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Current chemotherapy against Mycobacterium tuberculosis (Mtb), an important human pathogen, requires a multidrug regimen lasting several months. While efforts have been made to optimize therapy by exploiting drug-drug synergies, testing new drug combinations in relevant host environments remains arduous. In particular, host environments profoundly affect the bacterial metabolic state and drug efficacy, limiting the accuracy of predictions based on in vitro assays alone. In this study, we utilize conditional Mtb knockdown mutants of essential genes as an experimentally-tractable surrogate for drug treatment, and probe the relationship between Mtb carbon metabolism and chemical-genetic interactions (CGI). We examined the anti-tubercular drugs isoniazid, rifampicin and moxifloxacin, and found that CGI are differentially responsive to the metabolic state, defining both environment-independent and –dependent interactions. Specifically, growth on the in vivo-relevant carbon source, cholesterol, reduced rifampicin efficacy by altering mycobacterial cell surface lipid composition. We report that a variety of perturbations in cell wall synthesis pathways restore rifampicin efficacy during growth on cholesterol, and that both environment-independent and cholesterol-dependent in vitro CGI could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of novel chemical-genetic-environmental interactions that can be used to optimize drug-drug interactions as well as provide a framework for understanding in vitro correlates of in vivo efficacy.SignificanceEfforts to improve tuberculosis therapy include optimizing multi-drug regimens to take advantage of drug-drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug-drug interactions. We found that these interactions can be differentially sensitive to the metabolic state and select in vitro-defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest new strategies for optimizing tuberculosis therapy.

Characterization of gene essentiality across different conditions is a useful approach for predicting gene function. Transposon sequencing (TnSeq) is a powerful means of generating genome-wide profiles of essentiality and has been used extensively in Mycobacterium tuberculosis (Mtb) genetic research. Over the past two decades, dozens of TnSeq screens have been published, yielding valuable insights into the biology of Mtb in vitro, inside macrophages, and in model host organisms. However, these Mtb TnSeq profiles are distributed across dozens of research papers within supplementary materials, which makes querying them cumbersome and assembling a complete and consistent synthesis of existing data challenging. Here, we address this problem by building a central repository of publicly available TnSeq screens performed in M. tuberculosis, which we call the Mtb transposon sequencing database (MtbTnDB). The MtbTnDB encompasses 64 published and unpublished TnSeq screens, and is standardized, open-access, and allows users easy access to data, visualizations, and functional predictions through an interactive web-app (www.mtbtndb.app). We also present evidence that (i) genes in the same genomic neighborhood tend to have similar TnSeq profiles, and (ii) clusters of genes with similar TnSeq profiles tend to be enriched for genes belonging to the same functional categories. Finally, we test and evaluate machine learning models trained on TnSeq profiles to guide functional annotation of orphan genes in Mtb. In addition to facilitating the exploration of conditional genetic essentiality in this important human pathogen via a centralized TnSeq data repository, the MtbTnDB will enable hypothesis generation and the extraction of meaningful patterns by facilitating the comparison of datasets across conditions. This will provide a basis for insights into the functional organization of Mtb genes as well as gene function prediction.

Summary Antibacterial agents target the products of essential genes but rarely achieve complete target inhibition. Thus, the all-or-none definition of essentiality afforded by traditional genetic approaches fails to discern the most attractive bacterial targets: those whose incomplete inhibition results in major fitness costs. In contrast, gene “vulnerability” is a continuous, quantifiable trait that relates the magnitude of gene inhibition to the effect on bacterial fitness. We developed a CRISPR interference-based functional genomics method to systematically titrate gene expression in Mycobacterium tuberculosis (Mtb) and monitor fitness outcomes. We identified highly vulnerable genes in various processes, including novel targets unexplored for drug discovery. Equally important, we identified invulnerable essential genes, potentially explaining failed drug discovery efforts. Comparison of vulnerability between the reference and a hypervirulent Mtb isolate revealed incomplete conservation of vulnerability and that differential vulnerability can predict differential antibacterial susceptibility. Our results quantitatively redefine essential bacterial processes and identify high-value targets for drug development., Graphical abstract, Highlights • Titratable CRISPRi enables quantification of target vulnerability in mycobacteria • Essential genes and processes vary widely in their vulnerability • Differential vulnerability predicts differential antibacterial susceptibility • Generalizable approach allows prioritization of high-value targets for drug discovery, Conventional genetic approaches rely on complete gene inactivation to identify potential antimicrobial targets. In contrast to this all-or-nothing effect, small molecules rarely achieve complete target inhibition. Here, a CRISPR interference system using M. tuberculosis as a model organism is used to titrate gene expression and uncover gene vulnerability, redefining the concept of essential genes and identifying antimicrobial targets.

