Whole genome sequencing of clinical strains of Mycobacterium tuberculosis from Mumbai, India: A potential tool for determining drug-resistance and strain lineage

Chatterjee, Anirvan; Nilgiriwala, Kayzad; Saranath, Dhananjaya; Rodrigues, Camilla; Mistry, Nerges

doi:10.1016/j.tube.2017.08.002

Cited by 45 publications

(39 citation statements)

References 42 publications

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“…In this study, we found high concordance between WGS and conventional culture-based DST in predicting phenotypic drug resistance to anti-TB drugs, ranging from 81% for INH to 97% for RIF, and 95% concordance with Xpert® MTB/RIF (Cepheid, USA) for RIF. These findings are in agreements with those previously reported in different TB endemic settings [21][22][23][24]. The ability of Xpert® MTB/RIF and phenotypic detection of TB drug resistance cannot be underscored as it can pave a way to complementary and confirmatory WGS in early detection of resistance.…”

Section: Discussionsupporting

confidence: 90%

Whole genome sequencing of Mycobacterium tuberculosis isolates and clinical outcomes of patients treated for multidrug-resistant tuberculosis in Tanzania

Katale

Mbelele

Lema³

et al. 2020

BMC Genomics

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Background: Tuberculosis (TB), particularly multi-and or extensive drug resistant TB, is still a global medical emergency. Whole genome sequencing (WGS) is a current alternative to the WHO-approved probe-based methods for TB diagnosis and detection of drug resistance, genetic diversity and transmission dynamics of Mycobacterium tuberculosis complex (MTBC). This study compared WGS and clinical data in participants with TB.Results: This cohort study performed WGS on 87 from MTBC DNA isolates, 57 (66%) and 30 (34%) patients with drug resistant and susceptible TB, respectively. Drug resistance was determined by Xpert® MTB/RIF assay and phenotypic culture-based drug-susceptibility-testing (DST). WGS and bioinformatics data that predict phenotypic resistance to anti-TB drugs were compared with participant's clinical outcomes. They were 47 female participants (54%) and the median age was 35 years (IQR): 29-44). Twenty (23%) and 26 (30%) of participants had TB/HIV coinfection BMI < 18 kg/m 2 respectively. MDR-TB participants had MTBC with multiple mutant genes, compared to those with mono or polyresistant TB, and the majority belonged to lineage 3 Central Asian Strain (CAS). Also, MDR-TB was associated with delayed culture-conversion (median: IQR (83: 60-180 vs. 51:30-66) days). WGS had high concordance with both culture-based DST and Xpert® MTB/RIF assay in detecting drug resistance (kappa = 1.00). Conclusion: This study offers comparison of mutations detected by Xpert and WGS with phenotypic DST of M. tuberculosis isolates in Tanzania. The high concordance between the different methods and further insights provided by WGS such as PZA-DST, which is not routinely performed in most resource-limited-settings, provides an avenue for inclusion of WGS into diagnostic matrix of TB including drug-resistant TB.

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Section: Discussionsupporting

confidence: 90%

Whole genome sequencing of Mycobacterium tuberculosis isolates and clinical outcomes of patients treated for multidrug-resistant tuberculosis in Tanzania

Katale

Mbelele

Lema³

et al. 2020

BMC Genomics

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“…This sequence data was pooled with 2,222 additional MTB whole genome sequences curated by the ReSeqTB knowledgebase, which maintains a public data sharing platform (www.reseqtb.org) curating genotypic and phenotypic data of WHO-endorsed in vitro diagnostic assays for MTB [23]. The validation dataset of 792 MTB isolates was obtained by pooling additional data from ReSeqTB, without overlap with the training set, and other MTB whole genome sequences and phenotype data curated manually from the following references [24][25][26][27]. Antibiotic resistance phenotype data: All isolates included underwent culture based antibiotic susceptibility testing to two or more drugs at WHO approved critical concentrations and met other quality control criteria as detailed in [8].…”

Section: Data Descriptionmentioning

confidence: 99%

Deep learning predicts tuberculosis drug resistance status from genome sequencing data

Chen

Doddi

Royer

et al. 2018

Preprint

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One sentence summary: A unified multitask deep learning model can be used to identify multidrug resistant Mycobacterium tuberculosis using sequencing data. AbstractThe diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited scope of conventional phenotypic drug susceptibility but gaps remain for predicting phenotype accurately from genotypic data. Using targeted or whole genome sequencing and conventional drug resistance phenotyping data from 3,601 Mycobacterium tuberculosis strains, 1,228 of which were multidrug resistant, we implemented the first multitask deep learning framework to predict phenotypic drug resistance to 10 anti-tubercular drugs. The proposed wide and deep neural network (WDNN) achieved improved predictive performance compared to regularized logistic regression and random forest: the average sensitivities and specificities, respectively, were 92.7% and 92.7% for first-line drugs and 82.0% and 92.8% for second-line drugs during cross-validation. On an independent validation set, the multitask WDNN showed significant performance gains over baseline models, with average sensitivities and specificities, respectively, of 84.5% and 93.6% for first-line drugs and 64.0% and 95.7% for second-line drugs. In addition to being able to learn from samples that have only been partially phenotyped, our proposed multitask architecture shares information across different anti-tubercular drugs and genes to provide a more accurate phenotypic prediction. We use t-distributed Stochastic Neighbor Embedding (t-SNE) visualization and feature importance analyses to examine inter-drug similarities. Deep learning has a clear role in improving drug resistance predictive performance over traditional methods and holds promise in bringing sequencing technologies closer to the bedside.. CC-BY-NC-ND 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Diagnosing drug resistance remains a barrier to providing appropriate TB treatment. Due to insufficient resources for building diagnostic laboratories, fewer than half of the countries with a high MDR-TB burden have modern diagnostic capabilities (3). Even in the best equipped laboratories, conventional culture and culture based drug susceptibility testing (DST) constitutes a considerable biohazard and requires weeks to months before results are reported due to Mycobacterium tuberculosis's slow growth in vitro (1). Molecular diagnostics are now an increasingly common alternative to conventional cultures. The WHO has endorsed three such molecular tests: the GeneXpert MTB/RIF a rapid RT-PCR based diagnostic test assay that detects RIF resistance, the Hain line probe assay (LPA) that tests for both RIF and INH resistance, and the Hain MDRTBsl an LPA that tests for resistance to second-line in...

