In silico biomarker analysis of the adverse effects of perfluorooctane sulfonate (PFOS) exposure on the metabolic physiology of embryo-larval zebrafish - Nolen, Rayna M.; Petersen, Lene H.; Kaiser, Karl; Quigg, Antonietta; Hala, David (Frontiers in Systems Biology, 2024)
Perfluorooctane sulfonate (PFOS) is a ubiquitous pollutant in global aquatic ecosystems with increasing concern for its toxicity to aquatic wildlife through inadvertent exposures. To assess the likely adverse effects of PFOS exposure on aquatic wildlife inhabiting polluted ecosystems, there is a need to identify biomarkers of its exposure and toxicity. We used an integrated systems toxicological framework to identify physiologically relevant biomarkers of PFOS toxicity in fish.An in silico stoichiometric metabolism model of zebrafish (Danio rerio) was used to integrate available (published by other authors) metabolomics and transcriptomics datasets from in vivo toxicological studies with 5 days post fertilized embryo-larval life stage of zebrafish. The experimentally derived omics datasets were used as constraints to parameterize an in silico mathematical model of zebrafish metabolism. In silico simulations using flux balance analysis (FBA) and its extensions showed prominent effects of PFOS exposure on the carnitine shuttle and fatty acid oxidation. Further analysis of metabolites comprising the impacted metabolic reactions indicated carnitine to be the most highly represented cofactor metabolite. Flux simulations also showed a near dose-responsive increase in the pools for fatty acids and acyl-CoAs under PFOS exposure. Taken together, our integrative in silico results showed dyslipidemia effects under PFOS exposure and uniquely identified carnitine as a candidate metabolite biomarker. The verification of this prediction was sought in a subsequent in vivo environmental monitoring study by the authors which showed carnitine to be a modal biomarker of PFOS exposure in wild-caught fish and marine mammals sampled from the northern Gulf of Mexico. Therefore, we highlight the efficacy of FBA to study the properties of large-scale metabolic networks and to identify biomarkers of pollutant exposure in aquatic wildlife.