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Clémence Dupont Thibert

Metabolic modeling of the industrial oleaginous microalga Microchloropsis gaditana

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Published on 15 December 2023
Thesis presented Decembre 15, 2023

Abstract:
With the ongoing ecological and energy transitions, microalgae have attracted increasing interest as potential resources for a wide range of industrial applications. Among these organisms, oleaginous strains such as Microchloropsis gaditana stand out as promising candidates for biodiesel production, due to their capacity to accumulate large amounts of lipids, particularly triglycerides. However, several technological challenges remain before achieving industrial scales. To overcome these challenges, an in-depth understanding of the metabolism, specifically lipid metabolism of these strains is required. It is within this framework of research into the characterization and understanding of lipid metabolism of M. gaditana that this PhD project is situated.
First, lipid biosynthesis and degradation pathways of a genome-scale metabolic model of M. gaditana, available before of the PhD, were meticulously corrected by incorporating the most advanced knowledge of lipid metabolism from LPCV specialists and the literature. Then, BioModTool, a Python package, was developed to facilitate addition of biomass objective functions into metabolic models from experimental data such as glycerolipidomes. BioModTool was used to integrate the detailed lipid profile of a laboratory-generated mutant, the acsbg mutant, into M. gaditana metabolic model. This mutant exhibits an interesting phenotype, notably with an eight-fold increase in triglycerides accumulation compared to the wild-type strain. Flux distributions were simulated for this mutant and compared with fluxes predicted for the wild-type strain. The results of this analysis confirm the conclusions of the experimental analysis of the acsbg mutant.
The approaches developed and the results obtained in this project, hold significant promise for enhancing our understanding of lipid metabolism in M. gaditana. To date, the model developed in this study stands as one of the first microalgal models to incorporate such detailed lipid metabolism. As a result, it constitutes a valuable tool for a wide range of applications traditionally performed with genome-scale metabolic models. Deciphering lipid metabolism and in silico approaches are needed to industrial exploitation of microalgae for diverse applications, including biofuel production. The metabolic model developed during this PhD will enable the optimization of cultivation processes and the design of new strains with enhanced lipid production.

Keywords:
Genome-scale metabolic modeling, lipid metabolism, microalga, Microchloropsis gaditana, biofuel