Mutations in gidB confer low-level streptomycin resistance in Mycobacterium tuberculosis

Pangenome-wide association study reveals the selective absence of CRISPR genes (Rv2816c-19c) in drug-resistant Mycobacterium tuberculosis

The presence of intermittently dispersed insertion sequences and transposases in the Mycobacterium tuberculosis (Mtb) genome makes intra-genome recombination events inevitable. Understanding their effect on the gene repertoires (GR), which may contribute to the development of drug-resistant Mtb, is critical. In this study, publicly available WGS data of clinical Mtb isolates (endemic region n = 2,601; non-endemic region n = 1,130) were de novo assembled, filtered, scaffolded into assemblies, and functionally annotated. Out of 2,601 Mtb WGS data sets from endemic regions, 2,184 (drug resistant/sensitive: 1,386/798) qualified as high quality. We identified 3,784 core genes, 123 softcore genes, 224 shell genes, and 762 cloud genes in the pangenome of Mtb clinical isolates from endemic regions. Sets of 33 and 39 genes showed positive and negative associations (P < 0.01) with drug resistance status, respectively. Gene ontology clustering showed compromised immunity to phages and impaired DNA repair in drug-resistant Mtb clinical isolates compared to the sensitive ones. Multidrug efflux pump repressor genes (Rv3830c and Rv3855c) and CRISPR genes (Rv2816c-19c) were absent in the drug-resistant Mtb. A separate WGS data analysis of drug-resistant Mtb clinical isolates from the Netherlands (n = 1130) also showed the absence of CRISPR genes (Rv2816c-17c). This study highlights the role of CRISPR genes in drug resistance development in Mtb clinical isolates and helps in understanding its evolutionary trajectory and as useful targets for diagnostics development.IMPORTANCEThe results from the present Pan-GWAS study comparing gene sets in drug-resistant and drug-sensitive Mtb clinical isolates revealed intricate presence-absence patterns of genes encoding DNA-binding proteins having gene regulatory as well as DNA modification and DNA repair roles. Apart from the genes with known functions, some uncharacterized and hypothetical genes that seem to have a potential role in drug resistance development in Mtb were identified. We have been able to extrapolate many findings of the present study with the existing literature on the molecular aspects of drug-resistant Mtb, further strengthening the relevance of the results presented in this study.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

gcPathogen: a comprehensive genomic resource of human pathogens for public health

Here, we present the manually curated Global Catalogue of Pathogens (gcPathogen), an extensive genomic resource designed to facilitate rapid and accurate pathogen analysis, epidemiological exploration and monitoring of antibiotic resistance features and virulence factors. The catalogue seamlessly integrates and analyzes genomic data and associated metadata for human pathogens isolated from infected patients, animal hosts, food and the environment. The pathogen list is supported by evidence from medical or government pathogenic lists and publications. The current version of gcPathogen boasts an impressive collection of 1 164 974 assemblies comprising 986 044 strains from 497 bacterial taxa, 4794 assemblies encompassing 4319 strains from 265 fungal taxa, 89 965 assemblies featuring 13 687 strains from 222 viral taxa, and 646 assemblies including 387 strains from 159 parasitic taxa. Through this database, researchers gain access to a comprehensive 'one-stop shop' that facilitates global, long-term public health surveillance while enabling in-depth analysis of genomes, sequence types, antibiotic resistance genes, virulence factors and mobile genetic elements across different countries, diseases and hosts. To access and explore the data and statistics, an interactive web interface has been developed, which can be accessed at https://nmdc.cn/gcpathogen/. This user-friendly platform allows seamless querying and exploration of the extensive information housed within the gcPathogen database.

Evolution and transmission of antibiotic resistance is driven by Beijing lineage Mycobacterium tuberculosis in Vietnam

IMPORTANCE

Drug-resistant tuberculosis (TB) infection is a growing and potent concern, and combating it will be necessary to achieve the WHO's goal of a 95% reduction in TB deaths by 2035. While prior studies have explored the evolution and spread of drug resistance, we still lack a clear understanding of the fitness costs (if any) imposed by resistance-conferring mutations and the role that Mtb genetic lineage plays in determining the likelihood of resistance evolution. This study offers insight into these questions by assessing the dynamics of resistance evolution in a high-burden Southeast Asian setting with a diverse lineage composition. It demonstrates that there are clear lineage-specific differences in the dynamics of resistance acquisition and transmission and shows that different lineages evolve resistance via characteristic mutational pathways.

Mycobacterium tuberculosis Sub-Lineage 4.2.2/SIT149 as Dominant Drug-Resistant Clade in Northwest Ethiopia 2020-2022: In-silico Whole-Genome Sequence Analysis

Introduction

Drug resistance (DR) in Mycobacterium tuberculosis complex (MTBC) is mainly associated with certain lineages and varies across regions and countries. The Beijing genotype is the leading resistant lineage in Asia and western countries. M. tuberculosis (Mtb) (sub) lineages responsible for most drug resistance in Ethiopia are not well described. Hence, this study aimed to identify the leading drug resistance sub-lineages and characterize first-line anti-tuberculosis drug resistance-associated single nucleotide polymorphisms (SNPs).

Methods

A facility-based cross-sectional study was conducted in 2020-2022 among new and presumptive multidrug resistant-TB (MDR-TB) cases in Northwest Ethiopia. Whole-genome sequencing (WGS) was performed on 161 isolates using Illumina NovaSeq 6000 technology. The SNP mutations associated with drug resistance were identified using MtbSeq and TB profiler Bioinformatics softwares.

Results

Of the 146 Mtb isolates that were successfully genotyped, 20 (13.7%) harbored one or more resistance-associated SNPs. L4.2.2.ETH was the leading drug-resistant sub-lineage, accounting for 10/20 (50%) of the resistant Mtb. MDR-TB isolates showed extensive mutations against first-line anti-TB drugs. Ser450Leu/(tcg/tTg) for Rifampicin (RIF), Ser315Thr/(agc/aCc) for Isoniazid (INH), Met306Ile/(atg/atA(C)) for Ethambutol (EMB), and Gly69Asp for Streptomycin (STR) were the leading resistance associated mutations which accounted for 56.5%, 89.5%, 47%, and 29.4%, respectively. The presence of both clustered and non-clustered drug resistance (DR) isolates indicated that the epidemics is driven by both new DR development and acquired resistance.

Conclusion

The high prevalence of drug-resistant TB due to geographically restricted sub-lineages (L4.2.2.ETH) indicates the ongoing local micro epidemics. The Mtb drug resistance surveillance system must be improved. Further evolutionary analysis of L4.2.2.ETH strain is highly desirable to understand evolutionary forces that leads L4.2.2.ETH in to high level DR and transmissible sub-lineage.

Three genes controlling streptomycin susceptibility in Agrobacterium fabrum

Streptomycin (Sm) is a commonly used antibiotic for its efficacy against diverse bacteria. The plant pathogen Agrobacterium fabrum is a model for studying pathogenesis and interkingdom gene transfer. Streptomycin-resistant variants of A. fabrum are commonly employed in genetic analyses, yet mechanisms of resistance and susceptibility to streptomycin in this organism have not previously been investigated. We observe that resistance to a high concentration of streptomycin arises at high frequency in A. fabrum, and we attribute this trait to the presence of a chromosomal gene (strB) encoding a putative aminoglycoside phosphotransferase. We show how strB, along with rpsL (encoding ribosomal protein S12) and rsmG (encoding a 16S rRNA methyltransferase), modulates streptomycin sensitivity in A. fabrum. IMPORTANCE The plant pathogen Agrobacterium fabrum is a widely used model bacterium for studying biofilms, bacterial motility, pathogenesis, and gene transfer from bacteria to plants. Streptomycin (Sm) is an aminoglycoside antibiotic known for its broad efficacy against gram-negative bacteria. A. fabrum exhibits endogenous resistance to somewhat high levels of streptomycin, but the mechanism underlying this resistance has not been elucidated. Here, we demonstrate that this resistance is caused by a chromosomally encoded streptomycin-inactivating enzyme, StrB, that has not been previously characterized in A. fabrum. Furthermore, we show how the genes rsmG, rpsL, and strB jointly modulate streptomycin susceptibility in A. fabrum.

