Identification and Characterization of Genetic Determinants of Isoniazid and Rifampicin Resistance in Mycobacterium tuberculosis in Southern India

Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery. Unfortunately, there is an evident gap between the number of machine learning applications in science and the effective implementation of these systems. This narrative review highlights some of the outstanding opportunities that machine learning offers when applied in research related to antimicrobial resistance. In the future, machine learning tools may prove to be superbugs' kryptonite. This review aims to provide an overview of available publications to aid researchers that are looking to expand their work with new approaches and to acquaint them with the current application of machine learning techniques in this field.

Synergistic combination of antimicrobial peptide and isoniazid as inhalable dry powder formulation against multi-drug resistant tuberculosis

Multidrug-resistant tuberculosis (MDR-TB) has posed a serious threat to global public health, and antimicrobial peptides (AMPs) have emerged to be promising candidates to tackle this deadly infectious disease. Previous study has suggested that two AMPs, namely D-LAK120-A and D-LAK120-HP13, can potentiate the effect of isoniazid (INH) against mycobacteria. In this study, the strategy of combining INH and D-LAK peptide as a dry powder formulation for inhalation was explored. The antibacterial effect of INH and D-LAK combination was first evaluated on three MDR clinical isolates of Mycobacteria tuberculosis (Mtb). The minimum inhibitory concentrations (MICs) and fractional inhibitory concentration indexes (FICIs) were determined. The combination was synergistic against Mtb with FICIs ranged from 0.25 to 0.38. The INH and D-LAK peptide at 2:1 mole ratio (equivalent to 1: 10 mass ratio) was identified to be optimal. This ratio was adopted for the preparation of dry powder formulation for pulmonary delivery, with mannitol used as bulking excipient. Spherical particles with mass median aerodynamic diameter (MMAD) of around 5 µm were produced by spray drying. The aerosol performance of the spray dried powder was moderate, as evaluated by the Next Generation Impactor (NGI), with emitted fraction and fine particle fraction of above 70 % and 45 %, respectively. The circular dichroism spectra revealed that both D-LAK peptides retained their secondary structure after spray drying, and the antibacterial effect of the combination against the MDR Mtb clinical isolates was successfully preserved. The combination was found to be effective against MDR Mtb isolates with KatG or InhA mutations. Overall, the synergistic combination of INH with D-LAK peptide formulated as inhaled dry powder offers a new therapeutic approach against MDR-TB.

Correlation between serum isoniazid concentration and therapeutic response in patients of pulmonary tuberculosis in Central India: A prospective observational study

BACKGROUND

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis is one of the top ten causes of death worldwide. Isoniazid (INH) is an important component of anti-tuberculosis therapy (ATT). Low isoniazid levels can serve as a risk factor for the development of treatment failure, relapse of disease and acquired secondary resistance. Hence, serum level of isoniazid becomes a critical factor in determining the treatment outcome of patients on ATT. This study aimed to evaluate the correlation between serum isoniazid concentration and therapeutic response in patients of pulmonary tuberculosis in Central India.

METHODS

This was a prospective single cohort observational study conducted at a tertiary care hospital. Therapeutic response in newly diagnosed patients of pulmonary TB was determined based the microbiological, clinical and radiological parameters. Serum INH levels were estimated based on a spectrophotometric method using nano-spectrophotometer.

RESULTS

In this study, patients had a significant improvement in treatment outcome as evident by a significant decrease in the TB score I at end of IP (p = 0.001) and a significant decline in the Timika score at end of CP (p = 0.001). Although all patients converted to sputum negative at end of CP, 20% remained positive at end of IP. Lower INH levels were seen in 13.3% of the study population. Higher INH levels were observed in sputum converters, patients with low TB score I and low Timika score, although no statistically significant difference was noted (p > 0.05).

CONCLUSION

In this study, we could not find any statistically significant association between serum INH levels and therapeutic outcome of the patients. Further studies on a larger population could provide better understanding about the prevalence of low serum isoniazid levels among the Indian population and establish its relationship with therapeutic outcome. Also, the usage of a comparatively less expensive spectrophotometric method of analysis makes this feasible in almost every district hospital without the need of high-performance liquid chromatography which is costlier and needs more expertise.

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.

