117626 20240319081007.0 doi 10.3389/fmolb.2022.855735 sideral 129175 ART-2022-129175 eng Lázaro Ibáñez, J. Universidad de Zaragoza Combination of Genome-Scale Models and Bioreactor Dynamics to Optimize the Production of Commodity Chemicals 2022 Access copy available to the general public Unrestricted The current production of a number of commodity chemicals relies on the exploitation of fossil fuels and hence has an irreversible impact on the environment. Biotechnological processes offer an attractive alternative by enabling the manufacturing of chemicals by genetically modified microorganisms. However, this alternative approach poses some important technical challenges that must be tackled to make it competitive. On the one hand, the design of biotechnological processes is based on trial-and-error approaches, which are not only costly in terms of time and money, but also result in suboptimal designs. On the other hand, the manufacturing of chemicals by biological processes is almost exclusively carried out by batch or fed-batch cultures. Given that batch cultures are expensive and not easy to scale, technical means must be developed to make continuous cultures feasible and efficient. In order to address these challenges, we have developed a mathematical model able to integrate in a single model both the genome-scale metabolic model for the organism synthesizing the chemical of interest and the dynamics of the bioreactor in which the organism is cultured. Such a model is based on the use of Flexible Nets, a modeling formalism for dynamical systems. The integration of a microscopic (organism) and a macroscopic (bioreactor) model in a single net provides an overall view of the whole system and opens the door to global optimizations. As a case study, the production of citramalate with respect to the substrate consumed by E. coli is modeled, simulated and optimized in order to find the maximum productivity in a steady-state continuous culture. The predicted computational results were consistent with the wet lab experiments. Copyright © 2022 Lázaro, Jansen, Yang, Torres-Acosta, Lye, Oliver and Júlvez. info:eu-repo/grantAgreement/ES/MICINN/PID2020-113969RB-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 5.0 2022 BIOCHEMISTRY & MOLECULAR BIOLOGY 84 / 285 = 0.295 2022 Q2 T1 1.233 2022 Biochemistry 2022 Q1 Biochemistry, Genetics and Molecular Biology (miscellaneous) 2022 Q1 Molecular Biology 2022 Q2 4.8 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Jansen, G. Yang, Y. Torres-Acosta, M. Lye, G. Oliver, S. G. Júlvez Bueno, J. Universidad de Zaragoza (orcid)0000-0002-7093-228X 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 9 (2022), 855735 [24 pp] Front. mol. biosci. Frontiers in Molecular Biosciences 2296-889X 2191803 http://zaguan.unizar.es/record/117626/files/texto_completo.pdf Versión publicada 2109580 http://zaguan.unizar.es/record/117626/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:117626 articulos driver 2024-03-18-14:42:31 ARTICLE