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.

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.

Mycobacterial RNase E cleaves with a distinct sequence preference and controls the degradation rates of most Mycolicibacterium smegmatis mRNAs.

The mechanisms and regulation of RNA degradation in mycobacteria have been subject to increased interest following the identification of interplay between RNA metabolism and drug resistance. Mycobacteria encode multiple ribonucleases predicted to participate in mRNA degradation and/or processing of stable RNAs. RNase E is hypothesized to play a major role in mRNA degradation because of its essentiality in mycobacteria and its role in mRNA degradation in gram-negative bacteria. Here, we defined the impact of RNase E on mRNA degradation rates transcriptome-wide in the nonpathogenic model Mycolicibacterium smegmatis. RNase E played a rate-limiting role in degradation of the transcripts encoded by at least 89% of protein-coding genes, with leadered transcripts often being more affected by RNase E repression than leaderless transcripts. There was an apparent global slowing of transcription in response to knockdown of RNase E, suggesting that M. smegmatis regulates transcription in responses to changes in mRNA degradation. This compensation was incomplete, as the abundance of most transcripts increased upon RNase E knockdown. We assessed the sequence preferences for cleavage by RNase E transcriptome-wide in M. smegmatis and Mycobacterium tuberculosis and found a consistent bias for cleavage in C-rich regions. Purified RNase E had a clear preference for cleavage immediately upstream of cytidines, distinct from the sequence preferences of RNase E in gram-negative bacteria. We furthermore report a high-resolution map of mRNA cleavage sites in M. tuberculosis, which occur primarily within the RNase E-preferred sequence context, confirming that RNase E has a broad impact on the M. tuberculosis transcriptome.

Synthesis and Structure-Activity Relationships of a New Class of Oxadiazoles Targeting DprE1 as Antitubercular Agents.

The continuing prevalence of drug-resistant tuberculosis threatens global TB control programs, highlighting the need to discover new drug candidates to feed the drug development pipeline. In this study, we describe a high-throughput screening hit (4-benzylpiperidin-1-yl)(1-(5-phenyl-1,3,4-oxadiazol-2-yl)piperidin-4-yl)methanone (P1) as a potent antitubercular agent. Structure-activity guided synthesis led to the discovery of several analogs with high in vitro potency. P1 was found to have promising potency against many drug-resistant strains, as well as drug-susceptible clinical isolates. It also showed cidality against Mtb growing in host macrophages. Whole genome sequencing of genomic DNA from resistant mutants raised to P1 revealed mutations in decaprenylphosphoryl-ß-d-ribose 2'-oxidase (DprE1). This novel oxadiazole scaffold expands the set of chemical tools for targeting a well-validated pathway to treat tuberculosis.

Functional Whole Genome Screen of Nutrient-Starved Mycobacterium tuberculosis Identifies Genes Involved in Rifampin Tolerance.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), poses a global health challenge and is responsible for over a million deaths each year. Current treatment is lengthy and complex, and new, abbreviated regimens are urgently needed. Mtb adapts to nutrient starvation, a condition experienced during host infection, by shifting its metabolism and becoming tolerant to the killing activity of bactericidal antibiotics. An improved understanding of the mechanisms mediating antibiotic tolerance in Mtb can serve as the basis for developing more effective therapies. We performed a forward genetic screen to identify candidate Mtb genes involved in tolerance to the two key first-line antibiotics, rifampin and isoniazid, under nutrient-rich and nutrient-starved conditions. In nutrient-rich conditions, we found 220 mutants with differential antibiotic susceptibility (218 in the rifampin screen and 2 in the isoniazid screen). Following Mtb adaptation to nutrient starvation, 82 mutants showed differential antibiotic susceptibility (80 in the rifampin screen and 2 in the isoniazid screen). Using targeted mutagenesis, we validated the rifampin-hypersusceptible phenotype under nutrient starvation in Mtb mutants lacking the following genes: ercc3, moeA1, rv0049, and rv2179c. These findings shed light on potential therapeutic targets, which could help shorten the duration and complexity of antitubercular regimens.

Phase variation as a major mechanism of adaptation in Mycobacterium tuberculosis complex.

