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.

Structural and functional basis of the universal transcription factor NusG pro-pausing activity in Mycobacterium tuberculosis.

Transcriptional pauses mediate regulation of RNA biogenesis. DNA-encoded pause signals trigger pausing by stabilizing RNA polymerase (RNAP) swiveling and inhibiting DNA translocation. The N-terminal domain (NGN) of the only universal transcription factor, NusG/Spt5, modulates pausing through contacts to RNAP and DNA. Pro-pausing NusGs enhance pauses, whereas anti-pausing NusGs suppress pauses. Little is known about pausing and NusG in the human pathogen Mycobacterium tuberculosis (Mtb). We report that MtbNusG is pro-pausing. MtbNusG captures paused, swiveled RNAP by contacts to the RNAP protrusion and nontemplate-DNA wedged between the NGN and RNAP gate loop. In contrast, anti-pausing Escherichia coli (Eco) NGN contacts the MtbRNAP gate loop, inhibiting swiveling and pausing. Using CRISPR-mediated genetics, we show that pro-pausing NGN is required for mycobacterial fitness. Our results define an essential function of mycobacterial NusG and the structural basis of pro- versus anti-pausing NusG activity, with broad implications for the function of all NusG orthologs.

Incomplete transcripts dominate the Mycobacterium tuberculosis transcriptome.

Mycobacterium tuberculosis (Mtb) is a bacterial pathogen that causes tuberculosis (TB), an infectious disease that is responsible for major health and economic costs worldwide1. Mtb encounters diverse environments during its life cycle and responds to these changes largely by reprogramming its transcriptional output2. However, the mechanisms of Mtb transcription and how they are regulated remain poorly understood. Here we use a sequencing method that simultaneously determines both termini of individual RNA molecules in bacterial cells3 to profile the Mtb transcriptome at high resolution. Unexpectedly, we find that most Mtb transcripts are incomplete, with their 5' ends aligned at transcription start sites and 3' ends located 200-500 nucleotides downstream. We show that these short RNAs are mainly associated with paused RNA polymerases (RNAPs) rather than being products of premature termination. We further show that the high propensity of Mtb RNAP to pause early in transcription relies on the binding of the σ-factor. Finally, we show that a translating ribosome promotes transcription elongation, revealing a potential role for transcription-translation coupling in controlling Mtb gene expression. In sum, our findings depict a mycobacterial transcriptome that prominently features incomplete transcripts resulting from RNAP pausing. We propose that the pausing phase constitutes an important transcriptional checkpoint in Mtb that allows the bacterium to adapt to environmental changes and could be exploited for TB therapeutics.

Compensatory evolution in NusG improves fitness of drug-resistant M. tuberculosis.

Drug-resistant bacteria are emerging as a global threat, despite frequently being less fit than their drug-susceptible ancestors1-8. Here we sought to define the mechanisms that drive or buffer the fitness cost of rifampicin resistance (RifR) in the bacterial pathogen Mycobacterium tuberculosis (Mtb). Rifampicin inhibits RNA polymerase (RNAP) and is a cornerstone of modern short-course tuberculosis therapy9,10. However, RifR Mtb accounts for one-quarter of all deaths due to drug-resistant bacteria11,12. We took a comparative functional genomics approach to define processes that are differentially vulnerable to CRISPR interference (CRISPRi) inhibition in RifR Mtb. Among other hits, we found that the universally conserved transcription factor NusG is crucial for the fitness of RifR Mtb. In contrast to its role in Escherichia coli, Mtb NusG has an essential RNAP pro-pausing function mediated by distinct contacts with RNAP and the DNA13. We find this pro-pausing NusG-RNAP interface to be under positive selection in clinical RifR Mtb isolates. Mutations in the NusG-RNAP interface reduce pro-pausing activity and increase fitness of RifR Mtb. Collectively, these results define excessive RNAP pausing as a molecular mechanism that drives the fitness cost of RifR in Mtb, identify a new mechanism of compensation to overcome this cost, suggest rational approaches to exacerbate the fitness cost, and, more broadly, could inform new therapeutic approaches to develop drug combinations to slow the evolution of RifR in Mtb.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens.

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

Mutations in rv0678 Confer Low-Level Resistance to Benzothiazinone DprE1 Inhibitors in Mycobacterium tuberculosis.

