Large-scale genomic analysis of Mycobacterium tuberculosis reveals extent of target and compensatory mutations linked to multi-drug resistant tuberculosis

Combating antimicrobial resistance in malaria, HIV and tuberculosis

Antimicrobial resistance poses a significant threat to the sustainability of effective treatments against the three most prevalent infectious diseases: malaria, human immunodeficiency virus (HIV) infection and tuberculosis. Therefore, there is an urgent need to develop novel drugs and treatment protocols capable of reducing the emergence of resistance and combating it when it does occur. In this Review, we present an overview of the status and underlying molecular mechanisms of drug resistance in these three diseases. We also discuss current strategies to address resistance during the research and development of next-generation therapies. These strategies vary depending on the infectious agent and the array of resistance mechanisms involved. Furthermore, we explore the potential for cross-fertilization of knowledge and technology among these diseases to create innovative approaches for minimizing drug resistance and advancing the discovery and development of new anti-infective treatments. In conclusion, we advocate for the implementation of well-defined strategies to effectively mitigate and manage resistance in all interventions against infectious diseases.

Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR'-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M. tuberculosis samples. We performed association analysis (Fisher's exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR'-ahpC (N = 7) that were considered either 'highly likely' or 'likely' to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Compensatory mutations are associated with increased in vitro growth in resistant clinical samples of Mycobacterium tuberculosis

Mutations in Mycobacterium tuberculosis associated with resistance to antibiotics often come with a fitness cost for the bacteria. Resistance to the first-line drug rifampicin leads to lower competitive fitness of M. tuberculosis populations when compared to susceptible populations. This fitness cost, introduced by resistance mutations in the RNA polymerase, can be alleviated by compensatory mutations (CMs) in other regions of the affected protein. CMs are of particular interest clinically since they could lock in resistance mutations, encouraging the spread of resistant strains worldwide. Here, we report the statistical inference of a comprehensive set of CMs in the RNA polymerase of M. tuberculosis, using over 70 000 M. tuberculosis genomes that were collated as part of the CRyPTIC project. The unprecedented size of this data set gave the statistical tests more power to investigate the association of putative CMs with resistance-conferring mutations. Overall, we propose 51 high-confidence CMs by means of statistical association testing and suggest hypotheses for how they exert their compensatory mechanism by mapping them onto the protein structure. In addition, we were able to show an association of CMs with higher in vitro growth densities, and hence presumably with higher fitness, in resistant samples in the more virulent M. tuberculosis lineage 2. Our results suggest the association of CM presence with significantly higher in vitro growth than for wild-type samples, although this association is confounded with lineage and sub-lineage affiliation. Our findings emphasize the integral role of CMs and lineage affiliation in resistance spread and increases the urgency of antibiotic stewardship, which implies accurate, cheap and widely accessible diagnostics for M. tuberculosis infections to not only improve patient outcomes but also prevent the spread of resistant strains.

Phenotype versus genotype discordant rifampicin susceptibility testing in tuberculosis: implications for a diagnostic accuracy

IMPORTANCE

An accurate diagnosis of drug resistance in clinical isolates is an important step for better treatment outcomes. The current study observed a higher discordance rate of rifampicin resistance on Mycobacteria Growth Indicator Tube (MGIT) drug susceptibility testing (DST) than Lowenstein-Jenson (LJ) DST when compared with the rpoB sequencing. We detected a few novel mutations and their combination in rifampicin resistance isolates that were missed by MGIT DST and may be useful for the better management of tuberculosis (TB) treatment outcomes. Few novel deletions in clinical isolates necessitate the importance of rpoB sequencing in large data sets in geographic-specific locations, especially high-burden countries. We explored the discordance rate on MGIT and LJ, which is important for the clinical management of rifampicin resistance to avoid the mistreatment of drug-resistant TB. Furthermore, MGIT-sensitive isolates may be subjected to molecular methods of diagnosis for further confirmation and treatment options.

Diagnostic efficacy of an optimized nucleotide MALDI-TOF-MS assay for anti-tuberculosis drug resistance detection

PURPOSE

We aimed at evaluating the diagnostic efficacy of a nucleotide matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) assay to detect drug resistance of Mycobacterium tuberculosis.

METHODS

Overall, 263 M. tuberculosis clinical isolates were selected to evaluate the performance of nucleic MALDI-TOF-MS for rifampin (RIF), isoniazid (INH), ethambutol (EMB), moxifloxacin (MXF), streptomycin (SM), and pyrazinamide (PZA) resistance detection. The results for RIF, INH, EMB, and MXF were compared with phenotypic microbroth dilution drug susceptibility testing (DST) and whole-genome sequencing (WGS), and the results for SM and PZA were compared with those obtained by WGS.

RESULTS

Using DST as the gold standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 98.2%, 98.7%, and 0.97 for RIF; 92.8%, 99%, and 0.90 for INH; 82.4%, 98.0%, and 0.82 for EMB; and 92.6%, 99.5%, and 0.94 for MXF, respectively. Compared with WGS as the reference standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 97.4%, 100.0%, and 0.98 for RIF; 98.7%, 92.9%, and 0.92 for INH; 96.3%, 100.0%, and 0.98 for EMB; 98.1%, 100.0%, and 0.99 for MXF; 98.0%, 100.0%, and 0.98 for SM; and 50.0%, 100.0%, and 0.65 for PZA.

CONCLUSION

The nucleotide MALDI-TOF-MS assay yielded highly consistent results compared to DST and WGS, suggesting that it is a promising tool for the rapid detection of sensitivity to RIF, INH, EMB, and MXF.

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.