An integrated systems toxicological approach was taken to identify physiologically relevant biomarkers of perfluorooctane sulfonate (PFOS) toxicity in fish. PFOS is a ubiquitous pollutant in global aquatic ecosystems with increasing concern for its toxicity to aquatic wildlife. An in silico stoichiometric metabolism model of zebrafish was used to integrate available metabolomics and transcriptomics datasets from in vivo toxicological studies with 5 days post fertilized embryo-larval zebrafish. The experimentally derived omics datasets were used as constraints to parameterize the in silico zebrafish model. In silico simulations using flux balance analysis (FBA) showed prominent effects of PFOS exposure on the carnitine shuttle and fatty acid oxidation. Further analysis of impacted metabolites indicated carnitine to be the most highly represented cofactor metabolite. Taken together, our results showed dyslipidemia effects under PFOS exposure and uniquely identified carnitine as a candidate metabolite biomarker. Subsequently, verification of this prediction was sought through an in vivo environmental monitoring study 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 integrate multi-omics datasets to study the properties of large-scale metabolic networks and identify biomarkers of exposure and likely adverse effects.