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“…A total of seventy-four clinical isolates of M. tuberculosis from TB patients (49 new, 12 follow-ups and 13 re-treatment cases) were used in the study [7]. Along with the clinical isolates, standard strain H 37 Rv (ATCC 27294) was also processed in triplicate.…”

Section: Methodsmentioning

confidence: 99%

“…Genomic DNA was isolated from the clinical strains of M. tuberculosis using FastPrep24 lysis method (MP Biomedicals, California, USA) as per standard protocol [7]. The extracted DNA was quantified using Qubit (Life Technologies, Carlsbad, California, USA).…”

Section: Methodsmentioning

confidence: 99%

Genomic Polymorphisms in Toxin-Antitoxin Systems and Identification of Novel Phylo-SNPs and Polymorphisms Associated with Drug Resistance/Susceptibility in Clinical Isolates of Mycobacterium tuberculosis from Mumbai, India

Nilgiriwala

Chitalia

Shah

et al. 2019

Preprint

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27Toxin-antitoxin (TA) modules are one of the prominent determinants that triggers a persistent 28 state aiding Mycobacterium tuberculosis evasion to host generated stresses. The 79 29 characterized and putative TA systems described in M. tuberculosis are dominated by the 30 VapBC, MazEF, HigAB, RelBE and ParDE TA families, largely involved in persistence and 31 cell arrest. Hence, there is a need to maintain and conserve the TA loci in the chromosome of 32 the pathogen. It is essential to study the genomic differences of the TA systems in clinical 33 isolates along with its association to drug susceptibility patterns and lineage. In the current 34 study, the TA loci and their promoter sequences were analysed from the whole genome 35 sequence data of 74 clinical isolates. Mykrobe Predictor was used for lineage identification 36 and drug resistance predictions in the clinical isolates. Polymorphisms associated with 79.8% 37(63/79) TA systems were observed across 72 clinical isolates. Among the TA systems, the 38 isolates had a varying number of polymorphisms localised primarily in the toxin genes 39 (58.7%), antitoxin genes (40.7%) and chaperones (0.6%), due to Single Nucleotide 40 Polymorphism (SNP) resulting in transition (67.3%), transversion or frameshift mutations. 41 Our analysis suggests the presence of novel Phylo-SNPs by establishing high confidence 42 association of specific lineages to polymorphisms in the TA systems. Notably, association of 43 polymorphisms in Rv1838c-1839c (VapBC13), Rv3358-3357 (YefM/YoeB) and Rv0240-44 0239 (VapBC24) to Delhi/Central Asia lineage. The polymorphic loci of the 3 TA systems is 45 localised in the antitoxin gene of the Delhi/Central Asia strains, with a resultant silent 46 mutation. The assessment of correlation between TA polymorphisms and the drug resistance 47 Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis, with an annual estimate 52 of 10.4 million new cases globally, imposes a major burden of mortality and morbidity on the 53 human population [1]. The long duration of treatment and a large reservoir of people with 54 latent infection are major obstacles in controlling spread of the disease. Furthermore, 55 multidrug resistance is a deterrent for effective treatment of TB. Besides acquired drug 56 resistance, M. tuberculosis exhibits modified virulence, transmissibility and pathogenicity 57 [2]. The organism may employ endogenous mechanisms of stress evasion due to persistence 58 of the bacilli in the infected individual. The 'persister' state is a dormant state wherein the 59 bacterial cells are recalcitrant to the unfavourable conditions. The persistent cells revert back 60 to its proliferative growth on removal of the environmental stress factor such as nutrient 61 starvation or antibiotic presence. The persister cells are therefore not antibiotic resistant 62 mutants, but are highly antibiotic tolerant cells [3]. An important determinant of persistence 63 is the presence of multiple toxin-antitoxin (TA) systems [4]. 64 The TA syste...

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Whole genome sequencing of clinical strains of Mycobacterium tuberculosis from Mumbai, India: A potential tool for determining drug-resistance and strain lineage

Cited by 45 publications

References 42 publications

Whole genome sequencing of Mycobacterium tuberculosis isolates and clinical outcomes of patients treated for multidrug-resistant tuberculosis in Tanzania

Whole genome sequencing of Mycobacterium tuberculosis isolates and clinical outcomes of patients treated for multidrug-resistant tuberculosis in Tanzania

Deep learning predicts tuberculosis drug resistance status from genome sequencing data

Genomic Polymorphisms in Toxin-Antitoxin Systems and Identification of Novel Phylo-SNPs and Polymorphisms Associated with Drug Resistance/Susceptibility in Clinical Isolates of Mycobacterium tuberculosis from Mumbai, India

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