Analyzing the Fluxome of P. chrysogenum in an Industrial Environment - Workflows for 13C Metabolic Flux Analysis in Complex Systems

Metabolic engineering is a targeted and knowledge-based approach to improve production capabilities of microorganisms. It aims at increasing metabolic reaction rates towards product formation to obtain economic production processes. The fluxome, i.e. the computation of all metabolic reaction rates, is one cornerstone of metabolic engineering. For fluxomics, the study of intracellular reaction rates, several methods have been established. The most powerful one, C-metabolic flux analysis (13C-MFA), uses isotopically labeled substrates which are fed to cells. Emerging labeling patterns in the synthesized metabolites are measured by high-precision measurement devices like mass spectrometry. From the measured labeling pattern, the intracellular reaction rates can be estimated by mathematical modeling. The present work faces 13C-MFA of complex systems. The non-model organism P.chrysogenum strain BCB1 is investigated in industrial environment with special focus on penicillin V production. The term “complex” is not only referring to the growth behavior of P.chrysogenum, but also includes side-product formation and compartmentalization of metabolism. This thesis aims at the transfer of 13C-MFA from a scientific application in a nearly ideal environment to an industrial standard. For this reason, the prerequisites needed and compromises made for 13C-MFA work-flow are thoroughly discussed and adaption of the industrial process is highlighted. To systematically gain knowledge about the organism, the state-of-the-art work-flow for 13C-MFA is presented, pitfalls and limitations of the technique are revealed for a close-to-industrial context. The technology is established using chemostat experiments. In a second step, close-to-industrial fed-batch cultivations are investigated and the first quantitative flux map of P.chrysogenum for industrial process conditions is presented. Therefore, a kinetic model was implemented for the processes aiming at an accurate extracellular rate estimation. To apply 13C-MFA, stationary labeling patterns are derived from time resolved labeling data by extrapolation and correction for natural abundance. Large scale metabolic models for P.chrysogenum were built based on experimental, literature and database knowledge. Strain specific measurements of biomass compounds were introduced into the models. Using the constructed model, the first global sensitivity analysis was performed for 13C-MFA to evaluate its suitability for flux elucidation. Finally, 13C-MFA was conducted to gain knowledge about intracellular fluxes within P.chrysogenum BCB1 and experimental design was used to increase the information content of isotope labeling experiments. The conventional experimental design tools were extended by diversification-driven and multi-objective experimental design. The design space was explored and compared to single-objective applications. Thereby optimal, yet economic, experimental designs can be planed, fighting shortcomings of conventional techniques. From the results of the deduced flux maps, hints for strain and process development are derived. One major finding was that the flux in oxidative pentose phosphate pathway is strongly influenced by the biomass formation, leading to carefully balanced growth in cultivations and strain optimization

Exploration of multi-objective experimental design spaces for 13C metabolic flux analysis

, May 7-11 2017, Favrholm Campus, Hillerod, Denmar