Genome-wide mutational biases fuel transcriptional diversity in the Mycobacterium tuberculosis complex

Single nucleotide variation catalog from clinical isolates mapped on tertiary and quaternary structures of ESX-1-related proteins reveals critical regions as putative Mtb therapeutic targets

Proteins encoded by the ESX-1 genes of interest are essential for full virulence in all Mycobacterium tuberculosis complex (Mtbc) lineages, the pathogens causing the highest mortality worldwide. Identifying critical regions in these ESX-1-related proteins could provide preventive or therapeutic targets for Mtb infection, the game changer needed for tuberculosis control. We analyzed a compendium of whole genome sequences of clinical Mtb isolates from all lineages from >32,000 patients and identified single nucleotide polymorphisms. When mutations corresponding to all non-synonymous single nucleotide polymorphisms were mapped on structural models of the ESX-1 proteins, fully conserved regions emerged. Some could be assigned to known quaternary structures, whereas others could be predicted to be involved in yet-to-be-discovered interactions. Some mutants had clonally expanded (found in >1% of the isolates); these mutants were mostly located at the surface of globular domains, remote from known intra- and inter-molecular protein-protein interactions. Fully conserved intrinsically disordered regions of proteins were found, suggesting that these regions are crucial for the pathogenicity of the Mtbc. Altogether, our findings highlight fully conserved regions of proteins as attractive vaccine antigens and drug targets to control Mtb virulence. Extending this approach to the whole Mtb genome as well as other microorganisms will enhance vaccine development for various pathogens.

IMPORTANCE

We mapped all non-synonymous single nucleotide polymorphisms onto each of the experimental and predicted ESX-1 proteins' structural models and inspected their placement. Varying sizes of conserved regions were found. Next, we analyzed predicted intrinsically disordered regions within our set of proteins, finding two putative long stretches that are fully conserved, and discussed their potential essential role in immunological recognition. Combined, our findings highlight new targets for interfering with Mycobacterium tuberculosis complex virulence.

Expression of a unique M. tuberculosis DNA MTase Rv1509 in M. smegmatis alters the gene expression pattern and enhances virulence

Mycobacterium tuberculosis (M. tb) genome encompasses 4,173 genes, about a quarter of which remain uncharacterized and hypothetical. Considering the current limitations associated with the diagnosis and treatment of tuberculosis, it is imperative to comprehend the pathomechanism of the disease and host-pathogen interactions to identify new drug targets for intervention strategies. Using in-silico comparative genome analysis, we identified one of the M. tb genes, Rv1509, as a signature protein exclusively present in M. tb. To explore the role of Rv1509, a likely methyl transferase, we constructed a knock-in Mycobacterium smegmatis (M. smegmatis) constitutively expressing Rv1509 (Ms_Rv1509). The Ms_Rv1509 led to differential expression of many transcriptional regulator genes as assessed by RNA-seq analysis. Further, in-vitro and in-vivo studies demonstrated an enhanced survival of Ms_Rv1509 inside the host macrophages. Ms_Rv1509 also promoted phagolysosomal escape inside macrophages to boost bacterial replication and dissemination. In-vivo infection studies revealed that Ms_Rv1509 survives better than BCG and causes pathological manifestations in the pancreas after intraperitoneal infection. Long-time survival of Ms_Rv1509 resulted in lymphocyte migration, increased T regulatory cells, giant cell formation, and likely granuloma formation in the pancreas, pointing toward the role of Rv1509 in M. tb pathogenesis.

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.

