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Title Genetic diversity of multidrug resistant Mycobacterium tuberculosis Central Asian Strain isolates in Nepal

Author(s) SHAH, YOGENDRA

Citation 北海道大学. 博士(獣医学) 甲第12849号

Issue Date 2017-09-25

DOI 10.14943/doctoral.k12849

Doc URL http://hdl.handle.net/2115/71081

Type theses (doctoral)

File Information YOGENDRA_SHAH.pdf

Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP

1

Genetic diversity of multidrug resistant Mycobacterium tuberculosis Central

Asian Strain isolates in Nepal

（ネパールで分離された多剤耐性中央アジア型結核菌株の遺伝的多様性）

Yogendra Shah

2

CONTENTS

ABBREVIATIONS…………………………………………………………………………4

PREFACE…………………………………………………………………………………...6

CHAPTER I

High diversity of multidrug resistant Mycobacterium tuberculosis Central Asian Strain

isolates in Nepal

Introduction…………………………………………………………………………..……….9

Materials and Methods………………………………………………………………………10

-Sample collection and drug susceptibility test

-DNA extraction

-Spoligotyping

-MIRU-VNTR typing

-Sequencing of drug resistance associating genes

-Data management and analysis

-Ethics statement

Results………………………………………………………………………………………..12

-Demographic information

-Spoligotype

-MIRU-VNTR

-Sequencing analysis of drug resistance-associating genes

Discussion…………………………………………………………………………………….14

Summary……………………………………………………………………………...............27

3

CHAPTER II

Characterization of genetic diversity of multidrug resistant Mycobacterium tuberculosis

Central Asian Strain isolates from Nepal and comparison with neighboring countries

Introduction………………………………………………………………………………….28

Materials and Methods………………………………………………………………………29

-Sample collection and drug susceptibility test

-DNA extraction

-Spoligotyping and MIRU-VNTR typing

-Data management and analysis

-Minimum spanning tree (MST)

Results………………………………………..……………………………………………….31

-MIRU-VNTR analysis

-MST analysis

Discussion…………………………………………………………………………………….33

Summary…………………………………………………………………………………. .…43

CONCLUSION………………………………………………………………………………44

ACKNOWLEDGEMENTS…………………………………………………………………46

REFRERENCES…………………………………………………………………………….49

4

ABBREVIATIONS

TB Tuberculosis

MTB Mycobacterium tuberculosis

CAS Central Asian strain

MDR-TB Multi-drug resistant tuberculosis

XDR Extensively drug resistant

DOTS Directly observed short course therapy

WHO World Health Organization

GENETUP German Nepal tuberculosis project

NTP National tuberculosis program

NHRC Nepal Health Research Council

HIV Human immunodeficiency virus

DST Drug susceptibility test

LJ Löwenstein-Jensen

INH Isoniazid

RIF Rifampicin

STR Streptomycin

EMB Ethambutol

RR Rifampicin resistant

rpoB Gene encoding RNA polymerase β-subunit

RRDR Rifampicin resistance determining region

katG Gene encoding catalase-peroxidase

inhA Gene encoding enoyl-acyl carrier protein reductase

WT Wild type

SIT Spoligo-international type

MIRU Mycobacterial interspersed repetitive units

VNTR Variable number of tandem repeats

5

ETR Exact tandem repeats

QUB Queens University Belfast

RFLP Restriction fragment length polymorphism

SNP Single nucleotide polymorphism

LSP Large sequence polymorphism

DR Direct repeat

PCR Polymerase chain reaction

HGDI Hunter Gaston discriminatory index

MST Minimum spanning tree

SPSS Statistical package for the social science

UPGMA Unweighted pair group method with

arithmetic mean

6

PREFACE

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB),

which remains a major public health problem globally as one of the leading causes of mortality

and morbidity in developing countries. Although TB is a preventable and curable disease with

availability of effective anti-tuberculosis drugs for last five decades, the World Health

Organization (WHO) estimates that, in 2015 alone, 10.4 million new cases occurred around the

world, and of these, 1.4 million resulted in death (53). The majority of deaths were reported in

developing countries, with more than half occurring in Asia (58%). TB usually affects lungs

(pulmonary TB), although other organs (extrapulmonary TB) are involved in 15-30% of the

cases (53). The disease is spread when people who are sick with pulmonary TB expel the

bacteria into the air during coughing, sneezing and speaking (8). Overall, a relatively small

proportion (5-15%) of estimated 2-3 billion people infected with MTB will develop active TB

disease. However, the chance of developing TB disease is much higher among people infected

with human immunodeficiency virus (HIV) (53, 55).

Nepal is a landlocked country in South Asia, surrounded by two high TB burden countries,

north by China and to east, south and west by India sharing an open border with India. These

two neighboring countries together account for one third of the world’s TB cases (56). Nepal

experiences every year a large number of TB cases. In 2015, Nepal reported a TB mortality rate

of 21%, and estimates of TB prevalence and incidence were 215 and 156, respectively, per

100,000 inhabitants (53). Despite a TB control program run by the government, the number of

TB cases in Nepal has not decreased in the last decade. The reason behind this phenomenon

remains unknown; thus, comprehensive studies on MTB transmission in Nepal are needed.

The emergence of multidrug resistance (MDR) in TB, resistant to isoniazid (INH) and

rifampicin (RIF), poses a serious threat to the success of TB control programs. In 2015, WHO

estimated that 480,000 new cases of MDR-TB occurred globally. About 45% of the global

MDR-TB cases were from India, China and Russian federation countries (53). The latest (2014)

national drug resistance survey in Nepal revealed that 2.2% in new TB cases and 15.4% re-

treated cases were MDR (33). Studies on drug resistance-associated genes from different

countries have shown that resistance to RIF is due to a point mutation found in the region called

7

RIF resistance-determining region (RRDR) in the β-subunit of RNA polymerase gene (rpoB)

in more than 90% of the cases. RIF resistance can be used as a surrogate marker for MDR-TB

detection. Apparently more than 95% isolates that are RIF resistant are also resistant to INH (5,

19, 37, 39).

Genotyping of MTB isolates has been proven to be a powerful tool for investigating

suspected outbreaks, source of transmission, transmission chain and circulating strains (6, 14).

Spoligotyping (28), mycobacterial interspersed repetitive units-variable number of tandem

repeats (MIRU-VNTR) analysis (46) and IS6110 restriction fragment length polymorphism

(RFLP) typing (7) are commonly used techniques for genotyping. However, IS6110 RFLP

typing is a time-consuming technique and comparison of its results between laboratories is

difficult (48). As a result, spoligotyping and MIRU-VNTR have been used more often in recent

molecular epidemiological studies. Both of these genotyping methods are reliable,

discriminative and technically feasible for comparisons between laboratories (11, 13, 31).

Spoligotyping is based on the detection of 43 unique spacers situated among the direct repeats

at an exact locus of the MTB genome identified as the direct repeat (DR) locus (13).

Mycobacterial interspersed repetitive units (MIRUs) is DNA elements composed of tandemly

repeated sequences and distributed in the bacterial genome (4). The MIRU-VNTR genotyping

method depends on the identification of the difference in number of tandem repeats at several

loci as the repeat number varies among strains. The discriminatory power of MIRU-VNTR

analysis are depends on the number of MIRU loci assessed; 12 loci, 15 loci and 24 loci (10).

The combination of spoligotyping and MIRU-VNTR analysis have been shown to have similar

discriminatory power to IS6110 RFLP.

MTB complex associated with human infections consists of seven lineages based on

specific genetic markers and geographical areas: Lineage 1 (Indo-Oceanic lineage), Lineage 2

(East-Asian Lineage, includes Beijing family), Lineage 3 (East African Indian, includes

Delhi/CAS family), Lineage 4 (Euro-American lineage), Lineage 5 and 6 (M. africanum West

lineages 1 and 2) and Lineage 7 (Ethiopia) (11, 12, 20, 22). Lineage 3, Central Asian strain

(CAS) family has been reported as one of the dominant genotype of MTB in South Asian

countries. Beijing family belonging to Lineage 2 is well known to be associating with drug

8

resistance development, however, CAS family is also suggested to be associating to the

increasing number of MDR TB in South Asian countries (25, 44, 57). In Nepal, there has been

no report about the epidemiology and molecular analysis on MDR CAS MTB, although this

lineage is the majority among TB patients in this country. Thus, I decided to perform the

characterization of the MDR MTB isolates belonging to CAS family in Nepal.

The present thesis consists of two chapters; in chapter I, I have investigated the genetic

characteristics of MDR-MTB CAS family isolates in Nepalese patients. I analyzed 145 MDR

CAS family isolates from Nepal by spoligotyping, 24 loci MIRU-VNTR analysis and drug

resistance-associating gene sequencing. In Chapter II, I have further performed genetic

characterization of MDR CAS family isolates and elucidated evolutionary relationships of

predominant MDR CAS family, CAS_Delhi (SIT26), isolates in Nepal and neighboring

countries (India and Pakistan) by using molecular genotyping tools.

