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.