Chemical-genetics (C-G) experiments can be used to identify interactions between inhibitory compounds and bacterial genes, potentially revealing the targets of drugs, or other functionally interacting genes and pathways. C-G experiments involve constructing a library of hypomorphic strains with essential genes that can be knocked-down, treating it with an inhibitory compound, and using high-throughput sequencing to quantify changes in relative abundance of individual mutants. The hypothesis is that, if the target of a drug or other genes in the same pathway are present in the library, such genes will display an excessive fitness defect due to the synergy between the dual stresses of protein depletion and antibiotic exposure. While assays at a single drug concentration are susceptible to noise and can yield false-positive interactions, improved detection can be achieved by requiring that the synergy between gene and drug be concentration-dependent. We present a novel statistical method based on Linear Mixed Models, called CGA-LMM, for analyzing C-G data. The approach is designed to capture the dependence of the abundance of each gene in the hypomorph library on increasing concentrations of drug through slope coefficients. To determine which genes represent candidate interactions, CGA-LMM uses a conservative population-based approach in which genes with negative slopes are considered significant only if they are outliers with respect to the rest of the population (assuming that most genes in the library do not interact with a given inhibitor). We applied the method to analyze 3 independent hypomorph libraries of M. tuberculosis for interactions with antibiotics with anti-tubercular activity, and we identify known target genes or expected interactions for 7 out of 9 drugs where relevant interacting genes are known.

Of the ~80 putative toxin‐antitoxin (TA) modules encoded by the bacterial pathogen Mycobacterium tuberculosis (Mtb), three contain antitoxins essential for bacterial viability. One of these, Rv0060 (DNA ADP‐ribosyl glycohydrolase, DarGMtb), functions along with its cognate toxin Rv0059 (DNA ADP‐ribosyl transferase, DarTMtb), to mediate reversible DNA ADP‐ribosylation (Jankevicius et al., 2016). We demonstrate that DarTMtb‐DarGMtb form a functional TA pair and essentiality of darGMtb is dependent on the presence of darTMtb, but simultaneous deletion of both darTMtb‐darGMtb does not alter viability of Mtb in vitro or in mice. The antitoxin, DarGMtb, forms a cytosolic complex with DNA‐repair proteins that assembles independently of either DarTMtb or interaction with DNA. Depletion of DarGMtb alone is bactericidal, a phenotype that is rescued by expression of an orthologous antitoxin, DarGTaq, from Thermus aquaticus. Partial depletion of DarGMtb triggers a DNA‐damage response and sensitizes Mtb to drugs targeting DNA metabolism and respiration. Induction of the DNA‐damage response is essential for Mtb to survive partial DarGMtb‐depletion and leads to a hypermutable phenotype., DarT and DarG form a toxin‐antitoxin pair in M. tuberculosis. In the absence of DarG, the toxin ADP‐ribosylates DNA leading to cell death. In the presence of DarG, DarG binds to and neutralizes the toxin, and plausibly also recruits DNA repair machinery to remove the ADP‐ribosyl moiety and repair the DNA.

BackgroundDeep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions. Various analytical methods have been described for identifying conditionally essential genes whose tolerance for insertions varies between two conditions. However, for large-scale experiments involving many conditions, a method is needed for identifying genes that exhibit significant variability in insertions across multiple conditions.ResultsIn this paper, we introduce a novel statistical method for identifying genes with significant variability of insertion counts across multiple conditions based on Zero-Inflated Negative Binomial (ZINB) regression. Using likelihood ratio tests, we show that the ZINB distribution fits TnSeq data better than either ANOVA or a Negative Binomial (in a generalized linear model). We use ZINB regression to identify genes required for infection ofM. tuberculosisH37Rv in C57BL/6 mice. We also use ZINB to perform a analysis of genes conditionally essential in H37Rv cultures exposed to multiple antibiotics.ConclusionsOur results show that, not only does ZINB generally identify most of the genes found by pairwise resampling (and vastly out-performs ANOVA), but it also identifies additional genes where variability is detectable only when the magnitudes of insertion counts are treated separately from local differences in saturation, as in the ZINB model.

