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Modelling the immune response to the Porcine Reproductive and Respiratory Syndrome virus

Abstract : PRRSv is responsible for significant worldwide production losses and its control is a major challenge for the swine industry. Vaccination, the main control measure, does not allow to eradicate the infection and only confers a partial protection to the host. This lack of efficiency is mainly due to the strong variability in PRRSv strain virulence, which induces highly variable within-host dynamics. This thesis aims at better understanding the interactions between the virus and the immune response in order to improve PRRSv control. To tackle this issue, a dynamic and deterministic modelling approach was chosen. We developed an original immunological model consisting in an integrative representation of the within-host dynamics. It describes the immune mechanisms at the between-cell scale, including the innate response, the activation and orientation of the adaptive response and their complex regulations by the major cytokines. Our first results show that similar infection durations associated with contrasted immune dynamics are explained by the consideration of the immune mechanisms affected by the strain virulence. They provide new insights to explain apparent inconsistencies between experimental data. We then showed that the exposure, whose effect is often neglected, has an impact on the within-host dynamics, which varies depending on the virulence level. Finally, the within-host dynamics induced by the infection of a vaccinated pig was explored, providing new insights to improve vaccine efficiency. This thesis also provides new insights to guide further experimental and modelling approaches and promising prospects for PRRSv control at the herd level.
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Submitted on : Monday, June 29, 2015 - 10:44:06 PM
Last modification on : Wednesday, September 28, 2022 - 3:11:21 PM
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  • HAL Id : tel-01100983, version 2



Natacha Go. Modelling the immune response to the Porcine Reproductive and Respiratory Syndrome virus. Animal biology. AgroParisTech, 2014. English. ⟨NNT : 2014AGPT0070⟩. ⟨tel-01100983v2⟩



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