New anti-influenza agents are urgently needed to control seasonal epidemics and to complement already existing drugs in the fight against pandemics that pose a serious threat to humans and their livestock. The purpose of this grant is to systematically identify, validate, and classify the cellular proteins required by influenza A viruses during the replication cycle. Next, we will select the most promising drug targets among them for analysis, and provide information and support to a commercial effort to develop new anti influenza agents with the identified cellular proteins as targets. The drugs will differ from existing antiviral agents in that they affect cellular rather than viral activities. This approach has several advantages: the viruses are not likely to induce resistance, and the drugs target common pathways for human, avian, and other influenza viruses. Our proof of principle studies indicate that the number of possible targets is large, and that many kinases and other 'druggable'genes will be included. Using a systems biology approach we will be addressing the influenza/host cell interaction in all its complexity - from initial attachment of the incoming virus to the cell surface, to entry, transcription, replication, biosynthesis, and assembly of progeny particles. By employing a unique state-of-the-art siRNA screening platform available to us, we will use gene silencing to map the 'influenza infectome', a compilation of hundreds of cellular proteins that the virus needs to establish infection and drive the infectious cycle. Charting the infectome will not only enhance our understanding of influenza biology in general, but it will allow development of novel anti-influenza drugs that prevent the viruses from establishing productive infection in cells. The project involves several steps many of which will be pursued in parallel. Automated, primary, 7000 gene siRNA silencing screens using a human influenza A virus (X31/Aichi/68), HeLa cells and human airway epithelial cells, and a high-content, microscopy-based assay are already in progress. The results will undergo bioinformatic analysis to identify genes whose silencing blocks infection. Secondary screens will be used to validate and classify these 'hits', followed by characterization of selected hits using high-end light microscopy, cell biology, and biochemistry. Further validation will follow in airway epithelial cells and in a mouse model system. The screening of small compound inhibitors based on the hits will be performed throughout the grant period in collaboration with a newly founded start-up company focused on this approach.
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