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I want to understand how microbial communities learn and adapt to time varying environments

 Microbial communities are complex and dynamic, and play a crucial role in environments from soil to marine and host-associate microbiomes. Design and control of microbial function in those ecosystems are a fundamental part of facing global challenges in human health, environmental conservation, and sustainable agriculture in the coming decade. The existing design approach predict a desirable trait or function of the communities under controlled environmental conditions. It is uncertain how microbial communities will respond to dynamic environmental conditions preventing us to design and control their function.

I aim to understand the underlying mechanism in which microbial communities learn and predict multidimensional time varying environments. I address this inquiry by characterizing metabolic and bacterial growth dynamics in synthetic communities from soil isolates under different time schedules of oxygen and nitrate availability. Oxygen and nitrate fluctuations determine the phylogenetic and physiological composition of many natural bacterial communities from soil to gut microbiota. We hypothesized that metabolic plasticity promoted by time-varying conditions, dynamic gene regulation of phenotypes, and ecological interactions between community members are mechanisms by which communities learn. I will test this hypothesis via single-cell transcriptional and metabolite measurements,  and modeling  population dynamics.