Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

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 <i>Daphnia</i> to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a <i>Daphnia</i> 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 <i>Daphnia</i>.

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Publication Details

Journal
Environmental Science & Technology
Published
2024-12-20
DOI
https://doi.org/10.1021/acs.est.4c11095
Citations
3
Primary Topic
Chemical Safety and Risk Management
Type
article
Field-Weighted Citation Impact
5.50

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article

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Liang‐Hong Guo, Tobias Schulze, Luisa Orsini, Martin Krauß et al.
3 citations
Environmental Science & Technology
Chemical Safety and Risk Management
5.50
article

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Liang‐Hong Guo, Tobias Schulze, Luisa Orsini, Martin Krauß, Ben Brown, John K. Colbourne, Yaohui Bai, Xiaojing Li, Meng Qiao, Wei Xiong, Jiarui Zhou, Timothy D. Williams
article en
3 citations

Abstract

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 <i>Daphnia</i> to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a <i>Daphnia</i> 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 <i>Daphnia</i>.

Environmental Science & TechnologyVol. 59(1)
Turing Institute (GB), Helmholtz Centre for Environmental Research (DE), Lawrence Berkeley National Laboratory (US), Chinese Academy of Sciences (CN), Research Center for Eco-Environmental Sciences (CN), University of Birmingham (GB)
Royal Society, Sight Research UK, European Commission, National Natural Science Foundation of China, Helmholtz-Zentrum für Umweltforschung, Natural Environment Research Council, H2020 Health
Openalex Percentile: Top 4%
Chemical Safety and Risk Management
5.50
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