A breakthrough in the projection theory of influenza virus evolution

2016 Fiscal Year Final Research Report

• Project/Area Number: 25291099
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Ecology/Environment
• Research Institution: The Graduate University for Advanced Studies
• Principal Investigator: Sasaki Akira 総合研究大学院大学, その他の研究科, 教授 (90211937)
• Project Period (FY): 2013-04-01 – 2017-03-31
• Keywords: インフルエンザウイルス / 進化予測 / 宿主免疫 / ベイズ予測域 / 抗原連続変異 / 多次元尺度法 / マルコフ連鎖

Outline of Final Research Achievements

Human influenza viruses are known to escape continuously from host immune defense by accumulating mutations on hemagglutinin. A recent multivariate statistic technique has extracted their surprisingly simple evolutionary trajectories on a low dimensional projected trait spaces. Here I propose a simple Bayesian update model to reproduce such evolutionary trends.
In the model, a mutant that will cause epidemic in the next year is chosen randomly according the its probability of being generated by the parental strain, multiplied by its fitness determined by the past past infection history and accumulation of host herd immunity.
This model generates nearly linear trends in the series of epidemic strains placed on antigen space with a randomly chosen direction. The angles made by consecutive axes of annual antigenic changes are narrowly distributed around 0, and the distance between epidemic strains has a peaky distribution around the characteristic width of cross-immunity.

Free Research Field

数理生物学