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Detalle de: Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants

Title Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants
Abstract

This work presents a methodology to evaluate the bioenergetic feasibility of alternative metabolic pathways for a given microbial conversion, optimising their energy yield and driving forces as a function of the concentration of metabolic intermediates. The tool, based on thermodynamic principles and multi-objective optimisation, accounts for pathway variants in terms of different electron carriers, as well as energy conservation (proton translocating) reactions within the pathway. The method also accommodates other constraints, some of them non-linear, such as the balance of conserved moieties. The approach involves the transformation of the maximum energy yield problem into a multi-objective mixed-integer linear optimisation problem which is then subsequently solved using the epsilon-constraint method, highlighting the trade-off between yield and rate in metabolic reactions. The methodology is applied to analyse several pathway alternatives occurring during propionate oxidation in anaerobic fermentation processes, as well as to the reverse TCA cycle pathway occurring during autotrophic microbial CO 2 fixation. The results obtained using the developed methodology match previously reported literature and bring about insights into the studied pathways.

Apa Reference Taha, A., Patón, M., Penas, D. R., Banga, J. R., & Rodríguez, J. (2023). Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants. PLOS Computational Biology, 19(7), e1011264. 10.1371/journal.pcbi.1011264
Doi 10.1371/journal.pcbi.1011264
Publication Date 6 Jul 2023
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Pathway analysis
Research Groups Computational Biology Lab at MBG
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