tbvar: A comprehensive genome variation resource for Mycobacterium tuberculosis

An overview of next generation sequencing strategies and genomics tools used for tuberculosis research

Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of next generation sequencing (NGS) and WGS analysis in TB research, there are limited studies that provide a comprehensive summary of there role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and NGS strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.

An HLA-E-targeted TCR bispecific molecule redirects T cell immunity against Mycobacterium tuberculosis

Peptides presented by HLA-E, a molecule with very limited polymorphism, represent attractive targets for T cell receptor (TCR)-based immunotherapies to circumvent the limitations imposed by the high polymorphism of classical HLA genes in the human population. Here, we describe a TCR-based bispecific molecule that potently and selectively binds HLA-E in complex with a peptide encoded by the inhA gene of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis in humans. We reveal the biophysical and structural bases underpinning the potency and specificity of this molecule and demonstrate its ability to redirect polyclonal T cells to target HLA-E-expressing cells transduced with mycobacterial inhA as well as primary cells infected with virulent Mtb. Additionally, we demonstrate elimination of Mtb-infected cells and reduction of intracellular Mtb growth. Our study suggests an approach to enhance host T cell immunity against Mtb and provides proof of principle for an innovative TCR-based therapeutic strategy overcoming HLA polymorphism and therefore applicable to a broader patient population.

A Rapid Drug Resistance Genotyping Workflow for Mycobacterium tuberculosis, Using Targeted Isothermal Amplification and Nanopore Sequencing

Phenotypic drug susceptibility testing (DST) for tuberculosis (TB) requires weeks to yield results. Although molecular tests rapidly detect drug resistance-associated mutations (DRMs), they are not scalable to cover the full genome and the many DRMs that can predict resistance. Whole-genome sequencing (WGS) methods are scalable, but if conducted directly on sputum, typically require a target enrichment step, such as nucleic acid amplification. We developed a targeted isothermal amplification-nanopore sequencing workflow for rapid prediction of drug resistance of TB isolates. We used recombinase polymerase amplification (RPA) to perform targeted isothermal amplification (37°C for 90 min) of three regions within the Mycobacterium tuberculosis genome, followed by nanopore sequencing on the MinION. We tested 29 mycobacterial genomic DNA extracts from patients with drug-resistant (DR) TB and compared our results to those of WGS by Illumina and phenotypic DST to evaluate the accuracy of prediction of resistance to rifampin and isoniazid. Amplification by RPA showed fidelity equivalent to that of high-fidelity PCR (100% concordance). Nanopore sequencing generated DRM predictions identical to those of WGS, with considerably faster sequencing run times of minutes rather than days. The sensitivity and specificity of rifampin resistance prediction for our workflow were 96.3% (95% confidence interval [CI], 81.0 to 99.9%) and 100.0% (95% CI, 15.8 to 100.0%), respectively. For isoniazid resistance prediction, the sensitivity and specificity were 100.0% (95% CI, 86.3 to 100.0%) and 100.0% (95% CI, 39.8 to 100.0%), respectively. The workflow consumable costs per sample are less than £100. Our rapid and low-cost drug resistance genotyping workflow provides accurate prediction of rifampin and isoniazid resistance, making it appropriate for use in resource-limited settings. IMPORTANCE Current methods for diagnosing drug-resistant tuberculosis are time consuming, resulting in delays in patients receiving treatment and in transmission onwards. They also require a high level of laboratory infrastructure, which is often only available at centralized facilities, resulting in further delays to diagnosis and additional barriers to deployment in resource-limited settings. This article describes a new workflow that can diagnose drug-resistant TB in a shorter time, with less equipment, and for a lower price than current methods. The amount of TB DNA is first increased without the need for bulky and costly thermocycling equipment. The DNA is then read using a portable sequencer called a MinION, which indicates whether there are tell-tale changes in the DNA that indicate whether the TB strain is drug resistant. Our workflow could play an important role in the future in the fight against the public health challenge that is TB drug resistance.

