CRISPRi chemical genetics and comparative genomics identify genes mediating drug potency in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) infection is notoriously difficult to treat. Treatment efficacy is limited by Mtb's intrinsic drug resistance, as well as its ability to evolve acquired resistance to all antituberculars in clinical use. A deeper understanding of the bacterial pathways that influence drug efficacy could facilitate the development of more effective therapies, identify new mechanisms of acquired resistance, and reveal overlooked therapeutic opportunities. Here we developed a CRISPR interference chemical-genetics platform to titrate the expression of Mtb genes and quantify bacterial fitness in the presence of different drugs. We discovered diverse mechanisms of intrinsic drug resistance, unveiling hundreds of potential targets for synergistic drug combinations. Combining chemical genetics with comparative genomics of Mtb clinical isolates, we further identified several previously unknown mechanisms of acquired drug resistance, one of which is associated with a multidrug-resistant tuberculosis outbreak in South America. Lastly, we found that the intrinsic resistance factor whiB7 was inactivated in an entire Mtb sublineage endemic to Southeast Asia, presenting an opportunity to potentially repurpose the macrolide antibiotic clarithromycin to treat tuberculosis. This chemical-genetic map provides a rich resource to understand drug efficacy in Mtb and guide future tuberculosis drug development and treatment.

Chemical-genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy.

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 drug­drug 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 utilized conditional Mtb knockdown mutants of essential genes as an experimentally tractable surrogate for drug treatment and probe the relationship between Mtb carbon metabolism and chemical­genetic interactions (CGIs). We examined the antitubercular drugs isoniazid, rifampicin, and moxifloxacin and found that CGIs are differentially responsive to the metabolic state, defining both environment-independent and -dependent interactions. Specifically, growth on the in vivo­relevant 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 CGIs could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of chemical­genetic­environmental interactions that can be used to optimize drug­drug interactions, as well as provide a framework for understanding in vitro correlates of in vivo efficacy.

An improved statistical method to identify chemical-genetic interactions by exploiting concentration-dependence.

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.

Genome-wide gene expression tuning reveals diverse vulnerabilities of M. tuberculosis.

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.

Two interacting ATPases protect Mycobacterium tuberculosis from glycerol and nitric oxide toxicity.

The Mycobacterium tuberculosis H37Rv genome has been sequenced and annotated over 20 years ago, yet roughly half of the protein-coding genes still lack a predicted function. We characterized two genes of unknown function, rv3679 and rv3680, for which inconsistent findings regarding their importance for virulence in mice have been reported. We confirmed that a rv3679-80 deletion mutant (Δrv3679-80) was virulent in mice and discovered that Δrv3679-80 suffered from a glycerol-dependent recovery defect on agar plates following mouse infection. Glycerol also exacerbated killing of Δrv3679-80 by nitric oxide. Rv3679-Rv3680 have previously been shown to form a complex with ATPase activity and we demonstrate that the ability of M. tuberculosis to cope with elevated levels of glycerol and nitric oxide requires intact ATP-binding motifs in both Rv3679 and Rv3680. Inactivation of glycerol kinase or Rv2370c, a protein of unknown function, suppressed glycerol mediated toxicity in Δrv3679-80 Glycerol catabolism led to increased intracellular methylglyoxal pools and Δrv3679-80 was hypersusceptible to extracellular methylglyoxal suggesting that glycerol toxicity in Δrv3679-80 is caused by methylglyoxal. Rv3679 and Rv3680 interacted with Rv1509, and Rv3679 had numerous additional interactors including proteins of the type II fatty acid synthase (FASII) pathway and mycolic acid modifying enzymes linking Rv3679 to fatty acid or lipid synthesis. This work provides experimentally determined roles for Rv3679 and Rv3680 and stimulates future research on these and other proteins of unknown function.Importance A better understanding of the pathogenesis of tuberculosis requires a better understanding of gene function in M. tuberculosis This work provides the first functional insight into the Rv3679/Rv3680 ATPase complex. We demonstrate that M. tuberculosis requires this complex and specifically its ATPase activity to resist glycerol and nitric oxide toxicity. We provide evidence that the glycerol-derived metabolite methylglyoxal causes toxicity in the absence of Rv3679/Rv3680. We further show that glycerol-dependent toxicity is reversed when glycerol kinase (GlpK) is inactivated. Our work uncovered other genes of unknown function that interact with Rv3679 and/or Rv3680 genetically or physically, underscoring the importance of understanding uncharacterized genes.

Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes.

New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

Fumarase Deficiency Causes Protein and Metabolite Succination and Intoxicates Mycobacterium tuberculosis.

Enzymes of central carbon metabolism are essential mediators of Mycobacterium tuberculosis (Mtb) physiology and pathogenicity, but are often perceived to lack sufficient species selectivity to be pursued as potential drug targets. Fumarase (Fum) is an enzyme of the canonical tricarboxylic acid cycle and is dispensable in many organisms. Transposon mutagenesis studies in Mtb, however, indicate that Fum is required for optimal growth. Here, we report the generation and characterization of a genetically engineered Mtb strain in which Fum expression is conditionally regulated. This revealed that Fum deficiency is bactericidal in vitro and during both the acute and chronic phases of mouse infection. This essentiality is linked to marked accumulations of fumarate resulting in protein and metabolite succination, a covalent modification of cysteine thiol residues. These results identify Mtb Fum as a potentially species-specific drug target whose inactivation may kill Mtb through a covalently irreversible form of metabolic toxicity.