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Manchester Centre for Integrative Systems Biology

Growth control of the eukaryote cell: A systems biology study in yeast


Abstract

Background: Cell growth underlies many key cellular and development processes, yet a limited number of studies have been conducted on cell growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are presently lacking.

Results: Metabolic Control Analysis is being exploited in a Systems Biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endo- and exo-metabolomes of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly up-regulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are down-regulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologues with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Also, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth.

Conclusions: This work constitutes a first comprehensive Systems Biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale Systems Biology models of the eukaryotic cell.


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Data

  • Transcriptomics, proteomics and metabolomics data are available to download.


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