Anti-tuberculosis Compound Screen using a Zebrafish Infection Model identifies an Aspartyl-tRNA Synthetase Inhibitor

Finding new anti-tuberculosis compounds with convincing in vivo activity is an ongoing global challenge to fight the emergence of multidrug-resistant Mycobacterium tuberculosis isolates. In this study, we exploited the medium-throughput capabilities of the zebrafish embryo infection model with Mycobacterium marinum as a surrogate for M. tuberculosis. Using a representative set of clinically established drugs, we demonstrate that this model could be predictive and selective for antibiotics that can be administered orally. We further used the zebrafish infection model to screen 240 compounds from an anti-tuberculosis hit library for their in vivo activity and identified 14 highly active compounds. One of the most active compounds was the tetracyclic compound TBA161, which was studied in more detail. Analysis of resistant mutants revealed point mutations in aspS (rv2572c), encoding an aspartyl-tRNA synthetase. The target was genetically confirmed, and molecular docking studies propose the possible binding of TBA161 in a pocket adjacent to the catalytic site. This study shows that the zebrafish infection model is suitable for rapidly identifying promising scaffolds with in vivo activity.

Summary: Exploitation of the medium-throughput capabilities of a zebrafish embryo infection model of tuberculosis to screen compounds for their in vivo activity, one of which was characterized as an aspartyl-tRNA synthetase inhibitor.

Value of routine whole genome sequencing for Mycobacterium tuberculosis drug resistance detection

Routine whole genome sequencing (WGS) of pathogens is becoming more feasible as sequencing costs decrease and access to benchtop sequencing equipment and bioinformatics pipelines increases. This study examined the added value gained from implementing routine WGS of all Mycobacterium tuberculosis isolates in New South Wales, Australia. Drug resistance markers inferred from WGS data were compared to commercial genotypic drug susceptibility testing (DST) assays and conventional phenotypic DST in all isolates sequenced between 2016 and 2019. Of the 1107 clinical M. tuberculosis isolates sequenced, 29 (2.6%) were multi-drug resistant (MDR); most belonged to Beijing (336; 30.4%) or East-African Indian (332; 30%) lineages. Compared with conventional phenotypic DST, WGS identified an additional 1% of isolates which were likely drug resistant, explained by mutations previously associated with treatment failure and mixed bacterial populations. However, WGS provided a 20% increase in drug resistance detection in comparison with commercial genotypic assays by identifying mutations outside of the classic resistance determining regions in rpoB, inhA, katG, pncA and embB genes. Gains in drug resistance detection were significant (p = 0.0137, paired t-test), but varied substantially for different phylogenetic lineages. In low incidence settings, routine WGS of M. tuberculosis provides better guidance for person-centered management of drug resistant tuberculosis than commercial genotypic assays.

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches

Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce protein affinities within the RNA polymerase complex, subsequently reducing nucleic acid affinity. Here, we have used these insights to develop a computational rifampicin resistance predictor capable of identifying resistant mutations even outside the well-defined rifampicin resistance determining region (RRDR), using clinical M. tuberculosis sequencing information. Our tool successfully identified up to 90.9% of M. tuberculosis rpoB variants correctly, with sensitivity of 92.2%, specificity of 83.6% and MCC of 0.69, outperforming the current gold-standard GeneXpert-MTB/RIF. We show our model can be translated to other clinically relevant organisms: M. leprae, P. aeruginosa and S. aureus, despite weak sequence identity. Our method was implemented as an interactive tool, SUSPECT-RIF (StrUctural Susceptibility PrEdiCTion for RIFampicin), freely available at https://biosig.unimelb.edu.au/suspect_rif/ .

Correlation of drug resistance with single nucleotide variations through genome analysis and experimental validation in a multi-drug resistant clinical isolate of M. tuberculosis

BACKGROUND

Genome sequencing and genetic polymorphism analysis of clinical isolates of M. tuberculosis is carried out to gain further insight into molecular pathogenesis and host-pathogen interaction. Therefore the functional evaluation of the effect of single nucleotide variation (SNV) is essential. At the same time, the identification of invariant sequences unique to M. tuberculosis contributes to infection detection by sensitive methods. In the present study, genome analysis is accompanied by evaluation of the functional implication of the SNVs in a MDR clinical isolate VPCI591.

RESULT

By sequencing and comparative analysis of VPCI591 genome with 1553 global clinical isolates of M. tuberculosis (GMTV and tbVar databases), we identified 141 unique strain specific SNVs. A novel intergenic variation in VPCI591 in the putative promoter/regulatory region mapping between embC (Rv3793) and embA (Rv3794) genes was found to enhance the expression of embAB, which correlates with the high resistance of the VPCI591 to ethambutol. Similarly, the unique combination of three genic SNVs in RNA polymerase β gene (rpoB) in VPCI591 was evaluated for its effect on rifampicin resistance through molecular docking analysis. The comparative genomics also showed that along with variations, there are genes that remain invariant. 173 such genes were identified in our analysis.

