Integrating phenotypic and expression profiles to map arsenic-response networks.

TitleIntegrating phenotypic and expression profiles to map arsenic-response networks.
Publication TypeJournal Article
Year of Publication2004
AuthorsHaugen AC, Kelley R, Collins JB, Tucker CJ, Deng C, Afshari CA, Brown MJ, Ideker T, Van Houten B
JournalGenome Biol
Volume5
Issue12
PaginationR95
Date Published2004
ISSN1465-6914
KeywordsArsenic, Basic-Leucine Zipper Transcription Factors, Biodegradation, Environmental, Cysteine, DNA-Binding Proteins, Environmental Pollutants, Gene Expression Profiling, Gene Expression Regulation, Fungal, Glutathione, Heat-Shock Response, Methionine, Oxidative Stress, Phenotype, Proteasome Endopeptidase Complex, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins, Selenium, Sulfur, Toxicity Tests, Trans-Activators, Transcription Factors, Transcription, Genetic
Abstract

BACKGROUND: Arsenic is a nonmutagenic carcinogen affecting millions of people. The cellular impact of this metalloid in Saccharomyces cerevisiae was determined by profiling global gene expression and sensitivity phenotypes. These data were then mapped to a metabolic network composed of all known biochemical reactions in yeast, as well as the yeast network of 20,985 protein-protein/protein-DNA interactions.

RESULTS: While the expression data unveiled no significant nodes in the metabolic network, the regulatory network revealed several important nodes as centers of arsenic-induced activity. The highest-scoring proteins included Fhl1, Msn2, Msn4, Yap1, Cad1 (Yap2), Pre1, Hsf1 and Met31. Contrary to the gene-expression analyses, the phenotypic-profiling data mapped to the metabolic network. The two significant metabolic networks unveiled were shikimate, and serine, threonine and glutamate biosynthesis. We also carried out transcriptional profiling of specific deletion strains, confirming that the transcription factors Yap1, Arr1 (Yap8), and Rpn4 strongly mediate the cell's adaptation to arsenic-induced stress but that Cad1 has negligible impact.

CONCLUSIONS: By integrating phenotypic and transcriptional profiling and mapping the data onto the metabolic and regulatory networks, we have shown that arsenic is likely to channel sulfur into glutathione for detoxification, leads to indirect oxidative stress by depleting glutathione pools, and alters protein turnover via arsenation of sulfhydryl groups on proteins. Furthermore, we show that phenotypically sensitive pathways are upstream of differentially expressed ones, indicating that transcriptional and phenotypic profiling implicate distinct, but related, pathways.

DOI10.1186/gb-2004-5-12-r95
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/15575969?dopt=Abstract
PMCPMC545798
Alternate JournalGenome Biol.
PubMed ID15575969