Literature DB >> 29915257

Association of gyrA and rrs gene mutations detected by MTBDRsl V1 on Mycobacterium tuberculosis strains of diverse genetic background from India.

Syed Beenish Rufai1, Jitendra Singh1, Parveen Kumar1, Purva Mathur1, Sarman Singh2.   

Abstract

There is limited data on the use of Genotype MTBDRslVersion 1 (MTBDRsl V1) as an initial rapid screening test to rule out XDR-TB and most importantly its performance in various genotypes of Mycobacterium tuberculosis is scarcely studied. A total of 359 MDR-TB isolates were tested for gene mutations representing second line drug resistance, using the MTBDRsl_V.1 and the results were compared with phenotypic method (Bactec MGIT-960 system) for second-line drug (SLD) susceptibility testing. Genetic lineages of all these isolates were also determined using spoligotyping and SITVIT2 WEB database. The MTBDRsl V1 detected mutations in the gyrA, rrs, and emb genes in 108 (30%), 2 (0.5%) and 129 (35.9%) isolates, respectively. Remaining 120 (33.4%) had no second line drug (SLD) resistance. In 17 (4.7%) isolates mutations were detected in both gyrA and rrs genes. Its concordance with MGIT-960 culture drug susceptibility testing (DST) was 97% and 94.1%, 93.5%, 60.5% and 50% for the detection of XDR-TB, pre-XDR, Ethambutol, and Aminoglycosides/Cyclopeptides resistance. The Beijing lineage was predominant (46%) between both the pre-XDR/XDR-TB isolates. We conclude that MTBDRsl is useful for rapid detection of SLD resistance. Also in pre-XDR and XDR-TB isolates the frequency of relevant genetic mutations was significantly higher in the Beijing strains.

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Year:  2018        PMID: 29915257      PMCID: PMC6006251          DOI: 10.1038/s41598-018-27299-z

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

The recent estimates of World Health Organization (WHO) show that more than 10.4 million people had incidental tuberculosis (TB) and 1.7 million died of this disease in 2016 alone. The 2016 data also showed that India is the most vulnerable country to TB with 2.8 million new cases (26.9% of global cases) in the year 2016[1]. The scenario was not much different in 2017. Approximately 600,000 Rifampicin resistant (RIFR) cases were reported, of whom 490,000 had multi-drug resistant TB (MDR-TB). The drug resistance TB has become a major challenge to the success of TB control programmes around the globe[2]. Not only diagnosis, even the treatment of MDR-TB is difficult, requiring much longer duration of treatment with very costly and comparatively more toxic second-line drugs (SLDs) such as fluoroquinolones (FQ) and aminoglycosides/cyclic peptides (AG/CP)[3]. Moreover, emergence of resistance even to the SLDs is being reported from all parts of the world. This form of TB is known as extensively drug-resistant TB (XDR-TB), which is a more devastating condition with very poor treatment success[4]. In 2016, an estimated 6.2% patients with MDR-TB were found to have XDR-TB. India reported first case of XDR-TB[5] in 2007 and by 2015 more than 117 countries were already struggling with this condition[1,5]. Therefore, it is essential that all suspected cases of MDR-TB must be investigated for susceptibility to second drugs also, in a timely manner to control the spread of spread of XDR-TB. This has become essential in order to optimize the treatment regimen at the earliest. However, the conventional methods of drug susceptibility testing (DST) for SLDs are more complex due to non-standardized methods and protocols, leading to poor reproducibility and reliability[6]. Also, the conventional culture-based methods are labour intensive and require longer turn around time (TAT) with undesirable treatment outcome and wider window to disease transmission[7,8]. In 2013, a Line probe assay (LPA), also known as Genotype MTBDRsl (MTBDRsl) was developed by Hain’s Life Science GmbH, Germany and was approved by the WHO also for clinical use. This molecular test rapidly detects genotypic resistance to FQ, AG/CP and Ethambutol (EMB) within 48–72 h and makes it possible to diagnose pre-XDR-TB and XDR-TB at the earliest[9,10]. Therefore, the use of MTBDRsl has been recommended as a rapid and initial diagnostic test to rule out FQ and AG/CP resistance in all MDR-TB patients in order to initiate effective treatment at the earliest[11]. Recently, WHO recommended the use of MTBDRsl test in place of conventional phenotypic culture-based DST methods especially in high TB burden countries[12]. India, a high TB burden country is keen to implement these guidelines but usefulness of MTBDRsl on MDR TB isolates has not yet been evaluated from India. The genotypic characterization of MTB isolates becomes essential to understand the clonal expansion of the lineages, their transmission dynamics and association with drug resistance[13]. There are several studies which have shown association of different lineages of MTB with variable pathogenicity and vulnerability to drug resistance[14-17]. For genotyping of the MTB, spoligotyping is a widely used technique which detects the presence or absence of 43 spacer sequences in clustered regularly interspersed short palindromic repeat (CRISPR) region of MTB[14]. Though several studies are published on association of various lineages of MTB with first-line drug resistance, there is not enough literature on the association of MTB lineages with resistance to second-line drugs[14]. Thus, the main aim of the present study was to evaluate the usefulness of MTBDRsl assay in comparison with phenotypic line drug resistance testing using the Bactec MGIT-960 system in a programmatic mode. We also aimed to find if there was any association between the second line drug resistance pattern and genetic lineages of MTB isolates.

