A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data

BACKGROUND: Knowledge of which genes are essential to the survival of an organism is critical to understanding the function of genes, and for the identification of potential drug targets for antimicrobial treatment. Previous statistical methods for assessing essentiality based on sequencing of tranposon libraries have usually limited their assessment to strict 'essential’ or 'non-essential’ categories. However, this binary view of essentiality does not accurately represent the more nuanced ways the growth of an organism might be affected by the disruption of its genes. In addition, these methods often limit their analysis to open-reading frames. We propose a novel method for analyzing sequence data from transposon mutant libraries using a Hidden Markov Model (HMM), along with formulas to adapt the parameters of the model to different datasets for robustness. This approach allows for the clustering of insertion sites into distinct regions of essentiality across the entire genome in a statistically rigorous manner, while also allowing for the detection of growth-defect and growth-advantage regions. RESULTS: We evaluate the performance of a 4-state HMM on a sequence dataset of M. tuberculosis transposon mutants. We also test the HMM on several synthetic datasets representing different levels of transposon insertion density and sequence coverage. We show that the HMM produces results that are highly correlated with previous assignments of essentiality for this organism. We also show that it detects growth-defect and growth-advantage genes previously shown to impair or enhance growth when disrupted. CONCLUSIONS: A 4-state HMM provides an improved way of analyzing Tn-seq data and assessing different levels of essentiality that enables not only the characterization of essential and non-essential genes, but also genes whose disruption leads to impairment (or enhancement) of growth

Distinct Bacterial Pathways Influence the Efficacy of Antibiotics against Mycobacterium tuberculosis

Effective tuberculosis treatment requires at least 6 months of combination therapy. Alterations in the physiological state of the bacterium during infection are thought to reduce drug efficacy and prolong the necessary treatment period, but the nature of these adaptations remain incompletely defined. To identify specific bacterial functions that limit drug effects during infection, we employed a comprehensive genetic screening approach to identify mutants with altered susceptibility to the first-line antibiotics in the mouse model. We identified many mutations that increase the rate of bacterial clearance, suggesting new strategies for accelerating therapy. In addition, the drug-specific effects of these mutations suggested that different antibiotics are limited by distinct factors. Rifampin efficacy is inferred to be limited by cellular permeability, whereas isoniazid is preferentially affected by replication rate. Many mutations that altered bacterial clearance in the mouse model did not have an obvious effect on drug susceptibility using in vitro assays, indicating that these chemical-genetic interactions tend to be specific to the in vivo environment. This observation suggested that a wide variety of natural genetic variants could influence drug efficacy in vivo without altering behavior in standard drug-susceptibility tests. Indeed, mutations in a number of the genes identified in our study are enriched in drug-resistant clinical isolates, identifying genetic variants that may influence treatment outcome. Together, these observations suggest new avenues for improving therapy, as well as the mechanisms of genetic adaptations that limit it. IMPORTANCE Understanding how Mycobacterium tuberculosis survives during antibiotic treatment is necessary to rationally devise more effective tuberculosis (TB) chemotherapy regimens. Using genome-wide mutant fitness profiling and the mouse model of TB, we identified genes that alter antibiotic efficacy specifically in the infection environment and associated several of these genes with natural genetic variants found in drug-resistant clinical isolates. These data suggest strategies for synergistic therapies that accelerate bacterial clearance, and they identify mechanisms of adaptation to drug exposure that could influence treatment outcome

Statistical analysis of genetic interactions in Tn-Seq data

Tn-Seq is an experimental method for probing the functions of genes through construction of complex random transposon insertion libraries and quantification of each mutant\u27s abundance using next-generation sequencing. An important emerging application of Tn-Seq is for identifying genetic interactions, which involves comparing Tn mutant libraries generated in different genetic backgrounds (e.g. wild-type strain versus knockout strain). Several analytical methods have been proposed for analyzing Tn-Seq data to identify genetic interactions, including estimating relative fitness ratios and fitting a generalized linear model. However, these have limitations which necessitate an improved approach. We present a hierarchical Bayesian method for identifying genetic interactions through quantifying the statistical significance of changes in enrichment. The analysis involves a four-way comparison of insertion counts across datasets to identify transposon mutants that differentially affect bacterial fitness depending on genetic background. Our approach was applied to Tn-Seq libraries made in isogenic strains of Mycobacterium tuberculosis lacking three different genes of unknown function previously shown to be necessary for optimal fitness during infection. By analyzing the libraries subjected to selection in mice, we were able to distinguish several distinct classes of genetic interactions for each target gene that shed light on their functions and roles during infection

Mutations in the anti-sigma H factor RshA confer resistance to econazole and clotrimazole in Mycobacterium smegmatis

Azole drugs such as econazole, are active on Mycobacterium tuberculosis and Mycobacterium smegmatis; however, the identification of their target(s) is still pending. It has been reported that mutations in the non-essential system mmpL5-mmpS5 conferred resistance to econazole in M. tuberculosis. We herein report that an azole-resistant mutant screen in M. smegmatis rendered mutations in rshA, encoding a non-essential anti-sigma H protein.Fil: Morbidoni, Héctor Ricardo. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Laboratorio de Microbiología Molecular; ArgentinaFil: de la Iglesia, Agustina Inés. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Laboratorio de Microbiología Molecular; ArgentinaFil: Figueroa, Virginia. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Laboratorio de Microbiología Molecular; ArgentinaFil: Di Capua, Cecilia Beatriz. Universidad Nacional de Rosario. Facultad de Ciencias Médicas. Laboratorio de Microbiología Molecular; ArgentinaFil: Ioerger, Thomas R.. Texas A&M University; Estados UnidosFil: Parish, Tanya. Infectious Disease Research Institute. TB Discovery Research; Estados Unido

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