Demonstrating the utility of the ex vivo murine mycobacterial growth inhibition assay (MGIA) for high-throughput screening of tuberculosis vaccine candidates against multiple Mycobacterium tuberculosis complex strains

Human tuberculosis (TB) is caused by various members of the Mycobacterium tuberculosis (Mtb) complex. Differences in host response to infection have been reported, illustrative of a need to evaluate efficacy of novel vaccine candidates against multiple strains in preclinical studies. We previously showed that the murine lung and spleen direct mycobacterial growth inhibition assay (MGIA) can be used to assess control of ex vivo mycobacterial growth by host cells. The number of mice required for the assay is significantly lower than in vivo studies, facilitating testing of multiple strains and/or the incorporation of other cellular analyses. Here, we provide proof-of-concept that the murine MGIA can be applied to evaluate vaccine-induced protection against multiple Mtb clinical isolates. Using an ancient and modern strain of the Mtb complex, we demonstrate that ex vivo bacillus Calmette-Guérin (BCG)-mediated mycobacterial growth inhibition recapitulates protection observed in the lung and spleen following in vivo infection of mice. Further, we provide the first report of cellular and transcriptional correlates of BCG-induced growth inhibition in the lung MGIA. The ex vivo MGIA represents a promising platform to gain early insight into vaccine performance against a collection of Mtb strains and improve preclinical evaluation of TB vaccine candidates.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Mycobacterium tuberculosis complex molecular networks and their regulation: Implications of strain heterogeneity on epigenetic diversity and transcriptome regulation

Tuberculosis has been a public health crisis since the 1900, which has caused the highest mortalities due to a single bacterial infection worldwide, that was recently further complicated by the Coronavirus disease 2019 pandemic. The causative agent of Tuberculosis, Mycobacterium tuberculosis, belongs to a genetically well-characterized family of strains known as the Mycobacterium tuberculosis complex, which has complicated progress made towards eradicating Tuberculosis due to pathogen-specific phenotypic differences in the members of this complex. Mycobacterium tuberculosis complex strains are genetically diverse human- and animal-adapted pathogens belonging to 7 lineages (Indo-Oceanic, East-Asian, East-African Indian, Euro-American, M. africanum West Africa 1, M. africanum West Africa 2 and Ethopia), respectively and the recently identified Lineage 8 and M. africanum Lineage 9. Genomic studies have revealed that Mycobacterium tuberculosis complex members are ∼99 % similar, however, due to selective pressure and adaptation to human host, they are prone to mutations that have resulted in development of drug resistance and phenotypic heterogeneity that impact strain virulence. Furthermore, members of the Mycobacterium tuberculosis complex have preferred geographic locations and possess unique phenotypic characteristics that is linked to their pathogenicity. Due to the recent advances in development next generation sequencing platforms, several studies have revealed epigenetic changes in genomic regions combined with "unique" gene regulatory mechanisms through non-coding RNAs that are responsible for strain-specific behaviour on in vitro and in vivo infection models. The current review provides up to date epigenetic patterns, gene regulation through non-coding RNAs, together with implications of these mechanisms in down-stream proteome and metabolome, which may be responsible for "unique" responses to infection by members of the Mycobacterium tuberculosis complex. Understanding lineage-specific molecular mechanisms during infection may provide novel drug targets and disease control measures towards World Health organization END-TB strategy.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis ( M. tb ), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.

Importance

Understanding mechanisms of resistance and tolerance in Mycobacterium tuberculosis ( M. tb ) can help us develop new treatments that capitalize on M. tb 's vulnerabilities. Here we used transcriptomics to study both the regulation of biofilm formation in clinical isolates as well as how those regulatory systems adapt to new environments. We find that closely related clinical populations have diverse strategies for growth under biofilm conditions, and that genetic background plays a large role in determining the trajectory of evolution. These results have implications for future treatment strategies that may be informed by our knowledge of the evolutionary constraints on strain(s) from an individual infection. This work provides new information about the mechanisms of biofilm formation in M. tb and outlines a framework for population level approaches for studying bacterial adaptation.

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore samples with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA - and suggest mutations that may warrant reclassification as associated with resistance.

