Novel prioritisation strategies for evaluation of temporal trends in archived white-tailed sea eagle muscle tissue in non-target screening

Abstract

Environmental monitoring studies based on target analysis capture only a small fraction of contaminants of emerging concern (CECs) and miss pollutants potentially harmful to wildlife. Environmental specimen banks, with their archived samples, provide opportunities to identify new CECs by temporal trend analysis and nontarget screening. In this study, archived white-tailed sea eagle (Haliaeetus albicilla) muscle tissue was analysed by non-targeted high-resolution mass spectrometry. Univariate statistical tests (Mann-Kendall and Spearman rank) for temporal trend analysis were applied as prioritisation methods. A workflow for non-target data was developed and validated using an artificial time series spiked at five levels with gradient concentrations of selected CECs (n = 243). Pooled eagle muscle tissues collected 1965-2017 were then investigated with an eightpoint time series using the validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 14 409 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 207 features with increasing trends. Following unequivocal molecular formula assignment to prioritised features and further elucidation with MetFrag and EU Massbank, 13 compounds were tentatively identified, of which four were of anthropogenic origin. These results show that it is possible to prioritise new CECs in archived biological samples using univariate statistical approaches.

Keywords

Non-target analysis; Environmental specimen bank; White-tailed sea eagle; LC-QToF-MS; Temporal trend analysis

Published in

Journal of Hazardous Materials
2022, volume: 424, article number: 127331
Publisher: ELSEVIER

SLU Authors

• Dürig, Wiebke

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

• Menger, Frank

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

• Golovko, Oksana

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

• Wiberg, Karin

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

• Ahrens, Lutz

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Environmental Sciences

Publication identifier

• DOI: https://doi.org/10.1016/j.jhazmat.2021.127331

Permanent link to this page (URI)

https://res.slu.se/id/publ/114319