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A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals

Author

Listed:
  • Brianna N. Rivera

    (Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA
    These authors contributed equally to this work.)

  • Lindsay B. Wilson

    (Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA
    These authors contributed equally to this work.)

  • Doo Nam Kim

    (Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA 99354, USA)

  • Paritosh Pande

    (Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA 99354, USA)

  • Kim A. Anderson

    (Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA)

  • Susan C. Tilton

    (Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA)

  • Robyn L. Tanguay

    (Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA)

Abstract

A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.

Suggested Citation

  • Brianna N. Rivera & Lindsay B. Wilson & Doo Nam Kim & Paritosh Pande & Kim A. Anderson & Susan C. Tilton & Robyn L. Tanguay, 2022. "A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals," IJERPH, MDPI, vol. 19(7), pages 1-23, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:7:p:3829-:d:777947
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    References listed on IDEAS

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    1. Kerstin Howe & Matthew D. Clark & Carlos F. Torroja & James Torrance & Camille Berthelot & Matthieu Muffato & John E. Collins & Sean Humphray & Karen McLaren & Lucy Matthews & Stuart McLaren & Ian Sea, 2013. "The zebrafish reference genome sequence and its relationship to the human genome," Nature, Nature, vol. 496(7446), pages 498-503, April.
    2. Guozhu Zhang & Lisa Truong & Robert L Tanguay & David M Reif, 2017. "A New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-16, January.
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