9

Chapter I

High diversity of multidrug resistant Mycobacterium tuberculosis Central Asian

strain isolates in Nepal

Introduction

Previous studies on the genotype of MTB isolates in Nepalese patients reported the Lineage

3 Central Asian Strain (CAS) family as the most dominant in Nepal (29). Other studies also

reported the CAS family as dominant (1, 24, 41, 43) and as contributors to multi-drug resistance

(MDR) in TB in South Asian countries (57). For instance, in India, Stavrum et al. (2009) (44)

associated the CAS family with multi-drug resistant TB (MDR-TB), and in Pakistan it was

linked to the increasing prevalence of MDR-TB and emergence of extensively drug resistant

(XDR) TB (25). It is believed, therefore, that the emergence of MDR-TB in the CAS family

poses a serious threat to the success of TB control programs in the region. Likewise, in Nepal,

MDR-TB is one of the major emerging threats to the success of TB control. For instance, in

2010 a study conducted in Nepal showed a MDR-TB prevalence of 11.7% in re-treated cases

(32), but the latest national anti-TB drug resistance survey conducted between 2011 and 2012

showed that MDR-TB prevalence increased to 15.4% in re-treated cases (33).

The main purpose of the current study is to conduct a genetic analysis of MDR in MTB of

the CAS family and to understand its molecular epidemiological features and transmission

dynamics in Nepalese TB patients.

10

Materials and Methods

Sample collection and drug susceptibility test

A total of 601 MDR-MTB isolates collected from April 2008 to March 2013 by the German-

Nepal Tuberculosis Project (GENETUP) were used, of which 145 MDR-TB CAS family

isolates were purposively selected. Isolates were collected from a decentralized National

Tuberculosis Program (NTP) network of 11 MDR-TB treatment centers and 66 sub-treatment

centers. The location of the treatment centers and the sample numbers collected in each center

are shown in Figure 1. All samples were obtained from different individuals. Epidemiological

features of patients were also collected from hospital medical records. A phenotypic drug

susceptibility test (DST) was carried out using the proportional method on Löwenstein-Jensen

(LJ) medium with standard critical concentrations for isoniazid (INH) (0.2 µg/ml), rifampicin

(RIF) (40 µg/ml), streptomycin (STR) (4 µg/ml) and ethambutol (EMB) (2 µg/ml) (54).

DNA extraction

Mycobacterial colonies on positive LJ cultures were suspended in 300 µl of distilled water

and heated for 20 min at 95 ºC. Heated samples were sonicated in an ultra-sonic water bath

apparatus for 15 min and centrifuged for 5 min at 10,000× g. The bacterial DNA-containing

supernatant was retrieved and used for further molecular analysis.

Spoligotyping

All isolates were analyzed by spoligotyping, as described by Kamerbeek et al. (28). Briefly,

the direct repeat (DR) region was amplified with a pair of primers, and the resulting PCR

products were hybridized to a set of 43 spacer-specific oligonucleotide probes, which were

immobilized on the membrane. Spoligotyping data was analyzed using SITVIT database

(http://www.pasteur-guadeloupe.fr:8081/SITVIT_ONLINE/) to determine spoligo-

international type (SIT) (15).

11

MIRU-VNTR typing

MIRU-VNTR typing was carried out by amplifying 24 loci that included 12 MIRU loci

(MIRU2, MIRU4, MIRU10, MIRU16, MIRU20, MIRU23, MIRU24, MIRU26, MIRU27,

MIRU31, MIRU39 and MIRU40), 4 exact tandem repeats (ETR) loci (ETR-A, ETR-B, ETR-

C and ETR-F), 4 Queens University Belfast (QUB) loci (QUB11a, QUB11b, QUB26 and

QUB4156) and 4 VNTR loci (VNTR424, VNTR1955, VNTR2401 and VNTR3690) as

described by Supply et al. (46).

Sequencing of drug resistance associating genes

Isolates clustered by a combined analysis of spoligotyping and MIRU-VNTR typing were

further analyzed by sequencing of the drug resistance-associated genes, i.e. rifampicin

resistance determining region (RRDR) in rpoB for RIF resistance, katG coding and inhA

promoter regions for INH resistance, as previously described (37).

Data management and analysis

Demographic data including age, sex and treatment history of TB were analyzed with SPSS

(Statistical package for the social science) software version 19.0 and PRISM version 5

(GraphPad Software, Inc., La Jolla, CA, USA). Individual and cumulative Hunter Gaston

discriminatory indices (HGDI) were calculated to determine the discriminatory power of each

MIRU-VNTR locus and overall loci (27). The discriminatory power of each locus was

considered high (HGDI>0.6), moderate (0.3≤ HGDI ≤0.6) and poor (HGDI<0.3) as suggested

by Sola et al. (45). A cluster was defined as two or more isolates sharing the identical

spoligotype and MIRU-VNTR pattern, and clustering rate was calculated using the formula

number of clustered isolates / total number of isolates (23). A phylogenetic tree was constructed

by the unweighted pair group method with arithmetic mean (UPGMA) using an online MIRU-

VNTRplus web-based application [http://www.miru-vntrplus.org] (51).

Ethics statement

This study was ethically approved by the Nepal Health Research Council (NHRC)

12

Results

Demographic information

Age, sex and treatment history information of patients from whom 145 CAS and 456 non-

CAS MDR isolates were obtained are compared and shown in Table 1. Regarding the age group,

a significant difference was found between 0-20 and above 60 years (p < 0.05, test). There

were no other factors significantly associated with the CAS isolate infection among MDR-TB

patients.

Spoligotype

A total of 145 MDR CAS isolates were divided into 25 spoligotype patterns, and

CAS1_Delhi SIT26 was found to be most prevalent (60/145, 41.4%), followed by CAS SIT599

(15/145, 10.3%) and CAS SIT357 (9/145, 6.2%), as listed in Table 2.

MIRU-VNTR

Allelic diversity of each MIRU-VNTR locus and HGDI are shown in Table 3. Three out of

24 loci (QUB26, MIRU10, VNTR424) were found to be highly discriminant, 11 loci (MIRU26,

VNTR3960, MIRU31, MIRU40, ETR-A, QUB11a, QUB4156, VNTR2401, VNTR1955,

MIRU39 and ETR-F) were moderately discriminant and the remaining 10 loci were poorly

discriminant. The number of MIRU-VNTR patterns with the 24 loci was 107 including 21

clusters that consisted of 54 isolates (clustering rate: 37.2 %) (Table 4).

By combining the analysis of spoligotyping and MIRU-VNTR, I found 18 clusters consisting

of 47 isolates with identical pattern in each cluster. The clustering rate was 32.4%, and the

biggest cluster consisted of 6 isolates, followed by three 4-isolate clusters, one 3-isolate cluster,

and finally 13 clusters consisting of 2 isolates (Figure 2, Table 4).

13

Sequence analysis of drug resistance-associating genes

Clustered isolates were further analyzed by sequencing drug resistance-associated genes

(rpoB, katG coding and inhA promoter region) to identify possible MDR-MTB transmission

(Table 5). Among the 47 isolates, all but one had G944C mutation (i.e., Ser315Thr substitution)

in katG, which is a well-known INH resistance-associated mutation. In rpoB analysis, 45

isolates had a mutation or deletion in RRDR, and C1349T (Ser531Leu) was dominant (20/47,

42.6%). Among 18 clusters, 14 clusters had isolates sharing the same rpoB mutation, and half

of them were the major substitution Ser531Leu. Among the remaining clusters, Cluster 1

isolates shared the same 3-codon deletion in which the deletion pattern was identical. In the

biggest cluster, Cluster 13, four isolates shared the same substitution His526Asp and two of

them had a mutation T-8C in the inhA promoter region. In Cluster 6 and Cluster 14, two isolates

each shared a rare substitution, Asp516Phe (GAC→TTC) and Ser531Gln (TCG→CAG),

respectively, both of which require a double mutation in a codon. In Cluster 17, all four isolates

shared a relatively rare substitution, Gln513Leu; moreover, the substitution Leu511Pro shared

in Cluster 11 was also rare. Most of the isolates sharing rare mutations were restricted to the

same geographic locations (Table 5); however, none of those patients had personal contact with

the others sharing the genetically same bacteria. Other demographic features can also be found

in Table 5.

