Simplifying Nontargeted Analysis of PFAS in Complex Food Matrixes.

Abstract

Per- and polyfluoroalkyl substances (PFAS) are a class of toxic environmental contaminants that are characterized by their high chemical stability and enormous structural diversity. The limited availability of PFAS reference standards is the main motivation for developing nontargeted analytical methods. Current concepts are complex and rely on multiple filtering steps (e.g., assumption of homologous series, detection of mass defects, generic fragments, and spectra obtained from web-based sources). High-resolution mass spectrometry (HRMS)-based chromatograms of fish liver extracts were deconvoluted. Based on the ion abundance between the monoisotopic and the first isotopic peak, the number of carbons (C) was estimated for each extracted feature. A mass over carbon (m/C) and mass defect over carbon (md/C) ratio was calculated. PFAS-related peaks are strongly discriminated from matrix peaks when plotting m/C versus md/C. This enables nontarget detection of PFAS present at low µg/kg concentration in complex food matrixes. The proposed concept is highly selective by revealing a relatively small number of high-probability PFAS candidates (features). The small number of surviving candidates permits the MS/MS-based confirmation of each feature. This strategy led to the finding of one PFAS not present in the reference standard solution, as well as the detection of an unexpected set of PFAS adducts. The proposed concept of mass over carbon versus mass defect over carbon is suited for the nontarget detection of low amounts of PFAS in complex matrixes. It should be capable of detecting any PFAS (F/H ratio should be >1:1) regardless of the ionization mode.