CONCLUSION

The genetic variation in M. tuberculosis clinical isolate VPCI591 is found in almost all functional classes of genes. We have shown that SNV in rpoB gene mapping outside the drug binding site along with two SNVs in the binding site can contribute to quantitative change in MIC for rifampicin. Our results show the collective effect of SNVs on the structure of the protein, impacting the interaction between the target protein and the drug molecule in rpoB as an example. The study shows that intergenic variations bring about quantitative changes in transcription in embAB and in turn can lead to drug resistance.

Wild-Type MIC Distribution for Re-evaluating the Critical Concentration of Anti-TB Drugs and Pharmacodynamics Among Tuberculosis Patients From South India

The World Health Organization (WHO) has developed specific guidelines for critical concentrations (CCs) of antibiotics used for tuberculosis (TB) treatment, which is universally followed for drug susceptibility testing (DST) of clinical specimens. However, the CC of drugs can differ significantly among the mycobacterial species based on the population, geographic location, and the prevalence of the infecting strain in a particular area. The association between CC and the minimal inhibitory concentration (MIC) of anti-TB drugs is poorly understood. In this study, we assessed the MICs of anti-TB drugs, including isoniazid (INH), rifampicin (RMP), moxifloxacin (MXF), ethambutol (ETH), and p-aminosalicylic acid (PAS) on drug-sensitive Mtb isolates from pulmonary TB patients in South India. The MIC assays performed using solid- and liquid-growth media showed changes in the CC of a few of the tested antibiotics compared with the WHO-recommended levels. Our observation suggests that the WHO guidelines could potentially lead to overdiagnosis of drug-resistant cases, which can result in inappropriate therapeutic decisions. To evaluate the correlation between drug-resistance and CC, we performed the whole-genome sequencing for 16 mycobacterial isolates, including two wild-type and 14 resistant isolates. Our results showed that two of the isolates belonged to the W-Beijing lineage, while the rest were of the East-African-Indian type. We identified a total of 74 mutations, including five novel mutations, which are known to be associated with resistance to anti-TB drugs in these isolates. In our previous study, we determined the serum levels of INH and RMP among the same patients recruited in the current study and estimated the MICs of the corresponding infected isolates in these cases. Using these data and the CCs for INH and RMP from the present study, we performed pharmacodynamics (PD) evaluation. The results show that the PD of RMP was subtherapeutic. Together, these observations emphasize the need for optimizing the drug dosage based on the PD of large-scale studies conducted in different geographical settings.

MycoResistance: a curated resource of drug resistance molecules in Mycobacteria

The emergence and spread of drug-resistant Mycobacterium tuberculosis is of global concern. To improve the understanding of drug resistance in Mycobacteria, numerous studies have been performed to discover diagnostic markers and genetic determinants associated with resistance to anti-tuberculosis drug. However, the related information is scattered in a massive body of literature, which is inconvenient for researchers to investigate the molecular mechanism of drug resistance. Therefore, we manually collected 1707 curated associations between 73 compounds and 132 molecules (including coding genes and non-coding RNAs) in 6 mycobacterial species from 465 studies. The experimental details of molecular epidemiology and mechanism exploration research were also summarized and recorded in our work. In addition, multidrug resistance and extensively drug resistance molecules were also extracted to interpret the molecular mechanisms that are responsible for cross resistance among anti-tuberculosis drugs. Finally, we constructed an omnibus repository named MycoResistance, a user friendly interface to conveniently browse, search and download all related entries. We hope that this elaborate database will serve as a beneficial resource for mechanism explanations, precise diagnosis and effective treatment of drug-resistant mycobacterial strains.