Lineage classification and antitubercular drug resistance surveillance of Mycobacterium tuberculosis by whole-genome sequencing in Southern India

Whole-genome sequencing has created a revolution in tuberculosis management by providing a comprehensive picture of the various genetic polymorphisms with unprecedented accuracy. Studies mapping genomic heterogeneity in clinical isolates of Mycobacterium tuberculosis using a whole-genome sequencing approach from high tuberculosis burden countries are underrepresented. We report whole-genome sequencing results of 242 clinical isolates of culture-confirmed M. tuberculosis isolates from tuberculosis patients referred to a tertiary care hospital in Southern India. Phylogenetic analysis revealed that the isolates in our study belonged to five different lineages, with Indo-Oceanic (lineage 1, n = 122) and East-African Indian (lineage 3, n = 80) being the most prevalent. We report several mutations in genes conferring resistance to first and second line antitubercular drugs including the genes rpoB, katG, ahpC, inhA, fabG1, embB, pncA, rpsL, rrs, and gyrA. The majority of these mutations were identified in relatively high proportions in lineage 1. Our study highlights the utility of whole-genome sequencing as a potential supplemental tool to the existing genotypic and phenotypic methods, in providing expedited comprehensive surveillance of mutations that may be associated with antitubercular drug resistance as well as lineage characterization of M. tuberculosis isolates. Further larger-scale whole-genome datasets with linked minimum inhibition concentration testing are imperative for resolving the discrepancies between whole-genome sequencing and phenotypic drug sensitivity testing results and quantifying the level of the resistance associated with the mutations for optimization of antitubercular drug and precise dose selection in clinics. IMPORTANCE Studies mapping genetic heterogeneity of clinical isolates of M. tuberculosis for determining their strain lineage and drug resistance by whole-genome sequencing are limited in high tuberculosis burden settings. We carried out whole-genome sequencing of 242 M. tuberculosis isolates from drug-sensitive and drug-resistant tuberculosis patients, identified and collected as part of the TB Portals Program, to have a comprehensive insight into the genetic diversity of M. tuberculosis in Southern India. We report several genetic variations in M. tuberculosis that may confer resistance to antitubercular drugs. Further wide-scale efforts are required to fully characterize M. tuberculosis genetic diversity at a population level in high tuberculosis burden settings for providing precise tuberculosis treatment.

Insight into Population Structure and Drug Resistance of Pediatric Tuberculosis Strains from China and Russia Gained through Whole-Genome Sequencing

This study aimed to determine phenotypic and genotypic drug resistance patterns of Mycobacterium tuberculosis strains from children with tuberculosis (TB) in China and Russia, two high-burden countries for multi/extensively-drug resistant (MDR/XDR) TB. Whole-genome sequencing data of M. tuberculosis isolates from China (n = 137) and Russia (n = 60) were analyzed for phylogenetic markers and drug-resistance mutations, followed by comparison with phenotypic susceptibility data. The Beijing genotype was detected in 126 Chinese and 50 Russian isolates. The Euro-American lineage was detected in 10 Russian and 11 Chinese isolates. In the Russian collection, the Beijing genotype and Beijing B0/W148-cluster were dominated by MDR strains (68% and 94%, respectively). Ninety percent of B0/W148 strains were phenotypically pre-XDR. In the Chinese collection, neither of the Beijing sublineages was associated with MDR/pre-XDR status. MDR was mostly caused by low fitness cost mutations (rpoB S450L, katG S315T, rpsL K43R). Chinese rifampicin-resistant strains demonstrated a higher diversity of resistance mutations than Russian isolates (p = 0.003). The rifampicin and isoniazid resistance compensatory mutations were detected in some MDR strains, but they were not widespread. The molecular mechanisms of M. tuberculosis adaptation to anti-TB treatment are not unique to the pediatric strains, but they reflect the general situation with TB in Russia and China.

Heterologous production of the D-cycloserine intermediate O-acetyl-L-serine in a human type II pulmonary cell model

Tuberculosis (TB) is the second leading cause of death by a single infectious disease behind COVID-19. Despite a century of effort, the current TB vaccine does not effectively prevent pulmonary TB, promote herd immunity, or prevent transmission. Therefore, alternative approaches are needed. We seek to develop a cell therapy that produces an effective antibiotic in response to TB infection. D-cycloserine (D-CS) is a second-line antibiotic for TB that inhibits bacterial cell wall synthesis. We have determined D-CS to be the optimal candidate for anti-TB cell therapy due to its effectiveness against TB, relatively short biosynthetic pathway, and its low-resistance incidence. The first committed step towards D-CS synthesis is catalyzed by the L-serine-O-acetyltransferase (DcsE) which converts L-serine and acetyl-CoA to O-acetyl-L-serine (L-OAS). To test if the D-CS pathway could be an effective prophylaxis for TB, we endeavored to express functional DcsE in A549 cells as a human pulmonary model. We observed DcsE-FLAG-GFP expression using fluorescence microscopy. DcsE purified from A549 cells catalyzed the synthesis of L-OAS as observed by HPLC-MS. Therefore, human cells synthesize functional DcsE capable of converting L-serine and acetyl-CoA to L-OAS demonstrating the first step towards D-CS production in human cells.

Genomic Sequencing Profiles of Mycobacterium tuberculosis in Mandalay Region, Myanmar

This study aimed to characterize whole-genome sequencing (WGS) information of Mycobacterium tuberculosis (Mtb) in the Mandalay region of Myanmar. It was a cross-sectional study conducted with 151 Mtb isolates obtained from the fourth nationwide anti-tuberculosis (TB) drug-resistance survey. Frequency of lineages 1, 2, 3, and 4 were 55, 65, 9, and 22, respectively. The most common sublineage was L1.1.3.1 (n = 31). Respective multi-drug resistant tuberculosis (MDR-TB) frequencies were 1, 1, 0, and 0. Four clusters of 3 (L2), 2 (L4), 2 (L1), and 2 (L2) isolates defined by a 20-single-nucleotide variant (SNV) cutoff were detected. Simpson's index for sublineages was 0.0709. Such high diversity suggests that the area probably had imported Mtb from many geographical sources. Relatively few genetic clusters and MDR-TB suggest there is a chance the future control will succeed if it is carried out properly.

Genomic insights into antibiotic resistance and mobilome of lactic acid bacteria and bifidobacteria

Lactic acid bacteria (LAB) and Bifidobacterium sp. (bifidobacteria) can carry antimicrobial resistance genes (ARGs), yet data on resistance mechanisms in these bacteria are limited. The aim of our study was to identify the underlying genetic mechanisms of phenotypic resistance in 103 LAB and bifidobacteria using whole-genome sequencing. Sequencing data not only confirmed the presence of 36 acquired ARGs in genomes of 18 strains, but also revealed wide dissemination of intrinsic ARGs. The presence of acquired ARGs on known and novel mobile genetic elements raises the possibility of their horizontal spread. In addition, our data suggest that mutations may be a common mechanism of resistance. Several novel candidate resistance mechanisms were uncovered, providing a basis for further in vitro studies. Overall, 1,314 minimum inhibitory concentrations matched with genotypes in 92.4% of the cases; however, prediction of phenotype based on genotypic data was only partially efficient, especially with respect to aminoglycosides and chloramphenicol. Our study sheds light on resistance mechanisms and their transferability potential in LAB and bifidobacteria, which will be useful for risk assessment analysis.

Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan

Drug-resistant tuberculosis (DR-TB) posed challenges to global TB control. Whole-genome sequencing (WGS) is recommended for predicting drug resistance to guide DR-TB treatment and management. Nevertheless, data are lacking in Taiwan. Phenotypic drug susceptibility testing (DST) of 12 anti-TB drugs was performed for 200 Mycobacterium tuberculosis isolates. WGS was performed using the Illumina platform. Drug resistance profiles and lineages were predicted in silico using the Total Genotyping Solution for TB (TGS-TB). Using the phenotypic DST results as a reference, WGS-based prediction demonstrated high concordance rates of isoniazid (95.0%), rifampicin (RIF) (98.0%), pyrazinamide (98.5%) and fluoroquinolones (FQs) (99.5%) and 96.0% to 99.5% for second-line injectable drugs (SLIDs); whereas, lower concordance rates of ethambutol (87.5%), streptomycin (88.0%) and ethionamide (84.0%). Furthermore, minimum inhibitory concentrations confirmed that RIF rpoB S450L, FQs gyrA D94G and SLIDs rrs a1401g conferred high resistance levels. Besides, we identified lineage-associated mutations in lineage 1 (rpoB H445Y and fabG1 c-15t) and predominant lineage 2 (rpoB S450L and rpsL K43R). The WGS-based prediction of drug resistance is highly concordant with phenotypic DST results and can provide comprehensive genetic information to guide DR-TB precision therapies in Taiwan.

