Modeling Metabolic Networks and their Environment Interaction

Abstract : Metabolic networks allows to the user the construction of detailed models using high resolution ‘omics datasets. In particular, Constrained Based Models (CBMs) are used to obtain quantitative predictions from metabolic models. CBMs have been successfully applied to a wide range of problems for the last 20 years to several aspects of microbial physiology. Main objective of present thesis is to use CBMs as a modeling technique in Microbial Ecology context. In particular, both metabolic network effects over the environment and effects of environmental variables over physiology are explored using CBMs. In the first section, applications of CBMs to single metabolic networks are explored. First a novel application of CBMs is used to study gene insertion such they are optimal to maximize the growth rate. Next, effects of environmental conditions in a chemostat culture in metabolic network are assed by classical CBMs approaches and contrasted with experimental observations. Finally, a new CBMs is developed to determinate environmental conditions such as they favor gene loose. Second section deals with interactions between multiple metabolic networks. The use of compartments to represent different microorganisms is first justified. Next, a revision of existent approaches in the literature is carried. After this revision, a new CBM based in MultiObjective Optimization for microbial ecosystem is developed. Set of works developed in present thesis is expected to help filling the gap between Microbial Ecology and Constraint Based Modeling.
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Marko Abarca. Modeling Metabolic Networks and their Environment Interaction . Bioinformatics [q-bio.QM]. Université de Nantes, 2017. English. ⟨tel-01713629⟩

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