Classification of Mycobacterium tuberculosis DR, MDR,XDR Isolates and Identification of Signature MutationPattern of Drug Resistance

Mycobacterium tuberculosis - a global threat, the recent breakout in MDR-TB and XDR-TB has challenged researchers in diagnosis to provide effective treatment. The main objective to combat drug resistance is to provide rapid, reliable and sensitive diagnostic methods in health care centres. This study focuses on development of an effective pipeline to identify drug resistance mutations in whole genome data of Mycobacterium tuberculosis utilizing the Next Generation Sequencing approach and classification of drug resistance strains based on genetic markers obtained from TGS-TB, tbvar and TBDReamDB. 74 isolates are characterized into 20 DR-TB, 16 MDR-TB, 16 XDR-TB and 6 nonresistant strains based on known drug resistance genetic markers. Results provide mutation pattern for each of the classified strains and profiling of drug resistance to the group of anti-TB drugs. The presence of specific mutation causing resistance to a drug will help set the dosage levels which play an important role in the treatment. Findings on amino acid changes and its respective codon positions in candidate genes will provide insights in drug sensitivity and a way for discovery of potent drugs. The implementation of these approaches in clinical setting provides rapid and sensitive diagnostics to combat the emerging drug resistance.

DNA markers for tuberculosis diagnosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis complex (MTBC), is an infectious disease with more than 10.4 million cases and 1.7 million deaths reported worldwide in 2016. The classical methods for detection and differentiation of mycobacteria are: acid-fast microscopy (Ziehl-Neelsen staining), culture, and biochemical methods. However, the microbial phenotypic characterization is time-consuming and laborious. Thus, fast, easy, and sensitive nucleic acid amplification tests (NAATs) have been developed based on specific DNA markers, which are commercially available for TB diagnosis. Despite these developments, the disease remains uncontrollable. The identification and differentiation among MTBC members with the use of NAATs remains challenging due, among other factors, to the high degree of homology within the members and mutations, which hinders the identification of specific target sequences in the genome with potential impact in the diagnosis and treatment outcomes. In silico methods provide predictive identification of many new target genes/fragments/regions that can specifically be used to identify species/strains, which have not been fully explored. This review focused on DNA markers useful for MTBC detection, species identification and antibiotic resistance determination. The use of DNA targets with new technological approaches will help to develop NAATs applicable to all levels of the health system, mainly in low resource areas, which urgently need customized methods to their specific conditions.

A non-canonical mismatch repair pathway in prokaryotes

Mismatch repair (MMR) is a near ubiquitous pathway, essential for the maintenance of genome stability. Members of the MutS and MutL protein families perform key steps in mismatch correction. Despite the major importance of this repair pathway, MutS-MutL are absent in almost all Actinobacteria and many Archaea. However, these organisms exhibit rates and spectra of spontaneous mutations similar to MMR-bearing species, suggesting the existence of an alternative to the canonical MutS-MutL-based MMR. Here we report that Mycobacterium smegmatis NucS/EndoMS, a putative endonuclease with no structural homology to known MMR factors, is required for mutation avoidance and anti-recombination, hallmarks of the canonical MMR. Furthermore, phenotypic analysis of naturally occurring polymorphic NucS in a M. smegmatis surrogate model, suggests the existence of M. tuberculosis mutator strains. The phylogenetic analysis of NucS indicates a complex evolutionary process leading to a disperse distribution pattern in prokaryotes. Together, these findings indicate that distinct pathways for MMR have evolved at least twice in nature.

A Comparison of the Sensititre MycoTB Plate, the Bactec MGIT 960, and a Microarray-Based Molecular Assay for the Detection of Drug Resistance in Clinical Mycobacterium tuberculosis Isolates in Moscow, Russia

Background

The goal of this study was to compare the consistency of three assays for the determination of the drug resistance of Mycobacterium tuberculosis (MTB) strains with various resistance profiles isolated from the Moscow region.

Methods

A total of 144 MTB clinical isolates with a strong bias toward drug resistance were examined using Bactec MGIT 960, Sensititre MycoTB, and a microarray-based molecular assay TB-TEST to detect substitutions in the rpoB, katG, inhA, ahpC, gyrA, gyrB, rrs, eis, and embB genes that are associated with resistance to rifampin, isoniazid, fluoroquinolones, second-line injectable drugs and ethambutol.

Results

The average correlation for the identification of resistant and susceptible isolates using the three methods was approximately 94%. An association of mutations detected with variable resistance levels was shown. We propose a change in the breakpoint minimal inhibitory concentration for kanamycin to less than 5 μg/ml in the Sensititre MycoTB system. A pairwise comparison of the minimal inhibitory concentrations (MICs) of two different drugs revealed an increased correlation in the first-line drug group and a partial correlation in the second-line drug group, reflecting the history of the preferential simultaneous use of drugs from these groups. An increased correlation with the MICs was also observed for drugs sharing common resistance mechanisms.

