CM_GF SIGNED

Project "CM_GF" data sheet

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 Project objective

The last decade of research in enteric virus infection produced a body of compelling evidences that challenged the paradigm of the single infection unit, where a single virus is able to elicit infection of a target cell. Instead, observational studies of infection in vivo and in vitro suggest that enteric viruses travel in groups: in vesicles with inverted phosphatidylserine topology or at the surface of commensal bacteria. It has been proposed that both strategies increase locally the viral multiplicity of infection, thus favoring viral complementation of defective genomes. There is a lack of knowledge on the biological relevance of the so-called multiple infection unit (MIU) as it has not been mechanistically studied in physiologically relevant model of the GI tract. In addition, the MIU is a strategy employed by all the enteric viruses so far tested, therefore it might represent a valuable target for the design of broad spectrum therapeutics. The central hypothesis of this project is that targeting MIU will inhibit enteric virus infection ex vivo and in vivo. My model of enteric virus is human norovirus (HNoV) for its clinical relevance and for its well described interaction with commensal bacteria. In work package (WP)1, to gain insight on the biological relevance of MIU in ex vivo physiologically relevant models, I will test the hypothesis that MIU increases HNoV infection in human intestinal enteroids. In aim 2, I will develop an in vitro screening platform by pulldown assay with His-tagged HNoV virus-like particles to i) screen for small molecules inhibitors of the infection and ii) identify bacterial species that are bound to HNoV in stool derived from healthy volunteer and diseased patients (i.e. inflammatory bowel disease, Crohn) . In aim 3, in order to provide evidence that targeting MIU blocks viral infection, I will test the efficacy of the small molecules identified in aim 2 in the ex-vivo model established in aim 1 and/or in-vivo, in a murine model.