Prof. Dr. Alvaro Sanchez

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Given a list of candidate microbial species, which community should one form to
optimize a target function? To answer this question, we must develop predictive
quantitative models of community function, but doing so has been difficult due to the
complex web of interactions that take place in most communities. To address this
challenge, we are drawing inspiration from the theory of quantitative genetics, in
particular the concept of global epistasis on fitness landscapes. We find that similar
to genetics, community function follows simple, predictable patterns as a result of
widespread interactions. These simple patterns allow us to learn the quantitative
map between community composition and function in synthetic consortia and
rationally optimize their function. Our work seeks to place the goals of engineering
biological function across scales, from the molecular to the organismal to the
ecological, under a common theoretical and methodological framework that can
lead to the flow of ideas and methodologies across fields.

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University of Salamanca
Seminar Room 0.02 ETP
Contact: Gabriela Petrungaro