Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0
Abstract Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-31421-1 |
| _version_ | 1827377242120912896 |
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| author | Iván Domenzain Benjamín Sánchez Mihail Anton Eduard J. Kerkhoven Aarón Millán-Oropeza Céline Henry Verena Siewers John P. Morrissey Nikolaus Sonnenschein Jens Nielsen |
| author_facet | Iván Domenzain Benjamín Sánchez Mihail Anton Eduard J. Kerkhoven Aarón Millán-Oropeza Céline Henry Verena Siewers John P. Morrissey Nikolaus Sonnenschein Jens Nielsen |
| author_sort | Iván Domenzain |
| collection | DOAJ |
| description | Abstract Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens. In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes. |
| first_indexed | 2024-03-08T12:36:13Z |
| format | Article |
| id | doaj.art-2c658bb1c7854350acfe1f06f530ec04 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-08T12:36:13Z |
| publishDate | 2022-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-2c658bb1c7854350acfe1f06f530ec042024-01-21T12:25:45ZengNature PortfolioNature Communications2041-17232022-06-0113111310.1038/s41467-022-31421-1Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0Iván Domenzain0Benjamín Sánchez1Mihail Anton2Eduard J. Kerkhoven3Aarón Millán-Oropeza4Céline Henry5Verena Siewers6John P. Morrissey7Nikolaus Sonnenschein8Jens Nielsen9Department of Biology and Biological Engineering, Chalmers University of TechnologyDepartment of Biotechnology and Biomedicine, Technical University of DenmarkDepartment of Biology and Biological Engineering, Chalmers University of TechnologyDepartment of Biology and Biological Engineering, Chalmers University of TechnologyPlateforme d’analyse protéomique Paris Sud-Ouest (PAPPSO), INRAE, MICALIS Institute, Université Paris-SaclayPlateforme d’analyse protéomique Paris Sud-Ouest (PAPPSO), INRAE, MICALIS Institute, Université Paris-SaclayDepartment of Biology and Biological Engineering, Chalmers University of TechnologySchool of Microbiology, Environmental Research Institute and APC Microbiome Ireland, University College CorkDepartment of Biotechnology and Biomedicine, Technical University of DenmarkDepartment of Biology and Biological Engineering, Chalmers University of TechnologyAbstract Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens. In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes.https://doi.org/10.1038/s41467-022-31421-1 |
| spellingShingle | Iván Domenzain Benjamín Sánchez Mihail Anton Eduard J. Kerkhoven Aarón Millán-Oropeza Céline Henry Verena Siewers John P. Morrissey Nikolaus Sonnenschein Jens Nielsen Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 Nature Communications |
| title | Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 |
| title_full | Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 |
| title_fullStr | Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 |
| title_full_unstemmed | Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 |
| title_short | Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0 |
| title_sort | reconstruction of a catalogue of genome scale metabolic models with enzymatic constraints using gecko 2 0 |
| url | https://doi.org/10.1038/s41467-022-31421-1 |
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