Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jun 17:29:102674.
doi: 10.1016/j.fochx.2025.102674. eCollection 2025 Jul.

Advancing PFASs monitoring in food: from targeted SPE-LC-MS/MS to non-targeted QuEChERS-LC-HRMS approaches

Affiliations

Advancing PFASs monitoring in food: from targeted SPE-LC-MS/MS to non-targeted QuEChERS-LC-HRMS approaches

Cassandre Jeannot et al. Food Chem X. .

Abstract

Per- and polyfluoroalkyl substances (PFASs) are increasingly recognized as emerging contaminants, with some classified as persistent organic pollutants (POPs) and four recently regulated in food in the EU. However, due to the large structural diversity of PFASs, comprehensive monitoring remains essential. This study aimed to develop and apply a suspect and non-targeted screening approach to identify PFASs beyond those conventionally monitored in foodstuffs. The methodology combined optimized QuEChERS sample preparation, LC-HRMS acquisition, and prioritization of fluorinated signals, applying both suspect screening (SS) and non-targeted screening (NTS) strategies. Compared to targeted solid-phase extraction (SPE) coupled with MS/MS (QqQ) acquisition, this approach detected a broader range of PFASs in various food samples. Notably, as one of the first studies to apply NTS-a method typically used in environmental analysis-to food, it demonstrated the ability to detect both known and previously unlisted PFASs, such as PFPrA in an egg sample. This expanded approach enhances exposure assessment and supports the implementation of HRMS-based strategies for regulatory control and risk assessment.

Keywords: NTS; PFASs; QuEChERS; Sample preparation.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Detailed sample preparation steps using SPE and QuEChERS methods.
Fig. 2
Fig. 2
Relative signal Intensities (TICs) observed by LC-(ESI-)MS/MS for the analysis of PFASs in spiked milk (10 ng/mL) extracted by QuEChERS comparing 5 different solvent mixtures: ACN/H2O (grey), ACN/FA (red), ACN/H2O/FA (blue), MeOH (yellow) et MTBE/H2O (purple). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 3
Fig. 3
Concentrations of 4 selected PFASs (PFOA, PFOS, PFNA, PFHxS) measured by LC-MS/MS following the application of either the SPE or QuEChERS extraction protocol, with supplementation at three levels (1, 5, and 10 μg·kg−1, wet weight) across 20 food items.
Fig. 4
Fig. 4
Chromatographic profiles of PFPeA obtained from (1) an egg sample and (2) a crustacean sample in SS acquisition mode, comparing the extraction protocols: SPE and QuEChERS.
Fig. 5
Fig. 5
a) Kendrick mass defect for CF2 repeating unit vs m/z of 28 PFASs standard listed in our internal database and classified by family: PFCA (n = 11), PFSA (n = 10), Cl-PFESA (n = 2) and others PFASs (n = 5). Homologous series are identified by shifts in the x-axis divisible by 49.9968 (CF2) and the same CF2 normalized mass defect. In yellow, a suspect PFASs signal highlighted by NTS data processing. b) Chromatogram profile for PFPrA standard. c) Chromatogram profile for PFPrA in an egg sample. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

References

    1. Abunada Z., Alazaiza M.Y.D., Bashir M.J.K. An overview of per- and Polyfluoroalkyl substances (PFAS) in the environment: Source, fate, risk and regulations. Water. 2020;12 doi: 10.3390/w12123590. - DOI
    1. Acosta-Dacal A., Rial-Berriel C., Díaz-Díaz R., Bernal Suárez M.M., Zumbado M., Henríquez-Hernández L.A., Luzardo O.P. Supporting dataset on the optimization and validation of a QuEChERS-based method for the determination of 218 pesticide residues in clay loam soil. Data in Brief. 2020;33 doi: 10.1016/j.dib.2020.106393. - DOI - PMC - PubMed
    1. Adams K.J., Pratt B., Bose N., Dubois L.G., St. John-Williams L., Perrott K.M., Ky K., Kapahi P., Sharma V., MacCoss M.J., Moseley M.A., Colton C.A., MacLean B.X., Schilling B., Thompson J.W. Skyline for small molecules: A unifying software package for quantitative metabolomics. Journal of Proteome Research. 2020;19:1447–1458. doi: 10.1021/acs.jproteome.9b00640. - DOI - PMC - PubMed
    1. Aker A., Ayotte P., Caron-Beaudoin É., De Silva A., Ricard S., Lemire M. Associations between dietary profiles and perfluoroalkyl acids in Inuit youth and adults. Science of the Total Environment. 2023;857 doi: 10.1016/j.scitotenv.2022.159557. - DOI - PubMed
    1. Amziane A., Monteau F., El Djalil Lalaouna A., Alamir B., Le Bizec B., Dervilly G. Optimization and validation of a fast supercritical fluid chromatography tandem mass spectrometry method for the quantitative determination of a large set of PFASs in food matrices and human milk. Journal of Chromatography B. 2022;1210 doi: 10.1016/j.jchromb.2022.123455. - DOI - PubMed

LinkOut - more resources