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.

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.

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.

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.

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.

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. 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.

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, 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.

Cyclic AMP is a critical mediator of intrinsic drug resistance and fatty acid metabolism in M. tuberculosis.

Cyclic AMP (cAMP) is a ubiquitous second messenger that transduces signals from cellular receptors to downstream effectors. Mycobacterium tuberculosis (Mtb), the etiological agent of tuberculosis, devotes a considerable amount of coding capacity to produce, sense, and degrade cAMP. Despite this fact, our understanding of how cAMP regulates Mtb physiology remains limited. Here, we took a genetic approach to investigate the function of the sole essential adenylate cyclase in Mtb H37Rv, Rv3645. We found that a lack of rv3645 resulted in increased sensitivity to numerous antibiotics by a mechanism independent of substantial increases in envelope permeability. We made the unexpected observation that rv3645 is conditionally essential for Mtb growth only in the presence of long-chain fatty acids, a host-relevant carbon source. A suppressor screen further identified mutations in the atypical cAMP phosphodiesterase rv1339 that suppress both fatty acid and drug sensitivity phenotypes in strains lacking rv3645. Using mass spectrometry, we found that Rv3645 is the dominant source of cAMP under standard laboratory growth conditions, that cAMP production is the essential function of Rv3645 in the presence of long-chain fatty acids, and that reduced cAMP levels result in increased long-chain fatty acid uptake and metabolism and increased antibiotic susceptibility. Our work defines rv3645 and cAMP as central mediators of intrinsic multidrug resistance and fatty acid metabolism in Mtb and highlights the potential utility of small molecule modulators of cAMP signaling.

Unraveling the mechanisms of intrinsic drug resistance in Mycobacterium tuberculosis.

Tuberculosis (TB) is among the most difficult infections to treat, requiring several months of multidrug therapy to produce a durable cure. The reasons necessitating long treatment times are complex and multifactorial. However, one major difficulty of treating TB is the resistance of the infecting bacterium, Mycobacterium tuberculosis (Mtb), to many distinct classes of antimicrobials. This review will focus on the major gaps in our understanding of intrinsic drug resistance in Mtb and how functional and chemical-genetics can help close those gaps. A better understanding of intrinsic drug resistance will help lay the foundation for strategies to disarm and circumvent these mechanisms to develop more potent antitubercular therapies.

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.

Iron limitation in M. tuberculosis has broad impact on central carbon metabolism.

Mycobacterium tuberculosis (Mtb), the cause of the human pulmonary disease tuberculosis (TB), contributes to approximately 1.5 million deaths every year. Prior work has established that lipids are actively catabolized by Mtb in vivo and fulfill major roles in Mtb physiology and pathogenesis. We conducted a high-throughput screen to identify inhibitors of Mtb survival in its host macrophage. One of the hit compounds identified in this screen, sAEL057, demonstrates highest activity on Mtb growth in conditions where cholesterol was the primary carbon source. Transcriptional and functional data indicate that sAEL057 limits Mtb's access to iron by acting as an iron chelator. Furthermore, pharmacological and genetic inhibition of iron acquisition results in dysregulation of cholesterol catabolism, revealing a previously unappreciated linkage between these pathways. Characterization of sAEL057's mode of action argues that Mtb's metabolic regulation reveals vulnerabilities in those pathways that impact central carbon metabolism.

The essential M. tuberculosis Clp protease is functionally asymmetric in vivo.

The Clp protease system is a promising, noncanonical drug target against Mycobacterium tuberculosis (Mtb). Unlike in Escherichia coli, the Mtb Clp protease consists of two distinct proteolytic subunits, ClpP1 and ClpP2, which hydrolyze substrates delivered by the chaperones ClpX and ClpC1. While biochemical approaches uncovered unique aspects of Mtb Clp enzymology, its essentiality complicates in vivo studies. To address this gap, we leveraged new genetic tools to mechanistically interrogate the in vivo essentiality of the Mtb Clp protease. While validating some aspects of the biochemical model, we unexpectedly found that only the proteolytic activity of ClpP1, but not of ClpP2, is essential for substrate degradation and Mtb growth and infection. Our observations not only support a revised model of Mtb Clp biology, where ClpP2 scaffolds chaperone binding while ClpP1 provides the essential proteolytic activity of the complex; they also have important implications for the ongoing development of inhibitors toward this emerging therapeutic target.

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.

CRISPR Interference Reveals That All-Trans-Retinoic Acid Promotes Macrophage Control of Mycobacterium tuberculosis by Limiting Bacterial Access to Cholesterol and Propionyl Coenzyme A.

Macrophages are a protective replicative niche for Mycobacterium tuberculosis (Mtb) but can kill the infecting bacterium when appropriately activated. To identify mechanisms of clearance, we compared levels of bacterial restriction by human macrophages after treatment with 26 compounds, including some currently in clinical trials for tuberculosis. All-trans-retinoic acid (ATRA), an active metabolite of vitamin A, drove the greatest increase in Mtb control. Bacterial clearance was transcriptionally and functionally associated with changes in macrophage cholesterol trafficking and lipid metabolism. To determine how these macrophage changes affected bacterial control, we performed the first Mtb CRISPR interference screen in an infection model, identifying Mtb genes specifically required to survive in ATRA-activated macrophages. These data showed that ATRA treatment starves Mtb of cholesterol and the downstream metabolite propionyl coenzyme A (propionyl-CoA). Supplementation with sources of propionyl-CoA, including cholesterol, abrogated the restrictive effect of ATRA. This work demonstrates that targeting the coupled metabolism of Mtb and the macrophage improves control of infection and that it is possible to genetically map the mode of bacterial death using CRISPR interference. IMPORTANCE Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, is a leading cause of death due to infectious disease. Improving the immune response to tuberculosis holds promise for fighting the disease but is limited by our lack of knowledge as to how the immune system kills M. tuberculosis. Our research identifies a potent way to make relevant immune cells more effective at fighting M. tuberculosis and then uses paired human and bacterial genomic methods to determine the mechanism of that improved bacterial clearance.

CRISPR Interference (CRISPRi) for Targeted Gene Silencing in Mycobacteria.

The genetic basis for Mycobacterium tuberculosis pathogenesis is incompletely understood. One reason for this knowledge gap is the relative difficulty of genetic manipulation of M. tuberculosis. To close this gap, we recently developed a robust CRISPR interference (CRISPRi) platform for programmable gene silencing in mycobacteria. In this chapter, we: (1) discuss some of the advantages and disadvantages of CRISPRi relative to more traditional genetic approaches; and (2) provide a protocol for the application of CRISPRi to reduce transcription of target genes in mycobacteria.

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.

CRISPY-BRED and CRISPY-BRIP: efficient bacteriophage engineering.

Genome engineering of bacteriophages provides opportunities for precise genetic dissection and for numerous phage applications including therapy. However, few methods are available for facile construction of unmarked precise deletions, insertions, gene replacements and point mutations in bacteriophages for most bacterial hosts. Here we describe CRISPY-BRED and CRISPY-BRIP, methods for efficient and precise engineering of phages in Mycobacterium species, with applicability to phages of a variety of other hosts. This recombineering approach uses phage-derived recombination proteins and Streptococcus thermophilus CRISPR-Cas9.