In silico analyses of isoniazid and streptomycin resistance-associated mutations in Mycobacterium tuberculosis

Multi-drug resistant tuberculosis is categorised by the World Health Organisation (WHO) as a public health crisis. In silico techniques were used to probe the structural basis of Mycobacterium tuberculosis resistance to isoniazid and streptomycin. Isoniazid resistance-associated mutations in InhA were predicted to reduce the binding affinity of NADH to InhA, without affecting INH-NAD (competitive-inhibitor) binding. Perturbation of the mutated residues was predicted (with the AlloSigMA server) to modulate the free energy of allosteric modulation of key binding site residues F41, F149, Y158 and W222. These results suggest that allosteric modulation of the protein structure may be key to the mechanism by which isoniazid resistance-associated mutations act. Mutations in the methyltransferase glucose-inhibited division gene B (GidB) are associated with streptomycin resistance. Molecular docking was carried out to predict the structure of the GidB bound to its substrate (s-adenosyl methionine). The effects of streptomycin resistance-associated mutations in GidB on protein stability and substrate binding were predicted (using SDM and mCSM-lig). All GidB mutants were predicted to disfavour SAM binding.

Development and Assessment of a Novel Whole-Gene-Based Targeted Next-Generation Sequencing Assay for Detecting the Susceptibility of Mycobacterium tuberculosis to 14 Drugs

Targeted next-generation sequencing (tNGS) has emerged as an alternative method for detecting drug-resistant tuberculosis (DR-TB). To provide comprehensive drug susceptibility information and to address mutations missed by available commercial molecular diagnostics, we developed and evaluated a tNGS panel with 22 whole-gene targets using the Ion Torrent platform to predict drug resistance to 14 drugs, namely, rifampicin (RIF), isoniazid (INH), ethambutol (EMB), pyrazinamide (PZA), moxifloxacin (MFX), levofloxacin (LFX), amikacin (AMK), capreomycin (CM), kanamycin (KM), streptomycin (SM), bedaquiline (BDQ), clofazimine (CFZ), linezolid (LZD), and delamanid (DLM). We selected 50 and 35 Mycobacterium tuberculosis isolates with various DR profiles as the training set and the challenge set, respectively. Comparative variant analyses of the DR genes were performed using Sanger sequencing and whole-genome sequencing (WGS). Phenotypic drug susceptibility testing (pDST) results were used as gold standards. Regarding the limit of detection, the tNGS assay detected 2.9 to 3.8% minority variants in 4% mutant mixtures. The sensitivity and specificity of tNGS were 97.0% (95% confidence interval [CI] = 93.1 to 98.7%) and 99.1% (95% CI = 97.7 to 99.7%), respectively. The concordance of tNGS with pDST was 98.5% (95% CI = 97.2 to 99.2%), which was comparable to that of WGS (98.7%, 95% CI = 97.4 to 99.3%) and better than that of Sanger sequencing (96.9%, 95% CI = 95.3 to 98.0%). The agreement between tNGS and pDST was almost perfect for RIF, INH, EMB, MFX, LFX, AMK, CM, KM, SM, BDQ, and LZD (kappa value = 0.807 to 1.000) and substantial for PZA (kappa value = 0.791). Our customized novel whole-gene-based tNGS panel is highly consistent with pDST and WGS for comprehensive and accurate prediction of drug resistance in a strengthened and streamlined DR-TB laboratory program. IMPORTANCE We developed and validated a tNGS assay that was the first to target 22 whole genes instead of regions of drug resistance genes and comprehensively detected susceptibility to 14 anti-TB drugs, with great flexibility to include new or repurposed drugs. Notably, we demonstrated that our custom-designed Ion AmpliSeq TB research panel platform had high concordance with pDST and could significantly reduce turnaround time (by approximately 70%) to meet a clinically actionable time frame. Our tNGS assay is a promising DST solution for providing needed clinical information for precision medicine-guided therapies for DR-TB and allows the rollout of active pharmacovigilance.

Distribution of Mycobacterium tuberculosis Lineages and Drug Resistance in Upper Myanmar

Mycobacterium tuberculosis complex (MTBC) is divided into 9 whole genome sequencing (WGS) lineages. Among them, lineages 1−4 are widely distributed. Multi-drug resistant tuberculosis (MDR-TB) is a major public health threat. For effective TB control, there is a need to obtain genetic information on lineages of Mycobacterium tuberculosis (Mtb) and to understand distribution of lineages and drug resistance. This study aimed to describe the distribution of major lineages and drug resistance patterns of Mtb in Upper Myanmar. This was a cross-sectional study conducted with 506 sequenced isolates. We found that the most common lineage was lineage 2 (n = 223, 44.1%). The most common drug resistance mutation found was streptomycin (n = 44, 8.7%). Lineage 2 showed a higher number of MDR-TB compared to other lineages. There were significant associations between lineages of Mtb and drug resistance patterns, and between lineages and geographical locations of Upper Myanmar (p value < 0.001). This information on the distribution of Mtb lineages across the geographical areas will support a lot for the better understanding of TB transmission and control in Myanmar and other neighboring countries. Therefore, closer collaboration in cross border tuberculosis control is recommended.

Unraveling the mechanisms of intrinsic drug resistance in Mycobacterium tuberculosis

Tuberculosis (TB) is among the most difficult infections to treat, requiring several months of multidrug therapy to produce a durable cure. The reasons necessitating long treatment times are complex and multifactorial. However, one major difficulty of treating TB is the resistance of the infecting bacterium, Mycobacterium tuberculosis (Mtb), to many distinct classes of antimicrobials. This review will focus on the major gaps in our understanding of intrinsic drug resistance in Mtb and how functional and chemical-genetics can help close those gaps. A better understanding of intrinsic drug resistance will help lay the foundation for strategies to disarm and circumvent these mechanisms to develop more potent antitubercular therapies.

Mycobacterium tuberculosis functional genetic diversity, altered drug sensitivity, and precision medicine

In the face of the unrelenting global burden of tuberculosis (TB), antibiotics remain our most effective tools to save lives and control the spread of Mycobacterium tuberculosis (Mtb). However, we confront a dual challenge in our use of antibiotics: simplifying and shortening the TB drug regimen while also limiting the emergence and propagation of antibiotic resistance. This task is now more feasible due to the increasing availability of bacterial genomic data at or near the point of care. These resources create an opportunity to envision how integration of bacterial genetic determinants of antibiotic response into treatment algorithms might transform TB care. Historically, Mtb drug resistance studies focused on mutations in genes encoding antibiotic targets and the resulting increases in the minimal inhibitory concentrations (MICs) above a breakpoint value. But recent progress in elucidating the effects of functional genetic diversity in Mtb has revealed various genetic loci that are associated with drug phenotypes such as low-level MIC increases and tolerance which predict the development of resistance and treatment failure. As a result, we are now poised to advance precision medicine approaches in TB treatment. By incorporating information regarding Mtb genetic characteristics into the development of drug regimens, clinical care which tailors antibiotic treatment to maximize the likelihood of success has come into reach.

Acquisition of Streptomycin Resistance by Oxidative Stress Induced by Hydrogen Peroxide in Radiation-Resistant Bacterium Deinococcus geothermalis

Streptomycin is used primarily to treat bacterial infections, including brucellosis, plague, and tuberculosis. Streptomycin resistance easily develops in numerous bacteria through the inhibition of antibiotic transfer, the production of aminoglycoside-modifying enzymes, or mutations in ribosomal components with clinical doses of streptomycin treatment. (1) Background: A transposable insertion sequence is one of the mutation agents in bacterial genomes under oxidative stress. (2) Methods: In the radiation-resistant bacterium Deinococcus geothermalis subjected to chronic oxidative stress induced by 20 mM hydrogen peroxide, active transposition of an insertion sequence element and several point mutations in three streptomycin resistance (SmR)-related genes (rsmG, rpsL, and mthA) were identified. (3) Results: ISDge6 of the IS5 family integrated into the rsmG gene (dgeo_2335), called SrsmG, encodes a ribosomal guanosine methyltransferase resulting in streptomycin resistance. In the case of dgeo_2840-disrupted mutant strains (S1 and S2), growth inhibition under antibiotic-free conditions was recovered with increased growth yields in the presence of 50 µg/mL streptomycin due to a streptomycin-dependent (SmD) mutation. These mutants have a predicted proline-to-leucine substitution at the 91st residue of ribosomal protein S12 in the decoding center. (4) Conclusions: Our findings show that the active transposition of a unique IS element under oxidative stress conditions conferred antibiotic resistance through the disruption of rsmG. Furthermore, chronic oxidative stress induced by hydrogen peroxide also induced streptomycin resistance caused by point and frameshift mutations of streptomycin-interacting residues such as K43, K88, and P91 in RpsL and four genes for streptomycin resistance.

