Journal article Open Access

Improving the phenotype predictions of a yeast genome?scale metabolic model by incorporating enzymatic constraints

Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant; Lahtvee, Petri-Jaan; Kerkhoven, Eduard J; Nielsen, Jens


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    <subfield code="u">Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China</subfield>
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    <subfield code="u">Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.</subfield>
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    <subfield code="u">Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.</subfield>
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    <subfield code="u">Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.</subfield>
    <subfield code="a">Kerkhoven, Eduard J</subfield>
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    <subfield code="u">Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark</subfield>
    <subfield code="a">Nielsen, Jens</subfield>
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    <subfield code="u">Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.</subfield>
    <subfield code="a">Sanchez, Benjamin J.</subfield>
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    <subfield code="a">Improving the phenotype predictions of a yeast genome?scale metabolic model by incorporating enzymatic constraints</subfield>
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    <subfield code="a">Model-Based Construction And Optimisation Of Versatile Chassis Yeast Strains For Production Of Valuable Lipid And Aromatic Compounds</subfield>
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    <subfield code="a">&lt;p&gt;Genome‐scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a &lt;em&gt;Saccharomyces cerevisiae &lt;/em&gt;GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model‐based design in metabolic engineering.&lt;/p&gt;</subfield>
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