Materials and Methods

Setting

This retrospective study was conducted in the TB research laboratory, which is a certified routine diagnostic laboratory in the Division of Clinical Microbiology & Molecular Medicine, All India Institute of Medical Sciences, New Delhi, India. All the routine mycobacterial isolates are stored and maintained in laboratory repository after characterization. From this repository, 359 MDR-TB isolates that were stored during 2011–2015 were used in the present study. Patient’s clinical details were retrieved as published earlier[14,18] (Table 1). These isolations were made as a part of previous study, which was approved by Institutional ethics committee of the All India Institute of Medical Sciences, New Delhi (reference number IESC/T-39/04.01.2013). All in-vitro methods were performed in accordance with the standard guidelines and following the manufacturer’s instructions. The mycobacterial culture and DST were performed using the MGIT-960 system and identification of Mycobacterium tuberculosis (MTB) and Non-tuberculous Mycobacteria (NTM) was done by well established in-house multiplex polymerase chain reaction (PCR)[19].
Table 1

Showing association of lineages with place of origin, smear positivity, site of isolation and drug resistance.

Main Residence of patientSmear microscopySite of sampleDrug resistance PatternGenotypes
Smear + ve Smear −ve PTB EPTB Sensitive Pre-XDR XDR Beijing CAS EAI Manu T X S H Ural Unique
Assam (44)4404402021327921110003
Bihar (35)1223152023102101301300215
Delhi (132)61717458983132567251260807
Haryana (5)14234102100000101
J&K (1)01010100000000100
Meghalaya (20)200200145114500100000
Mizoram (2)02202000000002000
Madhya Pradesh (1)01010100100000000
Punjab (70)70070042235183440600008
Rajasthan (1)01010100000000001
Sikkim (10)82827306210000100
Tripura (13)13013065210210000000
Uttar Pradesh (24)1113111315816820310013
Uttarakhand (1)01010101000000000
Total (359) 240 119 259 100 231 111 17 119 142 12 7 26 8 2 13 2 28

PTB- Pulmonary Tuberculosis.

EPTB- Extra-pulmonary Tuberculosis.

Showing association of lineages with place of origin, smear positivity, site of isolation and drug resistance. PTB- Pulmonary Tuberculosis. EPTB- Extra-pulmonary Tuberculosis.

Demographic details and characteristics of MDR-TB patients

Out of the 359 patients from whom these isolations were made, 210 (58.5%) were males and 149 (41.5%) females with mean age of 31.4 ± 14.3 years and 27.1 ± 15.8 years, respectively. Majority of cases were adults [331 (92.2%)] and only a few [28(7.8%)] were from paediatric age group. Majority of isolates [259 (72.1%)] were from pulmonary samples and 100 (27.8%) isolates were from extra-pulmonary samples (Supplementary Fig. 1). A total of 240 (66.8%) isolates were from smear positive while 119 (33.2%) isolates were from smear negative samples (Table 1).

Subculture on Lowenstein Jensen (L-J) medium for pure growth

From each Bactec MGIT-960 tube, 200 μL of culture suspension was sub-cultured on L-J medium slants and incubated at 37°C to obtain pure growth (isolated colonies) of MTB. After 21–28 days of incubation, single colony with the help of sterile inoculating loop was picked from L-J medium and inoculated in the MGIT (Mycobacteria growth indicator tube). The tube was incubated in the Bactec MGIT-960 system until flagged positive and this growth was used for second-line MGIT DST and DNA extraction for spoligotyping and MTBDRsl[20].

Preparation of drug stock and working solutions

All SLDs were purchased from Sigma-Aldrich Corporation (St. Louis MO, USA) in the form of powder. The stock solutions of amikacin (AMK), kanamycin (KAN), and capreomycin (CAP) were prepared in sterile deionized water while ofloxacin (OFX) solution was prepared in 0.1N-NaOH. Stock solutions were sterilized through 0.22-μM-pore-size Milex-GS filter units (Millipore Bedford MA, USA) and the aliquots stored at −80 °C for further use.

Second Line Drug susceptibility (DST) testing using Bactec MGIT-960 system

Aliquots of OFX, AMK, KAN and CAP stock solutions were diluted to critical concentrations as recommended to perform the second line DST by Bactec MGIT-960 system[7]. DST was performed on Day 1 and Day 2 by single dilution [0.5 mL of 1:100 dilution inoculum for growth control (GC) and 0.5 mL of inoculums directly in four respective drug containing tubes] while from the growth of Day 3 to Day 5 by double dilution [inoculated 0.5 mL of 1:4 dilution inoculums directly into four drug containing tubes] and in GC tubes using the 1:100 dilution of the inocula from the day MGIT flashed positive. GC tubes and four drug panel tubes were set in the antimicrobial susceptibility testing (AST) carrier rack and loaded in the Bactec MGIT-960 system and continuously monitored by BD Epi-center[21]. As AST carrier rack for SLDs, the panel is not available commercially for the MGIT-960 system, it was registered as one of the SIRE (Streptomycin, Isoniazid, Rifampicin, Ethambutol) panel in order to get a printable report and drug susceptibility testing results[22].

Genotype MTBDRsl V1

The MTBDRsl test is based on the DNA strip technology having three steps: DNA extraction, multiplex PCR amplification, and reverse hybridization. All steps were performed as per manufacturer’s instructions[10,23]. The DNA obtained from the standard MTB- H37RV strain (as positive control) and one negative control was also tested in each batch in order to check the cross-contamination during hybridization assay and other quality parameters. The test was considered as valid; only when the hybridization bands were obtained on MTB complex control (TUB), conjugate controls (CC) and the amplification controls (AC) along with the targeted gene loci controls. For convenience MTBDRsl V1 will be referred as MTBDRsl only hereafter.

Genotyping of MDR-TB isolates by spoligotyping

DNA extraction for spoligotyping

DNA extraction from MTB cultures grown on L-J medium was performed using chloroform iso-amyl alcohol (CI) method as mentioned previously[24].

