Search

Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs., Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance., Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool., Measurements and Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci., Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.

Transcription factors (TFs) play a central role in regulating gene expression in all bacteria. Yet until recently, studies of TF binding were limited to a small number of factors at a few genomic locations. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) provides the ability to map binding sites globally for TFs, and the scalability of the technology enables the ability to map binding sites for every DNA binding protein in a prokaryotic organism. We have developed a protocol for ChIP-Seq tailored for use with mycobacteria and an analysis pipeline for processing the resulting data. The protocol and pipeline have been used to map over 100 TFs from Mycobacterium tuberculosis, as well as numerous TFs from related mycobacteria and other bacteria. The resulting data provide evidence that the long-accepted spatial relationship between TF binding site, promoter motif, and the corresponding regulated gene may be too simple a paradigm, failing to adequately capture the variety of TF binding sites found in prokaryotes. In this article we describe the protocol and analysis pipeline, the validation of these methods, and the results of applying these methods to M. tuberculosis.

M. tuberculosis is evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly sequenced and 7 previously sequenced M. tuberculosis whole genomes, we identified genome-wide signatures of positive selection specific to the 47 drug-resistant strains. By searching for convergent evolution--the independent fixation of mutations in the same nucleotide position or gene--we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode components in cell wall biosynthesis, transcriptional regulation and DNA repair pathways. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin.

Mycobacterium tuberculosis (M.tb), the cause of tuberculosis (TB), is estimated to infect a new host every second. While analyses of genetic data from natural populations of M.tb have emphasized the role of genetic drift in shaping patterns of diversity, the influence of natural selection on this successful pathogen is less well understood. We investigated the effects of natural selection on patterns of diversity in 63 globally extant genomes of M.tb and related pathogenic mycobacteria. We found evidence of strong purifying selection, with an estimated genome-wide selection coefficient equal to -9.5 × 10(-4) (95% CI -1.1 × 10(-3) to -6.8 × 10(-4)); this is several orders of magnitude higher than recent estimates for eukaryotic and prokaryotic organisms. We also identified different patterns of variation across categories of gene function. Genes involved in transport and metabolism of inorganic ions exhibited very low levels of non-synonymous polymorphism, equivalent to categories under strong purifying selection (essential and translation-associated genes). The highest levels of non-synonymous variation were seen in a group of transporter genes, likely due to either diversifying selection or local selective sweeps. In addition to selection, we identified other important influences on M.tb genetic diversity, such as a 25-fold expansion of global M.tb populations coincident with explosive growth in human populations (estimated timing 1684 C.E., 95% CI 1620-1713 C.E.). These results emphasize the parallel demographic histories of this obligate pathogen and its human host, and suggest that the dominant effect of selection on M.tb is removal of novel variants, with exceptions in an interesting group of genes involved in transportation and defense. We speculate that the hostile environment within a host imposes strict demands on M.tb physiology, and thus a substantial fitness cost for most new mutations. In this respect, obligate bacterial pathogens may differ from other host-associated microbes such as symbionts.

Transcription factors (TFs) play a central role in regulating gene expression in all bacteria. Yet, until recently, studies of TF binding were limited to a small number of factors at a few genomic locations. Chromatin immunoprecipitation followed by sequencing enables mapping of binding sites for TFs in a global and high-throughput fashion. The NIAID funded TB systems biology project http://www.broadinstitute.org/annotation/tbsysbio/home.html aims to map the binding sites for every transcription factor in the genome of Mycobacterium tuberculosis (MTB), the causative agent of human TB. ChIP-Seq data already released through TBDB.org have provided new insight into the mechanisms of TB pathogenesis. But in addition, data from MTB are beginning to challenge many simplifying assumptions associated with gene regulation in all bacteria. In this chapter, we review the global aspects of TF binding in MTB and discuss the implications of these data for our understanding of bacterial gene regulation. We begin by reviewing the canonical model of bacterial transcriptional regulation using the lac operon as the standard paradigm. We then review the use of ChIP-Seq to map the binding sites of DNA-binding proteins and the application of this method to mapping TF binding sites in MTB. Finally, we discuss two aspects of the binding discovered by ChIP-Seq that were unexpected given the canonical model: the substantial binding outside the proximal promoter region and the large number of weak binding sites.