An adenylyl cyclase from Mycobacterium avium, Mal 120, is a functional orthologue of a pseudogene Rv1120c from Mycobacterium tuberculosis. We report the crystal structure of Mal 120 in a monomeric form and its truncated construct as a dimer. Mal 120 exists as a monomer in solution and crystallized as a monomer in the absence of substrate or inhibitor. An additional alpha-helix present at the N-terminus of the monomeric structure blocks the active site by interacting with the substrate binding residues and occupying the dimer interface region. However, the enzyme has been found to be active in solution, indicating the movement of the helix away from the interface to facilitate the formation of active dimers in conditions favourable for catalysis. Thus, the N-terminal helix of Ma1120 keeps the enzyme in an autoinhibited state when it is not active. Deletion of this helix enabled us to crystallize the molecule as an active homodimer in the presence of a P-site inhibitor 2',5'-dideoxy-3'-ATP, or pyrophosphate along with metal ions. The substrate specifying lysine residue plays a dual role of interacting with the substrate and stabilizing the dimer. The dimerization loop region harbouring the second substrate specifying residue, an aspartate, shows significant differences in conformation and position between the monomeric and dimeric structures. Thus, this study has not only revealed that significant structural transitions are required for the interconversion of the inactive and the active forms of the enzyme, but also provided precise nature of these transitions. (C) 2015 Elsevier Inc. All rights reserved.

The cyclic AMP receptor protein (CRP) family of transcription factors consists of global regulators of bacterial gene expression. Here, we identify two paralogous CRPs in the genome of Mycobacterium smegmatis that have 78% identical sequences and characterize them biochemically and functionally. The two proteins (MSMEG_0539 and MSMEG_6189) show differences in cAMP binding affinity, trypsin sensitivity, and binding to a CRP site that we have identified upstream of the msmeg_3781 gene. MSMEG_6189 binds to the CRP site readily in the absence of cAMP, while MSMEG_0539 binds in the presence of cAMP, albeit weakly. msmeg_6189 appears to be an essential gene, while the Δmsmeg_0539 strain was readily obtained. Using promoter-reporter constructs, we show that msmeg_3781 is regulated by CRP binding, and its transcription is repressed by MSMEG_6189. Our results are the first to characterize two paralogous and functional CRPs in a single bacterial genome. This gene duplication event has subsequently led to the evolution of two proteins whose biochemical differences translate to differential gene regulation, thus catering to the specific needs of the organism.

cAMPhor: In the presence of cAMP, cAMPhor folds into a structure that binds DFHBI (green), increasing its fluorescence, while Alexa 647 (red) functions as a normalizing dye. It can thus be used to spatially image cAMP quantitatively in membrane-bound compartments.

All organisms have the capacity to sense and respond to environmental changes. These signals often involve the use of second messengers such as cyclic adenosine monophosphate (cAMP). This second messenger is widely distributed among organisms and coordinates gene expression related with pathogenesis, virulence, and environmental adaptation. Genomic analysis in Mycobacterium tuberculosis has identified 16 adenylyl cyclases (AC) and one phosphodiesterase, which produce and degrade cAMP, respectively. To date, ten AC have been biochemically characterized and only one (Rv0386) has been found to be important during murine infection with M. tuberculosis. Here, we investigated the impact of hsp60-driven Rv2212 gene expression in Mycobacterium bovis Bacillus Calmette-Guerin (BCG) during growth in vitro, and during macrophage and mice infection. We found that hsp60-driven expression of Rv2212 resulted in an increased capacity of replication in murine macrophages but an attenuated phenotype in lungs and spleen when administered intravenously in mice. Furthermore, this strain displayed an altered proteome mainly affecting proteins associated with stress conditions (bfrB, groEL-2, DnaK) that could contribute to the attenuated phenotype observed in mice.