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Derrick, D.

Publications and source records attributed to Derrick, D..

2 recordsLinked to original sources

A microbiota membrane disrupter disseminates to the pancreas and increases β-cell mass

Microbiome dysbiosis is a feature of diabetes, but how microbial products influence insulin production is poorly understood. Here we report the mechanism of BefA, a microbiome-derived protein that increases proliferation of insulin-producing {beta}-cells during pancreatic development in gnotobiotic zebrafish and mice. BefA disseminates systemically via multiple anatomic routes to act directly on pancreatic islets. We report the structure of BefA, containing a lipid-binding SYLF domain, and demonstrate that it permeabilizes synthetic liposomes and bacterial membranes. A BefA mutant impaired in membrane disruption fails to expand {beta}-cells whereas the pore-forming host defense protein, Reg3, stimulates {beta}-cell proliferation. Our work demonstrates that membrane permeabilization by microbiome-derived and host defense proteins is necessary and sufficient for {beta}-cell expansion during pancreas development, thereby connecting microbiome composition with diabetes risk.

molecular biology↗

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

systems biology↗