Prevalence of Mycobacterium tuberculosis mutations associated with isoniazid and rifampicin resistance: A systematic review and meta-analysis

Tuberculosis (TB) is still one of the leading causes of worldwide death, especially following the emergence of strains resistant to isoniazid (INH) and rifampicin (RIF). This study aimed to systematically review published articles focusing on the prevalence of INH and/or RIF resistance-associated mutations of Mycobacterium tuberculosis isolates in recent years. Literature databases were searched using appropriate keywords. The data of the included studies were extracted and used for a random-effects model meta-analysis. Of the initial 1442 studies, 29 were finally eligible to be included in the review. The overall resistance to INH and RIF was about 17.2% and 7.3%, respectively. There was no difference between the frequency of INH and RIF resistance using different phenotypic or genotypic methods. The INH and/or RIF resistance was higher in Asia. The S315T mutation in KatG (23.7 %), C-15 T in InhA (10.7 %), and S531L in RpoB (13.5 %) were the most prevalent mutations. Altogether, the results showed that due to S531L in RpoB, S315T in KatG, and C-15 T in InhA mutations INH- and RIF-resistant M. tuberculosis isolates were widely distributed. Thus, it would be diagnostically and epidemiologically beneficial to track these gene mutations among resistant isolates.

Molecular Characterization of Mutations in Isoniazid- and Rifampicin-Resistant Mycobacterium tuberculosis Isolated in Thailand

The control of drug-resistant tuberculosis (TB) is a major challenge. The frequency and mutation characteristics indicate the efficiency of molecular tests for the rapid detection of TB drug resistance. This study examined the existence of katG and inhA mutations for isoniazid (INH) resistance and rpoB mutations for rifampicin (RFP) resistance. In total, 178 drug-resistant Mycobacterium tuberculosis (MTB) isolates were analyzed. Mutations in katG encoding and inhA regulatory regions were detected in 136/168 (81.0%) and 29/168 (17.3%), respectively, with the most prominent mutation of Ser315Thr substitution in katG in 126/168 (75.0%), and -15 C to T substitution in the regulatory region of the inhA (26/168; 15.5%). Two distinct katG mutations (Tyr337Cys, 1003InsG) were identified. Of 125 RFP-resistant isolates, 118 (94.4%) carried mutations affecting the 81-bp RFP resistance-determining region, with the most commonly affected codons 450, 445, and 435 identified in 74 (59.2%), 26 (20.8%), and 12 (9.6%) isolates, respectively. Genetic mutations were highly associated with phenotypic INH and RFP resistance, and the majority shared similarities with those reported in previous studies in Thailand and other Asian countries. These data are useful for guiding the use and improvement of molecular tests for TB drug resistance.

Artificial Intelligence and Machine Learning for Lead-to-Candidate Decision-Making and Beyond

The use of artificial intelligence (AI) and machine learning (ML) in pharmaceutical research and development has to date focused on research: target identification; docking-, fragment-, and motif-based generation of compound libraries; modeling of synthesis feasibility; rank-ordering likely hits according to structural and chemometric similarity to compounds having known activity and affinity to the target(s); optimizing a smaller library for synthesis and high-throughput screening; and combining evidence from screening to support hit-to-lead decisions. Applying AI/ML methods to lead optimization and lead-to-candidate (L2C) decision-making has shown slower progress, especially regarding predicting absorption, distribution, metabolism, excretion, and toxicology properties. The present review surveys reasons why this is so, reports progress that has occurred in recent years, and summarizes some of the issues that remain. Effective AI/ML tools to derisk L2C and later phases of development are important to accelerate the pharmaceutical development process, ameliorate escalating development costs, and achieve greater success rates.

The pathogenic mechanism of Mycobacterium tuberculosis: implication for new drug development

