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Harnessing single cell sorting to identify cell division genes and regulators in bacteria.

ABSTRACT: Cell division is an essential cellular process that requires an array of known and unknown proteins for its spatial and temporal regulation. Here we develop a novel, high-throughput screening method for the identification of bacterial cell division genes and regulators. The method combines the over-expression of a shotgun genomic expression library to perturb the cell division process with high-throughput flow cytometry sorting to screen many thousands of clones. Using this approach, we recovered clones with a filamentous morphology for the model bacterium, Escherichia coli. Genetic analysis revealed that our screen identified both known cell division genes, and genes that have not previously been identified to be involved in cell division. This novel screening strategy is applicable to a wide range of organisms, including pathogenic bacteria, where cell division genes and regulators are attractive drug targets for antibiotic development.

SUBMITTER: Burke C

PROVIDER: S-EPMC3614548 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Harnessing single cell sorting to identify cell division genes and regulators in bacteria.

Burke Catherine C Liu Michael M Britton Warwick W Triccas James A JA Thomas Torsten T Smith Adrian L AL Allen Steven S Salomon Robert R Harry Elizabeth E

PloS one 20130402 4

Cell division is an essential cellular process that requires an array of known and unknown proteins for its spatial and temporal regulation. Here we develop a novel, high-throughput screening method for the identification of bacterial cell division genes and regulators. The method combines the over-expression of a shotgun genomic expression library to perturb the cell division process with high-throughput flow cytometry sorting to screen many thousands of clones. Using this approach, we recovere ...[more]

PMID: 23565292

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Project description:Sex differences in gene expression are widespread in the liver, where many autosomal factors act in tandem with growth hormone signaling to regulate individual variability of sex differences in liver metabolism and disease. Here, we compare hepatic transcriptomic and epigenetic profiles of mouse strains C57BL/6J and CAST/EiJ, representing two subspecies separated by 0.5-1 million years of evolution, to elucidate the actions of genetic factors regulating liver sex differences. We identify 144 protein coding genes and 78 lncRNAs showing strain-conserved sex bias; many have gene ontologies relevant to liver function, are more highly liver-specific and show greater sex bias, and are more proximally regulated than genes whose sex bias is strain-dependent. The strain-conserved genes include key growth hormone-dependent transcriptional regulators of liver sex bias; however, three other transcription factors, Trim24, Tox, and Zfp809, lose their sex-biased expression in CAST/EiJ mouse liver. To elucidate the observed strain specificities in expression, we characterized the strain-dependence of sex-biased chromatin opening and enhancer marks at cis regulatory elements (CREs) within expression quantitative trait loci (eQTL) regulating liver sex-biased genes. Strikingly, 208 of 286 eQTLs with strain-specific, sex-differential effects on expression were associated with a complete gain, loss, or reversal of the sex differences in expression between strains. Moreover, 166 of the 286 eQTLs were linked to the strain-dependent gain or loss of localized sex-biased CREs. Remarkably, a subset of these CREs apparently lacked strain-specific genetic variants yet showed coordinated, strain-dependent sex-biased epigenetic regulation. Thus, we directly link hundreds of strain-specific genetic variants to the high variability in CRE activity and expression of sex-biased genes and uncover underlying genetically-determined epigenetic states controlling liver sex bias in genetically diverse mouse populations.

Dataset Information

Harnessing single cell sorting to identify cell division genes and regulators in bacteria.

Publications

Harnessing single cell sorting to identify cell division genes and regulators in bacteria.

Similar Datasets

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