Integrating Kinetic Models with Genome-Scale Constraints to Explain Yeast-Based Batch Fermentation

Biotechnological processes utilizing cell factories hold great promise for producing various compounds through fermentation. Yeast species have emerged as crucial players in this field, contributing to producing pharmaceuticals, food ingredients, and beverages through batch fermentation. However, the effectiveness of these processes relies on optimizing fermentation parameters, including yeast species or strains, medium composition, and extracellular abiotic conditions. This work addresses the multi-scale modeling of batch fermentation, highlighting the need for suitable approaches to describe primary and secondary metabolism. We show that combining dynamic mechanistic and genome-scale constrained models can do the job, and we illustrate our point with some recent results on modeling batch fermentation processes led by Saccharomyces yeast species. The proposed in silico modeling may facilitate fine-tuning fermentation conditions and manipulating metabolic pathways, thus generating sustainable alternatives in pharmaceuticals and food production and driving the progression towards a greener future.