Predictively linking the composition and function of microbial consortia: Taking inspiration from quantitative genetics by Alvaro SANCHEZ

Abstract: Microbial communities provide countless ecological services essential for sustaining life on Earth, and they perform a wide array of functions in biotechnology—from food production to biofuel synthesis. The quantitative functions delivered by microbial communities depend on their composition, i.e. the specific genotypes present and their relative abundances. To engineer microbial consortia that optimize these functions, we must establish a predictive, quantitative link between community composition and function. Yet, developing mechanistic mathematical models to achieve this is exceptionally challenging due to the complex network of interactions involved. In this talk, I will explore how concepts from fitness landscape theory in genetics can help overcome these challenges and lead to the creation of predictive, quantitative models of community function that can guide the optimization of  synthetic microbial consortia.
 

Biography: Alvaro SANCHEZ holds an undergraduate degree in Theoretical Physics by UAM in Madrid. He did his doctoral and postdoctoral training in Biophysics and Evolutionary Systems Biology at Brandeis and MIT. In 2013 he started his own group as a Rowland Fellow at Harvard. He moved the lab to Yale in 2016 as an Assistant Professor of Ecology & Evolutionary Biology, and was promoted to Associate Professor in 2021. He moved back to Spain in 2022 first as a group leader first at CNB-CSIC and then as a CSIC Professor at IBFG in Salamanca. He's received multiple grants and awards, including an ERC Consolidator Grant, a Packard Fellowship, an NIH MIRA award, a BBVA Leonardo Fellowship, and an HFSP grant.

Alvaro SANCHEZ is Professor at CSIC - Salamanca University, more details -> Alvaro SANCHEZ