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Pollution-tolerant killifish inhabiting contaminated estuaries have evolved resistance to industrial pollutants such as polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs), yet the mechanisms underlying these adaptive traits beyond genetic variation in aryl hydrocarbon receptor (AHR) signaling pathways remain incompletely understood. Here, we investigated hepatic metabolomic profiles, as well as transcriptional and epigenetic responses to benzo[a]pyrene (BaP) exposure, in Gulf killifish (Fundulus grandis) from pollution-adapted (Vince Bayou, VB) and non-adapted (Smith Point, SP) populations. Basal metabolomic profiles differed markedly between field-caught and laboratory-acclimated fish, reflecting a dominant influence of environmental conditions. Despite relatively modest overall metabolomic differences, consistent reductions in energy-related metabolites following laboratory acclimation suggest persistent metabolic differences in adapted fish. In response to BaP exposure, non-adapted fish exhibited robust, dose-dependent induction of AHR pathway genes, whereas adapted fish showed reduced inducibility of cyp1a (6.67- and 13.58-fold in SP vs. 4.30- and 6.33-fold in VB at 2.5 and 5 mg/kg BaP, respectively) and cyp1c1 (4.33- and 6.79-fold in SP vs. 1.10- and 1.57-fold in VB), consistent with refractory AHR signaling linked to underlying genetic variation. While basal global DNA methylation levels were similar between populations, BaP exposure increased mean global DNA methylation only in the adapted population (0.132% in controls vs. 0.180% and 0.181% following 2.5 and 5 mg/kg BaP exposure, respectively), indicating a population-specific epigenetic response. Collectively, these findings highlight metabolic and epigenetic responses as additional features of the pollution-adapted phenotype alongside genetic mechanisms. Such multi-layered responses may provide insights into how populations survive and respond to chronic pollution, with important implications for ecological resilience and risk assessment of contaminated aquatic ecosystems.
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Kim et al. (2026) studied this question.
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