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Bioactivity Profiling of Chemical Mixtures for Hazard Characterization
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2024-12-20 , DOI: 10.1021/acs.est.4c11095 Xiaojing Li, Jiarui Zhou, Yaohui Bai, Meng Qiao, Wei Xiong, Tobias Schulze, Martin Krauss, Timothy D. Williams, Ben Brown, Luisa Orsini, Liang-Hong Guo, John K. Colbourne
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2024-12-20 , DOI: 10.1021/acs.est.4c11095 Xiaojing Li, Jiarui Zhou, Yaohui Bai, Meng Qiao, Wei Xiong, Tobias Schulze, Martin Krauss, Timothy D. Williams, Ben Brown, Luisa Orsini, Liang-Hong Guo, John K. Colbourne
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The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.
更新日期：2024-12-20
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