14

Discussion

This study was the first to demonstrate the genetic characteristics of MDR CAS isolates in

Nepal and showed their high diversity. CAS family is reported as being highly prevalent among

TB patients in certain regions of the Indian subcontinent, namely, Pakistan and the northern

half of India (24, 41, 43). Geographically, Nepal is located between two greatly TB-burdened

countries, India and China, which contribute one third of the world’s TB cases. Historically,

Nepal has an open border with India, and both Nepalese and Indian citizens often visit the

bordering area for work, pilgrimage and education. This regular interaction may open an

opportunity for direct transmission of the CAS family MTB between the Indian and Nepalese

populations. In the present study, the ratio of MDR-TB patients infected with the CAS family

was higher in the age group above 60 years than younger groups (Odds ratio 3.25 against 0-20

years old group, p<0.05, Table 1). This association between the CAS family and elderly people

might be related to the historical prevalence of CAS in Nepal and caused by reactivation of

latent TB infection. However, when comparing the patient-age distribution of clustered (n = 47)

and non-clustered (n = 98) isolates, I found that the average age of the clustered-isolate infected

patients was significantly lower than that of non-clustered group (t-test, p<0.05). It may suggest

that younger generations were more likely to be infected with clustered isolates, indicating those

were the outcome of recent transmissions (Figure 3). This phenomenon may be explained by

the higher social activity of younger generations compared with older generations, which likely

contributes to a higher transmission risk.

I found that spoligotyping alone could not identify diversity in the CAS family in Nepal due

to the dominant cluster of CAS1_Delhi SIT26 contributing 60 isolates (Table 2). However, all

145 MDR CAS family isolates were successfully differentiated into 116 patterns including 18

clusters (clustering rate 32.4%) by combining spoligotyping and 24-locus MIRU-VNTR

analyses (Figure 2). I further investigated the optimization of these MIRU-VNTR loci. As

expected, I was able to select an affordable locus set as suggested by previous studies (17, 50).

Based on the cumulative HGDI analysis of 24 loci with clustering rates (Table 4), a set of 15

loci was shown to have the same discrimination power as 24 loci. To get a higher discrimination

power, of the 24 loci reported by Supply et al. (46) I replaced two loci, Mtub29 and Mtub34,

15

with ETR-F and QUB11a. Both of the newly replaced loci were listed among the top 15

discriminant loci that successfully worked for the Nepali MDR CAS cases (Table 4). To save

time and cost, smaller locus numbers of VNTR are better than larger, even though MIRU-

VNTR analysis may be more feasible at local research centers than other typing methods.

In addition, I was able to discriminate clustered MDR isolates by conducting sequencing

analysis of drug resistance-associated genes, katG, rpoB and inhA promoter region. katG 315

substitution is an INH resistance-associated mutation well known for its low fitness cost (49).

However, in highly TB-burdened countries, the majority of INH-resistant MTB isolates have

this mutation, thus it cannot be used as a transmission marker, although, it still can be used as

a genetic marker of INH resistance (5, 37, 39). In contrast, rpoB mutations can be a good marker

for MDR-MTB transmission, as the variation of RFP resistance-associated mutation in RRDR

is much higher than katG in highly TB-burdened countries (5, 37, 39). Having a mutation in

RRDR strongly suggests that the isolate is RFP resistant. RNA polymerase is an essential

enzyme for bacteria, thus the majority of nonsynonymous mutations in RRDR deteriorate and

frequently observed mutations in RFP-resistant MTB are limited. Even such “acceptable”

amino acid substitutions still exert adverse effects on the enzyme function; therefore, RRDR

mutated survivors tend to have additional mutations known as “compensatory mutation” inside

the RRDR or nearby RNA polymerase components (16). In the current study, I found two

double mutations that occurred in one codon. One of them, Asp516Phe (GAC -> TTC), found

in Clusters 6 and 7, may be an example of the aforementioned compensatory mutation, as the

possible parent mutant Asp516Val (GAC -> GTC) was found in both clusters (Table 5). As

Clusters 6 and 7 were different by only one locus with high polymorphism (MIRU10) in the

lineage in MIRU-VNTR (Table 3), and all isolates were obtained from the same geographic

location, the original MDR-MTB bearing Asp516Val may be spread throughout this area. As a

result, some of the descendent bacteria may have acquired an additional mutation in the same

codon, possibly due to the above-mentioned compensatory mutation, which may have been

most suitable for the Asp516Val mutant. Since variety of the compensatory mutation is also

high in RRDR mutant cases (16), the combined analysis of those regions may improve the

detection rate of MDR-MTB transmissions.

16

I found several complete matches of genotypes, geographic locations and drug resistance-

associated mutations between two or more isolates in some clusters, suggesting possible

transmissions of MDR-MTB between individuals (Table 5). In particular, sharing a rare rpoB

mutation in the cluster strongly suggested acquisition of MDR-MTB via person-to-person

contact. I could not identify the exact epidemiological link between those patients, which

suggests that a common transmission source may exist in the geographic area. In some cases,

isolates were obtained from patients living in distant areas. For example, in the case of Cluster

17, four isolates were collected in three different areas, Dharan (East), Nepalgunj (Mid-West)

and Kathmandu (Central), which were as far apart as 200 ~ 600 km. In this cluster, the first case

was an old man in Kathmandu in 2009, and the remaining were young people visiting hospitals

in each area later on. In the case of the patient in the Eastern area of Dharan, it was a new case

of MDR-MTB that showed the same four-drug resistance as the others prior to the TB treatment

(Table 5). As Kathmandu is the capital city, people frequently visit from different areas of Nepal,

and thus, the city could be a site for transmission of infectious diseases (38). This hypothesis,

however, ought to be validated by further whole genome sequencing analysis.

Application of combined analysis of spoligotyping and MIRU-VNTR typing together with

rpoB sequencing is considered an effective approach to conduct molecular epidemiology of

MDR MTB.

17

Figure 1:

Locations of the 11 MDR-TB treatment centers at where samples were collected in Nepal.

A: Mahendranagar, B: Dhangadhi, C: Nepalgunj, D: Bhairahawa, E: Butwal, F: Pokhara, G:

Birgunj, H: Kathmandu, I: Dhanusa, J: Dharan and K: Biratnagar.

Sample numbers collected in each center: (CAS family / Total)

18

19

Figure 2: 24-locus MIRU-VNTR and spoligotyping-based dendrogram of 145 MDR CAS

isolates from Nepal. (A) The dendrogram was generated by UPGMA [www.miru-vntrplus.org].

(B) Strain identification number. (C) SIT (Spoligo-International type) number. (D) Clade

annotated by SITVIT database. (E) MIRU-VNTR results of 24 loci. The order of loci is as

follows, left to right: MIRU2, VNTR424, ETR-C, MIRU4, MIRU40, MIRU10, MIRU16,

VNTR 1955, MIRU20, QUB11b, ETR-A, QUB11a, VNTR 2401, ETR-B, MIRU23, MIRU24,

MIRU26, MIRU27, ETR-F, MIRU31, VNTR 3690, QUB26, QUB4156 and MIRU39. (F)

Spoligotype pattern. Isolates clusters (identical patterns of MIRU-VNTR and spoligotyping)

are enclosed in open boxes.

20

Figure 3: Scattered gram of patient ages for comparison between clustered isolates (n=47) and

non-clustered isolates (n=98) (t-test: P<0.05)

21

Table 1: Demographic and clinical characteristics of patients infected with CAS and non-CAS

genotype isolates.

Number of

CAS family

Number of

non-CAS family

Odds ratio

(95% CI)

p-value

Sex

Male 111 321 1

Female 34 135 0.728 (0.472-1.123) 0.151

Age

0-20 14 73 1

21-40 85 268 1.65 (0.88-3.07) 0.110

41-60 36 99 1.89 (0.95-3.77) 0.066

>60 10 16 3.25 (1.22-8.64) < 0.05a

Treatment status

CAT II failureb 122 393 1

CAT I failurec 18 42 1.38 (0.766-2.48) 0.282

New patients 5 21 0.76 (0.283-2.07) 0.813

a: p-value < 0.05 was considered as significant. Determined by test or Fisher’s exact test.

b: CAT II failure; patients who were either smear-positive relapse, chronic, MDR contact,

relapse and treatment after default

c: CAT I failure; failure in new cases of smear-positive pulmonary TB

22

Table 2: Distribution frequency of diverse CAS family strains

a: Clades were annotated using SITVITWEB database.

b: SIT (Spoligo international types) were assigned by SITVITWEB database and MIRU-VNTR

plus web tool.

c: Closed squares represent positive hybridization (presence of spacer), and open squares

represent no hybridization (absence of spacers).

