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 GEMs was first enabled by the GECKO method, allowing the study of phenotypes constrained by protein limitations. Here, we upgraded the GECKO toolbox in order to enhance models with enzyme and proteomics constraints for any organism with an available GEM reconstruction. With this, enzyme-constrained models (ecModels) for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus were generated, aiming to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions revealed that upregulation and high saturation of enzymes in amino acid metabolism were found to be 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 was further developed by the implementation of an automated framework for continuous and version-controlled update of ecModels, which was validated by producing additional high-quality ecModels for Escherichia coli and Homo sapiens. These efforts aim to facilitate the utilization of ecModels in basic science, metabolic engineering and synthetic biology purposes.

Adaptations in metabolism and protein translation give rise to the Crabtree effect in yeast

“…This method extends the classical flux balance analysis (FBA) (22) approach used for GEMs by incorporating a detailed description of enzymatic demands of metabolic reactions, while also allowing for integration of protein abundance data. We used the GECKO toolbox (23) to generate condition-specific models of two recently published ec models for S. cerevisiae and K. marxianus by constraining them with experimentally measured exchange fluxes, growth rates, and protein levels and used the models to predict the flux distribution under these conditions (Fig. 2A).…”

“…FBA. The ec consensus yeast metabolic model version 8.3.4 and the eciSM966 K. marxianus models used in this study were obtained from a GitHub repository hosted within the group (https://github.com/SysBioChalmers/ecModels) (23). Condition-specific models were created by incorporating and constraining the models with experimental measurements of protein content, metabolite exchange rates, and metabolic enzyme abundances using the GECKO toolbox (23).…”

“…The ec consensus yeast metabolic model version 8.3.4 and the eciSM966 K. marxianus models used in this study were obtained from a GitHub repository hosted within the group (https://github.com/SysBioChalmers/ecModels) (23). Condition-specific models were created by incorporating and constraining the models with experimental measurements of protein content, metabolite exchange rates, and metabolic enzyme abundances using the GECKO toolbox (23). This included scaling the coefficient of protein pseudoreaction to equal the measured protein content, as well as scaling the carbohydrate coefficient to maintain an equivalent amount of mass in the biomass pseudoreaction (9).…”

ECMpy, a Simplified Workflow for Constructing Enzymatic Constrained Metabolic Network Model

“…However, this calibration workflow is time consuming, going through protein pool calibration, manual kcat adjustment and automated kcat calibration, and there are some unreasonable places, such as the manual correction is simply expanded by 10 times or reduced by 10 times. In recently, GECKO 2.0 provided an automatic procedure, in which the top enzymatic limitation on growth rate is identified and its correspondent kcat is then iteratively replaced by the highest one available in BRENDA for the given enzyme class until the growth rate fit is normal [41]. Currently, we propose a simpler calibration process that…”

Genome-scale modeling of yeast metabolism: retrospectives and perspectives

“…Such enzyme-constrained models were also generated for some other yeast species including Y. lipolytica and K. marxianus with the release of the upgraded GECKO toolbox (Domenzain et al . 2021b ).…”