Prediction of drug resistance by Sanger sequencing of Mycobacterium tuberculosis complex strains isolated from multidrug resistant tuberculosis suspect patients in Ethiopia

Background

Ethiopia is one of the high multidrug-resistant tuberculosis (MDR-TB) burden countries. However, phenotypic drug susceptibility testing can take several weeks due to the slow growth of Mycobacterium tuberculosis complex (MTBC) strains. In this study, we assessed the performance of a Sanger sequencing approach to predict resistance against five anti-tuberculosis drugs and the pattern of resistance mediating mutations.

Methods

We enrolled 226 MTBC culture-positive MDR-TB suspects and collected sputum specimens and socio-demographic and TB related data from each suspect between June 2015 and December 2016 in Addis Ababa, Ethiopia. Phenotypic drug susceptibility testing (pDST) for rifampicin, isoniazid, pyrazinamide, ethambutol, and streptomycin using BACTEC MGIT 960 was compared with the results of a Sanger sequencing analysis of seven resistance determining regions in the genes rpoB, katG, fabG-inhA, pncA, embB, rpsL, and rrs.

Result

DNA isolation for Sanger sequencing was successfully extracted from 92.5% (209/226) of the MTBC positive cultures, and the remaining 7.5% (17/226) strains were excluded from the final analysis. Based on pDST results, drug resistance proportions were as follows: isoniazid: 109/209 (52.2%), streptomycin: 93/209 (44.5%), rifampicin: 88/209 (42.1%), ethambutol: 74/209 (35.4%), and pyrazinamide: 69/209 (33.0%). Resistance against isoniazid was mainly mediated by the mutation katG S315T (97/209, 46.4%) and resistance against rifampicin by rpoB S531L (58/209, 27.8%). The dominating resistance-conferring mutations for ethambutol, streptomycin, and pyrazinamide affected codon 306 in embB (48/209, 21.1%), codon 88 in rpsL (43/209, 20.6%), and codon 65 in pncA (19/209, 9.1%), respectively. We observed a high agreement between phenotypic and genotypic DST, such as 89.9% (at 95% confidence interval [CI], 84.2%–95.8%) for isoniazid, 95.5% (95% CI, 91.2%–99.8%) for rifampicin, 98.6% (95% CI, 95.9–100%) for ethambutol, 91.3% (95% CI, 84.6–98.1%) for pyrazinamide and 57.0% (95% CI, 46.9%–67.1%) for streptomycin.

Conclusion

We detected canonical mutations implicated in resistance to rifampicin, isoniazid, pyrazinamide, ethambutol, and streptomycin. High agreement with phenotypic DST results for all drugs renders Sanger sequencing promising to be performed as a complementary measure to routine phenotypic DST in Ethiopia. Sanger sequencing directly from sputum may accelerate accurate clinical decision-making in the future.

Resistance and tolerance of Mycobacterium tuberculosis to antimicrobial agents-How M. tuberculosis can escape antibiotics

Tuberculosis (TB) poses a serious threat to public health worldwide since it was discovered. Until now, TB has been one of the top 10 causes of death from a single infectious disease globally. The treatment of active TB cases majorly relies on various anti-tuberculosis drugs. However, under the selection pressure by drugs, the continuous evolution of Mycobacterium tuberculosis (Mtb) facilitates the emergence of drug-resistant strains, further resulting in the accumulation of tubercle bacilli with multiple drug resistance, especially deadly multidrug-resistant TB and extensively drug-resistant TB. Researches on the mechanism of drug action and drug resistance of Mtb provide a new scheme for clinical management of TB patients, and prevention of drug resistance. In this review, we summarized the molecular mechanisms of drug resistance of existing anti-TB drugs to better understand the evolution of drug resistance of Mtb, which will provide more effective strategies against drug-resistant TB, and accelerate the achievement of the EndTB Strategy by 2035. This article is categorized under: Infectious Diseases > Molecular and Cellular Physiology.

CRISPRi chemical genetics and comparative genomics identify genes mediating drug potency in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) infection is notoriously difficult to treat. Treatment efficacy is limited by Mtb's intrinsic drug resistance, as well as its ability to evolve acquired resistance to all antituberculars in clinical use. A deeper understanding of the bacterial pathways that influence drug efficacy could facilitate the development of more effective therapies, identify new mechanisms of acquired resistance, and reveal overlooked therapeutic opportunities. Here we developed a CRISPR interference chemical-genetics platform to titrate the expression of Mtb genes and quantify bacterial fitness in the presence of different drugs. We discovered diverse mechanisms of intrinsic drug resistance, unveiling hundreds of potential targets for synergistic drug combinations. Combining chemical genetics with comparative genomics of Mtb clinical isolates, we further identified several previously unknown mechanisms of acquired drug resistance, one of which is associated with a multidrug-resistant tuberculosis outbreak in South America. Lastly, we found that the intrinsic resistance factor whiB7 was inactivated in an entire Mtb sublineage endemic to Southeast Asia, presenting an opportunity to potentially repurpose the macrolide antibiotic clarithromycin to treat tuberculosis. This chemical-genetic map provides a rich resource to understand drug efficacy in Mtb and guide future tuberculosis drug development and treatment.

Whole-Genome Sequencing Reveals Recent Transmission of Multidrug-Resistant Mycobacterium tuberculosis CAS1-Kili Strains in Lusaka, Zambia

Globally, tuberculosis (TB) is a major cause of death due to antimicrobial resistance. Mycobacterium tuberculosis CAS1-Kili strains that belong to lineage 3 (Central Asian Strain, CAS) were previously implicated in the spread of multidrug-resistant (MDR)-TB in Lusaka, Zambia. Thus, we investigated recent transmission of those strains by whole-genome sequencing (WGS) with Illumina MiSeq platform. Twelve MDR CAS1-Kili isolates clustered by traditional methods (MIRU-VNTR and spoligotyping) were used. A total of 92% (11/12) of isolates belonged to a cluster (≤12 SNPs) while 50% (6/12) were involved in recent transmission events, as they differed by ≤5 SNPs. All the isolates had KatG Ser315Thr (isoniazid resistance), EmbB Met306 substitutions (ethambutol resistance) and several kinds of rpoB mutations (rifampicin resistance). WGS also revealed compensatory mutations including a novel deletion in embA regulatory region (−35A > del). Several strains shared the same combinations of drug-resistance-associated mutations indicating transmission of MDR strains. Zambian strains belonged to the same clade as Tanzanian, Malawian and European strains, although most of those were pan-drug-susceptible. Hence, complimentary use of WGS to traditional epidemiological methods provides an in-depth insight on transmission and drug resistance patterns which can guide targeted control measures to stop the spread of MDR-TB.

Whole genome sequencing reveals large deletions and other loss of function mutations in Mycobacterium tuberculosis drug resistance genes

Drug resistance in Mycobacterium tuberculosis, the causative agent of tuberculosis disease, arises from genetic mutations in genes coding for drug-targets or drug-converting enzymes. SNPs linked to drug resistance have been extensively studied and form the basis of molecular diagnostics and sequencing-based resistance profiling. However, alternative forms of functional variation such as large deletions and other loss of function (LOF) mutations have received much less attention, but if incorporated into diagnostics they are likely to improve their predictive performance. Our work aimed to characterize the contribution of LOF mutations found in 42 established drug resistance genes linked to 19 anti-tuberculous drugs across 32689 sequenced clinical isolates. The analysed LOF mutations included large deletions (n=586), frameshifts (n=4764) and premature stop codons (n=826). We found LOF mutations in genes strongly linked to pyrazinamide (pncA), isoniazid (katG), capreomycin (tlyA), streptomycin (e.g. gid) and ethionamide (ethA, mshA) (P<10^-5), but also in some loci linked to drugs where relatively less phenotypic data is available [e.g. cycloserine, delaminid, bedaquiline, para-aminosalicylic acid (PAS), and clofazimine]. This study reports that large deletions (median size 1115 bp) account for a significant portion of resistance variants found for PAS (+7.1% of phenotypic resistance percentage explained), pyrazinamide (+3.5%) and streptomycin (+2.6%) drugs, and can be used to improve the prediction of cryptic resistance. Overall, our work highlights the importance of including LOF mutations (e.g. large deletions) in predicting genotypic drug resistance, thereby informing tuberculosis infection control and clinical decision-making.