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a tenacious pathogen that has latently infected one third of the world's population. However, conventional TB treatment regimens are no longer sufficient to tackle the growing threat of drug resistance, stimulating the development of innovative anti-tuberculosis agents, with special emphasis on new protein targets. The Mtb genome encodes ~4000 predicted proteins, among which many enzymes participate in various cellular metabolisms. For example, more than 200 proteins are involved in fatty acid biosynthesis, which assists in the construction of the cell envelope, and is closely related to the pathogenesis and resistance of mycobacteria. Here we review several essential enzymes responsible for fatty acid and nucleotide biosynthesis, cellular metabolism of lipids or amino acids, energy utilization, and metal uptake. These include InhA, MmpL3, MmaA4, PcaA, CmaA1, CmaA2, isocitrate lyases (ICLs), pantothenate synthase (PS), Lysine-ε amino transferase (LAT), LeuD, IdeR, KatG, Rv1098c, and PyrG. In addition, we summarize the role of the transcriptional regulator PhoP which may regulate the expression of more than 110 genes, and the essential biosynthesis enzyme glutamine synthetase (GlnA1). All these enzymes are either validated drug targets or promising target candidates, with drugs targeting ICLs and LAT expected to solve the problem of persistent TB infection. To better understand how anti-tuberculosis drugs act on these proteins, their structures and the structure-based drug/inhibitor designs are discussed. Overall, this investigation should provide guidance and support for current and future pharmaceutical development efforts against mycobacterial pathogenesis.

High-Throughput Variant Detection Using a Color-Mixing Strategy

Many diseases are related to multiple genetic alterations along a single gene. Probing for highly multiple (>10) variants in a single quantitative PCR tube is not possible because of a limited number of fluorescence channels and one variant per channel, so many more tubes are needed. Herein, a novel color-mixing strategy that uses fluorescence combinations as digital color codes to probe multiple variants simultaneously was experimentally validated. The color-mixing strategy relies on a simple intratube assay that can probe for 15 variants as part of an intertube assay that can probe for an exponentially increased number of variants. This strategy is achieved by using multiplex double-stranded toehold probes modified with fluorophores and quenchers; the probes are designed to be quenched or luminous after binding to wild-type or variant templates. The color-mixing strategy was used to probe for 21 pathogenic variants in thalassemia and to distinguish between heterozygous and homozygous variants in six tubes, with a specificity of 99% and a sensitivity of 94%. To support tuberculosis diagnosis, the same strategy was applied to simultaneously probe in Mycobacterium tuberculosis for rifampicin-resistance mutations occurring within one 81-bp region and one 48-bp region in the rpoB gene, plus five isoniazid-resistance mutations in the inhA and katG genes.

Detection and characterization of mutations in genes related to isoniazid resistance in Mycobacterium tuberculosis clinical isolates from Iran

BACKGROUND

The global rise in drug-resistant Mycobacterium tuberculosis (M.tb), and especially the significant prevalence of isoniazid (INH)-resistance constitute a significant challenge to global health. Therefore, the present study aimed to investigate mutations in prevalent gene loci-involved in INH-resistance phenotype-among M.tb clinical isolates from southwestern Iran.

METHODS

Drug susceptibility testing (DST) was performed using the conventional proportional method on confirmed 6620 M.tb clinical isolates, and in total, 15 INH-resistant and 18 INH-susceptible isolates were included in the study. Fragments of six genetic loci most related to INH-resistance (katG, inhA promoter, furA, kasA, ndh, oxyR-ahpC intergenic region) were PCR-amplified and sequenced. Mutations were explored by pairwise alignment with the M.tb H37Rv genome.

RESULTS

The analysis of gene loci revealed 13 distinct mutations in INH-resistant isolates. 60% (n = 9) of the INH-resistant isolates had mutations in katG, with codon 315 predominately (53.3%, n = 8). Mutation at InhA - 15 was found in 20% (n = 3) of resistant isolates. 26.7% (n = 4) of the INH-resistant isolates had kasA mutations, of which G269S substitution was the most common (20%, n = 3). The percentage of mutations in furA, oxyR-ahpC and ndh was 6.7% (n = 1), 46.7% (n = 7), and 20% (n = 3), respectively. Of the mutations detected in ndh and oxyR-ahpC, 5 were also observed in INH-susceptible isolates. This study revealed seven novel mutations, four of which were exclusively in resistant isolates.

CONCLUSIONS

This study supports the usefulness of katG and inhA mutations as a predictive molecular marker for INH resistance. Co-detection of katG S315 and inhA-15 mutations identified 73.3% (11 out of 15 isolates) of INH-resistant isolates.