Spoligotyping

Spoligotyping was performed using the commercially available kit (Ocimum Biosolutions, Hyderabad, India) by amplification, hybridization and finally detection of hybridizing DNA[25]. In brief, the PCR amplified products were hybridized on a membrane and images were detected with electro-chemi-luminescence (ECL) detection kit (GE Healthcare, Life Sciences, UK) on X-ray films (Kodak, Rochester, NY)[14]. The MTB H37Rv and M. bovis-BCG strains were included as a quality control in every batch of test. The hybridization patterns obtained in the binary format were transformed to an octal code for assessment with the spoligotype patterns using SITVIT2 database, which is an updated version of SITVIT_WEB database[26]. A shared type was defined as a spoligotype pattern common to at least two isolates, and clades were assigned according to the signatures as published earlier[14].

Statistical analysis

Results of MTBDRsl were analysed and compared with second-line Bactec MGIT-960 DST, which was considered as the gold standard. Data was statistically analysed to calculate the agreement between MTBDRsl and SL-MGIT DST using OpenEpi 3.01. Moreover, Fisher’s exact test was performed using STATA 11.1 software to observe significance of the association amongst the second line drug resistant mutation patterns among the different genotypes.

Results

Second-line DST by Bactec MGIT-960 system

Using the phenotypic MGIT-960 system, of the 359 MDR-TB isolates subjected to second-line DST, 231 (64.4%) were found to be susceptible to all second line anti-TB drugs, 127 had resistance to FQ. Of the 127 isolates, 110 (30.6%) were mono-resistant to FQ (pre-XDR) and 10 (2.7%) isolates were resistant to all OFX-KAN-AMK-CAP, 6 (1.7%) were resistant to OFX-KAN-AMK and 1 (0.3%) isolate was resistant to OFX-KAN only. Thus, phenotypically these 17 (4.7%) isolates were labelled as XDR-TB isolates. Only one (0.3%) isolate was resistant to AG/CP (Table 2).
Table 2

Concordance between Genotype MTBDRsl and Bactec MGIT-960 based second-line drug susceptibility testing.

Genotype MTBDR sl SLD by Bactec MGIT 960
Sensitive (%)FQ mono-resistant (%)AG/CP mono-resistant (%)XDR (%)Concordance (%) k coeff
Sensitive (232) (64.6%)225 (97)7(3.0)970.92 Perfect
FQ- resistant (108) (30%)6(5.5)101 (93.5)1(0.9)93.50.89 Perfect
AG/CP- resistant (2) (0.5%)1(50)1 (50)500.66 Substantial
XDR (17) (4.7%)1(5.9)16(94.1)94.10.93 Perfect
Total (359)231 (64.4)110 (30.6)1 (0.3)17 (4.7)

FQ- Fluoroquinolone, AG- Aminoglycosides, CP-Cyclopeptide.

k coeff.- Cohens’s kappa as a measure of agreement between two values.

Concordance between Genotype MTBDRsl and Bactec MGIT-960 based second-line drug susceptibility testing. FQ- Fluoroquinolone, AG- Aminoglycosides, CP-Cyclopeptide. k coeff.- Cohens’s kappa as a measure of agreement between two values.

EMB resistance

All 359 isolates previously tested for SIRE DST, 143 (39.8%) isolates were detected as resistant and 216 (60.2%) isolates were detected sensitive to EMB (Supplementary Table 1).

Genotype MTBDRslV1

Out of 359 MDR-TB isolates, in 232 (64.6%) isolates no mutation was detected in gyrA and rrs genes, which means that these were sensitive to FQ and AG/CP drugs. However, 125 (34.8%) isolates showed mutations in gyrA region, of which 108 showed FQ mono-resistant (pre-XDR) but 17 also showed additional mutations in rrs genes (XDR-TB) (Table 2). Among the single codon mutations observed in gyrA region, the most prevalent mutation was ΔWT3-D94G (51; 40.8%) followed by ΔWT2-A90V (31; 24.8%). However, among the double codon mutations, the most prevalent mutation was A90V-D94G (7; 5.6%) followed by ΔWT3-D94G-D94H (2; 1.6%). Only one strain harboured triple codon mutation ΔWT3-D94N/Y-D94H-D94G in gyrA region (Table 3).
Table 3

Association of genotypes with mutational pattern in gyrA (108 FQ mono-resistant and 17 XDR-TB) and rrs gene regions (2 AG/CP mono-resistant and 17 XDR-TB isolates) detected by Genotype MTBDRsl assay on 125 culture isolates.

Codon mutation (gyrA)Total no. of isolates (%)Genotype (%)
BeijingCASEAIHManuTUralUniqueX
ΔWT3-D94G51 (40.8)23 (45.1)14 (27.4)1 (1.9)1 (1.9)3 (5.8)4 (7.8)5 (9.8)
ΔWT3-D94A6 (4.8)4 (66.7)1 (16.7)1 (16.6)
ΔWT3-D94N/Y6 (4.8)6 (100)
ΔWT3-D94H5 (4)3 (60)2 (40)
ΔWT33 (2.4)2 (66.7)1 (33.3)
ΔWT2-A90V31 (24.8)10 (32.2)8 (25.8)3 (9.7)3 (9.7)2(6.4)2 (6.4)2 (6.4)1(3.2)
ΔWT2-S91P1 (0.8)1 (100)
+WT-A90V3 (2.4)2 (66.7)1(33.3)
+WT-D94G2 (1.6)2 (100)
+WT-D94H2 (1.6)2 (100)
+WT-D94A1 (0.8)1 (100)
ΔWT3-D94G- D94H2 (1.6)2 (100)
A90V, D94A2 (1.6)1 (50)1 (50)
+WT-A90V- D94G7 (5.6)2 (28.6)3 (42.8)2 (28.5)
+WT-A90V-D94A1 (0.8)1 (100)
ΔWT3-D94A- D94G1 (0.8)1 (100)
ΔWT3-D94N/Y- D94G-D94H1 (0.8)1 (100)
Total:125 (34.8)56 (44.8)33 (26.4)4 (3.2)1 (0.8)4 (3.2)8(6.4)2 (1.6)11 (8.8)6 (4.8)
Codon Mutation ( rrs )
ΔWT1-A1401G11 (57.9)6 (54.5)2 (18.2)1 (9.1)1 (9.1)1 (9.1)
ΔWT1-G1484T1 (5.3)1 (100)
ΔWT1-C1402T1 (5.3)1 (100)
+WT-A1401G6 (31.6)3 (50)2 (33.3)1 (16.7)
Total: 19 (5.2) 10 (52.6) 4 (21.1) 1 (5.3) 1 (5.3) 1 (5.3) 1(5.3) 1 (5.3)

ΔWT- Deletion of wild type band. +WT- Presence of wild type band.

