Étude de la coopération hôte-microbiote par des problèmes d'optimisation basés sur la complétion de réseaux métaboliques

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 instance in marine biology. Sequencing advances and the growing importance of elucidating microbiotas’ roles, have led to an increased interest into these organisms. This thesis focuses on the modeling of the metabolism through networks, and of its functionality using graphs and constraints semantics. In particular, a first part presents work on gap-filling metabolic networks in the context of non-model organisms. A graph-based method is benchmarked and validated and a hybrid one is developed using Answer Set Programming (ASP) and linear programming. Such gap-filling is applied on algae and extended to decipher putative interactions between Ectocarpus siliculosus and a symbiotic bacterium. In this direction, the second part of the thesis aims at proposing formalisms and implementation of a tool for selecting and screening communities of interest within microbiotas. It enables to scale to large microbiotas and, with a two-step approach, to suggest symbionts that fit the desired objective. The modeling supports the computation of exchanges, and solving can cover the whole solution space. Applications are presented on the human gut microbiota and the selection of bacterial communities for a brown alga. Altogether, this thesis proposes modeling, software and biological applications using graph-based semantics to support the elaboration of hypotheses for elucidating the metabolism of organisms.La biologie des systèmes intègre données et connaissances par des méthodes bioinformatiques, afin de mieux appréhender la physiologie des organismes. Une problématique est l’applicabilité de ces techniques aux organismes non modèles, au centre de plus en plus d’études, grâce aux avancées de séquençage et à l’intérêt croissant de la recherche sur les microbiotes. Cette thèse s’intéresse à la modélisation du métabolisme par des réseaux, et de sa fonctionnalité par diverses sémantiques basées sur les graphes et les contraintes stoechiométriques. Une première partie présente des travaux sur la complétion de réseaux métaboliques pour les organismes non modèles. Une méthode basée sur les graphes est validée, et une seconde, hybride, est développée, en programmation par ensembles réponses (ASP). Ces complétions sont appliquées à des réseaux métaboliques d’algues en biologie marine, et étendues à la recherche de complémentarité métabolique entre Ectocarpus siliculosus et une bactérie symbiotique. En s’appuyant sur les méthodes de complétion, la seconde partie de la thèse vise à proposer et implémenter une sélection de communautés à l’échelle de grands microbiotes. Une approche en deux étapes permet de suggérer des symbiotes pour l’optimisation d’un objectif donné. Elle supporte la modélisation des échanges et couvre tout l’espace des solutions. Des applications sur le microbiote intestinal humain et la sélection de bactéries pour une algue brune sont présentées. Dans l’ensemble, cette thèse propose de modéliser, développer et appliquer des méthodes reposant sur des sémantiques de graphe pour élaborer des hypothèses sur le métabolisme des organismes

SAT-Based Metabolics Pathways Analysis without Compilation

International audienc

Endoluminal weight loss and metabolic therapies: current and future techniques

Background The majority of obese patients remain untreated, creating the need for an effective, well-tolerated, safe and appealing therapeutic approach. Endoluminal therapies have the potential to fulfil this unmet clinical need, though traditionally, these approaches mimic the restrictive elements of bariatric surgery but ignore the complex physiologic and neurohormonal mechanisms responsible for bariatric surgeries’ weight-independent reduction in metabolic comorbidities. Hypothesis The overarching hypothesis of this thesis was that although endoluminal gastric space occupying and restrictive interventions result in weight loss, weight-independent improvements in obesity related comorbidities require eradication of the gastric mucosa. Aims The aims of this thesis were to assess the efficacy and safety of the intragastric balloon (IGB) and endoscopic sleeve gastroplasty (ESG), and to evaluate whether gastric mucosal devitalization (GMD) is a potential therapeutic approach to treat patients with obesity. Methods Gastric space occupation and gastric volume reduction were modelled using IGB and ESG, respectively. To evaluate the effects of GMD (without alteration in gastric volume), high fat diet rats were compared to GMD, laparoscopic sleeve gastrectomy (LSG), and sham rats. To determine the translatability of GMD, the feasibility, efficacy and safety of GMD was compared to LSG and sham in a porcine model. Results The clinical research demonstrated that IGBs and ESG result in clinically meaningful weight loss with an acceptable safety profile. However, neither produced improvements in metabolic parameters that were disproportionate to the weight loss observed. GMD resulted in a reduction in body weight and visceral adiposity, improved serum lipid and glucose profiles, and reduced liver lipid content. GMD also resulted in a significant reduction in blood pressure, plasma renin activity and cardiac as well as aortic lipid droplet deposition. In a porcine model, GMD reduced visceral adiposity, with outcomes greater than what would be expected from weight loss alone. Conclusions Weight-independent metabolic improvements can be achieved by selecting the gastric mucosa as a therapeutic target; therefore, endoscopic GMD is a new potential approach for the management of obesity