Thesis presented November 28, 2013
Abstract : Metabolic engineering aims at designing high performance strains to produce compounds of interest. For this purpose and to predict metabolic fluxes, GEnome-scale Models (GEMs) are developed, integrating multi-OMICS experimental data. Particularly, accurate enzymes amounts are crucial data to determine kinetic parameters but remain difficult to obtain in a multiplexed and accurate fashion. In this Ph. D work we developed a highly accurate and multiplexed workflow for generating quantitative proteomic data, using full length protein labelled standards coupled to a mass spectrometry-based technique called Selected Reaction Monitoring (SRM). This workflow was applied to
E. coli strains: a wild-type and two other strains optimized for higher NADPH production. Results demonstrated that such data combined with measurements of metabolic fluxes, allow apprehending different levels of regulation, namely enzyme abundance and activity. In addition, accurate measurement of enzyme concentration is a key technology for the development of predictive kinetic models in the context of metabolic engineering. Finally, performances of a new technology called Parallel Reaction Monitoring (PRM) were explored. PRM mode, in our study case, can be an alternative to SRM, to increase again more multiplexing capabilities.
Keywords: Metabolic engineering, modeling, targeted proteomic, SRM, PRM, accurate quantification, protein standards production
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