Tuberculosis (TB) is the leading cause of death from any bacterial infection, causing 1.5 million deaths worldwide each year. Due to the emergence of drug-resistant strains of Mycobacterium tuberculosis (Mtb) there have been significant efforts aimed at developing novel drugs to treat TB. One promising drug target in Mtb is the arabinogalactan biosynthetic enzyme DprE1, and there have been over a dozen unique chemical scaffolds identified which inhibit the activity of this protein. Among the most promising lead compounds are the benzothiazinones BTZ043 and PBTZ169, both of which are currently in or have completed phase IIa clinical trials. Due to the potential clinical utility of these drugs, we sought to identify potential synergistic interactions and new mechanisms of resistance using a genome-scale CRISPRi chemical-genetic screen with PBTZ169. We found that knockdown of rv0678, the negative regulator of the mmpS5/L5 drug efflux pump, confers resistance to PBTZ169. Mutations in rv0678 are the most common form of resistance to bedaquiline and there is already abundant evidence of these mutations emerging in bedaquiline-treated patients. We confirmed that rv0678 mutations from clinical isolates confer low level cross-resistance to BTZ043 and PBTZ169. While it is yet unclear whether rv0678 mutations would render benzothiazinones ineffective in treating TB, these results highlight the importance of monitoring for clinically prevalent rv0678 mutations during ongoing BTZ043 and PBTZ169 clinical trials.

Tuberculosis drug discovery in the CRISPR era.

Stewart Cole and colleagues determined the complete genome sequence of Mycobacterium tuberculosis (Mtb), the etiological agent of tuberculosis (TB), in 1998 [1]. This was a landmark achievement that heralded a new age in TB drug discovery. With the genome sequence in hand, drug discoverers suddenly had thousands of new potential targets to explore. But the excitement has since faded [2]. It is unquestioned that genomics has transformed our understanding of the biology of this pathogen. However, the expectation that the Mtb genome sequence would rapidly lead to new therapeutic interventions remains unfulfilled [3]. One of the (many) reasons for this unrealized potential is that our tools to systematically interrogate the Mtb genome and its drug targets-so-called functional genomics-have been limited. In this Pearl, I argue that the recent development of robust CRISPR-based genetics in Mtb [4] overcomes many prior limitations and holds the potential to close the gap between genomics and TB drug discovery.

Correction: TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities.

[This corrects the article DOI: 10.1371/journal.ppat.1006939.].

Small RNA profiling in Mycobacterium tuberculosis identifies MrsI as necessary for an anticipatory iron sparing response.

One key to the success of Mycobacterium tuberculosis as a pathogen is its ability to reside in the hostile environment of the human macrophage. Bacteria adapt to stress through a variety of mechanisms, including the use of small regulatory RNAs (sRNAs), which posttranscriptionally regulate bacterial gene expression. However, very little is currently known about mycobacterial sRNA-mediated riboregulation. To date, mycobacterial sRNA discovery has been performed primarily in log-phase growth, and no direct interaction between any mycobacterial sRNA and its targets has been validated. Here, we performed large-scale sRNA discovery and expression profiling in M. tuberculosis during exposure to five pathogenically relevant stresses. From these data, we identified a subset of sRNAs that are highly induced in multiple stress conditions. We focused on one of these sRNAs, ncRv11846, here renamed mycobacterial regulatory sRNA in iron (MrsI). We characterized the regulon of MrsI and showed in mycobacteria that it regulates one of its targets, bfrA, through a direct binding interaction. MrsI mediates an iron-sparing response that is required for optimal survival of M. tuberculosis under iron-limiting conditions. However, MrsI is induced by multiple host-like stressors, which appear to trigger MrsI as part of an anticipatory response to impending iron deprivation in the macrophage environment.

Inhibition of Pseudomonas aeruginosa and Mycobacterium tuberculosis disulfide bond forming enzymes.

In bacteria, disulfide bonds confer stability on many proteins exported to the cell envelope or beyond, including bacterial virulence factors. Thus, proteins involved in disulfide bond formation represent good targets for the development of inhibitors that can act as antibiotics or anti-virulence agents, resulting in the simultaneous inactivation of several types of virulence factors. Here, we present evidence that the disulfide bond forming enzymes, DsbB and VKOR, are required for Pseudomonas aeruginosa pathogenicity and Mycobacterium tuberculosis survival respectively. We also report the results of a HTS of 216,767 compounds tested against P. aeruginosa DsbB1 and M. tuberculosis VKOR using Escherichia coli cells. Since both P. aeruginosa DsbB1 and M. tuberculosis VKOR complement an E. coli dsbB knockout, we screened simultaneously for inhibitors of each complemented E. coli strain expressing a disulfide-bond sensitive ß-galactosidase reported previously. The properties of several inhibitors obtained from these screens suggest they are a starting point for chemical modifications with potential for future antibacterial development.

TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities.

Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains.

Cdc15 integrates Tem1 GTPase-mediated spatial signals with Polo kinase-mediated temporal cues to activate mitotic exit.

In budding yeast, a Ras-like GTPase signaling cascade known as the mitotic exit network (MEN) promotes exit from mitosis. To ensure the accurate execution of mitosis, MEN activity is coordinated with other cellular events and restricted to anaphase. The MEN GTPase Tem1 has been assumed to be the central switch in MEN regulation. We show here that during an unperturbed cell cycle, restricting MEN activity to anaphase can occur in a Tem1 GTPase-independent manner. We found that the anaphase-specific activation of the MEN in the absence of Tem1 is controlled by the Polo kinase Cdc5. We further show that both Tem1 and Cdc5 are required to recruit the MEN kinase Cdc15 to spindle pole bodies, which is both necessary and sufficient to induce MEN signaling. Thus, Cdc15 functions as a coincidence detector of two essential cell cycle oscillators: the Polo kinase Cdc5 synthesis/degradation cycle and the Tem1 G-protein cycle. The Cdc15-dependent integration of these temporal (Cdc5 and Tem1 activity) and spatial (Tem1 activity) signals ensures that exit from mitosis occurs only after proper genome partitioning.

DNA Replication Fidelity in the Mycobacterium tuberculosis Complex.

Mycobacterium tuberculosis is genetically isolated, with no evidence for horizontal gene transfer or the acquisition of episomal genetic information in the modern evolution of strains of the Mycobacterium tuberculosis complex. When considered in the context of the specific features of the disease M. tuberculosis causes (e.g., transmission via cough aerosol, replication within professional phagocytes, subclinical persistence, and stimulation of a destructive immune pathology), this implies that to understand the mechanisms ensuring preservation of genomic integrity in infecting mycobacterial populations is to understand the source of genetic variation, including the emergence of microdiverse sub-populations that may be linked to the acquisition of drug resistance. In this chapter, we focus on mechanisms involved in maintaining DNA replication fidelity in M. tuberculosis, and consider the potential to target components of the DNA replication machinery as part of novel therapeutic regimens designed to curb the emerging threat of drug-resistance.

Precise genome modification in the crop species Zea mays using zinc-finger nucleases.

Agricultural biotechnology is limited by the inefficiencies of conventional random mutagenesis and transgenesis. Because targeted genome modification in plants has been intractable, plant trait engineering remains a laborious, time-consuming and unpredictable undertaking. Here we report a broadly applicable, versatile solution to this problem: the use of designed zinc-finger nucleases (ZFNs) that induce a double-stranded break at their target locus. We describe the use of ZFNs to modify endogenous loci in plants of the crop species Zea mays. We show that simultaneous expression of ZFNs and delivery of a simple heterologous donor molecule leads to precise targeted addition of an herbicide-tolerance gene at the intended locus in a significant number of isolated events. ZFN-modified maize plants faithfully transmit these genetic changes to the next generation. Insertional disruption of one target locus, IPK1, results in both herbicide tolerance and the expected alteration of the inositol phosphate profile in developing seeds. ZFNs can be used in any plant species amenable to DNA delivery; our results therefore establish a new strategy for plant genetic manipulation in basic science and agricultural applications.

Weak links: Advancing target-based drug discovery by identifying the most vulnerable targets.

Mycobacterium tuberculosis remains the most common infectious killer worldwide despite decades of antitubercular drug development. Effectively controlling the tuberculosis (TB) pandemic will require innovation in drug discovery. In this review, we provide a brief overview of the two main approaches to discovering new TB drugs-phenotypic screens and target-based drug discovery-and outline some of the limitations of each method. We then explore recent advances in genetic tools that aim to overcome some of these limitations. In particular, we highlight a novel metric to prioritize essential targets, termed vulnerability. Stratifying targets based on their vulnerability presents new opportunities for future target-based drug discovery campaigns.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens.

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

Beyond antibiotic resistance: The whiB7 transcription factor coordinates an adaptive response to alanine starvation in mycobacteria.

