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Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies.
- Source :
- Nature Communications; 2/10/2022, Vol. 13 Issue 1, p1-12, 12p
- Publication Year :
- 2022
-
Abstract
- When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here, we present a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions. The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data suggests that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation—known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimisation, providing a framework to understand metabolic adaptation in eukaryal cells. Metabolically active organelles compete for cytosolic space and resources during metabolism rewiring. Here, the authors develop a computational model of yeast metabolism and resource allocation to predict condition- and compartment-specific proteome constraints that govern metabolic strategies. [ABSTRACT FROM AUTHOR]
- Subjects :
- METABOLIC models
YEAST
PROTEIN expression
CELL metabolism
PROTEIN synthesis
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 13
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- 155186035
- Full Text :
- https://doi.org/10.1038/s41467-022-28467-6