Whole-Genome Sequencing to Identify Missed Rifampicin and Isoniazid Resistance Among Tuberculosis Isolates-Chennai, India, 2013-2016

India has a high burden of drug-resistant tuberculosis (DR TB) and many cases go undetected by current drug susceptibility tests (DSTs). This study was conducted to identify rifampicin (RIF) and isoniazid (INH) resistance associated genetic mutations undetected by current clinical diagnostics amongst persons with DR TB in Chennai, India. Retrospectively stored 166 DR TB isolates during 2013–2016 were retrieved and cultured in Löwenstein-Jensen medium. Whole genome sequencing (WGS) and MGIT DST for RIF and INH were performed. Discordant genotypic and phenotypic sensitivity results were repeated for confirmation and the discrepant results considered final. Further, drug resistance-conferring mutations identified through WGS were analyzed for their presence as targets in current WHO-recommended molecular diagnostics. WGS detected additional mutations for rifampicin and isoniazid resistance than WHO-endorsed line probe assays. For RIF, WGS was able to identify an additional 10% (15/146) of rpoB mutant isolates associated with borderline rifampicin resistance compared to MGIT DST. WGS could detect additional DR TB cases than commercially available and WHO-endorsed molecular DST tests. WGS results reiterate the importance of the recent WHO revised critical concentrations of current MGIT DST to detect low-level resistance to rifampicin. WGS may help inform effective treatment selection for persons at risk of, or diagnosed with, DR TB.

Investigating the effect of an identified mutation within a critical site of PAS domain of WalK protein in a vancomycin-intermediate resistant Staphylococcus aureus by computational approaches

Background

Vancomycin-intermediate resistant Staphylococcus aureus (VISA) is becoming a common cause of nosocomial infections worldwide. VISA isolates are developed by unclear molecular mechanisms via mutations in several genes, including walKR. Although studies have verified some of these mutations, there are a few studies that pay attention to the importance of molecular modelling of mutations.

Method

For genomic and transcriptomic comparisons in a laboratory-derived VISA strain and its parental strain, Sanger sequencing and reverse transcriptase quantitative PCR (RT-qPCR) methods were used, respectively. After structural protein mapping of the detected mutation, mutation effects were analyzed using molecular computational approaches and crystal structures of related proteins.

Results

A mutation WalK-H364R was occurred in a functional zinc ion coordinating residue within the PAS domain in the VISA strain. WalK-H364R was predicted to destabilize protein and decrease WalK interactions with proteins and nucleic acids. The RT-qPCR method showed downregulation of walKR, WalKR-regulated autolysins, and agr locus.

Conclusion

Overall, WalK-H364R mutation within a critical metal-coordinating site was presumably related to the VISA development. We assume that the WalK-H364R mutation resulted in deleterious effects on protein, which was verified by walKR gene expression changes.. Therefore, molecular modelling provides detailed insight into the molecular mechanism of VISA development, in particular, where allelic replacement experiments are not readily available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02298-9.

Compensatory effects of M. tuberculosis rpoB mutations outside the rifampicin resistance-determining region

Mycobacterium tuberculosis has been observed to develop resistance to the frontline anti-tuberculosis drug rifampicin, primarily through mutations in the rifampicin resistance-determining region (RRDR) of rpoB. While these mutations have been determined to confer a fitness cost, compensatory mutations in rpoA and rpoC that may enhance the fitness of resistant strains have been demonstrated. Recent genomic studies identified several rpoB non-RRDR mutations that co-occurred with RRDR mutations in clinical isolates without rpoA/rpoC mutations and may confer fitness compensation. In this study, we identified 33 evolutionarily convergent rpoB non-RRDR mutations through phylogenomic analysis of public genomic data for clinical M. tuberculosis isolates. We found that none of these mutations, except V170F and I491F, can cause rifampin resistance in Mycolicibacterium smegmatis. The compensatory effects of five representative mutations across rpoB were evaluated by an in vitro competition assay, through which we observed that each of these mutations can significantly improve the relative fitness of the initial S450L mutant (0.97–1.08 vs 0.87). Furthermore, we observed that the decreased RNAP transcription efficiency introduced by S450L was significantly alleviated by each of the five mutations. Structural analysis indicated that the fitness compensation observed for the non-RRDR mutations might be achieved by modification of the RpoB active centre or by changes in interactions between RNAP subunits. Our results provide experimental evidence supporting that compensatory effects are exerted by several rpoB non-RRDR mutations, which could be utilized as additional molecular markers for predicting the fitness of clinical rifampin-resistant M. tuberculosis strains.

