Soutenance de thèse: Investigating host-microbiota cooperation with gap-filling optimization problems

Clémence FRIOUX
Monday, November 19, 2018 - 14:00
Room Métivier
Talk abstract: 

Systems biology relies on computational biology to integrate knowledge and data, for a better understanding of organisms’ physiology. Challenges reside in the applicability of methods and tools to non-model organisms, for which data is limited, and more generally to host-microbiota systems. Understanding the interactions in the later is an objective of systems ecology. Metabolic networks are a useful solution to model them functionally. In this direction, several semantics exist and are at the core of metabolic network reconstruction, particularly for their refinement through gap-filling. Gap-filling is a combinatorial problem that aims at selecting reactions in databases to ensure the feasibility of a behaviour by the model. It is a very crucial step due to various pitfalls: model overfitting, false positive, choice of functionality semantics. This thesis aimed at better understand these limits and propose solutions to them. As a first results part, we benchmarked several gap-filling algorithms to assess the value of graph-based semantics with respect to the constraint based one. Then we propose a hybrid gap-filling method that reconciles both semantics. Finally, we extended the gap-filling problem towards the selection of communities and the screening of metabolic functions within large microbiotas. Problems modelled and solved during this PhD were applied to brown algae metabolism and to the human gut microbiota.