4.6 Article

Modeling Within-Host Dynamics of Influenza Virus Infection Including Immune Responses

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PLOS COMPUTATIONAL BIOLOGY
卷 8, 期 6, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1002588

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资金

  1. US Department of Energy [DE-AC52-06NA25396]
  2. NIH [P30-EB011339, HHSN272201000055C]
  3. National Center for Research Resources and the Office of Research Infrastructure Programs (ORIP) [8R01-OD011095-21]
  4. NSF [DMS-1122290, PHY-0551164]
  5. Los Alamos National Laboratory LDRD Program
  6. Direct For Mathematical & Physical Scien
  7. Division Of Mathematical Sciences [1122290] Funding Source: National Science Foundation

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Influenza virus infection remains a public health problem worldwide. The mechanisms underlying viral control during an uncomplicated influenza virus infection are not fully understood. Here, we developed a mathematical model including both innate and adaptive immune responses to study the within-host dynamics of equine influenza virus infection in horses. By comparing modeling predictions with both interferon and viral kinetic data, we examined the relative roles of target cell availability, and innate and adaptive immune responses in controlling the virus. Our results show that the rapid and substantial viral decline (about 2 to 4 logs within 1 day) after the peak can be explained by the killing of infected cells mediated by interferon activated cells, such as natural killer cells, during the innate immune response. After the viral load declines to a lower level, the loss of interferon-induced antiviral effect and an increased availability of target cells due to loss of the antiviral state can explain the observed short phase of viral plateau in which the viral level remains unchanged or even experiences a minor second peak in some animals. An adaptive immune response is needed in our model to explain the eventual viral clearance. This study provides a quantitative understanding of the biological factors that can explain the viral and interferon kinetics during a typical influenza virus infection.

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