Metabolic modeling of microorganisms and dynamics of microbial communities in the food industry

Abstract

In this thesis, we initially evaluated a wide range of reconstruction tools to determine their optimal performance in various cases. By utilizing the appropriate reconstruction tools, we successfully created a high-quality, genome-scale metabolic model for Lactobacillus delbrueckii subsp. bulgaricus, a bacterium commonly employed in yogurt production. Furthermore, we incorporated proteomic data into the model, acquired from two relevant conditions: growth on casein or amino acids. Through the incorporation of enzymatic capacity constraints into the model, we captured the emergence of glucose secretion as a system property, a phenomenon not discernible through the genome-scale model alone. Concluding our study, we introduce two innovative approaches to simulate the dynamics of co-evolved microbial communities. These methodologies are particularly suitable for species that release costly compounds into the surrounding medium due to co-evolution, as observed in the context of yogurt production. With this thesis, we have propelled the domain of systems biology as applied to the food industry, utilizing yogurt production as our focal case study.

Global sensitivity analysis for investigation of bacterial physiology in complex media with FBA-PRCC

“…But that type of model identification impose some limitations to the interpretation of the model results in nutrient-rich set up. The rich environment is very common as in biotechnological application, for example in the food industry (Mendoza Farías 2023;Qiu et al 2023) and when bacteria participate in the community and interact with its members by production and consumption of nutrients (Kost et al 2023). The interaction between pathways utilizing different substrates make solution space more complex, and increase number of non-unique solutions to the optimization FBA problem.…”