Genomic analysis of Mycobacterium brumae sustains its nonpathogenic and immunogenic phenotype

Mycobacterium brumae is a rapid-growing, non-pathogenic Mycobacterium species, originally isolated from environmental and human samples in Barcelona, Spain. Mycobacterium brumae is not pathogenic and it's in vitro phenotype and immunogenic properties have been well characterized. However, the knowledge of its underlying genetic composition is still incomplete. In this study, we first describe the 4 Mb genome of the M. brumae type strain ATCC 51384^T assembling PacBio reads, and second, we assess the low intraspecies variability by comparing the type strain with Illumina reads from three additional strains. Mycobacterium brumae genome is composed of a circular chromosome with a high GC content of 69.2% and containing 3,791 CDSs, 97 pseudogenes, one prophage and no CRISPR loci. Mycobacterium brumae has shown no pathogenic potential in in vivo experiments, and our genomic analysis confirms its phylogenetic position with other non-pathogenic and rapid growing mycobacteria. Accordingly, we determined the absence of virulence-related genes, such as ESX-1 locus and most PE/PPE genes, among others. Although the immunogenic potential of M. brumae was proved to be as high as Mycobacterium bovis BCG, the only mycobacteria licensed to treat cancer, the genomic content of M. tuberculosis T cell and B cell antigens in M. brumae genome is considerably lower than those antigens present in M. bovis BCG genome. Overall, this work provides relevant genomic data on one of the species of the mycobacterial genus with high therapeutic potential.

Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity

OBJECTIVES

Mycobacterium tuberculosis (Mtb) infections result in a wide spectrum of clinical presentations but without proven Mtb genetic determinants. Herein, we hypothesized that the genetic features of Mtb clinical isolates, such as specific polymorphisms or microdiversity, may be linked to tuberculosis (TB) severity.

METHODS

A total of 234 patients with pulmonary TB (including 193 drug-susceptible and 14 monoresistant cases diagnosed between 2017 and 2020 and 27 multidrug-resistant cases diagnosed between 2010 and 2020) were stratified according to TB disease severity, and Mtb genetic features were explored using whole genome sequencing, including heterologous single-nucleotide polymorphism (SNP), calling to explore microdiversity. Finally, we performed a structural equation modeling analysis to relate TB severity to Mtb genetic features.

RESULTS

The clinical isolates from patients with mild TB carried mutations in genes associated with host-pathogen interaction, whereas those from patients with moderate/severe TB carried mutations associated with regulatory mechanisms. Genome-wide association study identified an SNP in the promoter of the gene coding for the virulence regulator espR, statistically associated with moderate/severe disease. Structural equation modeling and model comparisons indicated that TB severity was associated with the detection of Mtb microdiversity within clinical isolates and to the espR SNP.

CONCLUSION

Taken together, these results provide a new insight to better understand TB pathophysiology and could provide a new prognosis tool for pulmonary TB severity.

Transcriptional regulation and drug resistance in Mycobacterium tuberculosis

Bacterial drug resistance is one of the major challenges to present and future human health, as the continuous selection of multidrug resistant bacteria poses at serious risk the possibility to treat infectious diseases in the near future. One of the infection at higher risk to become incurable is tuberculosis, due to the few drugs available in the market against Mycobacterium tuberculosis. Drug resistance in this species is usually due to point mutations in the drug target or in proteins required to activate prodrugs. However, another interesting and underexplored aspect of bacterial physiology with important impact on drug susceptibility is represented by the changes in transcriptional regulation following drug exposure. The main regulators involved in this phenomenon in M. tuberculosis are the sigma factors, and regulators belonging to the WhiB, GntR, XRE, Mar and TetR families. Better understanding the impact of these regulators in survival to drug treatment might contribute to identify new drug targets and/or to design new strategies of intervention.

Rapid adaptation of a complex trait during experimental evolution of Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), is a leading cause of death due to infectious disease. TB is not traditionally associated with biofilms, but M. tb biofilms are linked with drug and immune tolerance and there is increasing recognition of their contribution to the recalcitrance of TB infections. Here, we used M. tb experimental evolution to investigate this complex phenotype and identify candidate loci controlling biofilm formation. We identified novel candidate loci, adding to our understanding of the genetic architecture underlying M. tb biofilm development. Under selective pressure to grow as a biofilm, regulatory mutations rapidly swept to fixation and were associated with changes in multiple traits, including extracellular matrix production, cell size, and growth rate. Genetic and phenotypic paths to enhanced biofilm growth varied according to the genetic background of the parent strain, suggesting that epistatic interactions are important in M. tb adaptation to changing environments.

Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection

SignificancePrevious attempts to identify the action of natural selection in the Mycobacterium tuberculosis complex (MTBC) were limited by sample size and averaging across time and lineages. We investigate changes in selective pressures across time for every single gene of the MTBC. We developed a methodology to analyze temporal signals of selection in a large dataset (∼5,000 complete genomes) and showed that 1) almost half of the genes seem to have been under positive selection at some point in time; 2) experimentally confirmed epitopes tend to accumulate more mutations in deeper branches than in external branches; and 3) temporal signals identify genes that were conserved in the past but under positive selection in the present, suggesting ongoing adaptation to the host.

Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome

MOTIVATION

Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.

RESULTS

Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.

AVAILABILITY AND IMPLEMENTATION

All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DNA Methyltransferase HsdM Induce Drug Resistance on Mycobacterium tuberculosis via Multiple Effects

Besides the genomic variants, epigenetic mechanisms such as DNA methylation also have an effect on drug resistance. This study aimed to investigate the methylomes of totally/extensively drug-resistant M. tuberculosis clinical isolates using the PacBio single-molecule real-time technology. The results showed they were almost the same as the pan-susceptible ones. Genetics and bioinformatics analysis confirmed three DNA methyltransferases-MamA, MamB, and HsdM. Moreover, anti-tuberculosis drug treatment did not change the methylomes. In addition, the knockout of the DNA methyltransferase hsdM gene in the extensively drug-resistant clinical isolate 11826 revealed that the motifs of GTAYN4ATC modified by HsdM were completely demethylated. Furthermore, the results of the methylated DNA target analysis found that HsdM was mainly involved in redox-related pathways, especially the prodrug isoniazid active protein KatG. HsdM also targeted three drug-targeted genes, eis, embB, and gyrA, and three drug transporters (Rv0194, Rv1410, and Rv1877), which mildly affected the drug susceptibility. The overexpression of HsdM in M. smegmatis increased the basal mutation rate. Our results suggested that DNA methyltransferase HsdM affected the drug resistance of M. tuberculosis by modulating the gene expression of redox, drug targets and transporters, and gene mutation.

Challenges in defining the functional, non-coding, expressed genome of members of the Mycobacterium tuberculosis complex

A definitive transcriptome atlas for the non-coding expressed elements of the members of the Mycobacterium tuberculosis complex (MTBC) does not exist. Incomplete lists of non-coding transcripts can be obtained for some of the reference genomes (e.g., M. tuberculosis H37Rv) but to what extent these transcripts have homologues in closely related species or even strains is not clear. This has implications for the analysis of transcriptomic data; non-coding parts of the transcriptome are often ignored in the absence of formal, reliable annotation. Here, we review the state of our knowledge of non-coding RNAs in pathogenic mycobacteria, emphasizing the disparities in the information included in commonly used databases. We then proceed to review ways of combining computational solutions for predicting the non-coding transcriptome with experiments that can help refine and confirm these predictions.

Dissecting Host-Pathogen Interactions in TB Using Systems-Based Omic Approaches

Tuberculosis (TB) is a devastating infectious disease that kills over a million people every year. There is an increasing burden of multi drug resistance (MDR) and extensively drug resistance (XDR) TB. New and improved therapies are urgently needed to overcome the limitations of current treatment. The causative agent, Mycobacterium tuberculosis (Mtb) is one of the most successful pathogens that can manipulate host cell environment for adaptation, evading immune defences, virulence, and pathogenesis of TB infection. Host-pathogen interaction is important to establish infection and it involves a complex set of processes. Metabolic cross talk between the host and pathogen is a facet of TB infection and has been an important topic of research where there is growing interest in developing therapies and drugs that target these interactions and metabolism of the pathogen in the host. Mtb scavenges multiple nutrient sources from the host and has adapted its metabolism to survive in the intracellular niche. Advancements in systems-based omic technologies have been successful to unravel host-pathogen interactions in TB. In this review we discuss the application and usefulness of omics in TB research that provides promising interventions for developing anti-TB therapies.