Association of genotypes with mutational pattern in gyrA (108 FQ mono-resistant and 17 XDR-TB) and rrs gene regions (2 AG/CP mono-resistant and 17 XDR-TB isolates) detected by Genotype MTBDRsl assay on 125 culture isolates. ΔWT- Deletion of wild type band. +WT- Presence of wild type band. Of the 19 (15.2%) isolates that showed resistance mutation pattern in the rrs region, 17 (89.4%) were XDR-TB and 2 (10.6%) were AG/CP mono-resistant. In these isolates, most prevalent mutation was ΔWT1-A1401G (11; 57.9%) and A1401G (31.6%). The detailed mutational patterns in gyrA and rrs genes are shown in Table 3.

Detection of EMB resistance by Genotype MTBDRsl V1 in emb gene

Overall MTBDRsl detected 129 (35.9%) isolates having resistance to EMB. Of these 58 (44.6%) isolates were mono-resistant to FQ, 1 (0.7%) isolate was mono-resistant to AG/CP only and 9 (6.9%) isolates were XDR-TB isolates. The most prevalent mutations in the emb gene were ΔWT1-Mut1b in 95 (73.6%) isolates, ΔWT1-Mut1a in 20 (15.5%), ΔWT in 10 (7.7%), and ΔWT1-Mut1a-Mut1b in 4 (3.1%) isolates.

Comparison of second line DST using MGIT-960 versus Genotype MTBDRsl V1

The MTBDRsl showed 97% concordance with second-line MGIT-960 DST for detecting the sensitive isolates. However, mutations were detected in 101 (93.5%) isolates that were FQ resistant by MGIT-960 system. MTBDRsl also efficiently detected 17 (4.7%) isolates as XDR-TB giving a concordance rate of 94.1% with MGIT-960 system (Table 2). Of the 143 (39.8%) EMB resistant isolates identified by SIRE MGIT-960 DST, 86 (60.1%) were detected resistant and 57 (39.9%) as sensitive by the MTBDRsl. Thus, the overall concordance of MTBDRsl with MGIT-960 system was only 50% for detection of EMB resistance.

Genotyping Results

The spoligotyping results showed that 142 (39.5%) isolates belonged to CAS lineage, 119 (33.2%) Beijing, 26 (7.2%) T, 13 (3.6%) EAI, 12 (3.3%) Haarlem, 8 (2.2%) X, 7 (1.9%) Manu and 2 (0.5%) isolates each of Ural and S lineages. Twenty-eight (7.7%) isolates showed Unique (U) patterns. Out of 359 MDR-TB isolates, 322 (89.7%) were grouped in 55 SITs (Shared international types). Nine (2.5%) strains were identified as “orphans”. The remaining 28 (7.7%) isolates could not be categorized in any SITs (Table 4). Among the 55 STs (share types), the two most common were ST1 (Beijing) [111 (30.9%)] and ST26 (CAS1_DELHI) [84 (23.4%)] followed by ST25 (CAS1_DELHI, 3.3%) and ST53 (T1, 2.5%). The remaining SITs represented less than 2.5% isolates. Out of 9 orphans, 2 (0.5%) each belonged to CAS, T1, and Manu lineage and 1 (0.3%) each isolate belonged to CAS1_DELHI, T1, and H4 families (Table 4).
Table 4

Spoligotyping pattern, octal codes, SIT and lineage of overall MDR-TB isolates use