Label-Free Comparative Proteomics of Differentially Expressed Mycobacterium tuberculosis Protein in Rifampicin-Related Drug-Resistant Strains

Rifampicin (RIF) is one of the most important first-line anti-tuberculosis (TB) drugs, and more than 90% of RIF-resistant (RR) Mycobacterium tuberculosis clinical isolates belong to multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB. In order to identify specific candidate target proteins as diagnostic markers or drug targets, differential protein expression between drug-sensitive (DS) and drug-resistant (DR) strains remains to be investigated. In the present study, a label-free, quantitative proteomics technique was performed to compare the proteome of DS, RR, MDR, and XDR clinical strains. We found iniC, Rv2141c, folB, and Rv2561 were up-regulated in both RR and MDR strains, while fadE9, espB, espL, esxK, and Rv3175 were down-regulated in the three DR strains when compared to the DS strain. In addition, lprF, mce2R, mce2B, and Rv2627c were specifically expressed in the three DR strains, and 41 proteins were not detected in the DS strain. Functional category showed that these differentially expressed proteins were mainly involved in the cell wall and cell processes. When compared to the RR strain, Rv2272, smtB, lpqB, icd1, and folK were up-regulated, while esxK, PPE19, Rv1534, rpmI, ureA, tpx, mpt64, frr, Rv3678c, esxB, esxA, and espL were down-regulated in both MDR and XDR strains. Additionally, nrp, PPE3, mntH, Rv1188, Rv1473, nadB, PPE36, and sseA were specifically expressed in both MDR and XDR strains, whereas 292 proteins were not identified when compared to the RR strain. When compared between MDR and XDR strains, 52 proteins were up-regulated, while 45 proteins were down-regulated in the XDR strain. 316 proteins were especially expressed in the XDR strain, while 92 proteins were especially detected in the MDR strain. Protein interaction networks further revealed the mechanism of their involvement in virulence and drug resistance. Therefore, these differentially expressed proteins are of great significance for exploring effective control strategies of DR-TB.

Tryptophan Operon Diversity Reveals Evolutionary Trends among Geographically Disparate Chlamydia trachomatis Ocular and Urogenital Strains Affecting Tryptophan Repressor and Synthase Function

The obligate intracellular pathogen Chlamydia trachomatis (Ct) is the leading cause of bacterial sexually transmitted infections and blindness globally. To date, Ct urogenital strains are considered tryptophan prototrophs, utilizing indole for tryptophan synthesis within a closed-conformation tetramer comprised of two α (TrpA)- and two β (TrpB)-subunits. In contrast, ocular strains are auxotrophs due to mutations in TrpA, relying on host tryptophan pools for survival. It has been speculated that there is strong selective pressure for urogenital strains to maintain a functional operon. Here, we performed genetic, phylogenetic, and novel functional modeling analyses of 595 geographically diverse Ct ocular, urethral, vaginal, and rectal strains with complete operon sequences. We found that ocular and urogenital, but not lymphogranuloma venereum, TrpA-coding sequences were under positive selection. However, vaginal and urethral strains exhibited greater nucleotide diversity and a higher ratio of nonsynonymous to synonymous substitutions [Pi(a)/Pi(s)] than ocular strains, suggesting a more rapid evolution of beneficial mutations. We also identified nonsynonymous amino acid changes for an ocular isolate with a urogenital backbone in the intergenic region between TrpR and TrpB at the exact binding site for YtgR-the only known iron-dependent transcription factor in Chlamydia-indicating that selective pressure has disabled the response to fluctuating iron levels. In silico effects on protein stability, ligand-binding affinity, and tryptophan repressor (TrpR) affinity for single-stranded DNA (ssDNA) measured by calculating free energy changes (ΔΔG) between Ct reference and mutant tryptophan operon proteins were also analyzed. We found that tryptophan synthase function was likely suboptimal compared to other bacterial tryptophan prototrophs and that a diversity of urogenital strain mutations rendered the synthase nonfunctional or inefficient. The novel mutations identified here affected active sites in an orthosteric manner but also hindered α- and β-subunit allosteric interactions from distant sites, reducing efficiency of the tryptophan synthase. Importantly, strains with mutant proteins were inclined toward energy conservation by exhibiting an altered affinity for their respective ligands compared to reference strains, indicating greater fitness. This is not surprising as l-tryptophan is one of the most energetically costly amino acids to synthesize. Mutations in the tryptophan repressor gene (trpR) among urogenital strains were similarly detrimental to function. Our findings indicate that urogenital strains are evolving more rapidly than previously recognized with mutations that impact tryptophan operon function in a manner that is energetically beneficial, providing a novel host-pathogen evolutionary mechanism for intracellular survival.IMPORTANCE Chlamydia trachomatis (Ct) is a major global public health concern causing sexually transmitted and ocular infections affecting over 130 million and 260 million people, respectively. Sequelae include infertility, preterm birth, ectopic pregnancy, and blindness. Ct relies on available host tryptophan pools and/or substrates to synthesize tryptophan to survive. Urogenital strains synthesize tryptophan from indole using their intact tryptophan synthase (TS). Ocular strains contain a trpA frameshift mutation that encodes a truncated TrpA with loss of TS function. We found that TS function is likely suboptimal compared to other tryptophan prototrophs and that urogenital stains contain diverse mutations that render TS nonfunctional/inefficient, evolve more rapidly than previously recognized, and impact operon function in a manner that is energetically beneficial, providing an alternative host-pathogen evolutionary mechanism for intracellular survival. Our research has broad scientific appeal since our approach can be applied to other bacteria that may explain evolution/survival in host-pathogen interactions.

Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.

Mechanisms and detection methods of Mycobacterium tuberculosis rifampicin resistance: The phenomenon of drug resistance is complex

Tuberculosis (TB) is an infectious disease that poses a serious threat to human health. Rifampin (RIF) is an important first-line anti-TB drug, and rifampin resistance (RIF-R) is a key factor in formulating treatment regimen and evaluating the prognosis of TB. Compared with other drugs resistance, the RIF-R mechanism of Mycobacterium tuberculosis (M. tuberculosis) is one of the clearest, which is mainly caused by RIF resistance-related mutations in the rpoB gene. This provides a convenient condition for developing rapid detection methods, and also an ideal object for studying the general drug resistance mechanisms of M. tuberculosis. This review focuses on the mechanisms that influence the RIF resistance of M. tuberculosis and related detection methods. Besides the mutations in rpoB, M. tuberculosis can decrease the amount of drugs entering the cells, enhance the drugs efflux, and be heterogeneous RIF susceptibility to resist drug pressure. Based on the results of current researches, many genes participate in influencing the susceptibility to RIF, which indicates the phenomenon of M. tuberculosis drug resistance is very complex.

Abattoir survey of bovine tuberculosis in tanta, centre of the Nile delta, with in silico analysis of gene mutations and protein-protein interactions of the involved mycobacteria

Bovine tuberculosis is a transboundary disease of high economic and public health burden worldwide. In this study, post-mortem examination of 750 cattle and buffalo in Tanta abattoir, Centre of the Nile Delta, revealed visible TB in 4% of animals and a true prevalence of 6.85% (95% CI: 5.3%-8.9%). Mycobacterial culture, histopathology and RT-PCR targeting all members of M. tuberculosis complex were performed, upon which 85%, 80% and 100% of each tested lesions were confirmed as TB, respectively. Mpb70-targeting PCR was conducted on ten RT-PCR positive samples for sequencing and identified nine Mycobacterium (M.) bovis strains and, interestingly, one M. tuberculosis (Mtb) strain from a buffalo. Bioinformatics tools were used for prediction of mutations, nucleotide polymorphisms, lineages, drug resistance and protein-protein interactions (PPI) of the sequenced strains. The Mtb strain was resistant to rifampicin, isoniazid and streptomycin, and to the best of our knowledge, this is the first report of multidrug resistant (MDR)-Mtb originating from buffaloes. Seven M. bovis strains were resistant to ethambutol and ethionamide. Such resistances were associated with KatG, rpoB, rpsL, embB and ethA genes mutations. Other mutations and nucleotide polymorphisms were also predicted, some are reported for the first time and require experimental work for validation. PPI revealed more interactions than what would be expected for a random set of proteins of similar size and had dense interactions between nodes that are biologically connected, as a group. Two M. bovis strains belonged to BOV AFRI lineage (Spoligotypes BOV 1; BOV 2) and eight strains belonged to East-Asian (Beijing) lineage. In conclusion, visible TB was prevalent in the study area, RT-PCR is the best to confirm the disease, MDR-Mtb is associated with buffalo TB, and mycobacteria of different lineages carry many resistance genes to chemotherapeutic agents used in treatment of human TB constituting a major public health risk.

