1 Center for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark2 Department of Systems Biology, Technical University of Denmark3 Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4 Department of Biotechnology, Technical University of Denmark
The yeast Saccharomyces cerevisiae encounters a range of nitrogen sources at various concentrations in its environment. The impact of these two parameters on transcription and metabolism was studied by growing S. cerevisiae in chemostat cultures with L-glutamine, L-alanine, or L-ammonium in limitation and by growing cells in an excess of ammonium. Cells grown in L-alanine-limited cultures had higher biomass yield per nitrogen mole (19%) than those from ammonium-limited cultures. Whole-genome transcript profiles were analyzed with a genome-scalle metabolic model that suggested increased anabolic activity in L-alanine-limited cells. The changes in these cells were found to be focused around pyruvate, acetyl coenzyme A, glyoxylate, and alpha-ketoglutarate via increased levels of ALT1, DAL7, PYC1, GDH2, and ADH5 and decreased levels of GDH3, CIT2, and ACS1 transcripts. The transcript profiles were then clustered. Approximately 1,400 transcripts showed altered levels when amino acid-grown cells were compared to those from ammonium. Another 400 genes had low transcript levels when ammonium was in excess. Overrepresentation of the GATAAG element in their promoters suggests that nitrogen catabollite repression (NCR) may be responsible for this regulation. Ninety-one genes had transcript levels on both L-glutamine and ammonium that were decreased compared to those on L-alanine, independent of the concentration. The GATAAG element in these genes suggests two groups of NCR-responsive genes, those that respond to high levels of nitrogen and those that respond to levels below 30 mu M. In conclusion, our results reveal that the nitrogen source has substantial influence on the transcriptome of yeasts and that transcriptional changes may be correlated to physiology via a metabolic model.
Applied and Environmental Microbiology, 2006, Vol 72, Issue 9, p. 6194-6203