Conclusions

The quantitative measures of phenotypic drug resistance produced by the Sensititre MycoTB and the timely detection of mutations using the TB-TEST assay provide guidance for clinicians for the choice of the appropriate drug regimen.

Methodological and Clinical Aspects of the Molecular Epidemiology of Mycobacterium tuberculosis and Other Mycobacteria

Molecular typing has revolutionized epidemiological studies of infectious diseases, including those of a mycobacterial etiology. With the advent of fingerprinting techniques, many traditional concepts regarding transmission, infectivity, or pathogenicity of mycobacterial bacilli have been revisited, and their conventional interpretations have been challenged. Since the mid-1990s, when the first typing methods were introduced, a plethora of other modalities have been proposed. So-called molecular epidemiology has become an essential subdiscipline of modern mycobacteriology. It serves as a resource for understanding the key issues in the epidemiology of tuberculosis and other mycobacterial diseases. Among these issues are disclosing sources of infection, quantifying recent transmission, identifying transmission links, discerning reinfection from relapse, tracking the geographic distribution and clonal expansion of specific strains, and exploring the genetic mechanisms underlying specific phenotypic traits, including virulence, organ tropism, transmissibility, or drug resistance. Since genotyping continues to unravel the biology of mycobacteria, it offers enormous promise in the fight against and prevention of the diseases caused by these pathogens. In this review, molecular typing methods for Mycobacterium tuberculosis and nontuberculous mycobacteria elaborated over the last 2 decades are summarized. The relevance of these methods to the epidemiological investigation, diagnosis, evolution, and control of mycobacterial diseases is discussed.

Clinical value of whole-genome sequencing of Mycobacterium tuberculosis

Whole-genome sequencing (WGS) is now common as a result of new technologies that can rapidly sequence a complete bacterial genome for US$500 or less. Many studies have addressed questions about tuberculosis with WGS, and knowing the sequence of the entire genome, rather than only a few fragments, has greatly increased the precision of molecular epidemiology and contact tracing. Additionally, topics such as the mutation rate, drug resistance, the target of new drugs, and the phylogeny and evolution of the Mycobacterium tuberculosis complex bacteria have been elucidated by WGS. Nonetheless, WGS has not explained differences in transmissibility between strains, or why some strains are more virulent than others or more prone to development of multidrug resistance. With advances in technology, WGS of clinical specimens could become routine in high-income countries; however, its relevance will probably depend on easy to use software to efficiently process the sequences produced and accessible genomic databases that can be mined in future studies.

Databases for Microbiologists

Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.

TuberQ: a Mycobacterium tuberculosis protein druggability database

In 2012 an estimated 8.6 million people developed tuberculosis (TB) and 1.3 million died from the disease [including 320 000 deaths among human immunodeficiency virus (HIV)-positive people]. There is an urgent need for new anti-TB drugs owing to the following: the fact that current treatments have severe side effects, the increasing emergence of multidrug-resistant strains of Mycobacterium tuberculosis (Mtb), the negative drug-drug interactions with certain HIV (or other disease) treatments and the ineffectiveness against dormant Mtb. In this context we present here the TuberQ database, a novel resource for all researchers working in the field of drug development in TB. The main feature of TuberQ is to provide a druggability analysis of Mtb proteins in a consistent and effective manner, contributing to a better selection of potential drug targets for screening campaigns and the analysis of targets for structure-based drug design projects. The structural druggability analysis is combined with features related to the characteristics of putative inhibitor binding pockets and with functional and biological data of proteins. The structural analysis is performed on all available unique Mtb structures and high-quality structural homology-based models. This information is shown in an interactive manner, depicting the protein structure, the pockets and the associated characteristics for each protein. TuberQ also provides information about gene essentiality information, as determined from whole cell-based knockout experiments, and expression information obtained from microarray experiments done in different stress-related conditions. We hope that TuberQ will be a powerful tool for researchers working in TB and eventually will lead to the identification of novel putative targets and progresses in therapeutic activities. Database URL: http://tuberq.proteinq.com.ar/