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Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0
被引:64
作者:
Domenzain, Ivan
[1
,2
]
Sanchez, Benjamin
[3
,4
]
Anton, Mihail
[5
]
Kerkhoven, Eduard J.
[2
]
Millan-Oropeza, Aaron
[6
]
Henry, Celine
[6
]
Siewers, Verena
[2
]
Morrissey, John P.
[7
,8
]
Sonnenschein, Nikolaus
[3
]
Nielsen, Jens
[1
,2
,9
]
机构:
[1] Chalmers Univ Technol, Dept Biol & Biol Engn, SE-41296 Gothenburg, Sweden
[2] Chalmers Univ Technol, Novo Nordisk Fdn Ctr Biosustainabil, SE-41296 Gothenburg, Sweden
[3] Tech Univ Denmark, Dept Biotechnol & Biomed, DK-2800 Lyngby, Denmark
[4] Tech Univ Denmark, Novo Nordisk Fdn Ctr Biosustainabil, DK-2800 Lyngby, Denmark
[5] Chalmers Univ Technol, Dept Biol & Biol Engn, Natl Bioinformat Infrastruc Sweden Sci Life Lab, Kemivagen 10, SE-41258 Gothenburg, Sweden
[6] Univ Paris Saclay, MICALIS Inst, INRAE, Plateforme Analyse Proteom Paris Sud Ouest PAPPSO, F-78350 Jouy En Josas, France
[7] Univ Coll Cork, Sch Microbiol, Environm Res Inst, Cork T12 K8AF, Ireland
[8] Univ Coll Cork, APC Microbiome Ireland, Cork T12 K8AF, Ireland
[9] BioInnovat Inst, Ole Maaloes Vej 3, DK-2200 Copenhagen, Denmark
基金:
欧盟地平线“2020”;
关键词:
ESCHERICHIA-COLI;
ACID PRODUCTION;
BALANCE;
RESOURCE;
SEQUENCE;
PROTEIN;
YEAST;
D O I:
10.1038/s41467-022-31421-1
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
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.
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页数:13
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