Investigation of the performance of fermentation processes using a mathematical model including effects of metabolic bottleneck and toxic product on cells.
A number of recent research studies have focused on theoretical and experimental investigation of a bottleneck in a metabolic reaction network. However, there is no study on how the bottleneck affects the performance of a fermentation process when a product is highly toxic and remarkably influences the growth and death of cells. The present work therefore studies the effect of bottleneck on product concentrations under different product toxicity conditions. A generalized bottleneck model in a fed-batch fermentation is constructed including both the bottleneck and the product influences on cell growth and death. The simulation result reveals that when the toxic product strongly influences the cell growth and death, the final product concentration is hardly changed even if the bottleneck is removed, whereas it is markedly changed by the degree of product toxicity. The performance of an ethanol fermentation process is also discussed as a case example to validate this result. In conclusion, when the product is highly toxic, one cannot expect a significant increase in the final product concentration even if removing the bottleneck; rather, it may be more effective to somehow protect the cells so that they can continuously produce the product.
Sriyudthsak
Kansuporn
K
Department of Bio-System Design, Bio-Architecture Center, Kyushu University, Hakozaki, Fukuoka 812-8581, Japan.
Shiraishi
Fumihide
F
D000465:Algorithms; D001685:Biological Factors / Q000096:biosynthesis* / Q000494:pharmacology / Q000633:toxicity*; D016923:Cell Death / Q000187:drug effects; D049109:Cell Proliferation / Q000187:drug effects; D003198:Computer Simulation; D000431:Ethanol / Q000378:metabolism / Q000494:pharmacology; D005285:Fermentation / Q000187:drug effects* / Q000502:physiology*; D007700:Kinetics; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D050296:Microbial Viability / Q000187:drug effects; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000187:drug effects / Q000378:metabolism
D001685:Biological Factors; D000431:Ethanol