Using cryo-EM to understand antimycobacterial resistance in the catalase-peroxidase (KatG) from Mycobacterium tuberculosis

Resolution advances in cryoelectron microscopy (cryo-EM) now offer the possibility to visualize structural effects of naturally occurring resistance mutations in proteins and also of understanding the binding mechanisms of small drug molecules. In Mycobacterium tuberculosis the multifunctional heme enzyme KatG is indispensable for activation of isoniazid (INH), a first-line pro-drug for treatment of tuberculosis. We present a cryo-EM methodology for structural and functional characterization of KatG and INH resistance variants. The cryo-EM structure of the 161 kDa KatG dimer in the presence of INH is reported to 2.7 Å resolution allowing the observation of potential INH binding sites. In addition, cryo-EM structures of two INH resistance variants, identified from clinical isolates, W107R and T275P, are reported. In combination with electronic absorbance spectroscopy our cryo-EM approach reveals how these resistance variants cause disorder in the heme environment preventing heme uptake and retention, providing insight into INH resistance.

•

A cryo-EM structure to 2.7 Å resolution of M. tuberculosis KatG with isoniazid

•

Cryo-EM is able to visualize multiple dynamic binding modes of isoniazid to KatG

•

Structural disorder in isoniazid resistance mutations is observed

•

Structural disorder of the resistance mutations results in the lack of heme retention

Structural analyses and classification of novel isoniazid resistance coupled mutational landscapes in Mycobacterium tuberculosis: a combined molecular docking and MD simulation study

Drug resistance in Mycobacterium tuberculosis has become a major challenge to the current regime of treatment as well as to the containment of the disease globally. The molecular and genetic studies identified frequently occurring point mutations in the virulent protein such as KatG of M. tuberculosis resulted in the development of isoniazid tolerance in the pathogen. This study aims to analyze the structural basis of the disease mutations available in the literature as well as to predict novel alteration in the KatG which may cause similar deleterious effects. Around 15 experimentally derived mutations were included in this study and pathogenic mutational landscapes containing 60 site-specific alterations were predicted using the available in silico techniques. The effects of these mutations on the stability of the protein were studied and an exhaustive docking study was conducted for each classified perturbations, which identify the highest changes in the binding energies in p.Meth255Ile among experimental and p.Ala222Arg in computationally predicted mutations. Furthermore, the structural effects on these substitutions were analyzed using the principles of molecular dynamic simulations each for a 100 ns time scale, which validated the interaction studies. The outcome of this study may enable the identification of the novel drug resistance-associated point mutations which were not previously reported and may contribute significantly in a variety of experimental studies as well as facilitate the process of drug design and discovery.Communicated by Ramaswamy H. Sarma.

Genomics, Computational Biology and Drug Discovery for Mycobacterial Infections: Fighting the Emergence of Resistance

Tuberculosis (TB) and leprosy are mycobacterial infections caused by Mycobacterium tuberculosis and Mycobacterium leprae respectively. These diseases continue to be endemic in developing countries where the cost of new medicines presents major challenges. The situation is further exacerbated by the emergence of resistance to many front-line antibiotics. A priority now is to design new antimycobacterials that are not only effective in combatting the diseases but are also less likely to give rise to resistance. In both these respects understanding the structure of drug targets in M. tuberculosis and M. leprae is crucial. In this review we describe structure-guided approaches to understanding the impacts of mutations that give rise to antimycobacterial resistance and the use of this information in the design of new medicines.

Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine

Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.

Structure-Based Screening of DNA GyraseB Inhibitors for Therapeutic Applications in Tuberculosis: a Pharmacoinformatics Study

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB) and considered as serious public health concern worldwide which kills approximately five thousand people every day. Therefore, TB drug development efforts are in gigantic need for identification of new potential chemical agents to eradicate TB from the society. The bacterial DNA gyrase B (GyrB) protein as an experimentally widely accepted effective drug target for the development of TB chemotherapeutics. In the present study, advanced pharmacoinformatics approaches were used to screen the Mcule database against the GyrB protein. Based on a number of chemometric parameters, five molecules were found to be crucial to inhibit the GyrB. A number of molecular binding interactions between the proposed inhibitors and important active site residues of GyrB were observed. The predicted drug-likeness properties of all molecules were indicated that compounds possess characteristics to be the drug-like candidates. The dynamic nature of each molecule was explored through the molecular dynamics (MD) simulation study. Various analyzing parameters from MD simulation trajectory have suggested rationality of the molecules to be potential GyrB inhibitor. Moreover, the binding free energy was calculated from the entire MD simulation trajectories highlighted greater binding free energy values for all newly identified compounds also substantiated the strong binding affection towards the GyrB in comparison to the novobiocin. Therefore, the proposed molecules might be considered as potential anti-TB chemical agents for future drug discovery purposes subjected to experimental validation. Graphical Abstract.

