Towards a framework for precise inference of microbial community stability: from models to experiment design

Abstract

The human gut microbiome is a very diverse and complex ecosystem with many species interacting among themselves and with their environment. It is known to be connected to multiple aspects of the host's health, but it still needs more precise characterization to generate confident predictions of its behavior to help in the development of new techniques for disease prevention, diagnosis, and therapy. There has been a recent increase in the effort for sequencing and culturing gut bacterial species, which will lead to the generation of more data on the dynamics of gut microorganisms. However, we need a robust framework to process all this data and make predictions with confidence. This project intends to be a contribution on the formalization of a framework for gut microbiome data analysis, focusing on model selection for data analysis and its consequences for experiment design. We will be working with multiple adaptations of the generalized Lotka-Volterra model, testing different parameter estimation algorithms, and doing the identifiability analysis of the different models in order to determine the more appropriate mathematical tools and the optimal experiment design for different scenarios. (AU)