Cladea SIT

b Spoligotype pattern

c Number of

isolates (%)

1. CAS1_Delhi 26

60 (41.4)

2. CAS 599

15 (10.3)

3. CAS 357

9 (6.20)

4. CAS 142

7 (4.82)

5. CAS 288

7 (4.82)

6. CAS1_Delhi 471

6 (4.13)

7. CAS1_Delhi 1312

4 (2.75)

8. CAS1_Delhi 427

4 (2.75)

9. CAS 22

3 (2.06)

10. CAS1_Delhi 25

3 (2.06)

11. CAS 356

3 (2.06)

12. CAS 486

3 (2.06)

13. CAS1_Delhi 429

2 (1.37)

14. CAS 428

2 (1.37)

15. CAS 485

2 (1.37)

16 CAS 1093

2 (1.37)

17. CAS 1266

2 (1.37)

18. CAS1_Delhi 1343

2 (1.37)

19. CAS1_Delhi 1590

2 (1.37)

20. CAS 203

1 (0.68)

21. CAS 864

1 (0.68)

22. CAS 1151

1 (0.68)

23. CAS1_Delhi 1314

1 (0.68)

24. CAS 1606

1 (0.68)

25. CAS1_Delhi 1883

1 (0.68)

23

Table 3: Allelic diversity of each MIRU-VNTR locus for CAS MDR-MTB isolates of Nepal

(N = 145)

Locus Allele numbera HGDI

c Conclusion

0 1 2 3 4 5 6 7 8 9 10 NDb

QUB26 1 2 4 13 12 89 12 3 0.604 High

MIRU10 2 13 41 83 1 1 3 0.603 High

VNTR424 5 16 88 23 1 1 3 1

0.6 High

MIRU26 1 8 8 20 93 2 12 2 0.56 Moderate

VNTR3690 109 24 11 1 0.465 Moderate

MIRU31 2 1 31 103 5 3 0.448 Moderate

MIRU40 6 23 107 9 0.427 Moderate

ETR-A 1 23 119 2

0.395 Moderate

QUB11a 1 4 2 21 111 3 3 0.394 Moderate

QUB4156 2 2 23

114

4 0.39 Moderate

VNTR2401 119 26

0.351 Moderate

VNTR1955

14 4 116 6 2 3 0.34 Moderate

MIRU39 19 121 3 2 0.322 Moderate

ETR-F 8 124 10 3 0.309 Moderate

MIRU16

23 120 2 0.291 Poor

MIRU20 4 141

0.132 Poor

QUB11b 2 142 1

0.107 Poor

MIRU24 1 144

0.081 Poor

MIRU27 1 140 2 2 0.067 Poor

MIRU4 1 141 1 2 0.054 Poor

MIRU23 1 142 1 1 0.041 Poor

MIRU2 143 1 1 0.027 Poor

ETR-B 145 0 Poor

ETR-C 145 0 Poor

a: Number of tandem repeats

b: ND; Not determined because of PCR failure

c: Hunter Gaston discriminatory index. DI > 0.6: Highly discriminatory; 0.3 ≤ DI ≤ 0.6:

Moderately discriminatory; DI < 0.3 Poorly discriminatory

24

Table 4: Cumulative HGDI with successive addition of each MIRU-VNTR locus (N=145)

VNTR alias Individual

HGDI

No. of

patterns

No. of

clusters

No. of

clustered

isolates

Clustering

rate (%)

No. of

isolates in

each cluster

Cumulative

HGDI

QUB26 0.604 0.604

MIRU10 0.603 18 9 130 89.6 2-52 0.8187

VNTR424 0.6 35 16 121 83.4 2-39 0.8937

MIRU26 0.56 55 20 104 71.7 2-27 0.9453

VNTR3690 0.465 63 20 96 62.2 2-13 0.9674

MIRU31 0.448 70 22 90 62.0 2-11 0.9767

MIRU40 0.427 79 23 82 56.6 2-8 0.9846

ETR-A 0.395 86 25 79 54.4 2-7 0.9874

QUB11a 0.394 90 25 75 51.7 2-6 0.9899

QUB4156 0.39 92 26 73 50.3 2-5 0.9917

VNTR2401 0.351 93 26 71 48.9 2-5 0.9923

VNTR1955 0.34 95 23 62 42.7 2-5 0.9927

MIRU39 0.322 97 22 61 42.0 2-5 0.9927

ETR-F 0.309 97 22 60 41.3 2-5 0.9931

MIRU16 0.291 98 22 60 41.3 2-5 0.9942

MIRU20 0.132 100 21 60 41.3 2-5 0.9942

MIRU24 0.107 102 22 58 40.0 2-5 0.9942

QUB11b 0.081 103 22 57 39.3 2-5 0.9942

MIRU27 0.067 105 21 55 37.9 2-4 0.9942

MIRU4 0.054 106 21 55 37.9 2-4 0.9942

MIRU23 0.041 107 21 54 37.2 2-4 0.9944

MIRU2 0.027 107 21 54 37.2 2-4 0.9942

ETR-B 0 107 21 54 37.2 2-4 0.9942

ETR-C 0 107 21 54 37.2 2-4 0.9942

25

Table 5. Demographic information of patients and genetic characteristics of the 47 MDR-MTB clustered isolates belonging to the CAS genotype.

Location Age Sex Year Categolya

SITb

MIRU-VNTRc RpoB in codon rpoB in nucleotide KatG inhA

127 Nepalgunj 24 F 2008 cat II failure 26 252235442248225153353543 R,I Gln 513 His, del: 514~516 del: 1296~1304 attcatgga Ser 315 Thr WT Cluster 1

130 Nepalgunj 30 F 2008 cat II failure 26 252235442248225153353543 R,I,E Gln 513 His, del: 514~516 del: 1296~1304 attcatgga Ser 315 Thr WT

342 Janakpur 28 M 2012 cat II failure 26 242236442248225153353743 R,I Ser 531 Leu C 1349 T Ser 315 Thr C -15 T Cluster 2

479 Nepalgunj 41 M 2012 cat II failure 26 242236442248225153353743 R,I,S,E - - Ser 315 Thr -

400 Pokhara 50 F 2008 cat II failure 471 242235442248225133353743 R,I,S,E Ser 531 Leu C 1349 T Ser 315 Thr WT

414 Pokhara 82 M 2011 cat II failure 471 242235442248225133353743 R,I,S,E del: 517 del: 1306~1308 cag Ser 315 Thr WT Cluster 3

417 Pokhara 33 M 2012 relapse 471 242235442248225133353743 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT

491 Nepalgunj 34 F 2012 cat I failure 471 242235442248225133353743 R,I,S Asp 516 Tyr G 1303 T Ser 315 Thr WT

186 Dhangahi 22 F 2011 cat II failure 428 2422364422410225163323743 R,I Asp 516 Tyr G 1303 T Ser 315 Thr WT Cluster 4

516 Dhangahi 22 M 2012 cat II failure 428 2422364422410225163323743 R,I Asp 516 Tyr G 1303 T Ser 315 Thr WT

334 Janakpur 18 M 2009 cat II failure 356 242234442248225163353743 R,I,S,E Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 5

428 Bhairahawa 24 M 2008 cat II failure 356 242234442248225163353743 R,I,S Gln 513 Leu A 1295 T Ser 315 Thr WT

526 Kathmandu 40 F 2008 cat II failure 357 242234442238225163353743 R,I,S,E Asp 516 Val A 1304 T Ser 315 Thr WT

556 Kathmandu 34 M 2009 cat II failure 357 242234442238225163353743 R,I,E Asp 516 Phe G 1303 T, A 1304 T Ser 315 Thr WT Cluster 6

557 Kathmandu 40 M 2009 cat II failure 357 242234442238225163353743 R,I,E Asp 516 Phe G 1303 T, A 1304 T Ser 315 Thr WT

647 Kathmandu 24 M 2010 cat II failure 357 242235442238225163353743 R,I,S Asp 516 Val A 1304 T Ser 315 Thr WT Cluster 7

652 Kathmandu 35 M 2011 cat I failure 357 242235442238225163353743 R,I Asp 516 Phe G 1303 T, A 1304 T Ser 315 Thr WT

250 Kathmandu 36 M 2009 cat II failure 288 242235442248225183353743 R,I Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 8

617 Kathmandu 20 M 2010 cat II failure 288 242235442248225183353743 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT

181 Dhangahi 31 F 2010 cat II failure 26 282226442238225163353843 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 9

477 Nepalgunj 62 M 2012 defaulter 26 282226442238225163353843 R,I WT none WT WT

184 Dhangahi 32 F 2010 cat II failure 1312 232236442247225153353743 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 10

488 Nepalgunj 25 M 2012 cat II failure 1312 232236442247225153353743 R,I Ser 531 Leu C 1349 T Ser 315 Thr WT

505 Dhangahi 32 M 2011 cat II failure 25 232236422248225153353543 R,I Leu 511 Pro T 1289 C Ser 315 Thr WT Cluster 11

547 Kathmandu 36 F 2009 cat II failure 25 232236422248225153353543 R,IS,E Leu 511 Pro T 1289 C Ser 315 Thr WT

117 Butwal 34 M 2011 cat II failure 26 242236442248425163344642 R,I,S,E Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 12

