Genome reprogramming in Saccharomyces cerevisiae upon nonylphenol exposure
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info:eu-repo/semantics/closedAccessTarih
2017Erişim
info:eu-repo/semantics/closedAccessÜst veri
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Bioaccumulative environmental estrogen, nonylphenol (NP; 4-nonylphenol), is widely used as a nonionic surfactant and can affect human health. Since genomes of Saccharomyces cerevisiae and higher eukaryotes share many structural and functional similarities, we investigated subcellular effects of NP on S.cerevisiae BY4742 cells by analyzing genome-wide transcriptional profiles. We examined effects of low (1 mg/l; <15% cell number reduction) and high (5 mg/l; > 65% cell number reduction) inhibitory concentration exposures for 120 or 180 min. After 120 and 180 min of 1 mg/l NP exposure, 187 (63 downregulated, 124 upregulated) and 103 genes (56 downregulated, 47 upregulated), respectively, were differentially expressed. Similarly, 678 (168 repressed, 510 induced) and 688 genes (215 repressed, 473 induced) were differentially expressed in cells exposed to 5 mg/l NP for 120 and 180 min, respectively. Only 15 downregulated and 63 upregulated genes were common between low and high NP inhibitory concentration exposure for 120 min, whereas 16 downregulated and 31 upregulated genes were common after the 180-min exposure. Several processes/pathways were prominently affected by either low or high inhibitory concentration exposure, while certain processes were affected by both inhibitory concentrations, including ion transport, response to chemicals, transmembrane transport, cellular amino acids, and carbohydrate metabolism. While minimal expression changes were observed with low inhibitory concentration exposure, 5 mg/l NP treatment induced substantial expression changes in genes involved in oxidative phosphorylation, cell wall biogenesis, ribosomal biogenesis, and RNA processing, and encoding heat shock proteins and ubiquitin-conjugating enzymes. Collectively, these results provide considerable information on effects of NP at the molecular level.
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https://doi.org/10.1152/physiolgenomics.00034.2017https://hdl.handle.net/20.500.12440/3853