A novel yeast hybrid modeling framework integrating Boolean and enzyme-constrained networks enables exploration of the interplay between signaling and metabolism

• Published in: PLoS computational biology 2021-04, Vol.17 (4), p.e1008891-e1008891
• Main Authors: Österberg, Linnea, Domenzain, Iván, Münch, Julia, Nielsen, Jens, Hohmann, Stefan, Cvijovic, Marija
• Format: Article
• Language: English
• Subjects: Aging; Algebra, Boolean; Analysis; Biochemistry & Molecular Biology; Biology; Biology and Life Sciences; Biosynthesis; Boolean; Boolean algebra; Brewer's yeast; Carbon; Computer and Information Sciences; Constraints; Dextrose; Diabetes mellitus; Diabetes mellitus (non-insulin dependent); Enzymes; Fermentation; Gene expression; Genomes; Glucose; Isoenzymes; Matematik; Mathematical & Computational Biology; Mathematics; Metabolism; Metabolites; Nitrogen; Nutrients; Physical Sciences; Proteins; Proteomics; Robust control; Signaling; Transcription; Transcription factors; Yeast fungi; Yeasts
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1008891

The interplay between nutrient-induced signaling and metabolism plays an important role in maintaining homeostasis and its malfunction has been implicated in many different human diseases such as obesity, type 2 diabetes, cancer, and neurological disorders. Therefore, unraveling the role of nutrients as signaling molecules and metabolites together with their interconnectivity may provide a deeper understanding of how these conditions occur. Both signaling and metabolism have been extensively studied using various systems biology approaches. However, they are mainly studied individually and in addition, current models lack both the complexity of the dynamics and the effects of the crosstalk in the signaling system. To gain a better understanding of the interconnectivity between nutrient signaling and metabolism in yeast cells, we developed a hybrid model, combining a Boolean module, describing the main pathways of glucose and nitrogen signaling, and an enzyme-constrained model accounting for the central carbon metabolism of Saccharomyces cerevisiae, using a regulatory network as a link. The resulting hybrid model was able to capture a diverse utalization of isoenzymes and to our knowledge outperforms constraint-based models in the prediction of individual enzymes for both respiratory and mixed metabolism. The model showed that during fermentation, enzyme utilization has a major contribution in governing protein allocation, while in low glucose conditions robustness and control are prioritized. In addition, the model was capable of reproducing the regulatory effects that are associated with the Crabtree effect and glucose repression, as well as regulatory effects associated with lifespan increase during caloric restriction. Overall, we show that our hybrid model provides a comprehensive framework for the study of the non-trivial effects of the interplay between signaling and metabolism, suggesting connections between the Snf1 signaling pathways and processes that have been related to chronological lifespan of yeast cells.