PROJECT 2: Determine clinically relevant host-viral dependency networks for respiratory infections including SARS-CoV-2

项目 2：确定呼吸道感染（包括 SARS-CoV-2）的临床相关宿主病毒依赖性网络

• 批准号: 10550002
• 负责人: Melanie Maria Ott
• 金额: $ 67.25万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-17 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10550002
• 关键词: 2019-nCoV; 3-Dimensional; 5 year old; Acute respiratory infection; Affect; Animal Model; Antiviral Agents; Bioinformatics; Biological; COVID-19 pandemic; COVID-19 severity; CRISPR screen; Cell Line; Cell model; Cells; Cessation of life; Child; Clinical; Clinical Data; Cloning; Clustered Regularly Interspaced Short Palindromic Repeats; Computer Models; Data; Data Set; Dependence; Development; Disease; Disease Outbreaks; Economics; Engineering; Epithelial Cells; Event; Evolution; Failure; Future; Gene Expression; Genetic; Genomics; Global Change; Health; Human; In Vitro; Individual; Inequality; Inequity; Infection; Inflammatory; Influenza A virus; Influenza B Virus; Integration Host Factors; Knock-out; Lung; Maps; Mass Spectrum Analysis; Measures; Modeling; Mycobacterium tuberculosis; Open Reading Frames; Organoids; Pathogenesis; Pathogenicity; Pathway Analysis; Pathway interactions; Patients; Phosphorylation; Post-Translational Protein Processing; Protein Secretion; Proteins; Proteomics; Public Health; RNA Viruses; Recombinants; Recording of previous events; Resistance; Resistance development; Respiration; Respiratory Disease; Respiratory Tract Infections; Respiratory syncytial virus; Role; SARS-CoV-2 B.1.1.529; SARS-CoV-2 genome; SARS-CoV-2 infection; SARS-CoV-2 variant; Sampling; Serum; Signal Transduction; System; Systems Biology; Technology; Terminator Codon; Testing; Therapeutic Intervention; Therapeutic Monoclonal Antibodies; Tuberculosis; Vaccination; Vaccinee; Validation; Viral; Viral Pathogenesis; Viral Proteins; Viral Respiratory Tract Infection; Virus; Virus Diseases; Virus Inhibitors; Virus Replication; bronchial epithelium; burden of illness; candidate identification; cell dimension; clinically relevant; cytokine; data integration; data management; experimental study; flexibility; follow-up; functional genomics; future pandemic; genetic analysis; genetic technology; genome wide association study; genome wide screen; genome-wide; genomic data; health care availability; in vivo; influenzavirus; innovation; insight; knock-down; mortality; mouse model; novel; novel therapeutic intervention; overexpression; parainfluenza virus; pathogen; prevent; protein protein interaction; receptor; respiratory; respiratory infection virus; respiratory pathogen; respiratory virus; reverse genetics; social; targeted treatment; therapeutically effective; transcriptome; transcriptome sequencing; transcriptomics; underserved area; vaccine access; variants of concern; virus host interaction

PROJECT 2: DETERMINE CLINICALLY RELEVANT HOST-VIRAL DEPENDENCY NETWORKS FOR RESPIRATORY INFECTIONS INCLUDING SARS-COV-2 SUMMARY Respiratory viral infections caused by SARS-CoV-2, influenza A and B viruses, respiratory syncytial virus, and human parainfluenza virus are a significant public health burden globally. Although vaccines are available for some of these viruses, the inequality in access and the constant virus evolution diminish their efficacy. Moreover, effective therapeutics preventing and treating severe respiratory viral diseases are still largely lacking. In Project 2, we will exploit viral dependencies on host factor networks to gain insight into disease mechanisms and develop new therapeutic approaches. We focus on relevant primary cell models, panviral mechanisms and innovative reverse genetics technologies. In Aim 1, proteomics and transcriptomics analyses will be performed with the Technology Core to determine global changes in protein abundance, post-translational modifications, and gene expression profiles in infected primary human lung cells and three-dimensional human airway organoids. Results will be integrated by the Data Management and Bioinformatics and Modeling Cores using existing -omics and human GWAS datasets to search for signatures that correlate with clinical pathogenesis. In Aim 2, virus and host genetics will be used to uncover host dependency factors critical for respiratory infection, using rapid SARS- CoV-2 cloning as well as genome-wide CRISPR-screens. In Aim 3, using supernatants of infected cells and patient serum samples, we will characterize the pro-inflammatory effects of SARS-CoV-2 ORF8 and other secreted viral proteins in correlation with clinical data. With Project 1, we will test their effect on other respiratory viruses and Mycobacterium tuberculosis infection. We anticipate that these studies will have a significant impact on public health measures against respiratory virus infections in the future.

项目2：确定临床相关的宿主-病毒依赖网络