Background: The sequence of the pathogen Mycobacterium tuberculosis (Mtb) strain H37Rv has been available for over a decade, but the biology of the pathogen remains poorly understood. Genome sequences from other Mtb strains and closely related bacteria present an opportunity to apply the power of comparative genomics to understand the evolution of Mtb pathogenesis. We conducted a comparative analysis using 31 genomes from the Tuberculosis Database (TBDB.org), including 8 strains of Mtb and M. bovis, 11 additional Mycobacteria, 4 Corynebacteria, 2 Streptomyces, Rhodococcus jostii RHA1, Nocardia farcinia, Acidothermus cellulolyticus, Rhodobacter sphaeroides, Propionibacterium acnes, and Bifidobacterium longum., Results: Our results highlight the functional importance of lipid metabolism and its regulation, and reveal variation between the evolutionary profiles of genes implicated in saturated and unsaturated fatty acid metabolism. It also suggests that DNA repair and molybdopterin cofactors are important in pathogenic Mycobacteria. By analyzing sequence conservation and gene expression data, we identify nearly 400 conserved noncoding regions. These include 37 predicted promoter regulatory motifs, of which 14 correspond to previously validated motifs, as well as 50 potential noncoding RNAs, of which we experimentally confirm the expression of four., Conclusions: Our analysis of protein evolution highlights gene families that are associated with the adaptation of environmental Mycobacteria to obligate pathogenesis. These families include fatty acid metabolism, DNA repair, and molybdopterin biosynthesis. Our analysis reinforces recent findings suggesting that small noncoding RNAs are more common in Mycobacteria than previously expected. Our data provide a foundation for understanding the genome and biology of Mtb in a comparative context, and are available online and through TBDB.org.

Mycobacterium tuberculosis, the causative agent of most human tuberculosis, infects one third of the world's population and kills an estimated 1.7 million people a year. With the world-wide emergence of drug resistance, and the finding of more functional genetic diversity than previously expected, there is a renewed interest in understanding the forces driving genome evolution of this important pathogen. Genetic diversity in M. tuberculosis is dominated by single nucleotide polymorphisms and small scale gene deletion, with little or no evidence for large scale genome rearrangements seen in other bacteria. Recently, a single report described a large scale genome duplication that was suggested to be specific to the Beijing lineage. We report here multiple independent large-scale duplications of the same genomic region of M. tuberculosis detected through whole-genome sequencing. The duplications occur in strains belonging to both M. tuberculosis lineage 2 and 4, and are thus not limited to Beijing strains. The duplications occur in both drug-resistant and drug susceptible strains. The duplicated regions also have substantially different boundaries in different strains, indicating different originating duplication events. We further identify a smaller segmental duplication of a different genomic region of a lab strain of H37Rv. The presence of multiple independent duplications of the same genomic region suggests either instability in this region, a selective advantage conferred by the duplication, or both. The identified duplications suggest that large-scale gene duplication may be more common in M. tuberculosis than previously considered.

Epidemics of drug-resistant bacteria emerge worldwide, even as resistant strains frequently have reduced fitness compared to their drug-susceptible counterparts. Data from model systems suggest that the fitness cost of antimicrobial resistance can be reduced by compensatory mutations; however, there is limited evidence that compensatory evolution has any significant role in the success of drug-resistant bacteria in human populations. Here we describe a set of compensatory mutations in the RNA polymerase genes of rifampicin-resistant M. tuberculosis, the etiologic agent of human tuberculosis (TB). M. tuberculosis strains harboring these compensatory mutations showed a high competitive fitness in vitro. Moreover, these mutations were associated with high fitness in vivo, as determined by examining their relative clinical frequency across patient populations. Of note, in countries with the world's highest incidence of multidrug-resistant (MDR) TB, more than 30% of MDR clinical isolates had this form of mutation. Our findings support a role for compensatory evolution in the global epidemics of MDR TB.

Tuberculosis poses a global health emergency, which has been compounded by the emergence of drug-resistant Mycobacterium tuberculosis (Mtb) strains. We used whole-genome sequencing to compare the accumulation of mutations in Mtb isolated from cynomolgus macaques with active, latent or reactivated disease. We sequenced 33 Mtb isolates from nine macaques with an average genome coverage of 93% and an average read depth of 117×. Based on the distribution of SNPs observed, we calculated the mutation rates for these disease states. We found a similar mutation rate during latency as during active disease or in a logarithmically growing culture over the same period of time. The pattern of polymorphisms suggests that the mutational burden in vivo is because of oxidative DNA damage. We show that Mtb continues to acquire mutations during disease latency, which may explain why isoniazid monotherapy for latent tuberculosis is a risk factor for the emergence of isoniazid resistance.

Mycobacterium tuberculosis is an obligate human pathogen capable of persisting in individual hosts for decades. We sequenced the genomes of 21 strains representative of the global diversity and six major lineages of the M. tuberculosis complex (MTBC) at 40- to 90-fold coverage using Illumina next-generation DNA sequencing. We constructed a genome-wide phylogeny based on these genome sequences. Comparative analyses of the sequences showed, as expected, that essential genes in MTBC were more evolutionarily conserved than nonessential genes. Notably, however, most of the 491 experimentally confirmed human T cell epitopes showed little sequence variation and had a lower ratio of nonsynonymous to synonymous changes than seen in essential and nonessential genes. We confirmed these findings in an additional data set consisting of 16 antigens in 99 MTBC strains. These findings are consistent with strong purifying selection acting on these epitopes, implying that MTBC might benefit from recognition by human T cells.