Characterization of Mutations Associated with Streptomycin Resistance in Multidrug-Resistant Mycobacterium tuberculosis in Zambia

Streptomycin (STR) is recommended for the management of multidrug-resistant tuberculosis (MDR-TB). Streptomycin resistance-conferring mutation types and frequency are shown to be influenced by genotypes of circulating strains in a population. This study aimed to characterize the mutations in MDR-TB isolates and examine their relationship with the genotypes in Zambia. A total of 138 MDR-TB isolates stored at the University Teaching Hospital Tuberculosis Reference Laboratory in Zambia were analyzed using spoligotyping and sequencing of STR resistance-associated genes. Streptomycin resistance was observed in 65.9% (91/138) of MDR-TB isolates. Mutations in rpsL, rrs, and gidB accounted for 33%, 12.1%, and 49.5%, respectively. Amino acid substitution K43R in rpsL was strongly associated with the CAS1_Kili genotype (p < 0.0001). The combination of three genes could predict 91.2% of STR resistance. Clustering of isolates based on resistance-conferring mutations and spoligotyping was observed. The clustering of isolates suggests that the increase in STR-resistant MDR-TB in Zambia is largely due to the spread of resistant strains from inadequate treatment. Therefore, rapid detection of STR resistance genetically is recommended before its use in MDR-TB treatment in Zambia.

Specific phenotypic, genomic, and fitness evolutionary trajectories toward streptomycin resistance induced by pesticide co-stressors in Escherichia coli

To explore how co-occurring non-antibiotic environmental stressors affect evolutionary trajectories toward antibiotic resistance, we exposed susceptible Escherichia coli K-12 populations to environmentally relevant levels of pesticides and streptomycin for 500 generations. The coexposure substantially changed the phenotypic, genotypic, and fitness evolutionary trajectories, resulting in much stronger streptomycin resistance (>15-fold increase) of the populations. Antibiotic target modification mutations in rpsL and rsmG, which emerged and dominated at late stages of evolution, conferred the strong resistance even with less than 1% abundance, while the off-target mutations in nuoG, nuoL, glnE, and yaiW dominated at early stages only led to mild resistance (2.5-6-fold increase). Moreover, the strongly resistant mutants exhibited lower fitness costs even without the selective pressure and had lower minimal selection concentrations than the mildly resistant ones. Removal of the selective pressure did not reverse the strong resistance of coexposed populations at a later evolutionary stage. The findings suggest higher risks of the selection and propagation of strong antibiotic resistance in environments potentially impacted by antibiotics and pesticides.

Molecular Analysis of Streptomycin Resistance Genes in Clinical Strains of Mycobacterium tuberculosis and Biocomputational Analysis of the MtGidB L101F Variant

Globally, tuberculosis (TB) remains a prevalent threat to public health. In 2019, TB affected 10 million people and caused 1.4 million deaths. The major challenge for controlling this infectious disease is the emergence and spread of drug-resistant Mycobacterium tuberculosis, the causative agent of TB. The antibiotic streptomycin is not a current first-line anti-TB drug. However, WHO recommends its use in patients infected with a streptomycin-sensitive strain. Several mutations in the M. tuberculosisrpsL, rrs and gidB genes have proved association with streptomycin resistance. In this study, we performed a molecular analysis of these genes in clinical isolates to determine the prevalence of known or novel mutations. Here, we describe the genetic analysis outcome. Furthermore, a biocomputational analysis of the MtGidB L101F variant, the product of a novel mutation detected in gidB during molecular analysis, is also reported as a theoretical approach to study the apparent genotype-phenotype association.

Heterogeneous Streptomycin Resistance Level Among Mycobacterium tuberculosis Strains From the Same Transmission Cluster

Widespread and frequent resistance to the second-line tuberculosis (TB) medicine streptomycin, suggests ongoing transmission of low fitness cost streptomycin resistance mutations. To investigate this hypothesis, we studied a cohort of 681 individuals from a TB epidemic in Portugal. Whole-genome sequencing (WGS) analyses were combined with phenotypic growth studies in culture media and in mouse bone marrow derived macrophages. Streptomycin resistance was the most frequent resistance in the cohort accounting for 82.7% (n = 67) of the resistant Mycobacterium tuberculosis isolates. WGS of 149 clinical isolates identified 13 transmission clusters, including three clusters containing only streptomycin resistant isolates. The biggest cluster was formed by eight streptomycin resistant isolates with a maximum of five pairwise single nucleotide polymorphisms of difference. Interestingly, despite their genetic similarity, these isolates displayed different resistance levels to streptomycin, as measured both in culture media and in infected mouse bone marrow derived macrophages. The genetic bases underlying this phenotype are a combination of mutations in gid and other genes. This study suggests that specific streptomycin resistance mutations were transmitted in the cohort, with the resistant isolates evolving at the cluster level to allow low-to-high streptomycin resistance levels without a significative fitness cost. This is relevant not only to better understand transmission of streptomycin resistance in a clinical setting dominated by Lineage 4 M. tuberculosis infections, but mainly because it opens new prospects for the investigation of selection and spread of drug resistance in general.

Highlights Regarding the Use of Metallic Nanoparticles against Pathogens Considered a Priority by the World Health Organization

The indiscriminate use of antibiotics has facilitated the growing resistance of bacteria, and this has become a serious public health problem worldwide. Several microorganisms are still resistant to multiple antibiotics and are particularly dangerous in the hospital and nursing home environment, and to patients whose care requires devices, such as ventilators and intravenous catheters. A list of twelve pathogenic genera, which especially included bacteria that were not affected by different antibiotics, was released by the World Health Organization (WHO) in 2017, and the research and development of new antibiotics against these genera has been considered a priority. The nanotechnology is a tool that offers an effective platform for altering the physicalchemical properties of different materials, thereby enabling the development of several biomedical applications. Owing to their large surface area and high reactivity, metallic particles on the nanometric scale have remarkable physical, chemical, and biological properties. Nanoparticles with sizes between 1 and 100 nm have several applications, mainly as new antimicrobial agents for the control of microorganisms. In the present review, more than 200 reports of various metallic nanoparticles, especially those containing copper, gold, platinum, silver, titanium, and zinc were analyzed with regard to their anti-bacterial activity. However, of these 200 studies, only 42 reported about trials conducted against the resistant bacteria considered a priority by the WHO. All studies are in the initial stage, and none are in the clinical phase of research.

GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

Molecular Characteristics and Drug Resistance of Mycobacterium tuberculosis Isolate Circulating in Shaanxi Province, Northwestern China

Objective: Shaanxi is the most highly populated province with high burdens of tuberculosis in northwestern China. The aim of this study was to investigate the molecular characteristics and drug resistance of Mycobacterium tuberculosis isolates from Shaanxi province of China in 2018. Methods: Phenotypic drug susceptibility testing and spoligotyping methods were performed on 518 M. tuberculosis isolates; drug-resistant isolates were sequenced in 11 drug loci, including katG, inhA, oxyR-ahpC, rpoB, embB, rpsL, rrs₁ (nucleotides 388-1084), gyrA, gyrB, rrs₂ (nucleotides 1158-1674), and eis. Results: The prevalences of isoniazid, rifampicin, ethambutol, streptomycin, ofloxacin, and kanamycin resistance were 22.0%, 19.3%, 7.9%, 23.8%, 10.4%, and 3.3%, respectively. The Beijing family (82.8%) was the predominant genotype, followed by the T (9.3%), H (0.6%), CAS (0.4%), LAM (0.4%), and U (0.4%) families. The percentage of Beijing genotype in a central area (88.1%) was higher than in the south (77.3%) and the north area (80.1%) (p < 0.05), while the sex, age, and treatment history between Beijing and non-Beijing family were not statistically different. Mutation analysis found that the most prevalent mutations were katG315, rpoB531, embB306, rpsL43, gyrA94, and rrs1401; the Beijing family exhibited a high rate of isoniazid-resistant isolates carrying katG315 mutations (p < 0.05). Furthermore, compared with the phenotypic data, the sensitivities of isoniazid, rifampicin, ethambutol, streptomycin, ofloxacin, and kanamycin resistance by sequencing base on 11 loci were 85.1%, 94.0%, 53.7%, 74.8%, 77.8%, and 64.7%, respectively. Conclusions: Shaanxi has a serious epidemic of drug-resistant tuberculosis, Beijing family is the predominant genotype, and the distribution showed geographic diversity. The prevalence of Beijing genotypes has a tendency to promote the transmission of high-level isoniazid-resistant M. tuberculosis. Besides, the hot spot regions localized in the embB, rrs₂, and eis gene appear not to serve as excellent biomarkers for predicting ethambutol and kanamycin resistance in Shaanxi.