The Mycobacterial DNA Methyltransferase HsdM Decreases Intrinsic Isoniazid Susceptibility

Tuberculosis, caused by the pathogen Mycobacterium tuberculosis, is a serious infectious disease worldwide. Multidrug-resistant TB (MDR-TB) remains a global problem, and the understanding of this resistance is incomplete. Studies suggested that DNA methylation promotes bacterial adaptability to antibiotic treatment, but the role of mycobacterial HsdM in drug susceptibility has not been explored. Here, we constructed an inactivated Mycobacterium bovis (BCG) strain, ΔhsdM. ΔhsdM shows growth advantages over wild-type BCG under isoniazid treatment and hypoxia-induced stress. Using high-precision PacBio single-molecule real-time sequencing to compare the ΔhsdM and BCG methylomes, we identified 219 methylated HsdM substrates. Bioinformatics analysis showed that most HsdM-modified genes were enriched in respiration- and energy-related pathways. qPCR showed that HsdM-modified genes directly affected their own transcription, indicating an altered redox regulation. The use of the latent Wayne model revealed that ΔhsdM had growth advantages over wild-type BCG and that HsdM regulated trcR mRNA levels, which may be crucial in regulating transition from latency to reactivation. We found that HsdM regulated corresponding transcription levels via gene methylation; thus, altering the mycobacterial redox status and decreasing the bacterial susceptibility to isoniazid, which is closely correlated with the redox status. Our results provide valuable insight into DNA methylation on drug susceptibility.

Role of Epistasis in Amikacin, Kanamycin, Bedaquiline, and Clofazimine Resistance in Mycobacterium tuberculosis Complex

Antibiotic resistance among bacterial pathogens poses a major global health threat. Mycobacterium tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the low growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e., systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with an LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).

Gramtools enables multiscale variation analysis with genome graphs

Genome graphs allow very general representations of genetic variation; depending on the model and implementation, variation at different length-scales (single nucleotide polymorphisms (SNPs), structural variants) and on different sequence backgrounds can be incorporated with different levels of transparency. We implement a model which handles this multiscale variation and develop a JSON extension of VCF (jVCF) allowing for variant calls on multiple references, both implemented in our software gramtools. We find gramtools outperforms existing methods for genotyping SNPs overlapping large deletions in M. tuberculosis and is able to genotype on multiple alternate backgrounds in P. falciparum, revealing previously hidden recombination.

Toward a Phage Cocktail for Tuberculosis: Susceptibility and Tuberculocidal Action of Mycobacteriophages against Diverse Mycobacterium tuberculosis Strains

The global health burden of human tuberculosis (TB) and the widespread antibiotic resistance of its causative agent Mycobacterium tuberculosis warrant new strategies for TB control. The successful use of a bacteriophage cocktail to treat a Mycobacterium abscessus infection suggests that phages could play a role in tuberculosis therapy. To assemble a phage cocktail with optimal therapeutic potential for tuberculosis, we have explored mycobacteriophage diversity to identify phages that demonstrate tuberculocidal activity and determined the phage infection profiles for a diverse set of strains spanning the major lineages of human-adapted strains of the Mycobacterium tuberculosis complex. Using a combination of genome engineering and bacteriophage genetics, we have assembled a five-phage cocktail that minimizes the emergence of phage resistance and cross-resistance to multiple phages, and which efficiently kills the M. tuberculosis strains tested. Furthermore, these phages function without antagonizing antibiotic effectiveness, and infect both isoniazid-resistant and -sensitive strains.IMPORTANCE Tuberculosis kills 1.5 million people each year, and resistance to commonly used antibiotics contributes to treatment failures. The therapeutic potential of bacteriophages against Mycobacterium tuberculosis offers prospects for shortening antibiotic regimens, provides new tools for treating multiple drug-resistant (MDR)-TB and extensively drug-resistant (XDR)-TB infections, and protects newly developed antibiotics against rapidly emerging resistance to them. Identifying a suitable suite of phages active against diverse M. tuberculosis isolates circumvents many of the barriers to initiating clinical evaluation of phages as part of the arsenal of antituberculosis therapeutics.

