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.

Project description:Human toxicogenomic studies to date have been of limited size, have mainly addressed exposures at the upper end of typical ranges of human exposure, and have often lacked precise, individual estimates of exposure. Previously, we identified genes associated with exposure to high (>10 ppm) levels of the leukemogen, benzene, through transcriptomic analyses of blood cells from small numbers of occupationally exposed workers. Here, we have expanded the study to 125 workers exposed to a wide range of benzene levels, including <1 ppm. Study design, and analysis with a mixed effects model, removed sources of biological and experimental variability and revealed highly significant widespread perturbation of gene expression at all exposure levels. Benzene is an established cause of acute myeloid leukemia (AML), and may cause one or more lymphoid malignancies in humans. Interestingly, acute myeloid leukemia was among the most significant pathways impacted by benzene exposure in the present study. Further, at most exposure levels, immune response pathways including T cell receptor signaling, B cell receptor signaling, and Toll like receptor signaling were impacted, providing support for the biological plausibility of an association between lymphoma and benzene exposure. We also identified a 16-gene expression signature modified by all levels of benzene exposure, comprising genes with roles in immune response, inflammatory response, cell adhesion, cell-matrix adhesion, and blood coagulation. Overall, these findings support, and expand upon, our current understanding of the mechanisms by which benzene may induce hematotoxicity, leukemia and lymphoma. Furthermore, this study shows that with good study design and analysis, transcriptome profiling of the blood of chemically-exposed humans can identify relevant biomarkers across a range of exposures and inform about potential associations with disease risks. Key words: occupational exposure 29 workers exposed to <<1ppm benzene at most dosimetry reading over a 14-month period (Very Low), 30 exposed to average <1ppm (Low), 11 exposed to 5-10 ppm (High), 13 exposed to >10 ppm (Very High), and 42 unexposed controls (Control) who were frequency-matched to these subjects on the basis of age and gender were analyzed (technical replicates on some subjects, see SubjectID/description).

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