The role of growth rate density-dependence SHAPE in community assembly: ECOlogical experiments and theory

Descripción del proyecto

Estudio del efecto de las interacciones ecológicas en la formación de comunidades microbianas

Una de las principales preguntas en ecología es comprender cómo se forman y persisten las comunidades microbianas diversas. Los modelos predictivos actuales se basan en rasgos simplificados, como la tasa máxima de crecimiento, y no reflejan las interacciones dinámicas entre los organismos y su entorno. Los avances recientes permiten medir con precisión la dinámica del crecimiento microbiano y predecir con mayor exactitud el comportamiento de las comunidades. En el proyecto ECOSHAPE, respaldado por las acciones Marie Skłodowska-Curie, se investigará cómo el tipo de interacciones ecológicas determina la formación de comunidades microbianas. El objetivo es establecer la dependencia de la tasa de crecimiento respecto de la densidad como un rasgo ecológico fundamental. Para ello, se estudiarán aislados microbianos en monocultivos y cocultivos por pares en distintas condiciones ambientales, se generarán conjuntos de datos sobre el ensamblaje de comunidades multiespecíficas y se desarrollarán modelos predictivos con aplicaciones en medicina e industria.

Objetivo

A fundamental challenge in ecology is to understand and predict how diverse microbial communities assemble and persist, a question also relevant for medicine, biotechnology, and ecosystem management. While decades of theory have explored coexistence, predictive models often rely on overly simplified traits, such as maximum growth rate, that fail to capture the dynamic feedback between organisms and their environment. Direct experimental evidence linking functional traits to community-level outcomes remains scarce. This project aims to elucidate how the shape of ecological interactions drives microbial community assembly by combining high-throughput experiments and theoretical models. Recent experimental advances have enabled the precise measurement of growth dynamics in diverse synthetic communities, while theoretical models, inspired by statistical physics, can disentangle interactions and predict community dynamics. I propose to elevate the functional form of growth rate density-dependence to a fundamental ecological trait that integrates resource consumption, inhibition, and facilitation into a single measurable curve. I will use high-throughput techniques to measure the shape of density-dependence profiles for a broad library of microbial isolates, both in monoculture and in pairwise co-cultures under diverse environmental conditions. I will then experimentally assemble multi-species communities and track their composition over time to generate a systematic dataset of assembly outcomes. I will develop a novel theoretical model that incorporates the empirically measured profiles to predict these experimental outcomes. Utilizing statistical physics tools, I will generate predictions capable of interpreting the experiments and scale these insights to complex ecosystems. Beyond developing a new predictive framework for community ecology, this project has the potential to indicate new strategies for engineering microbial consortia relevant for medicine and industry.