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A systems biology approach to study glucose repression in the yeast Saccharomyces cerevisiae
Author(s) -
Westergaard Steen Lund,
Oliveira Ana Paula,
Bro Christoffer,
Olsson Lisbeth,
Nielsen Jens
Publication year - 2006
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.21135
Subject(s) - saccharomyces cerevisiae , psychological repression , biology , yeast , systems biology , reporter gene , transcription factor , gene , metabolic pathway , transcription (linguistics) , transcriptional regulation , signal transduction , mutant , biochemistry , regulation of gene expression , gene expression , genetics , linguistics , philosophy
Abstract Glucose repression in the yeast Saccharomyces cerevisiae has evolved as a complex regulatory system involving several different pathways. There are two main pathways involved in signal transduction. One has a role in glucose sensing and regulation of glucose transport, while another takes part in repression of a wide range of genes involved in utilization of alternative carbon sources. In this work, we applied a systems biology approach to study the interaction between these two pathways. Through genome‐wide transcription analysis of strains with disruption of HXK2, GRR1 , MIG1 , the combination of MIG1 and MIG2 , and the parental strain, we identified 393 genes to have significantly changed expression levels. To identify co‐regulation patterns in the different strains we applied principal component analysis. Disruption of either GRR1 or HXK2 were both found to have profound effects on transcription of genes related to TCA cycle and respiration, as well as ATP synthesis coupled proton transport, all displaying an increased expression. The hxk2Δ strain showed reduced overflow metabolism towards ethanol relative to the parental strain. We also used a genome‐scale metabolic model to identify reporter metabolites, and found that there is a high degree of consistency between the identified reporter metabolites and the physiological effects observed in the different mutants. Our systems biology approach points to close interaction between the two pathways, and our metabolism driven analysis of transcription data may find a wider application for analysis of cross‐talk between different pathways involved in regulation of metabolism. Biotechnol. Bioeng. 2007;96: 134–145. © 2006 Wiley Periodicals, Inc.