Phase variation induced by insertions and deletions (INDELs) in genomic homopolymeric tracts (HT) can silence and regulate genes in pathogenic bacteria, but this process is not characterized in MTBC (Mycobacterium tuberculosis complex) adaptation. We leverage 31,428 diverse clinical isolates to identify genomic regions including phase-variants under positive selection. Of 87,651 INDEL events that emerge repeatedly across the phylogeny, 12.4% are phase-variants within HTs (0.02% of the genome by length). We estimated the in-vitro frameshift rate in a neutral HT at 100× the neutral substitution rate at [Formula: see text] frameshifts/HT/year. Using neutral evolution simulations, we identified 4,098 substitutions and 45 phase-variants to be putatively adaptive to MTBC (P < 0.002). We experimentally confirm that a putatively adaptive phase-variant alters the expression of espA, a critical mediator of ESX-1-dependent virulence. Our evidence supports the hypothesis that phase variation in the ESX-1 system of MTBC can act as a toggle between antigenicity and survival in the host.

The Rip1 intramembrane protease contributes to iron and zinc homeostasis in Mycobacterium tuberculosis.

Mycobacterium tuberculosis is exposed to a variety of stresses during a chronic infection, as the immune system simultaneously produces bactericidal compounds and starves the pathogen of essential nutrients. The intramembrane protease, Rip1, plays an important role in the adaptation to these stresses, at least partially by the cleavage of membrane-bound transcriptional regulators. Although Rip1 is known to be critical for surviving copper intoxication and nitric oxide exposure, these stresses do not fully account for the regulatory protein's essentiality during infection. In this work, we demonstrate that Rip1 is also necessary for growth in low-iron and low-zinc conditions, similar to those imposed by the immune system. Using a newly generated library of sigma factor mutants, we show that the known regulatory target of Rip1, SigL, shares this defect. Transcriptional profiling under iron-limiting conditions supported the coordinated activity of Rip1 and SigL and demonstrated that the loss of these proteins produces an exaggerated iron starvation response. These observations demonstrate that Rip1 coordinates several aspects of metal homeostasis and suggest that a Rip1- and SigL-dependent pathway is necessary to thrive in the iron-deficient environments encountered during infection. IMPORTANCE Metal homeostasis represents a critical point of interaction between the mammalian immune system and potential pathogens. While the host attempts to intoxicate microbes with high concentrations of copper or starve the invader of iron and zinc, successful pathogens have acquired mechanisms to overcome these defenses. Our work identifies a regulatory pathway consisting of the Rip1 intramembrane protease and the sigma factor, SigL, that is essential for the important human pathogen, Mycobacterium tuberculosis, to grow in low-iron or low-zinc conditions such as those encountered during infection. In conjunction with Rip1's known role in resisting copper toxicity, our work implicates this protein as a critical integration point that coordinates the multiple metal homeostatic systems required for this pathogen to survive in host tissue.

Functional whole genome screen of nutrient-starved Mycobacterium tuberculosis identifies genes involved in antibiotic tolerance.

Mycobacterium tuberculosis ( Mtb ), the causative agent of tuberculosis (TB), poses a global health challenge and is responsible for over a million deaths each year. Current treatment is lengthy and complex, and new, abbreviated regimens are urgently needed. Mtb adapts to nutrient starvation, a condition experienced during host infection, by shifting its metabolism and becoming tolerant to the killing activity of bactericidal antibiotics. An improved understanding of the mechanisms mediating antibiotic tolerance in Mtb can serve as the basis for developing more effective therapies. We performed a forward genetic screen to identify candidate Mtb genes involved in tolerance to the two key first-line antibiotics, rifampin and isoniazid, under nutrient-rich and nutrient-starved conditions. In nutrient-rich conditions, we found 220 mutants with differential antibiotic susceptibility (218 in the rifampin screen and 2 in the isoniazid screen). Following Mtb adaptation to nutrient starvation, 82 mutants showed differential antibiotic susceptibility (80 in the rifampin screen and 2 in the isoniazid screen). Using targeted mutagenesis, we validated the rifampin-hypersusceptible phenotype under nutrient starvation in Mtb mutants lacking the following genes: ercc3 , moeA1 , rv0049 , and rv2179c . These findings shed light on potential therapeutic targets, which could help shorten the duration and complexity of antitubercular regimens. Importance: Treatment of Mtb infection requires a long course of combination antibiotics, likely due to subpopulations of tolerant bacteria exhibiting decreased susceptibility to antibiotics. Identifying and characterizing the genetic pathways involved in antibiotic tolerance is expected to yield therapeutic targets for the development of novel TB treatment-shortening regimens.

A mutant fitness assay identifies bacterial interactions in a model ocean hot spot.