Genome analyses of 174 strains of Mycobacterium tuberculosis provide insight into the evolution of drug resistance and reveal potential drug targets

Mycobacterium tuberculosis is a known human pathogen that causes the airborne infectious disease tuberculosis (TB). Every year TB infects millions of people worldwide. The emergence of multi-drug resistant (MDR), extensively drug resistant (XDR) and totally drug resistant (TDR) M. tuberculosis strains against the first- and second-line anti-TB drugs has created an urgent need for the development and implementation of new drug strategies. In this study, the complete genomes of 174 strains of M. tuberculosis are analysed to understand the evolution of molecular drug target (MDT) genes. Phylogenomic placements of M. tuberculosis strains depicted close association and temporal clustering. Selection pressure analysis by deducing the ratio of non-synonymous to synonymous substitution rates (dN/dS) in 51 MDT genes of the 174 M. tuberculosis strains led to categorizing these genes into diversifying (D, dN/dS>0.70), moderately diversifying (MD, dN/dS=0.35-0.70) and stabilized (S, dN/dS<0.35) genes. The genes rpsL, gidB, pncA and ahpC were identified as diversifying, and Rv0488, kasA, ndh, ethR, ethA, embR and ddn were identified as stabilized genes. Furthermore, sequence similarity networks were drawn that supported these divisions. In the multiple sequence alignments of diversifying and stabilized proteins, previously reported resistance mutations were checked to predict sensitive and resistant strains of M. tuberculosis. Finally, to delineate the potential of stabilized or least diversified genes/proteins as anti-TB drug targets, protein-protein interactions of MDT proteins with human proteins were analysed. We predict that kasA (dN/dS=0.29), a stabilized gene that encodes the most host-interacting protein, KasA, should serve as a potential drug target for the treatment of TB.

Whole-genome sequence analysis and comparisons between drug-resistance mutations and minimum inhibitory concentrations of Mycobacterium tuberculosis isolates causing M/XDR-TB

Drug resistance (DR) remains a major challenge for tuberculosis (TB) control. Whole-genome sequencing (WGS) provides the highest genetic resolution for genotypic drug-susceptibility tests (DST). We compared DST profiles of 60 Mycobacterium tuberculosis isolates which were drug resistant according to agar proportion tests (one poly DR-TB, 34 multidrug-resistant TB and 25 extensively drug-resistant TB). We additionally performed minimum inhibitory concentration (MIC) tests using Sensititre MYCOTBI plates (MYCOTB) and a WGS-based DST. Agreement between WGS-based DST and MYCOTB was high for all drugs except ethambutol (65%) and ethionamide (62%). Isolates harboring the -15 c/t inhA promoter mutation had a significantly lower MIC for isoniazid than did isolates with the katG Ser315Thr mutation (p < 0.001). Similar patterns were seen for ethambutol (embB Gly406Asp vs. embB Met306Ile), streptomycin (gid Gly73Ala vs. rpsL Lys43Arg), moxifloxacin (gyrA Ala90Val vs. gyrA Asp94Gly) and rifabutin (rpoB Asp435Phe/Tyr/Val vs. rpoB Ser450Leu). For genotypic heteroresistance, isolates with lower proportion of mapped read tended to has lower MIC of anti-TB drugs than those with higher proportion. These results emphasize the high applicability of WGS for determination of DR-TB and the association of particular mutations with MIC levels.

Loss of U1498 methylation in 16S rRNA by RsmE methyltransferase associates its role with aminoglycoside resistance in mycobacteria

OBJECTIVES

Modulation of methylation pattern through mutations in ribosomal methyltransferases is a key mechanism of bacterial drug resistance. However, RsmG (GidB), which specifically methylates G527 in 16S rRNA, remains the only conserved methyltransferase known to be associated with low-level drug resistance in mycobacterial isolates. The mycobacterial RsmE homologue methylates U1498 in 16S rRNA in a highly specific manner. U1498 lies in the vicinity of the binding site for various aminoglycosides in the ribosome. However, the association of methylation at U1498 with altered drug response remains poorly understood.

METHODS

A deletion mutant of the RsmE homologue in Mycobacterium smegmatis was generated by a suicidal vector strategy and drug susceptibility assays were performed on wild-type, knockout and complemented strains with varying concentrations of ribosomal- and non-ribosomal-targeting drugs.

RESULTS

Deletion of the RsmE homologue of M. smegmatis led to an at least two-fold increase in the minimum inhibitory concentrations (MICs) of aminoglycosides that bind in the decoding centre proximal to U1498 in the 30S subunit. The change in MICs was highly specific and reproducible and did not show any cross-resistance to other drug classes. Surprisingly, Rv2372c, the RsmE homologue of Mycobacterium tuberculosis, has the largest number of mutations among conserved ribosomal methyltransferases, after gidB, highlighting the role of mutations in RsmE methyltransferase as a key emerging mechanism of resistance in clinical strains.

CONCLUSION

We present the first evidence of an association of methylation of U1498 in 16S rRNA with development of low-level resistance in mycobacteria that must be tackled in a timely manner.

Exploiting Homoplasy in Genome-Wide Association Studies to Enhance Identification of Antibiotic-Resistance Mutations in Bacterial Genomes

Many antibacterial drugs have multiple mechanisms of resistance, which are often represented simultaneously by a mixture of resistance mutations (some more frequent than others) in a clinical population. This presents a challenge for Genome-Wide Association Studies (GWAS) methods, making it difficult to detect less prevalent resistance mechanisms purely through (weak) statistical associations. Homoplasy, or the occurrence of multiple independent mutations at the same site, is often observed with drug resistance mutations and can be a strong indicator of positive selection. However, traditional GWAS methods, such as those based on allele counting or linear regression, are not designed to take homoplasy into account. In this article, we present a new method, called ECAT (for Evolutionary Cluster-based Association Test), that extends traditional regression-based GWAS methods with the ability to take advantage of homoplasy. This is achieved through a preprocessing step which identifies hypervariable regions in the genome exhibiting statistically significant clusters of distinct evolutionary changes, to which association testing by a linear mixed model (LMM) is applied using GEMMA (a well-established LMM-based GWAS tool). Thus, the approach can be viewed as extending GEMMA from the usual site- or gene-level analysis to focusing on clustered regions of mutations. This approach was evaluated on a large collection of more than 600 clinical isolates of multidrug-resistant (MDR) Mycobacterium tuberculosis from Lima, Peru. We show that ECAT does a better job of detecting known resistance mutations for several antitubercular drugs (including less prevalent mutations with weaker associations), compared with (site- or gene-based) GEMMA, as representative of existing GWAS methods. The power of the multiphase approach in ECAT comes from focusing association testing on the hypervariable regions of the genome, which reduces complexity in the model and increases statistical power.

Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database – Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

Drug-Resistant Tuberculosis 2020: Where We Stand

The control of tuberculosis (TB) is hampered by the emergence of multidrug-resistant (MDR) Mycobacterium tuberculosis (Mtb) strains, defined as resistant to at least isoniazid and rifampin, the two bactericidal drugs essential for the treatment of the disease. Due to the worldwide estimate of almost half a million incident cases of MDR/rifampin-resistant TB, it is important to continuously update the knowledge on the mechanisms involved in the development of this phenomenon. Clinical, biological and microbiological reasons account for the generation of resistance, including: (i) nonadherence of patients to their therapy, and/or errors of physicians in therapy management, (ii) complexity and poor vascularization of granulomatous lesions, which obstruct drug distribution to some sites, resulting in resistance development, (iii) intrinsic drug resistance of tubercle bacilli, (iv) formation of non-replicating, drug-tolerant bacilli inside the granulomas, (v) development of mutations in Mtb genes, which are the most important molecular mechanisms of resistance. This review provides a comprehensive overview of these issues, and releases up-dated information on the therapeutic strategies recently endorsed and recommended by the World Health Organization to facilitate the clinical and microbiological management of drug-resistant TB at the global level, with attention also to the most recent diagnostic methods.

A landscape of genomic alterations at the root of a near-untreatable tuberculosis epidemic

BACKGROUND

Atypical Beijing genotype Mycobacterium tuberculosis strains are widespread in South Africa and have acquired resistance to up to 13 drugs on multiple occasions. It is puzzling that these strains have retained fitness and transmissibility despite the potential fitness cost associated with drug resistance mutations.

METHODS

We conducted Illumina sequencing of 211 Beijing genotype M. tuberculosis isolates to facilitate the detection of genomic features that may promote acquisition of drug resistance and restore fitness in highly resistant atypical Beijing forms. Phylogenetic and comparative genomic analysis was done to determine changes that are unique to the resistant strains that also transmit well. Minimum inhibitory concentration (MIC) determination for streptomycin and bedaquiline was done for a limited number of isolates to demonstrate a difference in MIC between isolates with and without certain variants.

RESULTS

Phylogenetic analysis confirmed that two clades of atypical Beijing strains have independently developed resistance to virtually all the potent drugs included in standard (pre-bedaquiline) drug-resistant TB treatment regimens. We show that undetected drug resistance in a progenitor strain was likely instrumental in this resistance acquisition. In this cohort, ethionamide (ethA A381P) resistance would be missed in first-line drug-susceptible isolates, and streptomycin (gidB L79S) resistance may be missed due to an MIC close to the critical concentration. Subsequent inadequate treatment historically led to amplification of resistance and facilitated spread of the strains. Bedaquiline resistance was found in a small number of isolates, despite lack of exposure to the drug. The highly resistant clades also carry inhA promoter mutations, which arose after ethA and katG mutations. In these isolates, inhA promoter mutations do not alter drug resistance, suggesting a possible alternative role.

