Unknown,Transcriptomics,Genomics,Proteomics

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Functional profiling in yeast with zinc-limitation

ABSTRACT: Zinc is an essential nutrient because it is a required cofactor for many enzymes and transcription factors. To discover genes and processes in yeast that are required for growth when zinc is limiting, we used genome-wide functional profiling. As a result, we identified over 400 different genes required for optimal growth under zinc-limiting conditions. Among these were several targets of the Zap1 zinc-responsive transcription factor. Their importance is consistent with their up-regulation by Zap1 in low zinc. We also identified genes that implicate Zap1-independent processes as important. These include endoplasmic reticulum function, oxidative stress resistance, vesicular trafficking, peroxisome biogenesis, and chromatin modification. Our studies also indicated the critical role of macroautophagy in low zinc growth. Finally, as a result of our analysis, we discovered a previously unknown role for the ICE2 gene in maintaining ER zinc homeostasis. Pools of homozygous diploid deletion mutants (n = 4,607 strains) were grown in zinc defined media (LZM) at 2 concentrations for 5 and 15 generations (5g, 15g). Each strain has a deletion in a different gene. In each strain, the gene was replaced by a deletion cassette containing a antibiotic resistance gene and two BARCODES, up and down tags (Please see Giaever et al, 2002, Nature). These tags in the DNA are specific to each strain. We pool all deletion strains and grow them under a selective condition; extract DNA; amplify barcodes using universal primers and hybridize to arrays containing complemetary sequences to the up and down tags. In this way, we can look at growth of each of the strains. Our strategy is to analyze separately the up and down tags. Therefore, for each array (CEL file), we generate two data files, one for all ups and another one for all downs. In these files, the list of genes are the same but the data come from different set of probes, up or down. The values are log2 averages of replicate probes for the same tag. These pre processed files were used to identify strains with differential growth in 1uM zinc by comparing to the 100uM zinc arrays.

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Chris Vulpe

PROVIDER: E-GEOD-37254 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Benzene is a ubiquitous environmental contaminant and is widely used in industry. Exposure to benzene causes a number of serious health problems, including blood disorders and leukemia. Benzene undergoes complex metabolism in humans, making mechanistic determination of benzene toxicity difficult. We used a functional genomics approach to identify the genes that modulate the cellular toxicity of three of the phenolic metabolites of benzene, hydroquinone (HQ), catechol (CAT) and 1,2,4-benzenetriol (BT), in the model eukaryote Saccharomyces cerevisiae. Benzene metabolites generate oxidative and cytoskeletal stress, and tolerance requires correct regulation of iron homeostasis and the vacuolar ATPase. We have identified a conserved bZIP transcription factor, Yap3p, as important for a HQ-specific response pathway, as well as two genes that encode putative NAD(P)H:quinone oxidoreductases, PST2 and YCP4. Many of the yeast genes identified have human orthologs that may modulate human benzene toxicity in a similar manner and could play a role in benzene exposure-related disease. Genome-Wide Functional Profiling Reveals Genes Required for Tolerance to Benzene Metabolites in Yeast. PLoS ONE 2011, 6(8):e24205 - PMID: 21912624. Pools of homozygous diploid deletion mutants (n = 4,607 strains) were grown in rich media (YPD) at 3 concentrations of hydroquinone (HQ), catechol (CAT) and 1,2,4-benzenetriol (BT) for 5 and 15 generations (5g, 15g). Each strain has a deletion in a different gene. In each strain, the gene was replaced by a deletion cassette containing a antibiotic resistance gene and two BARCODES, up and down tags (Please see Giaever et al, 2002, Nature). These tags in the DNA are specific to each strain. We pool all deletion strains and grow them under a selective condition; extract DNA; amplify barcodes using universal primers and hybridize to arrays containing complemetary sequences to the up and down tags. In this way, we can look at growth of each of the strains. Our strategy is to analyze separately the up and down tags. Therefore, for each array (CEL file), we generate two data files, one for all ups and another one for all downs. In these files, the list of genes are the same but the data come from different set of probes, up or down. The values are log2 averages of replicate probes for the same tag. These pre processed files were used to identify strains with differential growth in benzene metabolites by comparing to the control arrays.

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Functional profiling in yeast with zinc-limitation

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