469 Nepalgunj 30 M 2009 cat II failure 26 242236442248425163344-42 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT

421 Bhairahawa 61 M 2008 cat II failure 26 242236442248425183344742 R,I,S,E His 526 Asp C 1333 G Ser 315 Thr T -8 C

426 Bhairahawa 30 M 2009 cat II failure 26 242236442248425183344742 R,I,S,E His 526 Asp C 1333 G Ser 315 Thr T -8 C

439 Butwal 31 M 2012 cat II failure 26 242236442248425183344742 R,I His 526 Tyr C 1333 T Ser 315 Thr WT Cluster 13

536 Kathmandu 30 F 2009 cat II failure 26 242236442248425183344742 R,I,S,E His 526 Asp C 1333 G Ser 315 Thr WT

543 Kathmandu 73 M 2009 cat II failure 26 242236442248425183344742 R,I,S His 526 Asp C 1333 G Ser 315 Thr WT

641 Kathmandu 16 F 2010 cat I failure 26 242236442248425183344742 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT

176 Mahendranagar 34 M 2009 cat II failure 486 222235442247425153343343 R,I,S,E Ser 531 Gln T 1348 C, C 1349 A Ser 315 Thr WT Cluster 14

177 Mahendranagar 55 F 2010 cat II failure 486 222235442247425153343343 R,I,S,E Ser 531 Gln T 1348 C, C 1349 A Ser 315 Thr WT

309 Kathmandu 18 F 2012 cat I failure 599 242226422238225163355723 R,I Ser 531 Leu C 1349 T Ser 315 Thr WT

460 Butwal 18 M 2012 cat I failure 599 242226422238225163355723 R,I,E Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 15

537 Kathmandu 25 M 2009 cat II failure 599 242226422238225163355723 R,I Ser 531 Leu C 1349 T Ser 315 Thr WT

628 Kathmandu 21 M 2010 cat I failure 599 242226422238225163355723 R,I,S,E Ser 531 Leu C 1349 T Ser 315 Thr WT

IDDST

resultsd

Mutations in drug resistance-associated geneseDemographic information of patients Genotype of isolates

26

317 Kathmandu 36 M 2012 cat I failure 599 242226422248225163355723 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 16

538 Kathmandu 16 F 2009 MDR contact 599 242226422248225163355723 R,I,S Ser 531 Leu C 1349 T Ser 315 Thr WT

394 Dharan 25 F 2011 new 22 242216442248225163453543 R,I,S,E Gln 513 Leu A 1295 T Ser 315 Thr WT

471 Nepalgunj 23 M 2010 cat II failure 22 242216442248225163453543 R,I,S,E Gln 513 Leu A 1295 T Ser 315 Thr WT Cluster 17

483 Nepalgunj 22 M 2012 cat I failure 22 242216442248225163453543 R,I,S,E Gln 513 Leu A 1295 T Ser 315 Thr WT

542 Kathmandu 63 M 2009 cat II failure 22 242216442248225163453543 R,I,S,E Gln 513 Leu A 1295 T Ser 315 Thr WT

171 Nepalgunj 20 M 2011 cat II failure 427 242234452247425163253723 R,I,S,E Ser 531 Leu C 1349 T Ser 315 Thr WT Cluster 18

492 Nepalgunj 28 M 2012 relapse 427 242234452247425163253723 R,I Ser 531 Leu C 1349 T Ser 315 Thr WT

a: CAT II failure; patients who were either smear positive relapse, chronic, MDR contact, relapse and treatment after default, CAT I failure; failure in new cases of smear positive pulmonary TB

b: SIT (Spoligo International types) were assigned by SITVITWEB database and MIRU-VNTR plus web tool

c: Order of loci; MIRU2, VNTR424, ETR-C, MIRU4, MIRU40, MIRU10, MIRU16, VNTR1955, MIRU20, QUB11b, ETR-A, QUB11a, VNTR2401, ETR-B, MIRU23, MIRU24, MIRU26, MIRU27, ETR-F, MIRU31,

VNTR3690, QUB26, QUB4156 and MIRU39

d: Drug susceptibility test results. Isolates showed resistance against R: rifampicin, I: isoniazid, S: streptomycin, E: ehambutol

e: Amino acid substitutions are shown in the codon number. Del: deletion, -: PCR failed, WT: wild type sequence. KatG Ser 315 Thr substitution was by katG G944C mutation.

27

Summary

Tuberculosis caused by Mycobacterium tuberculosis (MTB) poses a major public health

problem in Nepal. Although it has been reported as one of the dominant genotypes of MTB in

Nepal, little information on the Central Asian Strain (CAS) family is available, especially

isolates related to multidrug resistance (MDR) cases. Here, I aimed to elucidate the genetic and

epidemiological characteristics of MDR CAS isolates in Nepal. A total of 145 MDR CAS

isolates collected in Nepal from 2008 to 2013 were characterized by spoligotyping,

mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR)

analysis and drug resistance-associating gene sequencing. Spoligotyping analysis showed

CAS1_Delhi SIT26 as predominant (60/145, 41.4%). However, by combining spoligotyping

and MIRU-VNTR typing, I was able to successfully discriminate all 145 isolates into 116

different types including 18 clusters with 47 isolates (clustering rate: 32.4%). About a half of

these isolates shared the same genetic and geographical characteristics with other isolates in

each cluster, and some of them shared rare point mutations in rpoB that were thought to

associate with rifampicin resistance. Although the obtained data showed little evidence that

large outbreaks of MDR-TB by CAS family occurred in Nepal, they strongly suggested several

MDR-MTB transmission cases. Therefore, I believe the proposed 15 loci MIRU-VNTR typing

scheme is well suited to assess the population structure of the MDR CAS family and trace back

the transmission dynamics in Nepal.

28

Chapter II

Characterization of genetic diversity of multidrug resistant Mycobacterium tuberculosis

Central Asian Strain isolates from Nepal and comparison with neighboring countries

Introduction

MTB comprises of four major lineages, which can be differentiated based on specific

genetic markers and geographical areas (11, 20, 21, 22). Lineage 3 including the spoligotype-

defined Central Asian Strain (CAS) family is predominant genogroup and spreading in South

Asian countries including India, Pakistan and Nepal (1, 2, 24, 29, 41, 43, 44, 48). In

spoligotyping, CAS family is characterized by the deletion of spacers 4-7 and 23-34 in the direct

repeat locus and divided into more than 25 subfamilies (36). Some studies on genotyping from

Nepal, Northern India and Pakistan revealed that the emergence of MDR CAS family is posing

a serious threat to TB control in South Asian countries (1, 41, 43, 44).

The main purpose of this study was to better understand the genetic diversity, transmission

dynamics and evolutionary relationships of MDR CAS family isolates, especially the major

clade of CAS1_Dehli SIT26, circulating in Nepal and neighboring countries. For this purpose,

I constructed a phylogenetic tree and minimum spanning trees (MSTs) to gain insight into the

genetic characteristics of MDR CAS family by using molecular genotyping tools such as

spoligotyping and MIRU-VNTR typing.

29

Materials and Methods

Sample collection and drug susceptibility test

A total of 145 MDR-TB CAS family isolates were purposively collected from April 2008 to

March 2013 by German Nepal Tuberculosis Project (GENETUP) using a decentralized Nepal

Tuberculosis Programme (NTP) network (Figure 1). Drug susceptibility test (DST) was carried

out using the conventional proportion method for all first line anti-TB drugs (INH, RIF, STR,

EMB) as described previously (54). Furthermore, I reviewed publications on MDR-TB CAS

family from neighboring countries, India and Pakistan (1, 2, 9), to collect the genotyping data

to compare their genetic diversity with Nepalese samples.

DNA extraction

DNA was extracted from mycobacterial culture. Briefly, colonies from positive LJ cultures were

suspended in 300 µl of DNA free distilled water and heated for 20 min at 95 oC. The heated

samples were incubated in an ultra-sonic water bath for 15 min, centrifuged for 5 min at 10,000

g and then supernatant containing bacterial DNA was used for further molecular analysis.

Spoligotyping and MIRU-VNTR typing

All isolates were analyzed by spoligotyping, as described by Kamerbeek et al. (28). Spoligo-

international type (SIT) were determined using SITVITWEB database (http://www.pasteur-

guadeloupe.fr:8081/SITVIT_ONLINE/) and MIRU-VNTRplus (15). MIRU-VNTR typing was

carried out by amplifying 24 loci that included 12 MIRU loci (MIRU2, MIRU4, MIRU10,

MIRU16, MIRU20, MIRU23, MIRU24, MIRU26, MIRU27, MIRU31, MIRU39 and MIRU40),

4 exact tandem repeats (ETR) loci (ETR-A, ETR-B, ETR-C and ETR-F), 4 Queens University

Belfast (QUB) loci (QUB11a, QUB11b, QUB26 and QUB4156) and 4 VNTR loci (VNTR424,

VNTR1955, VNTR2401 and VNTR3690) as described by Supply et al. (46). The copy number

of repeats for each locus was determined based on the allelic table as given by Supply et al.