CONCLUSION

The presence of the ethA mutation in otherwise susceptible isolates from ethionamide-naïve patients demonstrates that known exposure is not an adequate indicator of drug susceptibility. Similarly, it is demonstrated that bedaquiline resistance can occur without exposure to the drug. Inappropriate treatment regimens, due to missed resistance, leads to amplification of resistance, and transmission. We put these results into the context of current WHO treatment regimens, underscoring the risks of treatment without knowledge of the full drug resistance profile.

Genomic Analysis of Mycobacterium tuberculosis Isolates and Construction of a Beijing Lineage Reference Genome

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, kills over 1 million people worldwide annually. Development of drug resistance (DR) in the pathogen is a major challenge for TB control. We conducted whole-genome analysis of seven Taiwan M. tuberculosis isolates: One drug susceptible (DS) and five DR Beijing lineage isolates and one DR Euro-American lineage isolate. Developing a new method for DR mutation identification and applying it to the next-generation sequencing (NGS) data from the 6 Beijing lineage isolates, we identified 13 known and 6 candidate DR mutations and provided experimental support for 4 of them. We assembled the genomes of one DS and two DR Beijing lineage isolates and the Euro-American lineage isolate using NGS data. Moreover, using both PacBio and NGS sequencing data, we obtained a high-quality assembly of an extensive DR Beijing lineage isolate. Comparative analysis of these five newly assembled genomes and two published complete genomes revealed a large number of genetic changes, including gene gains and losses, indels and translocations, suggesting rapid evolution of M. tuberculosis. We found the MazEF toxin-antitoxin system in all the seven isolates studied and several interesting mutations in MazEF proteins. Finally, we used the four assembled Beijing lineage genomes to construct a high-quality Beijing lineage reference genome that is DS and contains all the genes in the four genomes. It contains 212 genes not found in the standard reference H37Rv, which is Euro-American. It is therefore a better reference than H37Rv for the Beijing lineage, the predominant lineage in Asia.

Improved Resistance Prediction in Mycobacterium tuberculosis by Better Handling of Insertions and Deletions, Premature Stop Codons, and Filtering of Non-informative Sites

Resistance in Mycobacterium tuberculosis is a major obstacle for effective treatment of tuberculosis. Multiple studies have shown promising results for predicting drug resistance in M. tuberculosis based on whole genome sequencing (WGS) data, however, these tools are often limited to this single species. We have previously developed a common platform for resistance prediction in multiple species. This platform detects acquired resistance genes (ResFinder) and species-specific chromosomal mutations (PointFinder) associated with resistance, all based on WGS data. In this study, we present a new version of PointFinder together with an updated M. tuberculosis database. PointFinder now includes predictions based on insertions and deletions, and it explicitly reports frameshift mutations and premature stop codons. We found that premature stop codons in four resistance-associated genes (katG, ethA, pncA, and gidB) were over-represented in resistant strains, and we saw an increased prediction performance when including premature stop codons in these genes as resistance markers. Different M. tuberculosis resistance prediction tools vary in performance mostly due to the mutation library used. We found that a well-established mutation library included non-predictive linage markers, and through forward feature selection we eliminated those from the mutation library. Compared to other similar web-based tools, PointFinder performs equally good. The advantages of PointFinder is that together with ResFinder it serves as a common web-based and downloadable platform for resistance detection in multiple species. It is easy to use for clinicians and already widely used in the research community.

Evaluation of Whole-Genome Sequence Method to Diagnose Resistance of 13 Anti-tuberculosis Drugs and Characterize Resistance Genes in Clinical Multi-Drug Resistance Mycobacterium tuberculosis Isolates From China

Background: Whole-genome sequencing (WGS) is a viable and financially feasible tool for timely and comprehensive diagnosis of drug resistance in developed countries. With the increase in the incidence of multidrug-resistant tuberculosis (MDR-TB), second-line anti-TB drugs are gaining importance. However, genetic resistance to second-line anti-TB drugs based on WGS has not been fully studied.

Methods: We randomly selected 100 MDR-TB and 10 non-MDR-TB isolates from a hospital in Zhejiang Province, China. Drug susceptibility tests against 13 anti-TB drugs were performed, and 34 drug resistance-related genes were analyzed using WGS in all isolates. For each drug, the accuracy, sensitivity, specificity, and positive and negative predictive values of WGS were compared with those of the conventional drug susceptibility test.

Results: The overall sensitivity and specificity for WGS were respectively, 99.0 and 100.0% for isoniazid (INH), 99.0 and 100.0% for rifampicin (RIF), 94.8 and 65.3% for ethambutol (EMB), 86.2 and 84.4% for pyrazinamide (PZA), 95.6 and 95.6% for levofloxacin (LFX), 89.5 and 65.3% for moxifloxacin (MFX), 91.3 and 95.1% for streptomycin (SM), 90.9 and 99.0% for kanamycin, 90.9 and 100.0% for amikacin, 88.9 and 98.0% for capreomycin, 87.0 and 85.1% for prothionamide (PTO), 85.7 and 99.0% for para-aminosalicylic acid (PAS), and 66.7 and 95.9% for clofazimine (CLO).

Conclusions: WGS is a promising approach to predict resistance to INH, RIF, PZA, LFX, SM, second-line injectable drugs (SLIDs), and PTO with satisfactory accuracy, sensitivity, and specificity of over 85.0%. The specificity of WGS in diagnosing resistance to EMB, and high-level resistance to MFX (2.0 mg/L) needs to be improved.

Deciphering drug resistance in Mycobacterium tuberculosis using whole-genome sequencing: progress, promise, and challenges

Tuberculosis (TB) is a global infectious threat that is intensified by an increasing incidence of highly drug-resistant disease. Whole-genome sequencing (WGS) studies of Mycobacterium tuberculosis, the causative agent of TB, have greatly increased our understanding of this pathogen. Since the first M. tuberculosis genome was published in 1998, WGS has provided a more complete account of the genomic features that cause resistance in populations of M. tuberculosis, has helped to fill gaps in our knowledge of how both classical and new antitubercular drugs work, and has identified specific mutations that allow M. tuberculosis to escape the effects of these drugs. WGS studies have also revealed how resistance evolves both within an individual patient and within patient populations, including the important roles of de novo acquisition of resistance and clonal spread. These findings have informed decisions about which drug-resistance mutations should be included on extended diagnostic panels. From its origins as a basic science technique, WGS of M. tuberculosis is becoming part of the modern clinical microbiology laboratory, promising rapid and improved detection of drug resistance, and detailed and real-time epidemiology of TB outbreaks. We review the successes and highlight the challenges that remain in applying WGS to improve the control of drug-resistant TB through monitoring its evolution and spread, and to inform more rapid and effective diagnostic and therapeutic strategies.

The roles of rpsL, rrs, and gidB mutations in predicting streptomycin-resistant drugs used on clinical Mycobacterium tuberculosis isolates from Hebei Province, China

Streptomycin (STR) is a component of first-line drugs used to treat multidrug-resistant tuberculosis. The purpose of this study was to investigate the proportion and type of mutations in Mycobacterium tuberculosis isolates resistant to STR and their relationship with the STR-resistant phenotype and with the epidemiological molecular model of the isolates. A total of 302 clinical isolates, including 215 STR-resistant and 87 STR-susceptible isolates, were characterized using the proportion method with Lowenstein-Jensen medium. The genes rpsL, rrs and gidB were screened for mutations using DNA sequencing methodology. All strains were genotyped using the spoligotyping technique. Mutations in rpsL and in rrs were observed in 63.3% and 15.8% of the STR-resistance isolates, respectively. The most prevalent mutations were the Lys43Arg substitution in the rpsL gene and the A514C change in the rrs gene. Ten novel mutations were identified in gidB. These novel mutations might be new potential markers for predicting STR-resistance in clinical Mycobacterium tuberculosis isolates. Mutations in rpsL, rrs, and gidB had a sensitivity of 84.2% and a specificity of 77.0% for the detection of STR-resistance isolates. The Beijing lineage strains were associated with the rpsL mutation Lys43Arg (P = 0.051), as well as the dual gidB mutations Glu92Asp and Ala205Ala (P < 0.001). Our study suggested that rpsL and rrs can act as useful genetic markers for predicting STR-resistance, and gidB polymorphisms play an important role in STR-resistant clinical Mycobacterium tuberculosis isolates from Hebei, China.