SITSPOLIGOTYPE DESCRIPTIONOCTAL CODELINEAGERESISTANT TYPETotal (%)
MDR (N = 231)Pre-XDR (N = 111)XDR (N = 17)
1□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□■■■■■■■■■000000000003771BEIJING57 (24.7)46 (41.4)8 (47.1)111 (30.9)
11■□□■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■□■■□□□■■■■477777777413071EAI3_IND4 (1.7)1 (0.9)05 (1.4)
25■■■□□□□■■■■■■■■■■■■■■■□□□□□□□□□□□□■■□□■■■■■703777740003171CAS1 DELHI11 (4.7)1 (0.9)012 (3.3)
26■■■□□□□■■■■■■■■■■■■■■■□□□□□□□□□□□□■■■■■■■■■703777740003771CAS1 DELHI65 (28.1)18 (16.2)1 (5.8)84 (23.4)
27**■■■□□□□■■■■■■■■■■■■■■■□□■■■■■■■■■□□□□■■■■■■■703777747770371URAL01 (0.9)01 (0.3)
34■■■■■■■■□□■■■■■■■■■■■■■■■■■■■■■■■□□□□■■■■■■776377777760771S2 (0.9)002 (0.6)
37■■■■■■■■■■■■□■■■■■■■■■■■■■■■■■■■□□□□■■■■■■■777737777760771T31 (0.4)001 (0.3)
48■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■□■■■■■□■■■777777777413731EAI2_SOM02 (1.8)02 (0.6)
52■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■■■□■■■777777777760731T21 (0.4)001 (0.3)
53■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■■■■■■■777777777760771T19 (3.9)009 (2.5)
54■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□■■■■■■■■■777777777763771MANU22 (0.9)2 (1.8)04 (1.1)
67■■■■■■■■■■■■□■■■■■□□□□■■■■■■■■□■□□□□■■■■■■■777777037720771H34 (1.7)1 (0.9)05 (1.4)
92■■■□□□□□□□□□■■■■■□■■■■■■■■■■■■■■□□□□■■■■■■■700076777760771X31 (0.4)001 (0.3)
100■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■□■■■■■■■■■777777777773771MANU11 (0.4)001 (0.3)
119■■■■■■■■■■■■■■■■■□■■■■■■■■■■■■■■□□□□■■■■■■■777776777760771X104 (3.6)1 (5.8)5 (1.4)
125**□□□□□□□□□□□□□□□□□□□□□□□□□■■■■■■■■□□□□■■■□■■■000000007760731T201 (0.9)01 (0.3)
127■□■■■■■■■■■■■■■■■■■■■■■■■■■■□□□■□□□□■■■■■■■577777777420771H42 (0.9)002 (0.6)
137■■■■■■■■■■■■■■■■■□■■■■■■■■■■■■■■□□□□■■□□□□■777776777760601X201 (0.9)01 (0.3)
190**□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□■■■■■□■■■000000000003731BEIJING02 (1.8)02 (0.6)
236■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■□■■■■■■■■■777777777413771EAI5001 (5.8)1 (0.3)
243■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■■□□□□□777777777760600T12 (0.9)2 (1.8)04 (1.1)
250*□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□□■■■■■■000000000000371BEIJING2 (0.9)002 (0.6)
283■■■■■■■■■■■■■■■■■■■■■□□□■□□□□□□■□□□□■■■■■■■777777704020771H13 (1.3)1 (0.9)04 (1.1)
288■■■□□□□□□□■■■■■■■■■■■■□□□□□□□□□□□□■■■■■■■■■700377740003771CAS21 (0.4)1 (0.9)02 (0.6)
289■■■□□□□■■■■■■■■■■■■■■■□□□□□□□□□□□□■■■□■■■■■703777740003571CAS1 DELHI2 (0.9)002 (0.6)
344■■■□□□□□□□□□■■■■■■■■■■■■■■■■■■■■□□□□■■■■■■■700077777760771T11 (0.4)001 (0.3)
357■■■□□□□■■■■■■■■■■■■■■■□□□□□□□□□□□□□□■■■■■■■703777740000771CAS3 (1.5)003 (0.8)
358**■■■□□■■■■■■■■■■■■■■■■■■■■■■■■■■■□□□□■■■■■■■717777777760771T101 (0.9)01 (0.3)
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*SITs- that are evolved among MDR-TB isolates (second-line sensitive) from India.

**SITs-that are evolved among pre-XDR TB isolates from India.

***SITs that are evolved among XDR-TB isolates from India.

Spoligotyping pattern, octal codes, SIT and lineage of overall MDR-TB isolates use *SITs- that are evolved among MDR-TB isolates (second-line sensitive) from India. **SITs-that are evolved among pre-XDR TB isolates from India. ***SITs that are evolved among XDR-TB isolates from India.

Frequency of various Genotypes in second line drug sensitive isolates

Out of the 231 (64.3%) isolates that were found sensitive to second line drugs, 108 (46.7%) belong to the CAS lineage, 62 (26.8%) to Beijing and 18 (7.7%) to the T lineage. Seventeen (7.3%) isolates showed Unique SIT patterns, 10 (4.3%) belonged to Haarlem, 9 (3.8%) EAI, 3 (1.3%) Manu and 2 (0.8%) each belong to X and S lineages. While analysing the clustering of these strains, 207 (89.6%) strains could be grouped under 39 STs, while 7(3.4%) were identified as orphans and the rest 19 (8.2%) had unique patterns (Tables 4 and 5). Among the 39 SITs the commonest were SIT26 (CAS1_DELHI), SIT1 (Beijing) and SIT25 (CAS1_DELHI) with 65 (28.1%), 57 (24.7%) and 11 (4.7%) strains each group. Other genotypes representing fewer genotypes are given in the Table (4).
Table 5

Distribution and clustering pattern of MDR-TB isolates.

LINEAGEMDRPre-XDRXDRTOTAL
BEIJING
Clustered3(2–57)2(2–46)1(8)6(2–57)
Un-clustered0011
CAS
Clustered11(2–65)5(2–18)016(2–65)
Un-clustered75315
EAI
Clustered3(2–4)1(2)04(2–4)
Un-clustered1113
MANU
Clustered1(2)1(2)02(2)
Un-clustered1001
H
Clustered3(3–4)1(3)04(3–4)
Un-clustered1102
X
Clustered01(5)01(5)
Un-clustered2114
T
Cluster2(2–9)1(2)1 (1)4(2–9)
Un-clustered4509
S
Clustered1(2)001(2)
Un-clustered0000
URAL
Clustered0000
Un-clustered0112
ORPHAN
Clustered2(2)1(2)03(2)
Un-clustered3003
UNIQUE
Clustered5(2)1(2)06(2)
Un-clustered76114
Total
Clustered31(2–65)14(2–46)2(9)47(2–65)
Un-clustered2620854
Distribution and clustering pattern of MDR-TB isolates.

Frequency of various Genotypes in pre-XDR-MTB isolates

Out of 111 (30.9%) pre-XDR TB isolates detected by MGIT-960 DST system, the most frequent genotypes belonged to Beijing (48, 43.2%) genotype, CAS (31, 27.9%) and Unique (10, 9.1%). Other genotypes were less commonly seen and are given in Table (4). Among the 26 SITs identified, like second line drug susceptible isolates, in pre-XDR isolates also, the SIT1 (Beijing) [46; 41.4%] and SIT26 (CAS1_DELHI) [18; 16.2%] were the two most common types followed by ST119 (X1, 3.6%). But the predominance of Beijing genotype was unequivocal (26.8% v 43.2%). Of the two Orphans identified, both belonged to the CAS1_DELHI genotype. The remaining SITs represented less than 3.6% isolate (Supplementary Fig. 2).