(46).

Data management and analysis

Hunter Gaston discriminatory indices (HGDI) were calculated to determine the diversity of

each locus (27). The discriminatory power of each locus was determined as high (HGDI>0.6),

moderate (0.3≤ HGDI ≤0.6) and poor (HGDI<0.3) as suggested by Sola et al. (45). A cluster

was defined as two or more isolates sharing the identical spoligotype and MIRU-VNTR patterns

30

and clustering rate was calculated using the formula: number of clustered isolates / total number

of isolates (23). Phylogenetic tree was constructed by unweighted pair group method with

arithmetic averages (UPGMA) using an online MIRU-VNTRplus web based application

[http://www.miru-vntrplus.org] (51).

Minimum spanning trees (MSTs)

MSTs were generated by all the obtained MIRU-VNTR data (n=145) to analyze the

evolutionary relationship among the Nepalese isolates using BioNumerics software version 6.6

(Applied Maths, Sint-Martens-Latem, Belgium) with additional information of spoligotype

(SIT), isolated reagions or isolated years. For the comparison with neighboring-countries’

isolates of India (Mumbai n=16) (9) and Pakistan (n=62) (2), MSTs were drawn with the MIRU-

VNTR patterns of CAS1_Delhi SIT26 subfamily of Nepal (n=60), since the data of other

subfamilies were not available from those neighboring countries.

31

Results

MIRU-VNTR analysis

A combination of spoligotyping and 24-loci MIRU-VNTR analysis could differentiate the 145

MDR CAS family isolates into 116 different patterns as shown in Chapter I. The biggest

spoligotype cluster CAS1_Delhi SIT26, which consisted of 60 isolates, was further

differentiated into 49 MIRU-VNTR types, i.e. five clusters composed of 14 isolates and

remaining isolates with unique patterns. The clustering rate was 23.3% and the biggest cluster

consisted of 6 isolates whereas other four clusters were by 2 isolates (Figure 4). Individual

allelic diversity of each MIRU-VNTR locus of the 60 isolates was estimated by using HGDI

(Table 6). The discriminatory powers of three out of 24 loci (QUB26, MIRU26, VNTR424)

were found to be highly discriminatory, 8 loci (MIRU10, MIRU31, VNTR3690, MIRU39,

VNTR 2401, MIRU40, QUB4156 and ETR-F) were moderately discriminatory and remaining

13 loci (QUB11a, MIRU16, ETRA, MIRU4, VNTR1955, MIRU27, QUB11, MIRU20, MIRU2,

ETR-C, MIRU23, MIRU24 and ETR-B) were poorly discriminatory. I also calculated and

compared the allelic diversity of MIRU-VNTR of Nepalese CAS1_Delhi SIT26 isolates with

those reported from neighboring countries, Pakistan and India, in Table 7. Allelic diversity,

HGDI, of each MIRU-VNTR loci were different among countries and those values of Nepalese

isolates tended to lower than other countries.

MST analysis

MSTs were drawn with the 24-loci MIRU-VNTR typing data of 145 MDR CAS family isolates

from Nepal with following variables; SIT, isolated region and year as shown in Figures 5, 6 and

7, respectively. CAS1_Delhi SIT26 subfamily isolates were more diverse than other SITs and

formed the biggest cluster (Figure 5). No specific regional clusters or yearly trends were

observed by the region wise (Figure 6) and year wise (Figure 7) MST analyses. To compare the

Nepalese CAS1_Delhi SIT26 isolates with neighboring countries, MST analysis were carried

out with 15-loci MIRU-VNTR for Pakistani isolates and 12-loci MIRU-VNTR for Indian

isolates (Figure 8) depending on the data availability. An Indian isolate shared identical MIRU-

VNTR pattern to Nepalese strains, while no Pakistani strain shared the same pattern with

32

Nepalese. Pakistani isolates showed higher genetic diversity than Nepalese isolates.

33

Discussion

CAS family is reported to be highly prevalent among MTB strains in Nepal and

neighboring countries like India (46-68%) (9, 44) and Pakistan (77%) (57). These data support

that the CAS family is a dominate lineage of MTB in certain regions of Indian subcontinent.

However, recent studies demostrated that this strain is also circulating among the local

population in other geographical areas like Sudan (49%), Ethiopia (38.9%), Saudi Arabia

(26.4%), Iraq (24%), Iran (24%) and Egypt (6.1%) (3, 17, 26, 31, 40, 47). Geographically, Nepal

is located between two high TB burden countries, India and China which contribute one third

of world’s TB cases (53, 56). CAS family is one of the dominant strains in northern part of

India whereas Indo-Oceanic family is dominant in the southern and central India (34, 42, 43).

Nepal has open borders with India and Nepalese citizens visit the bordering area of northern

India for different purposes including work, pilgrimage and education. This contact could

provide an opportunity of transmission for CAS family. A similar study in Tibet also linked the

spread of CAS family to trade, tourism and migration from India (18). Current study found

clustering rates of 32.4% in total 145 MDR CAS isolates and 23.3% in subcluster SIT26

suggesting a possible ongoing transmission. Similar to our findings, high clustering rate among

the CAS family have been reported from Saudi Arabia (22.2%) among the foreign-born

nationals, South East Asia (35.3%), Indian sub-continent (18.4%) and West/Horn of Africa

(10.2%) (3). Therefore, there is urgent need for effective control strategies to cut the MTB

transmission chain between Nepal and neighboring countries.

MSTs were constructed to understand the genetic characteristics and evolutional

relationship of 145 MDR CAS family isolates from Nepal (Figure 5, 6 and 7). Overall analysis

of SIT, region wise and year wise MSTs strongly suggested that the Nepalese MDR CAS family

isolates were genetically diverse and most probably, MDR strains emerged in each patient

independently due to a selective pressure of anti-TB drugs. On the other hand, only little

evidences of possible MDR-MTB transmissions between individuals in the same cluster were

shown (Table 5). I could not trace out any personal contacts of patients who were in the MDR-

MTB transmission-suggested cases, and it ought to be indicating the existence of a common

source. It could be speculated that a trans-border visitor might be a missing link of the

34

transmission chain since a large number of TB patients from northern India have been travelling

to Nepal for cheaper TB treatment (35, 37).

In this study, spoligotyping only could not precisely discriminate the pattern of diverse CAS

family in Nepal. By a spoligotyping, CAS1_Delhi SIT26 comprised of 60 isolates was the most

predominant subfamily among 145 CAS family strains (Figure 4). Thus, the 60 MDR

CAS1_Delhi SIT26 strains were subjected to further analysis using the 24-loci MIRU-VNTR

typing to see the genetic diversity and were successfully discriminated into 49 different MIRU

patterns including 5 clusters. The largest MIRU-VNTR-defined cluster composed of six isolates

and these isolates were from three different geographic locations (Table 5). This strain type may

be one of the dominant strains of CAS family in Nepal. Isolates belonging to CAS1_Delhi

SIT26 isolates exhibited diverse MIRU-VNTR patterns in MST (Figure 5). This observation

may suggest that the strain might have adapted to Nepalese people over a long period with

acquiring genetic diversity and resulted in the establishment as the dominant strain among

Nepalese population (35). Since the CAS1_Delhi SIT26 spoligotype has the basic pattern of

the CAS family (spacers 4-7 and 23-34 deleted), this strain should be the parental type that must

have a longer history than others SITs, which evolved later on.

I also compared allelic diversity of MIRU-VNTR of CAS1_Delhi SIT26 with those

published from neighboring countries. In our study MIRU alleles (QUB11a, MIRU16, ETR-A,

MIRU4, VNTR1955, MIRU27, QUB11b, MIRU20, MIRU2, ETR-C, MIRU23, MIRU24 and

ETR-B) were highly conserved and showed poor discriminatory power (HGDI<0.3). However,

the same locus had different allelic diversity in surrounding countries and Nepalese HGDIs

tended to lower than other countries (Table 7). This finding is consisent with the other reports

that suggest difference in allelic diversity due to difference in geographical region and genetic

diversity of MTB families (1, 2). Since, I was interested to understand the relationship between

Nepalese isolates and other South Asian countries isolates, I constructed MSTs of our MDR

CAS1_Delhi SIT26 isolates together with those isolates previously reported from surrounding

countries, India and Pakistan (2, 9) (Figure 8). The topologies of MSTs based on the data of

three countries suggested that clones of CAS1_Delhi SIT26 in Pakistan were highly diverse

and genetically distant from Nepalese when compared with Indian. As expected, an Indian

35

isolate shared the same MIRU-VNTR pattern with a Nepalese MDR CAS1_Delhi SIT26 cluster.