Stepwise pathogenic evolution of Mycobacterium abscessus

Although almost all mycobacterial species are saprophytic environmental organisms, a few, such as Mycobacterium tuberculosis, have evolved to cause transmissible human infection. By analyzing the recent emergence and spread of the environmental organism M. abscessus through the global cystic fibrosis population, we have defined key, generalizable steps involved in the pathogenic evolution of mycobacteria. We show that epigenetic modifiers, acquired through horizontal gene transfer, cause saltational increases in the pathogenic potential of specific environmental clones. Allopatric parallel evolution during chronic lung infection then promotes rapid increases in virulence through mutations in a discrete gene network; these mutations enhance growth within macrophages but impair fomite survival. As a consequence, we observe constrained pathogenic evolution while person-to-person transmission remains indirect, but postulate accelerated pathogenic adaptation once direct transmission is possible, as observed for M. tuberculosis Our findings indicate how key interventions, such as early treatment and cross-infection control, might restrict the spread of existing mycobacterial pathogens and prevent new, emergent ones.

Integrated characterization of SARS-CoV-2 genome, microbiome, antibiotic resistance and host response from single throat swabs

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, poses a severe threat to humanity. Rapid and comprehensive analysis of both pathogen and host sequencing data is critical to track infection and inform therapies. In this study, we performed unbiased metatranscriptomic analysis of clinical samples from COVID-19 patients using a recently developed RNA-seq library construction method (TRACE-seq), which utilizes tagmentation activity of Tn5 on RNA/DNA hybrids. This approach avoids the laborious and time-consuming steps in traditional RNA-seq procedure, and hence is fast, sensitive, and convenient. We demonstrated that TRACE-seq allowed integrated characterization of full genome information of SARS-CoV-2, putative pathogens causing coinfection, antibiotic resistance, and host response from single throat swabs. We believe that the integrated information will deepen our understanding of pathogenesis and improve diagnostic accuracy for infectious diseases.

In-host population dynamics of Mycobacterium tuberculosis complex during active disease

Tuberculosis (TB) is a leading cause of death globally. Understanding the population dynamics of TB’s causative agent Mycobacterium tuberculosis complex (Mtbc) in-host is vital for understanding the efficacy of antibiotic treatment. We use longitudinally collected clinical Mtbc isolates that underwent Whole-Genome Sequencing from the sputa of 200 patients to investigate Mtbc diversity during the course of active TB disease after excluding 107 cases suspected of reinfection, mixed infection or contamination. Of the 178/200 patients with persistent clonal infection >2 months, 27 developed new resistance mutations between sampling with 20/27 occurring in patients with pre-existing resistance. Low abundance resistance variants at a purity of ≥19% in the first isolate predict fixation in the subsequent sample. We identify significant in-host variation in 27 genes, including antibiotic resistance genes, metabolic genes and genes known to modulate host innate immunity and confirm several to be under positive selection by assessing phylogenetic convergence across a genetically diverse sample of 20,352 isolates.

Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery

Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.

