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Systems dynamics of stochastic infection outcomes in Drosophila

A central question in infection biology is to understand why two individuals exposed to the same pathogen may have life-versus-death differences in outcome. Host or pathogen heterogeneity is a natural explanation, but even when this is drastically constrained (genetically identical hosts reared together, identical infection protocols) we have found that many bacterial pathogens in Drosophila melanogaster have bimodal outcomes, with some hosts dying at high bacteria burden while others survive indefinitely with a persistent but fairly asymptomatic infection. We have previously constructed a conceptual model, based on experimental results, wherein pathogen proliferation rate and timing of host immune response interact to determine the outcome (Duneau et al, eLife 2017;6:e28298). We now seek a quantitative biologist to develop and test process-based system dynamics models to understand mechanistically when and how bimodal outcomes can be robust across a wide region of parameter space. Modeling should be complemented by theoretical and empirical study of host immune kinetics and bacterial behavior, to identify which processes govern the dynamics and outcome of the host-pathogen interaction.

This project is a collaboration between the Lazzaro, Buchon, and Ellner labs.