000117626 001__ 117626
000117626 005__ 20240319081007.0
000117626 0247_ $$2doi$$a10.3389/fmolb.2022.855735
000117626 0248_ $$2sideral$$a129175
000117626 037__ $$aART-2022-129175
000117626 041__ $$aeng
000117626 100__ $$aLázaro Ibáñez, J.$$uUniversidad de Zaragoza
000117626 245__ $$aCombination of Genome-Scale Models and Bioreactor Dynamics to Optimize the Production of Commodity Chemicals
000117626 260__ $$c2022
000117626 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117626 5203_ $$aThe current production of a number of commodity chemicals relies on the exploitation of fossil fuels and hence has an irreversible impact on the environment. Biotechnological processes offer an attractive alternative by enabling the manufacturing of chemicals by genetically modified microorganisms. However, this alternative approach poses some important technical challenges that must be tackled to make it competitive. On the one hand, the design of biotechnological processes is based on trial-and-error approaches, which are not only costly in terms of time and money, but also result in suboptimal designs. On the other hand, the manufacturing of chemicals by biological processes is almost exclusively carried out by batch or fed-batch cultures. Given that batch cultures are expensive and not easy to scale, technical means must be developed to make continuous cultures feasible and efficient. In order to address these challenges, we have developed a mathematical model able to integrate in a single model both the genome-scale metabolic model for the organism synthesizing the chemical of interest and the dynamics of the bioreactor in which the organism is cultured. Such a model is based on the use of Flexible Nets, a modeling formalism for dynamical systems. The integration of a microscopic (organism) and a macroscopic (bioreactor) model in a single net provides an overall view of the whole system and opens the door to global optimizations. As a case study, the production of citramalate with respect to the substrate consumed by E. coli is modeled, simulated and optimized in order to find the maximum productivity in a steady-state continuous culture. The predicted computational results were consistent with the wet lab experiments. Copyright © 2022 Lázaro, Jansen, Yang, Torres-Acosta, Lye, Oliver and Júlvez.
000117626 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-113969RB-I00
000117626 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000117626 590__ $$a5.0$$b2022
000117626 592__ $$a1.233$$b2022
000117626 591__ $$aBIOCHEMISTRY & MOLECULAR BIOLOGY$$b84 / 285 = 0.295$$c2022$$dQ2$$eT1
000117626 593__ $$aBiochemistry$$c2022$$dQ1
000117626 593__ $$aBiochemistry, Genetics and Molecular Biology (miscellaneous)$$c2022$$dQ1
000117626 593__ $$aMolecular Biology$$c2022$$dQ2
000117626 594__ $$a4.8$$b2022
000117626 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117626 700__ $$aJansen, G.
000117626 700__ $$aYang, Y.
000117626 700__ $$aTorres-Acosta, M.
000117626 700__ $$aLye, G.
000117626 700__ $$aOliver, S. G.
000117626 700__ $$0(orcid)0000-0002-7093-228X$$aJúlvez Bueno, J.$$uUniversidad de Zaragoza
000117626 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000117626 773__ $$g9 (2022), 855735 [24 pp]$$pFront. mol. biosci.$$tFrontiers in Molecular Biosciences$$x2296-889X
000117626 8564_ $$s2191803$$uhttps://zaguan.unizar.es/record/117626/files/texto_completo.pdf$$yVersión publicada
000117626 8564_ $$s2109580$$uhttps://zaguan.unizar.es/record/117626/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117626 909CO $$ooai:zaguan.unizar.es:117626$$particulos$$pdriver
000117626 951__ $$a2024-03-18-14:42:31
000117626 980__ $$aARTICLE