Frequency of various Genotypes of XDR-MTB isolates

Out of 17 (4.7%) XDR-TB isolates that were detected by the SLD MGIT-960 DST, 9 (52.9%) isolates represented as Beijing lineage, 3 (17.6%) as CAS and 1 (5.8%) each belong to EAI, X, T, Ural, and Unique patterns. Therefore, there was a clear pattern of Beijing genotype become more and more and common in isolates developing drug resistance. A total of 9 SITs were identified among 16 (94.1%) strains and one (5.8%) strain had unique spoligotype pattern. Beijing strains of SIT1 predominated [8 (47%)], whereas the remaining 15 SITS represented one (5.8%) isolate each (Table 4).

Cluster analysis

The cluster analysis revealed that our isolates belonged to overall 47 clusters with the size of 2–65 isolates in each cluster. The highest clustering (31 clusters) was found among the MDR-TB isolates but sensitive to second-line drugs. Amongst the pre-XDR-TB isolates highest number of clusters were observed in the CAS lineage having 5 clusters (2–18 isolates in each cluster) followed by Beijing with 2 clusters of 2–46 isolates. However, in the XDR-TB isolates only one cluster was found with 8 isolates all belonging to the Beijing lineage. Isolates showing unique patterns were also found in a single cluster with two isolates in the pre-XDR TB isolates. Interestingly, most of the X, T, orphan and unique strains were un-clustered (Table 5). Minimum Spanning Tree (MST) analysis done by using the MIRU-VNTRplus software, revealed various SITs amongst different regions showing predominant SITs and evolutionary relationship of the lineages and their SITs. MST connects each genotype based on the degree of changes required to go from one allele to another. The length of the branches denotes the distance between any two patterns whereas the intricacy of the lines indicates the number of spacers between the two patterns. The thicker lines represent 1 change while thinner ones indicate 2 or 3. The size of the circle is comparative to the total number of MTB isolates in this study. The colour of the circles represents the phylogenetic lineage to which the specific pattern belongs. Beijing patterns are circled in red and yellow indicates CAS strains. EAI strains are in dark green colour while EAI strains are in dark green colour. The Clustering and MST of MDR-TB isolates (but susceptible to second line drugs) is shown in Fig. (1). The clustering details for pre-XDR strains are given in Fig. (2). Out of 111 isolates, a total of 88 (79.3%) were grouped into 13 clusters, whereas 23 (20.7%) were non-clustered isolates of which 8 (34.8%.) were unique non-clustered isolates. In case of XDR-TB strains these details are shown in Fig. (3). Out of 17 isolates, 8 (47.1%) isolates could be grouped only in 1 cluster, whereas 9(52.9%) were non-clustered isolates of which 1 (11.1%.) was unique non-clustered isolate.
Figure 1

The figure shows minimum spanning tree of MDR-TB (but sensitive to second-line drug) isolates characterized by spoligotyping. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other.

Figure 2

Minimum spanning tree of pre-XDR-TB isolates using the same spoligotyping method as mentioned above. Each circle represents a genotype. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other.

Figure 3

Minimum spanning tree of XDR-TB isolates using spoligotyping method as mentioned above. Each circle represents a genotype. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other.

The figure shows minimum spanning tree of MDR-TB (but sensitive to second-line drug) isolates characterized by spoligotyping. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other. Minimum spanning tree of pre-XDR-TB isolates using the same spoligotyping method as mentioned above. Each circle represents a genotype. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other. Minimum spanning tree of XDR-TB isolates using spoligotyping method as mentioned above. Each circle represents a genotype. Each circle represents a genotype. The distance between circles represents how closely related are different genotypes to each other.

Evolution of new share types among MDR-TB isolates

In our study 18 new SITs, were found in MDR-TB isolates, which have not been previously reported so far from India in the SITVIT2 database. Among the second line drug susceptible isolates, SIT 250 (Beijing, n = 1); SIT 462 (T1, n = 1); SIT 1628 (EAI5, n = 1); SIT 1168 (Beijing, n = 3); SIT 1394 (X1, n = 1); SIT 1401 (CAS1_DELHI, n = 3); SIT 2419 (CAS, n = 1); Orphan1 (CAS, n = 2); Orphan2 (CAS1_DELHI, n = 1); Orphan3 (T1, n = 1); Orphan 6 (T1, n = 2) were found to be evolved. New SITs, which were common in both MDR, and pre-XDR-TB isolates, included SIT 67 (H3, n = 5), SIT 243 (T1, n = 4) and SIT 794 (CAS, n = 4), respectively. Amongst the pre-XDR TB isolates, SIT 27 (Ural, n = 1); SIT 125 (T2, n = 1); SIT 190 (Beijing, n = 2); SIT 358 (T1, n = 1); SIT 798 (T1, n = 1); SIT 2147 (CAS, n = 2) and SIT 1166 (T1, n = 1) were found. In the XDR-TB isolates, SIT 464 (Ural, n = 1) was the only new SIT found to be evolved (Table 4).

Association of genetic mutations in gyrA and rrs genes and phenotypic drug resistance

Among the FQ resistant isolates, ΔWT3-D94G (40.8%) was most prevalent mutation and the frequency of this mutation was higher in Beijing strain (45.1%) followed by CAS (27.4%), X (9.8%), Unique (7.8%), T (5.8%), Manu and H (1.9%). The ΔWT2-A90V mutation (24.8%) was most common mutation in the Beijing (32.2%) and CAS (25.8%) strains. Only Beijing strain (100%) was associated with ΔWT3-D94N/Y (4.8%) mutations. However, among the AG/CP resistant isolates, ΔWT1-A1401G (57.9%) was the most prevalent mutation and the frequency of this mutation was higher (57.9%) in Beijing strains (Table 4).