First genetic characterisation of multidrug-resistant Mycobacterium tuberculosis isolates from Algeria

OBJECTIVES

To characterise the genotypes of multidrug-resistant (MDR) Mycobacterium tuberculosis (MTB) isolated in Algeria, where there is a low MDR-MTB incidence rate.

METHODS

Ten MDR isolates and one resistant to isoniazid were investigated by PCR-Sanger sequencing for 10 loci involved in resistance. Amplicon-based next generation sequencing (NGS) of 15 loci was additionally performed on isolates harbouring novel mutations.

RESULTS

Sanger and amplicon-NGS provided the same results as with GenoType kits. Mutations known to be associated with resistance were described for most isolates: rpoB S531L in seven of 10 rifampicin-R MTB isolates, katG S315T in nine of 11 isoniazid-R, and promoter inhA c-15t in three of 11, embB M306V or M306I in two of two ethambutol-R, rpsL K43R in four of eight or rrs a514c associated with gidB L16R in streptomycin-R, gyrA A90V in the ofloxacin-R pre-XDR isolate. New and rare mutations were also described in rpoB (deletion 512-513-514), katG (S315R, M126I/ R496L), gidB (V124G, E92A, V139A, G37V), and gyrA (P8A). Mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) profiles were similar for three isolates (lineage Cameroon), indicating a possible clonal diffusion in epidemiologically unrelated patients.

CONCLUSIONS

Resistant MTB isolates in Algeria harbour resistance genotypes similar to other countries, but some rare patterns may result from selection and transmission processes inherent to the country.

A new oligonucleotide array for the detection of multidrug and extensively drug-resistance tuberculosis

Drug-resistant tuberculosis (TB) is a global crisis and a threat to health security. Since conventional drug susceptibility testing (DST) takes several weeks, we herein described a molecular assay to rapidly identify multidrug-resistant (MDR) and extensively drug-resistant (XDR) and reveal transmission associated-mutations of Mycobacterium tuberculosis complex (MTBC) isolates in 6 to 7 hours. An array was designed with 12 pairs of primers and 60 single nucleotide polymorphisms of 9 genes: rpoB, katG, inhA, ahpC, embB, rpsL, gyrA, rrs and eis. We assessed the performance of the array using 176 clinical MTBC isolates. The results of culture-based DST were used as the gold standard, the GenoType MTBDRplus and MTBDRsl tests were used for parallel comparison, and gene sequencing was performed to resolve the discordance. The sensitivities and specificities of the array are comparable to those of the MTBDRplus test for resistance to isoniazid (INH) (100.0%, 96.7%) and rifampicin (RIF) (99.4%, 96.7%) and of the MTBDRsl test for resistance to fluoroquinolones (FQs) (100%, 100%) and second-line injectable drugs (SLIDs) (98.3%, 100%). The sensitivities of the array for detecting resistance to ethambutol and streptomycin were 79.3% and 64.9%, respectively. The array has potential as a powerful tool for clinical diagnosis and epidemiological investigations.

Whole Genome Sequencing of Mycobacterium tuberculosis Clinical Isolates From India Reveals Genetic Heterogeneity and Region-Specific Variations That Might Affect Drug Susceptibility

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has been constructive in understanding its evolution, genetic diversity and the mechanisms involved in drug resistance. A large number of sequencing efforts from across the globe have revealed genetic diversity among clinical isolates and the genetic determinants for their resistance to anti-tubercular drugs. Considering the high TB burden in India, the availability of WGS studies is limited. Here we present, WGS results of 200 clinical isolates of M. tuberculosis from North India which are categorized as sensitive to first-line drugs, mono-resistant, multi-drug resistant and pre-extensively drug resistant isolates. WGS revealed that 20% of the isolates were co-infected with M. tuberculosis and non-tuberculous mycobacteria species. We identified 12,802 novel genetic variations in M. tuberculosis isolates including 343 novel SNVs in 38 genes which are known to be associated with drug resistance and are not currently used in the diagnostic kits for detection of drug resistant TB. We also identified M. tuberculosis lineage 3 to be predominant in the northern region of India. Additionally, several novel SNVs, which may potentially confer drug resistance were found to be enriched in the drug resistant isolates sampled. This study highlights the significance of employing WGS in diagnosis and for monitoring further development of MDR-TB strains.

Unveiling the structural features that determine the dual methyltransferase activities of Streptococcus pneumoniae RlmCD

Methyltransferase RlmCD was previously shown to be responsible for the introduction of C5 methylation at both U747 and U1939 of the 23S ribosomal RNA in Streptococcus pneumoniae. Intriguingly, its structural homologue, RumA, can only catalyze the methylation of U1939, while RlmC is the dedicated enzyme for m5U747 in Escherichia coli. In this study, we describe the structure of RlmCD in complex with its cofactor and the RNA substrate containing U747 at 2.00 Å or U1939 at 3.10 Å. We demonstrate that multiple structural features collaborate to establish the dual enzymatic activities of RlmCD. Of them, the side-chain rearrangement of F145 was observed to be an unusual mechanism through which RlmCD can discriminate between U747- and U1939-containing RNA substrate by switching the intermolecular aromatic stacking between protein and RNA on/off. An in-vitro methyltransferase assay and electrophoretic mobility shift assay were performed to validate these findings. Overall, our complex structures allow for a better understanding of the dual-functional mechanism of RlmCD, suggesting useful implications for the evolution of the RumA-type enzyme and the potential development of antibiotic drugs against S. pneumoniae.

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many publicly available datasets describing its AMR characteristics demand disparate data-type analyses. Here, we develop a reference strain-agnostic computational platform that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics. This platform is applied to 1595 sequenced strains to yield four key results. First, a pan-genome analysis shows that M. tuberculosis is highly conserved with sequenced variation concentrated in PE/PPE/PGRS genes. Second, the platform corroborates 33 genes known to confer resistance and identifies 24 new genetic signatures of AMR. Third, 97 epistatic interactions across 10 resistance classes are revealed. Fourth, detailed structural analysis of these genes yields mechanistic bases for their selection. The platform can be used to study other human pathogens.

Drug resistance mechanisms and drug susceptibility testing for tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) is the deadliest infectious disease and the associated global threat has worsened with the emergence of drug resistance, in particular multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB). Although the World Health Organization (WHO) End-TB Strategy advocates for universal access to antimicrobial susceptibility testing, this is not widely available and/or it is still underused. The majority of drug resistance in clinical MTB strains is attributed to chromosomal mutations. Resistance-related mutations could also exert certain fitness cost to the drug-resistant MTB strains and growth fitness could be restored by the presence of compensatory mutations. Understanding these underlying mechanisms could provide an important insight into TB pathogenesis and predict the future trend of MDR-TB global pandemic. This review covers the mechanisms of resistance in MTB and provides a comprehensive overview of current phenotypic and molecular approaches for drug susceptibility testing, with particular attention to the methods endorsed and recommended by the WHO.

Comparative Genome Analysis of 2 Mycobacterium Tuberculosis Strains from Pakistan: Insights Globally Into Drug Resistance, Virulence, and Niche Adaptation

Multidrug-resistant Mycobacterium tuberculosis is a global threat particularly in developing countries like Pakistan. In this study, we identified 2 M tuberculosis strains, mnpk and swlpk, by 16S RNA genes, sequenced their draft genome, and compared the 2 genomes with reference strain H37Rv and gene expression analysis of selected virulent genes. Phylogenetic analysis of M tuberculosis strains, mnpk and swlpk, using 16S RNA genes revealed that the strains are closely related with reference strain H37Rv. The draft genome sequence of mnpk and swlpk contains 4305 and 4295 protein-coding genes, respectively, having 99.9% with high collinearity when compared with H37Rv. Although some important drug-resistant genes such as fabG, faDE24, and iniA were missing, genome mining also revealed key drug-resistant genes such as katG, inhA, rpoA, rpoB, and rpoC against first-line isoniazid and rifampicin drug. The strain mnpk and swlpk encodes 257 putative and 86 verified virulent genes including type 7 secretion system (T7SS) key genes. The variation in the expression profile of selected T7SS genes, particularly low expression level of EspK, raised concern that the mechanism of virulence of mnpk and swlpk might be different from H37Rv strains as espK is associated with ATPase EccC1a and EccC1b which showed high expression level. Briefly, this study shows that the strains mnpk and swlpk are linked with H37Rv having 99% similarity in genomes, but the absence of drug-resistant genes and variation in key genes’ expression profile espK, EccE1, PPE41, and espC provide a rationale for the future investigation of M tuberculosis mnpk and swlpk pathogenesis via RNA sequencing, single-nucleotide polymorphisms, as well as gene manipulation.