Negative No Yes Yes Gram-type negative230 B 079 Negative No Yes Yes Gram-type negative231 B 080 Negative No Yes Yes Gram-type negative232 B 081 Positive No No No None detected233 B 082 Negative No Yes Yes Gram-type negative

Sample Name

Coagulase negative StaphylococciCoagulase negative Staphylococci

Bacillus sp.Acinetobacter baumaniiAcinetobacter baumaniiSalmonella enteritidisBacillus sp.Klebsiella pneumoniae

Appendices

Appendix F

Examples of

Electropherograms

from the DNA Sequencing

of the PCR-positive

Clinical Samples

Appendix F-1

Appendix F- Examples of Electropherograms from the DNA Sequencing of the PCR-positive Clinical Samples.

Figure AppF-1: Electropherogram from the DNA sequencing of 16S rDNA obtained from a cerebrospinal fluid sample (C003).

Appendix F-2

Figure AppF-2: Electropherogram from the DNA sequencing of 16S rDNA obtained from a blood culture bottle sample (B073).

Appendix F-3

Figure AppF-3: Electropherogram from the DNA sequencing of 16S rDNA obtained from a peritoneal fluid sample (P045).

Appendix F-4

Figure AppF-4: Electropherogram from the DNA sequencing of 16S rDNA obtained from a synovial fluid sample (S010).

Appendices

Appendix G- Calculation of the Number of Escherichia coli cells

detected by DNA amplification in this study.

It is given that:

1. Escherichia coli K12 (reference strain MG1655) consists of 4,639,221 bp from a

single circular DNA molecule (no plasmids) and has 7 rRNA gene operons (Blattner

et al., 1997).

2. 1 pmol of double-stranded DNA that is 1kb in size weighs 0.66 µg.

3. 1 pmol of double-stranded DNA that is 1kb in size contains 6.02x1011 genomes.

Therefore:

1 pmol of E. coli DNA that is 1 kb in size

= 4, 639.221 kb x 0.66 µg

= 3, 061.89 µg

The lowest detection limit for the Gram-negative specific primer on E. coli DNA is 10 pg

per 5 µl of sample (Section 3.4) or 2 pg/µl or 2x10-3 µg/ml.

Number of genomes in 2x10-3 µg/ml of E. coli DNA

= 2x10-3 x 6.02x1011 3, 061.89

= 3.93x105 genome/ml

Number of genomes in 5 µl of E. coli template solution is 1,965 genomes.

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GenBank http://www.ncbi.nlm.nih.gov/Genbank/

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pcr amplification of bacterial dna for the rapid diagnosis of infections

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