Pathogenic mycobacteria are a significant cause of morbidity and mortality worldwide. The conserved whiB7 stress response reduces the effectiveness of antibiotic therapy by activating several intrinsic antibiotic resistance mechanisms. Despite our comprehensive biochemical understanding of WhiB7, the complex set of signals that induce whiB7 expression remain less clear. We employed a reporter-based, genome-wide CRISPRi epistasis screen to identify a diverse set of 150 mycobacterial genes whose inhibition results in constitutive whiB7 expression. We show that whiB7 expression is determined by the amino acid composition of the 5' regulatory uORF, thereby allowing whiB7 to sense amino acid starvation. Although deprivation of many amino acids can induce whiB7, whiB7 specifically coordinates an adaptive response to alanine starvation by engaging in a feedback loop with the alanine biosynthetic enzyme, aspC. These findings describe a metabolic function for whiB7 and help explain its evolutionary conservation across mycobacterial species occupying diverse ecological niches.

Functional genomics, proteomics, and regulatory DNA analysis in isogenic settings using zinc finger nuclease-driven transgenesis into a safe harbor locus in the human genome.

Isogenic settings are routine in model organisms, yet remain elusive for genetic experiments on human cells. We describe the use of designed zinc finger nucleases (ZFNs) for efficient transgenesis without drug selection into the PPP1R12C gene, a "safe harbor" locus known as AAVS1. ZFNs enable targeted transgenesis at a frequency of up to 15% following transient transfection of both transformed and primary human cells, including fibroblasts and hES cells. When added to this locus, transgenes such as expression cassettes for shRNAs, small-molecule-responsive cDNA expression cassettes, and reporter constructs, exhibit consistent expression and sustained function over 50 cell generations. By avoiding random integration and drug selection, this method allows bona fide isogenic settings for high-throughput functional genomics, proteomics, and regulatory DNA analysis in essentially any transformed human cell type and in primary cells.

Incomplete transcripts dominate the Mycobacterium tuberculosis transcriptome.

Mycobacterium tuberculosis (Mtb) is a bacterial pathogen that causes tuberculosis, an infectious disease that inflicts major health and economic costs around the world 1 . Mtb encounters a diversity of environments during its lifecycle, and responds to these changing environments by reprogramming its transcriptional output 2 . However, the transcriptomic features of Mtb remain poorly characterized. In this work, we comprehensively profile the Mtb transcriptome using the SEnd-seq method that simultaneously captures the 5' and 3' ends of RNA 3 . Surprisingly, we find that the RNA coverage for most of the Mtb transcription units display a gradual drop-off within a 200-500 nucleotide window downstream of the transcription start site, yielding a massive number of incomplete transcripts with heterogeneous 3' ends. We further show that the accumulation of these short RNAs is mainly due to the intrinsically low processivity of the Mtb transcription machinery rather than trans-acting factors such as Rho. Finally, we demonstrate that transcription-translation coupling plays a critical role in generating full-length protein-coding transcripts in Mtb. In sum, our results depict a mycobacterial transcriptome that is dominated by incomplete RNA products, suggesting a distinctive set of transcriptional regulatory mechanisms that could be exploited for new therapeutics.

Beyond antibiotic resistance: the whiB7 transcription factor coordinates an adaptive response to alanine starvation in mycobacteria.

Pathogenic mycobacteria are a significant cause of morbidity and mortality worldwide. These bacteria are highly intrinsically drug resistant, making infections challenging to treat. The conserved whiB7 stress response is a key contributor to mycobacterial intrinsic drug resistance. Although we have a comprehensive structural and biochemical understanding of WhiB7, the complex set of signals that activate whiB7 expression remain less clear. It is believed that whiB7 expression is triggered by translational stalling in an upstream open reading frame (uORF) within the whiB7 5' leader, leading to antitermination and transcription into the downstream whiB7 ORF. To define the signals that activate whiB7, we employed a genome-wide CRISPRi epistasis screen and identified a diverse set of 150 mycobacterial genes whose inhibition results in constitutive whiB7 activation. Many of these genes encode amino acid biosynthetic enzymes, tRNAs, and tRNA synthetases, consistent with the proposed mechanism for whiB7 activation by translational stalling in the uORF. We show that the ability of the whiB7 5' regulatory region to sense amino acid starvation is determined by the coding sequence of the uORF. The uORF shows considerable sequence variation among different mycobacterial species, but it is universally and specifically enriched for alanine. Providing a potential rationalization for this enrichment, we find that while deprivation of many amino acids can activate whiB7 expression, whiB7 specifically coordinates an adaptive response to alanine starvation by engaging in a feedback loop with the alanine biosynthetic enzyme, aspC. Our results provide a holistic understanding of the biological pathways that influence whiB7 activation and reveal an extended role for the whiB7 pathway in mycobacterial physiology, beyond its canonical function in antibiotic resistance. These results have important implications for the design of combination drug treatments to avoid whiB7 activation, as well as help explain the conservation of this stress response across a wide range of pathogenic and environmental mycobacteria.