Quantitative studies of influenza evolution

流感进化的定量研究

• 批准号: 8615424
• 负责人: Sagi Shapira
• 金额: $ 51.64万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8615424
• 关键词: Affect; Animal Model; Antibody Activation; Attention; Avian Influenza; Avian Influenza A Virus; Binding; Biology; Biomedical Computing; Birds; Cell Communication; Cells; Cessation of life; Collaborations; Complex; Coupled; Cytotoxic T-Lymphocytes; Data; Dissection; Evolution; Fostering; Genetic; Genomics; High-Throughput RNA Sequencing; Human; Immune response; Immune system; In Vitro; Individual; Infection; Influenza; Interferon Type I; Laboratories; Lead; Life Cycle Stages; Livestock; Methods; Mission; Modeling; Monitor; Mutation; Pattern; Phase; Phenotype; Population; Population Dynamics; Population Study; Process; Production; Public Health; RNA; Research Infrastructure; Research Personnel; Risk; Shapes; Source; Structure; System; Systems Biology; Technology; Universities; Viral; Viral Genome; Virus; Virus Diseases; World Health Organization; Zoonoses; base; complex biological systems; computer framework; fitness; gain of function; in vitro Model; in vivo Model; influenza epidemic; influenza virus vaccine; influenzavirus; insight; mathematical model; member; novel; pandemic disease; pandemic influenza; pressure; protein protein interaction; public health relevance; research study; seasonal influenza; segregation; surveillance data; tool

An enormous mutation rate, coupled with reassortment (a process analogous to chromosomal segregation) of RNA segments of the viral genome, and natural zoonosis, have lead to influenza epidemics and pandemics in humans. It has been estimated seasonal influenza causes approximately 5 million cases annually, resulting in 250,000 to 500,000 deaths. Deaths resulting from pandemic influenza can reach millions and each year, the World Health Organization predicts which strains of the virus are most likely to be circulating in the following year. This approach relies on yearly global surveillance data to monitor ongoing infections in humans and livestock and is prone to significant error. A major shortcoming of these data is that they represent a partial landscape of circulating viruses due to limitations in surveillance and the selective pressures are generated in an uncontrolled setting making it difficult to assess the affect of complex evolutionary processes. However, even when such predictions are accurate, a particular influenza vaccine usually confers protection for no more We propose to overcome these limitations by integrating the experimental expertise of the Shapira and Garcia-Sastre laboratories together with than a few years due to the high mutation rate of the virus. mathematical modeling and computational framework of the Rabadan laboratory, a member of the Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet; which provides a core framework for applying systems biology approaches to studying complex biological systems such as influenza evolution). While it is well established that reassortment between influenza isolates from different host species can generate viruses with pandemic potential, the relationship between reassortment, viral mutation rates, as well as the selective pressures imposed on this virus remain key questions in influenza biology and are major issues for global public health. Not only does influenza represent an ideal laboratory model for quantitative studies of evolution, In collaboration with MAGNet, we propose to use modern genomic approaches, coupled with genetically tractable mammalian systems, to determine, in an unprecedented fashion, precisely what evolutionary changes the virus undergoes as it adapts across species, or as it interacts with the host innate and adaptive immune systems, to compute the evolutionary trajectory of individual viral sequences, and to identify selection pressures exerted on the virus. We expect that the experimental and computational platform described in this proposal will foster new insights into the evolutionary constrains that govern viral evolution. Coupled with ongoing surveillance efforts, even modest improvements on the current understanding of the influenza fitness landscape will allow for better assessment of pandemic risk potential of circulating strains. understanding the variables that influence antigenic drift, and viral adaptation is paramount.

巨大的突变率，加上重组（类似于染色体分离的过程）