Dataset Information

Gene fitness landscape of group A streptococcus during necrotizing myositis.

ABSTRACT: Necrotizing fasciitis and myositis are devastating infections characterized by high mortality. Group A streptococcus (GAS) is a common cause of these infections, but the molecular pathogenesis is poorly understood. We report a genome-wide analysis using serotype M1 and M28 strains that identified GAS genes contributing to necrotizing myositis in nonhuman primates (NHP), a clinically relevant model. Using transposon-directed insertion-site sequencing (TraDIS), we identified 126 and 116 GAS genes required for infection by serotype M1 and M28 organisms, respectively. For both M1 and M28 strains, more than 25% of the GAS genes required for necrotizing myositis encode known or putative transporters. Thirteen GAS transporters contributed to both M1 and M28 strain fitness in NHP myositis, including putative importers for amino acids, carbohydrates, and vitamins and exporters for toxins, quorum-sensing peptides, and uncharacterized molecules. Targeted deletion of genes encoding 5 transporters confirmed that each isogenic mutant strain was significantly (P < 0.05) impaired in causing necrotizing myositis in NHPs. Quantitative reverse-transcriptase PCR (qRT-PCR) analysis showed that these 5 genes are expressed in infected NHP and human skeletal muscle. Certain substrate-binding lipoproteins of these transporters, such as Spy0271 and Spy1728, were previously documented to be surface exposed, suggesting that our findings have translational research implications.

SUBMITTER: Zhu L

PROVIDER: S-EPMC6355216 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Gene fitness landscape of group A streptococcus during necrotizing myositis.

Zhu Luchang L Olsen Randall J RJ Beres Stephen B SB Eraso Jesus M JM Saavedra Matthew Ojeda MO Kubiak Samantha L SL Cantu Concepcion C CC Jenkins Leslie L Charbonneau Amelia R L ARL Waller Andrew S AS Musser James M JM

The Journal of clinical investigation 20190122 2

Necrotizing fasciitis and myositis are devastating infections characterized by high mortality. Group A streptococcus (GAS) is a common cause of these infections, but the molecular pathogenesis is poorly understood. We report a genome-wide analysis using serotype M1 and M28 strains that identified GAS genes contributing to necrotizing myositis in nonhuman primates (NHP), a clinically relevant model. Using transposon-directed insertion-site sequencing (TraDIS), we identified 126 and 116 GAS genes ...[more]

PMID: 30667377

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Project description:Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a "sweet spot" of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings.

Dataset Information

Gene fitness landscape of group A streptococcus during necrotizing myositis.

Publications

Gene fitness landscape of group A streptococcus during necrotizing myositis.

Similar Datasets

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