Determining dose-response relationship is essential for comprehensively revealing chemical-caused effects on organisms. However, uncertainty and complexity of gene/protein interactions cause the inability of traditional toxicogenomic methods (e.g., transcriptomics, proteomics and metabolomics) to effectively establish the direct relationship between chemical exposure and genes. In this work, we built an effective dose-dependent yeast functional genomics approach, which can clearly identify the direct gene-chemical link in the process of cadmium (Cd) toxification from a genome-wide scale with wide range concentrations (0.83, 2.49, 7.48, 22.45, 67.34, 202.03 and 606.1 μM). Firstly, we identified 220 responsive strains, and found that 142, 110, 91, 34, 8, 0 and 0 responsive strains can be respectively modulated by seven different Cd exposure concentrations ranging from high to low. Secondly, our results demonstrated that these genes induced by the high Cd exposure were mainly enriched in the process of cell autophagy, but ones caused by the low Cd exposure were primarily involved in oxidative stress. Thirdly, we found that the top-ranked GO biological processes with the lowest point of departure (POD) were transmembrane transporter complex and mitochondrial respiratory chain complex III, suggesting that mitochondrion might be the toxicity target of Cd. Similarly, nucleotide excision repair was ranked first in KEGG pathway with the least POD, indicating that this dose-dependent functional genomics approach can effectively detect the molecular initiating event (MIE) of cadmium toxification. Fourthly, we identified four key mutant strains (RIP1, QCR8, CYT1 and QCR2) as biomarkers for Cd exposure. Finally, the dose-dependent functional genomics approach also performed well in identifying MIE for additional genotoxicity chemical 4-nitroquinoline-1-oxide (4-NQO) data. Overall, our study developed a dose-dependent functional genomics approach, which is powerful to delve into the MIE of chemical toxification and is beneficial for guiding further chemical risk assessment.

• PMID: 36791950
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Journal Article

Authors

Guan M, Wang X, Pan Y, Xu Y, Cao Y, Yan L, Ma L, Ma F, Zhang X

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