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Cellular targets of IL-4 and IL-13 in worm expulsion

$295,500R01FY2004AINIH

University Of Cincinnati, Cincinnati OH

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Abstract

DESCRIPTION (provided by the applicant): Gastrointestinal roundworm parasites infect approximately one billion people worldwide and are believed to cause approximately one million deaths annually. Protective immunity against these parasites is dependent upon the cytokines IL-4 and IL-13, which both bind to receptors that contain the IL-4R alpha polypeptide. In mice, the expression of both IL-4R alpha and Stat6, a signaling molecule that is activated when IL-4 or IL-13 bind to IL-4R alpha, are essential for expulsion of gastrointestinal nematode parasites. Studies in mice infected with Nippostrongylus brasiliensis and Trichinella spiralis demonstrate that worm expulsion requires IL-4R alpha expression by non-bone marrow-derived cells. Both IL-4 and IL-13 affect non-bone marrow-derived cells, including intestinal epithelium, goblet cells, Paneth cells, smooth muscle, and vascular endothelium, in ways that might contribute to worm expulsion from the gut; however, there is no evidence that any of these effects or cell types is sufficient or essential for worm expulsion. This proposal will test the hypothesis that one or more or these effects is sufficient and/or essential for worm expulsion by producing transgenic mice that selectively express IL-4R alpha or Stat6 on one or more of these cell types, as well as transgenic mice that selectively fail to express IL-4R alpha on one or more of these cell types. The physiological responses of these mice to IL-4 and IL-13 and their abilities to expel N. brasiliensis and T. spiralis will be determined. Identifying the cell types that participate in worm expulsion should facilitate identification of the IL-4/IL-13/IL-4R alpha/Stat6-dependent mechanisms that protect vertebrate hosts by expelling gastrointestinal worms. This information should be useful for the rationale design of pharmaceuticals that prevent or treat gastrointestinal worm infections. It should also be useful for the intelligent prediction of risks associated with agents that inhibit allergic inflammation.

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