A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics
Autor: | Pierre Salvy, Ljubisa Miskovic, Maria Masid, Vassily Hatzimanikatis, Maxime Curvat, Omid Oftadeh |
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Rok vydání: | 2021 |
Předmět: |
Computer science
fermentative capacity growth Science enzymes Saccharomyces cerevisiae Genome scale Thermodynamics Industrial biotechnology Bioenergetics encyclopedia Models Biological Article ribosomal-proteins Gene Expression Regulation Fungal Protein biosynthesis Escherichia coli Computational models Computer Simulation Biomass Overflow metabolism Gene database Biomass composition Genome biology Biochemical networks gibbs energies RNA balance Metabolism Expression (computer science) biology.organism_classification cultures Glucose Phenotype Metabolic Engineering Computer modelling escherichia-coli Flux (metabolism) Biological network Metabolic Networks and Pathways Biotechnology |
Zdroj: | Nature Communications Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021) |
ISSN: | 2041-1723 |
Popis: | Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research. Formulating metabolic networks mathematically can help researchers study metabolic diseases and optimize the production of industrially important molecules. Here, the authors propose a framework that allows to model eukaryotic metabolism considering gene expression and thermodynamic constraints. |
Databáze: | OpenAIRE |
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