Comprehensive Emerging Chemical Discovery: Novel Polyfluorinated Compounds in Lake Michigan Trout

A versatile screening algorithm capable of efficiently searching liquid chromatographic/mass spectrometric data for unknown compounds has been developed using a combination of open source and generic computing software packages. The script was used to search for select novel polyfluorinated contaminants in Great Lakes fish. However, the framework is applicable whenever full-scan, high-resolution mass spectral and chromatographic data are collected. Target compound classes are defined and a matrix of candidates is generated that includes mass spectral profiles and likely fragmentation pathways. The initial calibration was performed using a standard solution of known linear perfluoroalkyl acids. Once validated, Lake Michigan trout data files were analyzed for polyfluoroalkyl acids using the algorithm referencing 3570 possible compounds including C4-C10 perfluoro- and polyfluoroalkyl, polyfluorochloroalkyl acids and sulfonates, and potential ether forms. The results suggest the presence of 30 polyfluorinated chemical formulas which have not been previously reported in the literature. The identified candidates included mono- to hexafluoroalkyl carboxylic acids, mono- and trifluoroalkyl carboxylic acid ethers, and novel polyfluoroalkyl sulfonates. Candidate species identified in lake trout were qualified using theoretical isotopic profile matching, characteristic fragmentation patterns based on known linear perfluoroalkyl acid (PFAA) fragmentation, and retention time reproducibility among replicate extractions and injections. In addition, the relative retention times of multiple species within a compound class were compared based on theoretical octanol-water partition coefficients.