I therefore elucidate that the existence of evolutionary relationship and possible trans-border

transmission between Nepal and India. The present study findings support Wirth et al. (52) who

speculated that CAS family might have emerged over 9,000 years ago in the Indian subcontinent.

Therefore, further studies of MDR-MTB CAS family isolates of Nepal and surrounding

countries will be needed to elucidate the epidemiological link, transmission chains and also its

evolutionary history using validated molecular approaches e.g. whole genome sequence

analysis.

36

Table 6: Individual and Cumulative HGDI of CAS1_ Delhi (SIT26) (N=60)

VNTR alias Individual

HGDI

No. of

clusters

No. of

clustered

isolates

Clustering

rate (%)

No. of

isolates in

each cluster

Cumulative

HGDI

QUB26 0.6712 0.6712

MIRU26 0.6292 9 58 96.6 2-19 0.8965

VNTR424 0.6185 10 44 73.3 2-8 0.9595

MIRU10 0.5330 11 40 66.6 2-7 0.9728

MIRU31 0.5105 11 35 58.3 2-7 0.9779

VNTR3690 0.4920 10 31 51.6 2-7 0.9810

MIRU39 0.4889 10 31 51.6 2-7 0.9810

VNTR2401 0.4004 9 28 46.6 2-7 0.9841

MIRU40 0.3973 9 25 41.6 2-6 0.9866

QUB4156 0.3195 9 24 40.0 2-6 0.9882

ETR-F 0.3143 9 24 40.0 2-6 0.9882

QUB11a 0.2908 8 21 35.0 2-6 0.9897

MIRU16 0.2800 8 21 35.0 2-6 0.9897

ETR-A 0.2759 8 21 35.0 2-6 0.9897

MIRU4 0.1536 8 21 35.0 2-6 0.9897

VNTR1955 0.1525 7 19 31.6 2-6 0.9902

MIRU27 0.0937 7 19 31.6 2-6 0.9902

QUB11b 0.0317 7 19 31.6 2-6 0.9902

MIRU20 0.0317 6 17 28.3 2-6 0.9907

MIRU2 0 6 17 28.3 2-6 0.9907

ETR-C 0 6 17 28.3 2-6 0.9907

MIRU23 0 6 17 28.3 2-6 0.9907

MIRU24 0 6 17 28.3 2-6 0.9907

ETR-B 0 6 17 28.3 2-6 0.9907

37

Figure 4: 24-locus MIRU-VNTR based dendrogram of 60 MDR CAS1_Delhi (SIT26) isolates

from Nepal. (A) The dendrogram was generated by UPGMA [www.miru-vntrplus.org]. (B)

Strain identification number. (C) MIRU-VNTR results of 24 loci. The order of loci is as follows,

left to right: MIRU2, VNTR424, ETR-C, MIRU4, MIRU40, MIRU10, MIRU16, VNTR 1955,

MIRU20, QUB11b, ETR-A, QUB11a, VNTR 2401, ETR-B, MIRU23, MIRU24, MIRU26,

MIRU27, ETR-F, MIRU31, VNTR 3690, QUB26, QUB4156 and MIRU39. (D) Spoligotype

pattern. (E) SIT (Spoligo-international type) number. (F) Clade annotated by SITVIT database.

Isolates clusters (identical patterns of MIRU-VNTR) are enclosed in open boxes.

38

Table 7: Allelic diversity of MIRU-VNTR loci in MDR CAS family (SIT26) strains from

Nepal and neighboring countries.

VNTR alias VNTR

locus

Nepal (N=60)

(current

study)

Pakistan

(N=62) [1]

Pakistan

(N=20) [2]

India

(Munbai)

(N=16) [9]

QUB26 4052 0.671 - 0.821 -

MIRU26 2996 0.629 0.808 0.721 0.766

VNTR424 424 0.618 - 0.721 -

MIRU10 960 0.533 0.753 0.70 0.775

MIRU31 3192 0.510 0.758 0.668 0.241

VNTR3690 3690 0.492 - 0.568 -

MIRU39 4348 0.488 0.715 - 0.125

VNTR2401 2401 0.400 - 0.568 -

MIRU40 802 0.397 0.715 0.468 0.675

QUB4156 4156 0.319 - 0.594 -

ETR-F 3293 0.314 - - -

QUB11a 2163a 0.290 - - -

MIRU16 1644 0.280 0.778 0.531 0.575

ETR-A 2165 0.275 - 0.531 -

MIRU4 580 0.153 0.287 0 0.125

VNTR1955 1955 0.152 - 0.194 -

MIRU27 3007 0.093 0.750 - 0

QUB11b 2163b 0.031 - 0.268 -

MIRU20 2059 0.031 0.670 - 0

MIRU2 154 0 0.546 - 0.125

ETR-C 577 0 - 0.278 -

MIRU23 2531 0 0.546 - 0.233

MIRU24 2687 0 0.521 - 0.125

ETR-B 2461 0 - - -

N: Number of MDR CAS family (SIT26) isolates

-: Not reported

[1] Ali A et al. (2007)

[2] Ali A et al. (2014)

[9] Chatterje and Mistry (2012)

39

Figure 5: Minimum spanning tree (MST) constructed based on diversity of the 24 loci MIRU-

VNTR results of 145 MDR MTB CAS family. The size of circle is proportional to the total

number of isolates representing unique isolates (smaller nodes) and clustered isolates (bigger

nodes). The color of the circles indicates the CAS family belongs to particular Spoligotype-

International type (SIT). The MST connects each sub-family based on degree of changes

required from one allele to another; solid lines (1or 2 or 3 changes), gray dashed lines (4) and

gray dotted lines (5 or more changes).

Lines denotes the number of allele changes

1 2 3 4 5 ................

40

Figure 6: Minimum spanning tree (MST) constructed based on region wise distribution of 145

MDR MTB CAS family. The size of circle is proportional to the total number of isolates

representing unique isolates (smaller nodes) and clustered isolates (bigger nodes). The color of

the circles indicates the CAS family belongs to regionwise. The MST connects each sub-family

based on degree of changes required from one allele to another; solid lines (1or 2 or 3 changes),

gray dashed lines (4) and gray dotted lines (5 or more changes).

41

Figure 7: Minimum spanning tree (MST) constructed based on year wise isolation MIRU-

VNTR results of 145 MDR MTB CAS family. The size of circle is proportional to the total

number of isolates representing unique isolates (smaller nodes) and clustered isolates (bigger

nodes). The color of the circles indicates the CAS family belongs to yearwise. The MST

connects each sub-family based on degree of changes required from one allele to another; solid

lines (1or 2 or 3 changes), gray dashed lines (4) and gray dotted lines (5 or more changes).

42

Figure 8: MIRU-VNTR based minimum spanning tree (MST) was constructed to trace out the

evolutionary relationship of MDR MTB CAS family (SIT26) of Nepal and neighboring

countries (India and Pakistan). (a) Comparative MST based on 15 loci between Pakistan and

Nepal (b) Comparative MST based on 12 loci between India and Nepal. The size of circle is

proportional to the total number of isolates; unique isolates (smaller nodes) and clustered

isolates (bigger nodes). The color of nodes indicates corresponding country of origin of isolates.

Pakistan (Ali A et al.2014)

Nepal (In this study)

India (Chatterjee and Mistry 2012)

Nepal (In this study)

a.15 loci MIRU-VNTR b.12 loci MIRU-VNTR

43

Summary

Multidrug-resistant Tuberculosis (MDR-TB) is an emerging threat for successful TB

control in Indian subcontinent region. Central Asian strain (CAS) family has been reported as

one of the dominant families contributing to MDR-TB in South Asia including Nepal, India

and Pakistan. The aim of this study was to better understand the genetic characteristics of MDR

CAS family isolates circulating in Nepal, as well as in neighboring countries.

A total of 145 MDR-TB CAS family isolates collected in Nepal from 2008 to 2013 were

analyzed by spoligotyping and mycobacterial interspersed repetitive units-variable number of

tandem repeats (MIRU-VNTR) analysis. I also compared these data with published data from

India and Pakistan to investigate possible epidemiological link through construction of

Minimum spanning tree (MST). Spoligotyping analysis exhibited CAS1_Delhi SIT26 (n=60)

was the predominant lineage among MDR CAS family in all three countries. However, by

combining two genotyping methods, spoligotyping and MIRU-VNTR, 60 isolates were further

discrimnated into 49 different types and 5 clusters. These clusters composed of 14 isolates with

clustering rate (23.3%), suggesting ongoing transmissions. Based on MST data from

neighboring countries, I elucidated an evolutionary relationship between the two countries,

Nepal and India, which could be explained by their open borders. This study identified the

evolutionary relationships among MDR CAS1_Delhi subfamily isolates from Nepal and those

from neighboring countries.