Bacteria that assemble in phycospheres surrounding living phytoplankton cells metabolize a substantial proportion of ocean primary productivity. Yet the type and extent of interactions occurring among species that colonize these micron-scale "hot spot" environments are challenging to study. We identified genes that mediate bacterial interactions in phycosphere communities by culturing a transposon mutant library of copiotrophic bacterium Ruegeria pomeroyi DSS-3 with the diatom Thalassiosira pseudonana CCMP1335 as the sole source of organic matter in the presence or absence of other heterotrophic bacterial species. The function of genes having significant effects on R. pomeroyi fitness indicated explicit cell-cell interactions initiated in the multibacterial phycospheres. We found that R. pomeroyi simultaneously competed for shared substrates while increasing reliance on substrates that did not support the other species' growth. Fitness outcomes also indicated that the bacterium competed for nitrogen in the forms of ammonium and amino acids; obtained purines, pyrimidines, and cofactors via crossfeeding; both initiated and defended antagonistic interactions; and sensed an environment with altered oxygen and superoxide levels. The large genomes characteristic of copiotrophic marine bacteria are hypothesized to enable responses to dynamic ecological challenges occurring at the scale of microns. Here, we discover >200 nonessential genes implicated in the management of fitness costs and benefits of membership in a globally significant bacterial community.

The Myxobacterial Antibiotic Myxovalargin: Biosynthesis, Structural Revision, Total Synthesis, and Molecular Characterization of Ribosomal Inhibition.

Resistance of bacterial pathogens against antibiotics is declared by WHO as a major global health threat. As novel antibacterial agents are urgently needed, we re-assessed the broad-spectrum myxobacterial antibiotic myxovalargin and found it to be extremely potent against Mycobacterium tuberculosis. To ensure compound supply for further development, we studied myxovalargin biosynthesis in detail enabling production via fermentation of a native producer. Feeding experiments as well as functional genomics analysis suggested a structural revision, which was eventually corroborated by the development of a concise total synthesis. The ribosome was identified as the molecular target based on resistant mutant sequencing, and a cryo-EM structure revealed that myxovalargin binds within and completely occludes the exit tunnel, consistent with a mode of action to arrest translation during a late stage of translation initiation. These studies open avenues for structure-based scaffold improvement toward development as an antibacterial agent.

Deletion of Rv2571c confers resistance to arylamide compounds in Mycobacterium tuberculosis.

Tuberculosis, caused by Mycobacterium tuberculosis, is an urgent global health problem requiring new drugs, new drug targets and an increased understanding of antibiotic resistance. We have determined the mode of resistance to a series of arylamide compounds in M. tuberculosis We isolated M. tuberculosis resistant mutants to two arylamide compounds which are inhibitory to growth under host-relevant conditions (butyrate as a sole carbon source). Thirteen mutants were characterized, and all had mutations in Rv2571c; mutations included a premature stop codon and frameshifts as well as non-synonymous polymorphisms. We isolated a further ten strains with mutations in Rv2571c with resistance. Complementation with a wild-type copy of Rv2571c restored arylamide sensitivity. Over-expression of Rv2571c was toxic in both wild-type and mutant backgrounds. We constructed M. tuberculosis strains with an unmarked deletion of the entire Rv2571c gene by homologous recombination and confirmed that these were resistant to the arylamide series. Rv2571c is a member of the aromatic amino acid transport family and has a fusaric acid resistance domain which is associated with compound transport. Since loss or inactivation of Rv2571c leads to resistance, we propose that Rv2571c is involved in the import of arylamide compounds.

Developing synergistic drug combinations to restore antibiotic sensitivity in drug-resistant Mycobacterium tuberculosis.

Tuberculosis (TB) is a leading global cause of mortality owing to an infectious agent, accounting for almost one-third of antimicrobial resistance (AMR) deaths annually. We aimed to identify synergistic anti-TB drug combinations with the capacity to restore therapeutic efficacy against drug-resistant mutants of the causative agent, Mycobacterium tuberculosis We investigated combinations containing the known translational inhibitors, spectinomycin (SPT) and fusidic acid (FA), or the phenothiazine, chlorpromazine (CPZ), which disrupts mycobacterial energy metabolism. Potentiation of whole-cell drug efficacy was observed in SPT-CPZ combinations. This effect was lost against an M. tuberculosis mutant lacking the major facilitator superfamily (MFS) efflux pump, Rv1258c. Notably, the SPT-CPZ combination partially restored SPT efficacy against an SPT-resistant mutant carrying a g1379t point mutation in rrs, encoding the mycobacterial 16S ribosomal RNA. Combinations of SPT with FA, which targets the mycobacterial elongation factor G, exhibited potentiating activity against wild-type M. tuberculosis Moreover, this combination produced a modest potentiating effect against both FA-monoresistant and SPT-monoresistant mutants. Finally, combining SPT with the frontline anti-TB agents, rifampicin (RIF) and isoniazid, resulted in enhanced activity in vitro and ex vivo against both drug-susceptible M. tuberculosis and a RIF-monoresistant rpoB S531L mutant.These results support the utility of novel potentiating drug combinations in restoring antibiotic susceptibility of M. tuberculosis strains carrying genetic resistance to any one of the partner compounds.

