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整合表型和表达谱以绘制砷反应网络。

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

作者信息

Haugen Astrid C, Kelley Ryan, Collins Jennifer B, Tucker Charles J, Deng Changchun, Afshari Cynthia A, Brown J Martin, Ideker Trey, Van Houten Bennett

机构信息

Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.

出版信息

Genome Biol. 2004;5(12):R95. doi: 10.1186/gb-2004-5-12-r95. Epub 2004 Nov 29.

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.

摘要

背景

砷是一种影响数百万人的非诱变致癌物。通过分析全基因组表达和敏感性表型,确定了这种类金属对酿酒酵母的细胞影响。然后将这些数据映射到一个由酵母中所有已知生化反应以及包含20985个蛋白质-蛋白质/蛋白质-DNA相互作用的酵母网络组成的代谢网络中。

结果

虽然表达数据在代谢网络中未揭示显著节点,但调控网络揭示了几个重要节点作为砷诱导活性的中心。得分最高的蛋白质包括Fhl1、Msn2、Msn4、Yap1、Cad1(Yap2)、Pre1、Hsf1和Met31。与基因表达分析相反,表型分析数据映射到了代谢网络。揭示的两个重要代谢网络是莽草酸途径以及丝氨酸、苏氨酸和谷氨酸的生物合成途径。我们还对特定缺失菌株进行了转录谱分析,证实转录因子Yap1、Arr1(Yap8)和Rpn4强烈介导细胞对砷诱导应激的适应,但Cad1的影响可忽略不计。

结论

通过整合表型和转录谱分析并将数据映射到代谢和调控网络上,我们表明砷可能将硫导入谷胱甘肽进行解毒,通过耗尽谷胱甘肽池导致间接氧化应激,并通过蛋白质巯基的砷化改变蛋白质周转。此外,我们表明表型敏感途径位于差异表达途径的上游,这表明转录和表型谱分析涉及不同但相关的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5be/545798/61b9bbf200d5/gb-2004-5-12-r95-1.jpg

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