Unbiased Functional Characterization of Enterovirus-Host Interactions
Unbiased Functional Characterization of Enterovirus-Host Interactions
批准号:
8892041
负责人:
Nevan J Krogan
金额:
$31.24万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
已结题
起止时间:
至 2017-06-30
关键词:
AffinityAlgorithmsAntibodiesBiochemicalBioinformaticsCapsid ProteinsCellsClinicalCollaborationsComplexCoxsackie VirusesDataData SetDatabasesDependencyDepositionEnterovirusEpitopesEvolutionFibroblastsGenerationsGenesGeneticGenomic approachHIVHomeostasisHumanHuman poliovirusImageryInfectionInfluenza A Virus, H1N1 SubtypeInstitutesInstructionIntegration Host FactorsLeadLinkMapsMass Spectrum AnalysisMeningitisMethodologyMethodsModelingMolecular ChaperonesMonitorMutationOutcomePathogenesisPathway AnalysisPathway interactionsPatternPharmaceutical PreparationsPhosphorylationPoliovirusesPost Translational Modification AnalysisPost-Translational Protein ProcessingProcessProtein-Protein Interaction MapProteinsProteomicsPublicationsQuality ControlQuantitative GeneticsRNA InterferenceResearchStructural ModelsStructureTechnologyTestingTimeUbiquitinUbiquitinationVaccinesViralViral GenomeViral ProteinsVirusWorkanalytical toolbasecomparativecomputerized toolsdata integrationfollow-upgenome-wideinsightinterestmembernovelpathogenprotein complexprotein degradationprotein functionprotein protein interactionrespiratoryscreeningtoolvectorvirus pathogenesis
中文摘要
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英文摘要
PROJECT SUMMARY (See instructions):
In this study, we aim to functionally Interrogate host-pathogen relationships using three different enteroviruses (poliovirus, EV71 and coxsackievirus). To this end, we will use a variety of methods to systematically generate viral-host protein-protein and genetic interaction maps. The data generated using these initial, unbiased approaches will fuel more targeted, hypothesis-driven research in the subsequent projects. Although we intend to follow up on the most Interesting, unanticipated connections we uncover, we will be closely monitoring for links to host factors involved in quality control processes,
including chaperone function, protein ubiquitination and protein degradation, which will link this work to the work described in Projects 2 and 3. In collaboration with Sumit Chanda (Burnham Institute) and John Young (Salk Institute), we will utilize RNAI methodology to globally assess the genetic dependencies, both positive and negative, of host factors to the pathogenesis of the three enteroviruses (Aim 1). Next,
to characterize the enterovlrus-human protein-protein interactions, we intend to collaborate with Al Burlingame (UCSF) to employ a systematic affinity tag/purlflcation-mass spectrometry approach to Identify the viral-host protein complexes (Aim 2). We also Intend to globally ascertain the effects of protein post-translational modifications upon infection using mass spectrometry (Aim 3). Finally, In Aim
4, we will utilize a suite of bioinformatic and visualization tools to integrate the data sets in a meaningful fashion so that specific hypotheses regarding quality control processes can be generated and tested in collaboration with Judith Frydman (Project 2) and Raul Andino (Project 3). This integrated approach will leverage the expertise from multiple groups, including Pis of the Technology Core (Andrej Sali and Joe Derisi), so that novel host pathways that are hijacked during Infection can be Identified and characterized.
This information will hopefully lead to breakthroughs with anti-viral drugs and vaccines.
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资助金额:$37.79万
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