Dual ICA to extract interacting sets of genes and conditions from transcriptomic data.

One of the challenges in RNA-Seq studies is finding subsets of genes that share a common mechanism of action or are associated with a regulon/pathway. Existing approaches often extract modules that reflect quantitative similarities (such as genes with correlated log-fold-changes) but do not adequately capture biological significance. In this work, we propose the Dual ICA methodology, which provides an agnostic way to extract "interacting modules" composed of sets of genes and conditions that exhibit strong associations. Dual ICA involves performing Independent Component Analysis (ICA) twice, once on the genes and once on the conditions. Using the resulting signal matrices, we extract respective sets of genes and conditions. The interaction between these sets is quantified using the coefficients from a linear regression and significance is determined through the Wald test and Z-score filtering. These coefficients are equivalent to the outer product of independent components obtained from the two signal matrices. Not only do the gene sets extracted align with known regulons, but the significant interacting modules they instantiate also encompass conditions that influence the expression of these regulons through shared mechanisms of action. Compared to traditional unsupervised clustering methods, Dual ICA demonstrates superior performance and provides explicit gene-condition sets for exploring functional relationships.

1,3-Diarylpyrazolyl-acylsulfonamides Target HadAB/BC Complex in Mycobacterium tuberculosis.

Alternative mode-of-inhibition of clinically validated targets is an effective strategy for circumventing existing clinical drug resistance. Herein, we report 1,3-diarylpyrazolyl-acylsulfonamides as potent inhibitors of HadAB/BC, a 3-hydroxyl-ACP dehydratase complex required to iteratively elongate the meromycolate chain of mycolic acids in Mycobacterium tuberculosis (Mtb). Mutations in compound 1-resistant Mtb mutants mapped to HadC (Rv0637; K157R), while chemoproteomics confirmed the compound's binding to HadA (Rv0635), HadB (Rv0636), and HadC. The compounds effectively inhibited the HadAB and HadBC enzyme activities and affected mycolic acid biosynthesis in Mtb, in a concentration-dependent manner. Unlike known 3-hydroxyl-ACP dehydratase complex inhibitors of clinical significance, isoxyl and thioacetazone, 1,3-diarylpyrazolyl-acylsulfonamides did not require activation by EthA and thus are not liable to EthA-mediated resistance. Further, the crystal structure of a key compound in a complex with Mtb HadAB revealed unique binding interactions within the active site of HadAB, providing a useful tool for further structure-based optimization of the series.

Transposon mutagenesis in Mycobacterium abscessus identifies an essential penicillin-binding protein involved in septal peptidoglycan synthesis and antibiotic sensitivity.

Mycobacterium abscessus (Mab) is a rapidly growing non-tuberculous mycobacterium (NTM) that causes a wide range of infections. Treatment of Mab infections is difficult because the bacterium is intrinsically resistant to many classes of antibiotics. Developing new and effective treatments against Mab requires a better understanding of the unique vulnerabilities that can be targeted for future drug development. To achieve this, we identified essential genes in Mab by conducting transposon sequencing (TnSeq) on the reference Mab strain ATCC 19977. We generated ~51,000 unique transposon mutants and used this high-density library to identify 362 essential genes for in vitro growth. To investigate species-specific vulnerabilities in Mab, we further characterized MAB_3167c, a predicted penicillin-binding protein and hypothetical lipoprotein (PBP-lipo) that is essential in Mab and non-essential in Mycobacterium tuberculosis (Mtb). We found that PBP-lipo primarily localizes to the subpolar region and later to the septum as cells prepare to divide. Depletion of Mab PBP-lipo causes cells to elongate, develop ectopic branches, and form multiple septa. Knockdown of PBP-lipo along with PbpB, DacB1, and a carboxypeptidase, MAB_0519 lead to synergistic growth arrest. In contrast, these genetic interactions were absent in the Mtb model organism, Mycobacterium smegmatis, indicating that the PBP-lipo homologs in the two species exist in distinct genetic networks. Finally, repressing PBP-lipo sensitized the reference strain and 11 Mab clinical isolates to several classes of antibiotics, including the ß-lactams, ampicillin, and amoxicillin by greater than 128-fold. Altogether, this study presents PBP-lipo as a key enzyme to study Mab-specific processes in cell wall synthesis and importantly positions PBP-lipo as an attractive drug target to treat Mab infections.