The mismatch repair system (mutS and mutL) in Acinetobacter baylyi ADP1

Background

Acinetobacter baylyi ADP1 is an ideal bacterial strain for high-throughput genetic analysis as the bacterium is naturally transformable. Thus, ADP1 can be used to investigate DNA mismatch repair, a mechanism for repairing mismatched bases. We used the mutS deletion mutant (XH439) and mutL deletion mutant (XH440), and constructed a mutS mutL double deletion mutant (XH441) to investigate the role of the mismatch repair system in A. baylyi.

Results

We determined the survival rates after UV irradiation and measured the mutation frequencies, rates and spectra of wild-type ADP1 and mutSL mutant via rifampin resistance assay (Rif^R assay) and experimental evolution. In addition, transformation efficiencies of genomic DNA in ADP1 and its three mutants were determined. Lastly, the relative growth rates of the wild type strain, three constructed deletion mutants, as well as the rifampin resistant mutants obtained from Rif^R assays, were measured. All three mutants had higher survival rates after UV irradiation than wild type, especially the double deletion mutant. Three mutants showed higher mutation frequencies than ADP1 and favored transition mutations in Rif^R assay. All three mutants showed increased mutation rates in the experimental evolution. However, only XH439 and XH441 had higher mutation rates than the wild type strain in Rif^R assay. XH441 showed higher transformation efficiency than XH438 when donor DNA harbored transition mutations. All three mutants showed higher growth rates than wild-type, and these four strains displayed higher growth rates than almost all their rpoB mutants. The growth rate results showed different amino acid mutations in rpoB resulted in different extents of reduction in the fitness of rifampin resistant mutants. However, the fitness cost brought by the same mutation did not vary with strain background.

Conclusions

We demonstrated that inactivation of both mutS and mutL increased the mutation rates and frequencies in A. baylyi, which would contribute to the evolution and acquirement of rifampicin resistance. The mutS deletion is also implicated in increased mutation rates and frequencies, suggesting that MutL may be activated even in the absence of mutS. The correlation between fitness cost and rifampin resistance mutations in A. baylyi is firstly established.

Association Between the Phenotype and Genotype of Isoniazid Resistance Among Mycobacterium tuberculosis Isolates in Thailand

Purpose

The emergence of isoniazid-resistant tuberculosis (HR-TB) is a global public health problem, causing treatment failure and high mortality rates. This study aimed to determine the minimal inhibitory concentration (MIC) of isoniazid and detect the gene mutation in HR-TB and any association between the level of isoniazid resistance and gene mutation.

Methods

We collected 74 clinical HR-TB isolates from two tertiary-care centers in Thailand. MICs were established using broth macrodilution. A line probe assay (LPA) was used to detect gene mutations that confer resistance to isoniazid, rifampicin, aminoglycosides, and fluoroquinolones.

Results

Sixty-one (82.4%) isolates were monoresistant to isoniazid and 44 (72.1%) were highly resistant to isoniazid. From the clinical isolates, the range of isoniazid MICs was 0.4–16 μg/mL. The katG S315T gene mutation was the prominent mutation in both isoniazid-monoresistant TB (70.5%) and multidrug-resistant TB (72.7%) isolates. The positive predictive value (PPV) of katG was 100% in detecting high levels of isoniazid resistance. The PPV of the inhA mutation was 93.8% in detecting low levels of isoniazid resistance. Five isolates (6.8%) exhibited low-level phenotypic resistance, whereas an LPA failed to detect an isoniazid gene mutation. Our study found one HR-TB isolate with a gyrA fluoroquinolone-resistant gene mutation.

Conclusion

Most HR-TB isolates had high isoniazid-resistance levels associated with the katG gene mutation. High-dose isoniazid should be used with caution in patients with HR-TB. Early detection of drug resistance by genotypic assay can help determine an appropriate regimen.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.