Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden.
Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden.
Nat Commun. 2022 Jun 30;13(1):3766. doi: 10.1038/s41467-022-31421-1.
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.
基因组规模代谢模型(GEMs)已被广泛用于定量探索基因型和表型之间的关系。通过 GECKO 工具箱,首次实现了将酶限制和蛋白质组学数据简化集成到此类模型中,从而可以研究受蛋白质限制的表型。在这里,我们升级了该工具包,以便为任何具有兼容 GEM 重建的生物体增强具有酶和蛋白质组学限制的模型。有了这个工具,我们为 budding 酵母 Saccharomyces cerevisiae、Yarrowia lipolytica 和 Kluyveromyces marxianus 生成了受酶限制的模型,通过整合蛋白质组学数据来研究它们对几种应激因素的长期适应。预测表明,氨基酸代谢中酶的上调和高饱和度在生物体和条件中普遍存在,这表明在应激和营养受限条件下,微生物生长的细胞目标是代谢稳健性,而不是最佳蛋白质利用。GECKO 的功能通过一个自动框架得到扩展,用于连续和版本控制更新受酶限制的 GEM,还为 Escherichia coli 和 Homo sapiens 生成了此类模型。在这项工作中,我们促进了受酶限制的 GEM 在基础科学、代谢工程和合成生物学方面的应用。