Multiplexed Strain Phenotyping Defines Consequences of Genetic Diversity in Mycobacterium tuberculosis for Infection and Vaccination Outcomes.

There is growing evidence that genetic diversity in Mycobacterium tuberculosis, the causative agent of tuberculosis, contributes to the outcomes of infection and public health interventions, such as vaccination. Epidemiological studies suggest that among the phylogeographic lineages of M. tuberculosis, strains belonging to a sublineage of Lineage 2 (mL2) are associated with concerning clinical features, including hypervirulence, treatment failure, and vaccine escape. The global expansion and increasing prevalence of this sublineage has been attributed to the selective advantage conferred by these characteristics, yet confounding host and environmental factors make it difficult to identify the bacterial determinants driving these associations in human studies. Here, we developed a molecular barcoding strategy to facilitate high-throughput, experimental phenotyping of M. tuberculosis clinical isolates. This approach allowed us to characterize growth dynamics for a panel of genetically diverse M. tuberculosis strains during infection and after vaccination in the mouse model. We found that mL2 strains exhibit distinct growth dynamics in vivo and are resistant to the immune protection conferred by Bacillus Calmette-Guerin (BCG) vaccination. The latter finding corroborates epidemiological observations and demonstrates that mycobacterial features contribute to vaccine efficacy. To investigate the genetic and biological basis of mL2 strains' distinctive phenotypes, we performed variant analysis, transcriptional studies, and genome-wide transposon sequencing. We identified functional genetic changes across multiple stress and host response pathways in a representative mL2 strain that are associated with variants in regulatory genes. These adaptive changes may underlie the distinct clinical characteristics and epidemiological success of this lineage. IMPORTANCE Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, is a remarkably heterogeneous disease, a feature that complicates clinical care and public health interventions. The contributions of pathogen genetic diversity to this heterogeneity are uncertain, in part due to the challenges of experimentally manipulating M. tuberculosis, a slow-growing, biosafety level 3 organism. To overcome these challenges, we applied a molecular barcoding strategy to a panel of M. tuberculosis clinical isolates. This novel application of barcoding permitted the high-throughput characterization of M. tuberculosis strain growth dynamics and vaccine resistance in the mouse model of infection. Integrating these results with genomic analyses, we uncover bacterial pathways that contribute to infection outcomes, suggesting targets for improved therapeutics and vaccines.

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.

PPE51 mediates uptake of trehalose across the mycomembrane of Mycobacterium tuberculosis.

The disaccharide trehalose is essential for viability of Mycobacterium tuberculosis, which synthesizes trehalose de novo but can also utilize exogenous trehalose. The mycobacterial cell wall encompasses two permeability barriers, the cytoplasmic membrane and the outer mycolic acid-containing mycomembrane. The ABC transporter LpqY-SugA-SugB-SugC has previously been demonstrated to mediate the specific uptake of trehalose across the cytoplasmic membrane. However, it is still unclear how the transport of trehalose molecules across the mycomembrane is mediated. In this study, we harnessed the antimycobacterial activity of the analogue 6-azido trehalose to select for spontaneous resistant M. tuberculosis mutants in a merodiploid strain harbouring two LpqY-SugA-SugB-SugC copies. Mutations mediating resistance to 6-azido trehalose mapped to the proline-proline-glutamate (PPE) family member PPE51 (Rv3136), which has recently been shown to be an integral mycomembrane protein involved in uptake of low-molecular weight compounds. A site-specific ppe51 gene deletion mutant of M. tuberculosis was unable to grow on trehalose as the sole carbon source. Furthermore, bioorthogonal labelling of the M. tuberculosis Δppe51 mutant incubated with 6-azido trehalose corroborated the impaired internalization. Taken together, the results indicate that the transport of trehalose and trehalose analogues across the mycomembrane of M. tuberculosis is exclusively mediated by PPE51.

Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice.

The outcome of an encounter with Mycobacterium tuberculosis (Mtb) depends on the pathogen's ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen's genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.