Professor, Pathology and Laboratory Medicine Emory University School of Medicine
"Tissue Redox Signaling Induced by the Microbiota"
Dr. Neish's research focuses on the interactions of bacteria with human epithelial cells in an effort to understand the molecular mechanisms of immune and inflammatory reactions that may mediate pathogenic and commensal relationships.
Host-microbe interactions: Our laboratory studies innate immunity and epithelial biology relevant to normal intestinal physiology as well as infectious (Gram negative enterocolitis), idiopathic (idiopathic inflammatory bowel disease) and developmental (necrotizing enterocolitis) inflammatory disorders of the gut. Specifically, our research program investigates the interactions of enteric pathogens and members of the normal gut microbiota and their products with epithelial cells in an effort to understand the molecular mechanisms of pathological and commensal eukaryotic-prokaryotic relationships. Eukaryotic cells recognize bacteria via surface receptors (pattern recognition receptors) that bind conserved microbial structural motifs. This includes the formyl peptide receptors, which can mediate both inflammatory and non inflammatory signaling, and potentially play key roles in normal intestinal homeostasis and response to infection. These receptors induce the formation of reactive oxygen species, which can play a wide role in host homeostatic signaling and maintenance of normal physiological functions. We are actively exploring how beneficial commensal bacteria modulate these processes. Additionally, pathogenic bacteria are thought to mediate interactions with eukaryotic cells by preformed effector proteins that are translocated into the host epithelia and usurp normal cellular functions. We are also interested in exploiting these proteins as potential therapeutics. The laboratory employs a variety of microbiologic, genetic, biochemical and cell biological techniques to approach theses questions, including use of mammalian cell culture, murine and Drosophila models and large-scale informatics approaches.