44

Conclusion

Central Asian strain (CAS) family is one of the dominant MTB families among MDR-MTB,

which is emerging in South Asian countries including Nepal. To date, there are only limited

studies have been reported and little is known about the genetic diversity of MDR-MTB CAS

family in Nepal and neighboring countries. Therefore, the present study was necessary to gain

insight into the characteristics of MDR CAS family circulating in Nepal and neighboring

countries like India and Pakistan.

In this regard, in chapter I, I investigated the genetic characteristics of MDR-MTB CAS

family isolates from Nepal by applying three molecular approaches, i.e. Spoligotyping, 24-loci

MIRU-VNTR analysis and drug resistance-associating genes (rpoB, KatG and the inhA

promoter region) analysis. Those molecular analyses demonstrated that the MDR CAS family

isolates were highly diverse in Nepal, which suggested that the bacteria progressively acquired

drug resistance and ultimately became MDR in each patient. Nonetheless, the genetic and

epidemiological characteristics of some clustered isolates showed the evidence of actual MDR-

MTB transmission. A large MDR-TB outbreak would be more likely to occur among the

Nepalese population if transmission trends observed in the present study grew out of control.

Thus, our results highlight the importance of laboratory diagnosis of TB, intensified finding of

cases and timely and appropriate treatment of TB patients to cut the transmission chain.

Therefore, I believe the proposed 15 loci MIRU-VNTR typing scheme will be well suited to

assess the population structure of the MDR CAS family and trace back the transmission

dynamics in Nepal.

In Chapter II, I elucidated the genetic characteristics and evolutionary relationships of

predominant MDR CAS subfamily isolates circulating in Nepal and neighboring countries by

using molecular approach. I found that CAS1_Delhi SIT26 was predominant among MDR-

MTB CAS family in South Asia, and widely spread throughout the Nepalese population with

higher diversity than other subfamilies. On the contrary, its diversity in Nepal was relatively

low in the comparison with neighboring countries, India and Pakistan, suggesting a shorter

endemicity history than those countries. In MST analysis, isolates of CAS1_Delhi SIT26 in

45

Pakistan were highly diverse and genetically distant from Nepalese when compared with Indian.

Indian CAS1_Delhi SIT26 family had similar MIRU-VNTR patterns to Nepalese strains with

one isolate shared the identical pattern with a Nepalese isolate cluster. Nepal has an open border

with India, and both Nepalese and Indian citizens often visit the bordering area for work,

pilgrimage and education. This regular interaction may open an opportunity for direct

transmission of the CAS family MTB between the Indian and Nepalese populations.

I believe that the findings of my study on the genetic diversity, epidemiological

characteristics and evolutionary relationships have extended our understandings on the

predominant MDR CAS family genotypes from Nepal and neighboring countries. It is foreseen

that the results from the present study will contribute to improve epidemiological surveillance,

which in turn could lead to implementation of more effective control measures against the

spread of MDR-MTB in Nepal and surrounding countries. The information gained by genetic

diversity of MDR CAS family isolates from the present study and comparison with neighboring

countries may provide base line information for future molecular epidemiological studies and

will also be helpful for assessments of TB Control programs in their respective countries.

46

ACKNOWLEDGEMENTS

It is my immense pleasure to express heartfelt appreciation and an enormous debt to my

respected supervisor Prof. Yasuhiko Suzuki from Division of Bioresources, Hokkaido

University Research Center for Zoonosis Control, Sapporo, Japan, for providing an excellent

opportunity for PhD study under his excellent supervision. His outstanding mentorship,

continuous support and valuable suggestions were extremely helpful to enhance my knowledge

and understanding in the field of tuberculosis (TB) research during my study.

I would also like to especially express my sincere and profound gratitude, and earnest

compliment to Assoc. Prof. Chie Nakajima, Division of Bioresources, Hokkaido University

Research Center for Zoonosis Control, Sapporo, Japan, for her invaluable guidance, outstanding

inspiration, tremendous support and encouragement to widen my knowledge and understanding

of TB and the genetic analyses of the isolates. Her guidance was very instrumental in planning

of the research, conducting the experiments and preparation of manuscript

I would like to express my sincere gratitude to Prof. Hideaki Higashi and Assoc. Prof.

Norikazu Isoda for their valuable suggestions, guidance and inputs in my TB research that was

extremely helpful to carry out my proposed research successfully. I am highly thankful to all

the faculties from Hokkaido University Research Center for Zoonosis control and Graduate

School of Veterinary Medicine for their kind support, guidance and recommendations in my

research as well as for their support to complete the required credit courses during my PhD

training here at Hokkaido University.

I am highly grateful to Mr. Bhagwan Maharjan and all members of German Nepal

Tuberculosis Project (GENETUP), Kathmandu, Nepal for their enormous help with collections,

processing and providing the DNA samples extracted from isolates of M. tuberculosis collected

from human TB patients of Nepal for my entire PhD research works. Everyone at GENETUP

were so welcoming and they were always ready to help with my research. I am also highly

indebted to Dr. Basu Dev Pandey from Everest International Clinic and Research Center, Nepal

for his genuine cooperation and encouragement throughout my study.

My especially thanks go to Dr. Ajay Poudel (Chitwan Medical College and teaching Hospital,

Nepal), Mr. Jeewan Thapa (Division of Bioresources, CZC), Dr. Hassan Mahmoud Diab (South

47

Valley University, Egypt), Mr. Eddie Solo (University Teaching Hospital, Zambia) supports

during the research experiments as well as preparation of the manuscript. I would also like to

thanks to Ms. Yukari Fukushima and Ms. Haruka Suzuki from Division of Bioresources,

Hokkaido University Research Center for Zoonosis control for their technical support during

the genotyping experiments.

I would like to express my heartfelt thanks to Dr. Kanjana Changkaew, Dr. Siriporn Kongsoi,

Dr. Ruchirada Changkwanyeun, Dr. Marvin Ardeza Villanueza, Dr. Tomoyuki Yamaguchi, Ms.

Nan Aye Thida Oo, Ms. Lai Lai San, Ms. Charitha Mendis, Mr. Jong-Hoon Park, Mr. Yuko

Ouchi, Mr. Kentaro Koide, Ms. Dipti Shrestha, Ms. Ruttana Pachanon, Mr. Thoka Flav

Kapalamula, Ms. Mwangala Lonah Akapelwa, Ms. Risa Tsunoda, Ms. Conschilliah Menda, Dr.

Yayoi Kameda, Ms. Miki Nakagawa, Ms. Janisara Rudeeaneksin, Dr. Fuangfa Utrarakij, Dr.

Nipawit Karnbunchob, Mr. Alex Samuel Kiarie Gaithuma and the rest of the members of CZC

for creation my four years stay in Sapporo, Japan fruitful, enjoyable and unforgettable moments

through out of my life as well as for their kind support and constant inspirations during my

research and studies. I am also like to conveying especially thanks our division secretaries Ms.

Midori Yoshida and Ms.Yuko Hidaka for their countless help me in many administrative works

and additional support in my difficult situation during my stay in Sapporo, Japan.

Respectfully, I would like to jot down my deepest thanks to all my senior teachers and friends

especially to Dr. Sher Bahadur Pun (Sukraraj Tropical and Infectious Disease Hospital,

Kathmandu, Nepal), Dr. Kishor Pandey (Nepal Academy of Science and Technology, Lalitpur,

Nepal), Dr.Sarad Paudel (Department of Cell physiology, Hokkaido University, Sapporo,

Japan) and Mr.Rabin Kadariya (Laboratory of Wildlife Biology and Medicine, Hokkaido

University, Sapporo, Japan) for providing me necessary assistance and invaluable suggestions

during the study period.

This research study was supported by the Leading Program at Hokkaido University, Graduate

School of Veterinary Medicine, Japan “Fostering Global Leaders in Veterinary Science toward

Contributing to ‘One Health’” from Ministry of Education, Culture, Sports, Science and

Technology, Japan (MEXT), U.S.-Japan Cooperative Medical Science Programs from Japan

Agency for Medical Research and development (AMED), Japanese Society for the Promotion

48

of Science (JSPS) ROMPAKU Program, MEXT/JSPS KAKENHI and Research Program on

Emerging and Re-emerging Infectious Diseases from AMED.

Finally, I am greatly obliged to my parents, wife and lovely (Priya/Priyan) without whose

constant inspiration and unconditional support, this work would not have been completed.

49

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