Thesis Go Natacha

Natacha Go

Modelling the immune response to the Porcine Respiratory and Reproductive Syndrome virus (PRRSv)

Abstract :

PRRSv is responsible for signi cant worldwide production loses and its control is a major challenge for the swine industry. The vaccination, which is the main control measure, did not allow to eradicate the infection and confers only a partial protection of the host. This e ciency lack is mainly due to the strong variability in PRRSv strain virulence, which induces highly variable within-host dynamics. This thesis aims to better understand the interactions between the virus and the immune response in order to improve the PRRS control. To tackle this issue, a modelling approach (deterministic and dynamic) has been choose. We developed an original immunological model, particularly adapted to PRRS. It consists of an integrative view of the interactions between the PRRSv and the immune system, representing the mechanisms at the between-cell scale. First, our results show that similar infection durations associated with contrasted immune dynamics are explained by the consideration of the immune mechanisms involved by the strain virulence. This provides new insights to explain apparent inconsistencies between experimental data. Then, an impact of both exposure intensity and duration on the within-host dynamics (which have not yet been explored for PRRS) has been shown and this impact varied depending on the strain virulence. Finally, the within-host dynamics induced by vaccinated pig infection in the eld has been explored, providing new insights to improve the vaccine e ciency. This thesis also provides new insights to guide further experimental and modelling approaches and promising prospects for the PRRS control at the herd level.

Key words :

PRRSv, respiratory pathogen, mathematical model, within-host dynamics, between-cell scale, immune response (innate and adaptive), strain virulence, exposure, vaccination

Modification date : 11 September 2023 | Publication date : 29 June 2017 | Redactor : ML