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Non-targeted screening workflows for gas chromatography-high-resolution mass spectrometry analysis and identification of biomagnifying contaminants in biota samples.

ABSTRACT: The health of key species in the Baltic region has been impaired by exposure to anthropogenic hazardous substances (AHSs), which accumulate in organisms and are transferred through food chains. There is, thus, a need for comprehensive characterization of the occurrence and accumulation of AHSs in the ecosystem. In this study, we use a non-target screening (NTS) approach for this purpose. A major challenge in NTS of biological samples is the removal of matrix components such as lipids that may interfere with the detection and identification of compounds of interest. Here, we combine gel permeation chromatography with Florisil^® column fractionation to achieve sufficient lipid removal for gas chromatography-high-resolution mass spectrometry analysis using electron ionization (EI) and electron capture negative ion chemical ionization (ECNI). In addition, we present new data processing workflows designed to systematically find and identify frequently occurring and biomagnifying AHSs, including known, emerging, and new contaminants. Using these workflows, we discovered a wide range of contaminants in tissue samples from blue mussels, fish, and marine mammals, and calculated their biomagnification factors (BMFs). Compounds with BMFs above 1 for herring and at least one marine mammal included legacy chlorinated pollutants (polychlorinated biphenyls, DDTs, chloro-benzenes/cyclohexanes, chlordanes, toxaphenes, dieldrin), polybrominated diphenyl ethers (PBDEs), and brominated biphenyls. However, there were also several halogenated natural products (halogenated methoxylated brominated diphenyl ethers, 1'-methyl-1,2'-bipyrroles, 1,1'-dimethyl-2,2'-bipyrroles, and the halogenated monoterpene mixed halogenated compound 1) as well as the novel flame retardant Dechlorane 602 and several polycyclic aromatic hydrocarbons, terpenoids, and steroids. The legacy pollutants exhibited the expected biomagnification behavior, demonstrating the utility of the unguided data processing workflow. Graphical abstract.

SUBMITTER: Rebryk A

PROVIDER: S-EPMC7806533 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Non-targeted screening workflows for gas chromatography-high-resolution mass spectrometry analysis and identification of biomagnifying contaminants in biota samples.

Rebryk Andriy A Haglund Peter P

Analytical and bioanalytical chemistry 20201106 2

The health of key species in the Baltic region has been impaired by exposure to anthropogenic hazardous substances (AHSs), which accumulate in organisms and are transferred through food chains. There is, thus, a need for comprehensive characterization of the occurrence and accumulation of AHSs in the ecosystem. In this study, we use a non-target screening (NTS) approach for this purpose. A major challenge in NTS of biological samples is the removal of matrix components such as lipids that may in ...[more]

PMID: 33156400

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Project description:Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.

Dataset Information

Non-targeted screening workflows for gas chromatography-high-resolution mass spectrometry analysis and identification of biomagnifying contaminants in biota samples.

Publications

Non-targeted screening workflows for gas chromatography-high-resolution mass spectrometry analysis and identification of biomagnifying contaminants in biota samples.

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