Discussion

The first decade of this century witnessed the emergence of XDR-TB strains for which management is extremely difficult, and this imposed serious concerns for the health care systems around the world[1,5]. To develop tests to diagnose XDR-MTB strains at the earliest possible time have become an urgent need. Various research organizations are working untiringly to develop such tests and devices. A German based company developed the first version of MTBDRsl for rapid screening of FQ and AG/CP resistance in the MDR-TB isolates. After preliminary evaluations, in 2013, the WHO recommended use of this test to rule out the XDR-TB[27]. However, despite India being the high TB burden country, its usefulness of this test has not been evaluated on a large number of isolates. In the present work, we evaluated the efficiency of MTBDRsl V.1 in comparison to the second-line DST using MGIT-960 system, which still remain the gold standard for second line drug susceptibility testing. We also analysed for the first time, the association of various lineages of MTB with genetic mutational patterns. Even though it is a molecular test, which is prone to several procedural errors, we found that the test protocol is highly standardized giving no invalid results, which means that all (100%) tests were valid. Taking the phenotypic MGIT-960 system as the gold standard, we found very high (97%) concordance of MTBDRsl for detecting the second drug susceptible isolates and for FQ resistance detection (93.5%). However, more improvised version will be required to detect AG/CP resistance, where its performance was not found very high (50%). Similar findings regarding detection of AG/CP resistance have also been previously published from Spain and China reporting sensitivity of 56% and 67% respectively[28,29]. Nevertheless, the test was found extremely good (94.1%) for XDR-TB detection in our study as well as by other studies published from Serbia and Netherlands both showing 100% sensitivity[3,30]. Similar to our results the lower detection rate for EMB resistance of 56.2% was reported from China. These authors performed this test on MDR-TB isolates and emphasized identification of other mutations for detection of EMB resistance for improvement of the test[31]. Hence the identification of novel mutations outside the QRDR gene region of gyrA and gyrB and rrs gene is urgently needed. The new version of the assay (i.e. MTBDRsl V.2.0) has been recently developed by the company for improvement to overall performance of MTBDRsl V.1 and in particular to its sensitivity for detection of kanamycin resistance. However, at the time of study this version was not available in India[32,33]. While correlating the association of gyrA and rrs gene mutations in various lineages[34] we found that even though most of our isolates were from the Northern-Western part of India (270; 75.2%) where prevalence of CAS strain is predominant yet the association of Beijing isolates was statistically significantly high (p-0.0006) with gyrA gene mutations but insignificant (p-0.079) with rrs gene mutations. Beijing strains are considerably prevalent in South East Asia and North-Eastern region of India, where its is posing a major concern due to its high prevalence among the MDR-TB patients[19,31,35,36]. However, the recent studies from India show that this strain is spreading fast to other parts of India and neighbouring countries[14], which can be warning signal to the TB control programme managers. Within the Beijing genotype SIT1 was most predominant share type amongst the pre-XDR and XDR-TB isolates in our study. SIT1 was also reported predominant among XDR- TB isolates from Africa (34%) and Russia (9.5%)[37,38]. We for the first time reported 18 new SITs and 5 Orphans in the Indian MDR-TB isolates, though these types have previously been reported from other countries, like SIT67 (1.4%) from United States and Mexico, SIT243 (1.1%) from Zambia, Vietnam and Italy, SIT 794 (1.1%) from Bangladesh, Pakistan and United States[39-43]. The two newly evolving SITs in the Beijing genotype [SIT 1168 (0.8%) and SIT 190 (0.5%)], were found only in the MDR and pre-XDR TB isolates. These SITs have been reported from Unites States, Thailand, Japan, Vietnam and China, but never from India[41,43]. The Ural SIT 464 was the only strain evolved among the XDR-TB isolate which have never been reported from India but only from United States of America[39]. Evolution of new share types among the MDR, pre-XDR and XDR-TB isolates from India indicates these strains got transmitted to India through migration of population from such geographical regions in recent years[14]. We also report association of Beijing genotypes with very high frequency of 2 gyrA gene mutations-ΔWT3-D94G and ΔWT2-A90V (Table 4). In conclusion, even though our study had some limitations such as not being able to monitor the progression of disease and treatment outcome of patients due to the use of archival MDR culture isolates, our study signifies that MTBDRsl V1 is a good diagnostic tool for the detection of pre-XDR and XDR-TB. We propose that MTBDRsl V1 should be used on all MDR-TB isolates in place of phenotypic culture DST methods, till its second version is made available, in the programmatic mode. This strategy is more pertinent for countries and regions where pre-XDR and XDR-TB prevalence is high. We also conclude that more prospective genotyping studies along with next-generation sequencing methods be implemented in order to ensure the understanding of the vulnerability of some genotypes to the drug resistance development and the molecular mechanisms leading to the emergence of pre-XDR and XDR-TB strains.
  37 in total

1.  Evolution of drug resistance in different sublineages of Mycobacterium tuberculosis Beijing genotype.

Authors:  Igor Mokrousov; Wei Wei Jiao; Gui Zhi Sun; Jia Wen Liu; Violeta Valcheva; Mo Li; Olga Narvskaya; A Dong Shen
Journal:  Antimicrob Agents Chemother       Date:  2006-08       Impact factor: 5.191

2.  Genotypic diversity of extensively drug-resistant tuberculosis (XDR-TB) in South Africa.

Authors:  C K Mlambo; R M Warren; X Poswa; T C Victor; A G Duse; E Marais
Journal:  Int J Tuberc Lung Dis       Date:  2008-01       Impact factor: 2.373

3.  Performance assessment of the GenoType MTBDRsl test and DNA sequencing for detection of second-line and ethambutol drug resistance among patients infected with multidrug-resistant Mycobacterium tuberculosis.