Drivers and sites of diversity in the DNA adenine methylomes of 93 Mycobacterium tuberculosis complex clinical isolates

This study assembles DNA adenine methylomes for 93 Mycobacterium tuberculosis complex (MTBC) isolates from seven lineages paired with fully-annotated, finished, de novo assembled genomes. Integrative analysis yielded four key results. First, methyltransferase allele-methylome mapping corrected methyltransferase variant effects previously obscured by reference-based variant calling. Second, heterogeneity analysis of partially active methyltransferase alleles revealed that intracellular stochastic methylation generates a mosaic of methylomes within isogenic cultures, which we formalize as ‘intercellular mosaic methylation’ (IMM). Mutation-driven IMM was nearly ubiquitous in the globally prominent Beijing sublineage. Third, promoter methylation is widespread and associated with differential expression in the ΔhsdM transcriptome, suggesting promoter HsdM-methylation directly influences transcription. Finally, comparative and functional analyses identified 351 sites hypervariable across isolates and numerous putative regulatory interactions. This multi-omic integration revealed features of methylomic variability in clinical isolates and provides a rational basis for hypothesizing the functions of DNA adenine methylation in MTBC physiology and adaptive evolution.

A positive perspective on DNA methylation: regulatory functions of DNA methylation outside of host defense in Gram-positive bacteria

The presence of post-replicative DNA methylation is pervasive among both prokaryotic and eukaryotic organisms. In bacteria, the study of DNA methylation has largely been in the context of restriction-modification systems, where DNA methylation serves to safeguard the chromosome against restriction endonuclease cleavage intended for invading DNA. There has been a growing recognition that the methyltransferase component of restriction-modification systems can also regulate gene expression, with important contributions to virulence factor gene expression in bacterial pathogens. Outside of restriction-modification systems, DNA methylation from orphan methyltransferases, which lack cognate restriction endonucleases, has been shown to regulate important processes, including DNA replication, DNA mismatch repair, and the regulation of gene expression. The majority of research and review articles have been focused on DNA methylation in the context of Gram-negative bacteria, with emphasis toward Escherichia coli, Caulobacter crescentus, and related Proteobacteria. Here we summarize the epigenetic functions of DNA methylation outside of host defense in Gram-positive bacteria, with a focus on the regulatory effects of both phase variable methyltransferases and DNA methyltransferases from traditional restriction-modification systems.

Genetic Diversity in Mycobacterium tuberculosis Clinical Isolates and Resulting Outcomes of Tuberculosis Infection and Disease

Tuberculosis claims more human lives than any other bacterial infectious disease and represents a clear and present danger to global health as new tools for vaccination, treatment, and interruption of transmission have been slow to emerge. Additionally, tuberculosis presents with notable clinical heterogeneity, which complicates diagnosis, treatment, and the establishment of nonrelapsing cure. How this heterogeneity is driven by the diversity ofclinical isolates of the causative agent, Mycobacterium tuberculosis, has recently garnered attention. Herein, we review advances in the understanding of how naturally occurring variation in clinical isolates affects transmissibility, pathogenesis, immune modulation, and drug resistance. We also summarize how specific changes in transcriptional responses can modulate infection or disease outcome, together with strain-specific effects on gene essentiality. Further understanding of how this diversity of M. tuberculosis isolates affects disease and treatment outcomes will enable the development of more effective therapeutic options and vaccines for this dreaded disease.

Mycobacterium tuberculosis associated with severe tuberculosis evades cytosolic surveillance systems and modulates IL-1β production

Genetic diversity of Mycobacterium tuberculosis affects immune responses and clinical outcomes of tuberculosis (TB). However, how bacterial diversity orchestrates immune responses to direct distinct TB severities is unknown. Here we study 681 patients with pulmonary TB and show that M. tuberculosis isolates from cases with mild disease consistently induce robust cytokine responses in macrophages across multiple donors. By contrast, bacteria from patients with severe TB do not do so. Secretion of IL-1β is a good surrogate of the differences observed, and thus to classify strains as probable drivers of different TB severities. Furthermore, we demonstrate that M. tuberculosis isolates that induce low levels of IL-1β production can evade macrophage cytosolic surveillance systems, including cGAS and the inflammasome. Isolates exhibiting this evasion strategy carry candidate mutations, generating sigA recognition boxes or affecting components of the ESX-1 secretion system. Therefore, we provide evidence that M. tuberculosis strains manipulate host-pathogen interactions to drive variable TB severities.