Large-scale production of plant secondary metabolites is of interest because of their application in production of many valuable products. Recent advances in the area of DNA recombinant technology has made it possible to produce these valuable compounds using microbial routes. The objective of this work was, to design a platform strain of Saccharomyces cerevisiae with improved intracellular tyrosine pools using computational modeling. This engineered yeast could be used as a host for producing important plant secondary metabolites on an industrial-scale. In this study, a combination of steady-state and dynamic modeling methods were used for strain design. Initial strain design was performed using steady-state modeling, and the predictions from steady-state modeling were prioritized for experimental validation using dynamic modeling. The final strategy proposed included deletion of PDC1, ZWF1, ARO10; over-expression of ALD6, and alleviation of tyrosine feedback resistance in shikimate pathway. Initial experiments for validation of this strategy showed promising results.

Large-scale production of plant secondary metabolites is of interest because of their application in production of many valuable products. Recent advances in the area of DNA recombinant technology has made it possible to produce these valuable compounds using microbial routes. The objective of this work was, to design a platform strain of Saccharomyces cerevisiae with improved intracellular tyrosine pools using computational modeling. This engineered yeast could be used as a host for producing important plant secondary metabolites on an industrial-scale. In this study, a combination of steady-state and dynamic modeling methods were used for strain design. Initial strain design was performed using steady-state modeling, and the predictions from steady-state modeling were prioritized for experimental validation using dynamic modeling. The final strategy proposed included deletion of PDC1, ZWF1, ARO10; over-expression of ALD6, and alleviation of tyrosine feedback resistance in shikimate pathway. Initial experiments for validation of this strategy showed promising results.

La conception de souches efficacespour la production de composés d’intérêt offredes potentiels immenses qui restent trop peu exploitéspar manque de lien entre les étapes d’optimisationde la conception de souche et celle dela conduite du bioprocédé.Pour combler ce manque, cette thèse proposeune description des bioprocédés intégrant pleinementle fonctionnement interne des microorganismesimpliqués dans la production decomposés d’intérêt. Cette description permetd’optimiser simultanément la souche et le procédépour maximiser la production d’un composéd’intérêt en respectant les contraintes attachéesà ces deux étapes.Dans un premier temps, une nouvelle classe demodélisation de bioprocédés est développée, àl’interface entre les modèles intracellulaires degestion de ressources et les modèles macroscopiquesusuellement utilisés dans la commandede bioprocédés en bioréacteurs. Dans un secondtemps, des contraintes liées à l’implémentationbiologique de la stratégie de contrôle sont intégréesau problème. Ceci permet d’obtenir uneconception plus réaliste du point de vue de l’ingénieriedes génomes. Enfin, la dernière partiede la thèse montre que la méthodologie présentéejusqu’alors sur un modèle agrégé peut êtreétendue à des représentations détaillées du comportementdes micro-organismes. / The design of efficient strains forthe production of compounds of interest offerstremendous potentials that remain insufficientlyexploited due to the lack of link between theoptimization stages of strain design and that ofbioprocess control.This thesis proposes a description of bioprocessesthat fully integrates the internal functioningof micro-organisms involved in the productionof compounds of interest. This descriptionallows the strain and process to be optimizedsimultaneously to maximize the productionof a compound of interest while respecting theconstraints attached to these two stages.First, a new bioprocess modelling class is developedat the interface between intracellular resourceallocation models and macroscopic modelscommonly used in bioprocess control. In asecond stage, constraints linked to the biologicalimplementation of the control strategy are integratedinto the problem. This provides a morerealistic genome engineering design. Finally, thelast part of the thesis shows that the methodologypresented so far on an aggregate model canbe extended to detailed representations of thebehaviour of micro-organisms.