Authors:  Wei-Lun Huang; Ting-Lin Chi; Mei-Hua Wu; Ruwen Jou
Journal:  J Clin Microbiol       Date:  2011-05-11       Impact factor: 5.948

Review 4.  GenoType® MTBDRsl assay for resistance to second-line anti-tuberculosis drugs.

Authors:  Grant Theron; Jonny Peter; Marty Richardson; Rob Warren; Keertan Dheda; Karen R Steingart
Journal:  Cochrane Database Syst Rev       Date:  2016-09-08

5.  Molecular characterization of Mycobacterium tuberculosis isolates from North Indian patients with extrapulmonary tuberculosis.

Authors:  Manimuthu Mani Sankar; Jitendra Singh; Selvaraj Cynthiya Angelin Diana; Sarman Singh
Journal:  Tuberculosis (Edinb)       Date:  2012-11-07       Impact factor: 3.131

6.  Comparative study on genotypic and phenotypic second-line drug resistance testing of Mycobacterium tuberculosis complex isolates.

Authors:  Jakko van Ingen; Sami Simons; Rina de Zwaan; Tridia van der Laan; Miranda Kamst-van Agterveld; Martin J Boeree; Dick van Soolingen
Journal:  J Clin Microbiol       Date:  2010-06-16       Impact factor: 5.948

7.  The diagnostic accuracy of the MTBDRplus and MTBDRsl assays for drug-resistant TB detection when performed on sputum and culture isolates.

Authors:  Michele Tomasicchio; Grant Theron; Elize Pietersen; Elizabeth Streicher; Danielle Stanley-Josephs; Paul van Helden; Rob Warren; Keertan Dheda
Journal:  Sci Rep       Date:  2016-02-10       Impact factor: 4.379

8.  Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology.

Authors:  Karine Brudey; Jeffrey R Driscoll; Leen Rigouts; Wolfgang M Prodinger; Andrea Gori; Sahal A Al-Hajoj; Caroline Allix; Liselotte Aristimuño; Jyoti Arora; Viesturs Baumanis; Lothar Binder; Patricia Cafrune; Angel Cataldi; Soonfatt Cheong; Roland Diel; Christopher Ellermeier; Jason T Evans; Maryse Fauville-Dufaux; Séverine Ferdinand; Dario Garcia de Viedma; Carlo Garzelli; Lidia Gazzola; Harrison M Gomes; M Cristina Guttierez; Peter M Hawkey; Paul D van Helden; Gurujaj V Kadival; Barry N Kreiswirth; Kristin Kremer; Milan Kubin; Savita P Kulkarni; Benjamin Liens; Troels Lillebaek; Minh Ly Ho; Carlos Martin; Christian Martin; Igor Mokrousov; Olga Narvskaïa; Yun Fong Ngeow; Ludmilla Naumann; Stefan Niemann; Ida Parwati; Zeaur Rahim; Voahangy Rasolofo-Razanamparany; Tiana Rasolonavalona; M Lucia Rossetti; Sabine Rüsch-Gerdes; Anna Sajduda; Sofia Samper; Igor G Shemyakin; Urvashi B Singh; Akos Somoskovi; Robin A Skuce; Dick van Soolingen; Elisabeth M Streicher; Philip N Suffys; Enrico Tortoli; Tatjana Tracevska; Véronique Vincent; Tommie C Victor; Robin M Warren; Sook Fan Yap; Khadiza Zaman; Françoise Portaels; Nalin Rastogi; Christophe Sola
Journal:  BMC Microbiol       Date:  2006-03-06       Impact factor: 3.605

9.  Drug susceptibility profiles of pulmonary Mycobacterium tuberculosis isolates from patients in informal urban settlements in Nairobi, Kenya.

Authors:  Glennah Kerubo; Evans Amukoye; Stefan Niemann; Samuel Kariuki
Journal:  BMC Infect Dis       Date:  2016-10-19       Impact factor: 3.090

10.  Trends in molecular epidemiology of drug-resistant tuberculosis in Republic of Karelia, Russian Federation.

Authors:  Igor Mokrousov; Anna Vyazovaya; Natalia Solovieva; Tatiana Sunchalina; Yuri Markelov; Ekaterina Chernyaeva; Natalia Melnikova; Marine Dogonadze; Daria Starkova; Neliya Vasilieva; Alena Gerasimova; Yulia Kononenko; Viacheslav Zhuravlev; Olga Narvskaya
Journal:  BMC Microbiol       Date:  2015-12-18       Impact factor: 3.605

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  3 in total

1.  Performance of Genotype MTBDRsl V2.0 over the Genotype MTBDRsl V1 for detection of second line drug resistance: An Indian perspective.

Authors:  Syed Beenish Rufai; Kulsum Umay; Praveen Kumar Singh; Sarman Singh
Journal:  PLoS One       Date:  2020-03-04       Impact factor: 3.240

2.  Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China.

Authors:  Shiv Kumar Rashmi Mudliar; Umay Kulsum; Syed Beenish Rufai; Mika Umpo; Moi Nyori; Sarman Singh
Journal:  Genes (Basel)       Date:  2022-01-29       Impact factor: 4.096

3.  Genotype analysis of ofloxacin-resistant multidrug-resistant Mycobacterium tuberculosis isolates in a multicentered study from India.

Authors:  Anamika Gupta; Pallavi Sinha; Sunita Rathod; Siva Kumar Shanmugam; K R Uma Devi; Shampa Anupurba; Vijay Nema
Journal:  Indian J Med Res       Date:  2020-04       Impact factor: 2.375

  3 in total

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