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Impacts on Atlantic Killifish from Neurotoxicants: Genes, Behavior, and Population-Relevant Outcomes
Janice L Albers1, Lori N Ivan1, Bryan W Clark2
1Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan 48824, United States.
Environmental Science & Technology
|September 17, 2024
Summary
This study links molecular and behavioral changes in Atlantic killifish to ecological risks from neurotoxicants like methylmercury and PCBs. Models predict chemical impacts on fish growth and survival, improving ecological risk assessment.
Area of Science:
- Environmental toxicology
- Ecotoxicology
- Molecular biology
Background:
- Linking molecular and cellular changes to population-level ecological risks is challenging.
- Atlantic killifish (Fundulus heteroclitus) populations exhibit varying tolerance to contaminants.
- Neurotoxicants like methylmercury and polychlorinated biphenyls (PCBs) pose ecological threats.
Purpose of the Study:
- To link molecular and behavioral data to ecological risk predictions in Atlantic killifish.
- To model the effects of methylmercury and PCB126 on fish cohort growth and survival.
- To assess the ecological relevance of molecular and behavioral responses to toxicants.
Main Methods:
- Used laboratory gene expression and behavioral data from reference (SCOKF) and PCB-contaminated (NBHKF) killifish populations.
- Employed individual-based models to simulate cohort growth and survival from embryonic exposure.
- Quantified gene expression changes and behavioral alterations in response to methylmercury and PCB126.
Main Results:
- Methylmercury exposure altered specific brain gene expression and behaviors in reference killifish, but models showed no growth/survival effects.
- PCB126 exposure reduced physical activity and altered brain gene sets in reference killifish; models predicted decreased growth.
- PCB-tolerant killifish showed altered swimming behaviors with fewer gene set changes; models predicted PCB126 decreased survival in both populations.
Conclusions:
- Molecular and behavioral data can inform quantitative predictions of ecological risk.
- Individual-based models integrating molecular and behavioral endpoints enhance ecological risk assessment.
- This study demonstrates a framework for linking molecular responses to population-level outcomes in environmental toxicology.

