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Prioritisation, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS

ABSTRACT: Recycled textile samples obtained in Sweden, 2021. Multi-residue extraction method used. Top-5 DDA + Inclusion List employed for MS2 acquisition. mzML files converted from raw data (ProteoWizard::msConvert).

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Na

SUBMITTER: Anneli Kruve Drew Szabo

PROVIDER: MSV000095185 | MassIVE | Sat Jun 29 09:49:00 BST 2024

REPOSITORIES: MassIVE

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Prioritization, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS.

Szabo Drew D Fischer Stellan S Mathew Aji P AP Kruve Anneli A

Analytical chemistry 20240819 35

Recycled textiles are becoming widely available to consumers as manufacturers adopt circular economy principles to reduce the negative impact of garment production. Still, the quality of the source material directly impacts the final product, where the presence of harmful chemicals is of utmost concern. Here, we develop a risk-based suspect and non-targeted screening workflow for the detection, identification, and prioritization of the chemicals present in consumer-based recycled textile product ...[more]

PMID: 39160693

Similar Datasets

GNPS - Prioritisation, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS

Project description:Recycled textile samples obtained in Sweden, 2021. Multi-residue extraction method used. Top-5 DDA + Inclusion List employed for MS2 acquisition. mzML files converted from raw data (ProteoWizard::msConvert).

2024-06-29 | MSV000095185 | GNPS

Prioritization, Identification, and Quantification of Emerging Contaminants in Recycled Textiles Using Non-Targeted and Suspect Screening Workflows by LC-ESI-HRMS.

Project description:Recycled textiles are becoming widely available to consumers as manufacturers adopt circular economy principles to reduce the negative impact of garment production. Still, the quality of the source material directly impacts the final product, where the presence of harmful chemicals is of utmost concern. Here, we develop a risk-based suspect and non-targeted screening workflow for the detection, identification, and prioritization of the chemicals present in consumer-based recycled textile products after manufacture and transport. We apply the workflow to characterize 13 recycled textile products from major retail outlets in Sweden. Samples were extracted and analyzed by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). In positive and negative ionization mode, 20,119 LC-HRMS features were detected and screened against persistent, mobile, and toxic (PMT) as well as other textile-related chemicals. Six substances were matched with PMT substances that are regulated in the European Union (EU) with a Level 2/3 confidence. Forty-three substances were confidently matched with textile-related chemicals reported for use in Sweden. For estimating the relative priority score, aquatic toxicity and concentrations were predicted for 7416 features with tandem mass spectra (MS2) and used to rank the non-targeted features. The top 10 substances were evaluated due to elevated environmental risk linked to the recycling process and potential release at end-of-life.

| S-EPMC11375621 | biostudies-literature

Guide to Semi-Quantitative Non-Targeted Screening Using LC/ESI/HRMS.

Project description:Non-targeted screening (NTS) with reversed phase liquid chromatography electrospray ionization high resolution mass spectrometry (LC/ESI/HRMS) is increasingly employed as an alternative to targeted analysis; however, it is not possible to quantify all compounds found in a sample with analytical standards. As an alternative, semi-quantification strategies are, or at least should be, used to estimate the concentrations of the unknown compounds before final decision making. All steps in the analytical chain, from sample preparation to ionization conditions and data processing can influence the signals obtained, and thus the estimated concentrations. Therefore, each step needs to be considered carefully. Generally, less is more when it comes to choosing sample preparation as well as chromatographic and ionization conditions in NTS. By combining the positive and negative ionization mode, the performance of NTS can be improved, since different compounds ionize better in one or the other mode. Furthermore, NTS gives opportunities for retrospective analysis. In this tutorial, strategies for semi-quantification are described, sources potentially decreasing the signals are identified and possibilities to improve NTS are discussed. Additionally, examples of retrospective analysis are presented. Finally, we present a checklist for carrying out semi-quantitative NTS.

| S-EPMC8228683 | biostudies-literature

Analysis of the honeybee sperm proteome using MudPit and 2D PAGE

Project description:Honeybee semen was collected by gently squeezing the male abdomens. Samples were pooled and then centrifuged. Pelleted sperm was collected and analysed with both 2D PAGE and gel-free methods. For the 2D PAGE, protein spots were digested using trypsin. Extracted peptides, resolved on a C18 column, were analysed by an Agilent LC/MSD Trap XCT Ultra 6330 mass spectrometer. Spectra were searched against the honeybee protein sequences (RefSeq release 48) using Mascot algorithm (with 1 missed cleavage, Cys-carbamidomethylation as fixed modification, and Met-oxidation and N/Q-deamidation as variable modifications). For the MudPit analysis the sperm sample was digested by trypsin. Peptides were resolved using strong cation exchange chromatography followed by reverse phase (C18) HPLC and finally analysed by an Agilent QTOF mass spectrometer. Resulting spectrum files were converted to mzXML and merged using ProteoWizard msconvert. These were then searched against honeybee protein sequences using Mascot, Omssa and X!tandem (all with 1 missed cleavage, and Met-oxidation and N/Q-deamidation as variable modifications). Results of the three search engines were pooled using TPP.

2020-01-17 | PXD000169 | Pride

Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data.

Project description:The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normal- and reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions.

| S-EPMC7570355 | biostudies-literature

PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows.

Project description:A crucial part of a successful systems biology experiment is an assay that provides reliable, quantitative measurements for each of the components in the system being studied. For proteomics to be a key part of such studies, it must deliver accurate quantification of all the components in the system for each tested perturbation without any gaps in the data. This will require a new approach to proteomics that is based on emerging targeted quantitative mass spectrometry techniques. The PeptideAtlas Project comprises a growing, publicly accessible database of peptides identified in many tandem mass spectrometry proteomics studies and software tools that allow the building of PeptideAtlas, as well as its use by the research community. Here, we describe the PeptideAtlas Project, its contents and components, and show how together they provide a unique platform to select and validate mass spectrometry targets, thereby allowing the next revolution in proteomics.

| S-EPMC2373374 | biostudies-other

Profiling of glucosinolates and flavonoids in Rorippa indica (Linn.) Hiern. (Cruciferae) by UHPLC-PDA-ESI/HRMS(n).

Project description:An UHPLC-PDA-ESI/HRMS(n) profiling method was used to identify the glucosinolates and flavonoids of Rorippa indica (Cruciferae), a wild vegetable and Chinese herb used to treat cough, diarrhea, and rheumatoid arthritis. Thirty-three glucosinolates, more than 40 flavonol glycosides, and 18 other phenolic and common organic compounds were identified. The glucosinolates and polyphenols were separated by UHPLC. High-resolution deprotonated molecules provided high accuracy mass values that were used to determine formulas and provide putative identification of the glucosinolates and flavonoids. The fragments from multistage mass spectrometry were used to elucidate the structures. The concentrations of the main components were based on UV peak areas and molar relative response factors with a single calibration standard. This study found this plant to be a rich source for glucosinolates, containing 24 new glucosinolates, including 14 glucosylated glucosinolates that were previously unidentified.

| S-EPMC4082396 | biostudies-other

OpenHiCAMM: High-Content Screening Software for Complex Microscope Imaging Workflows.

Project description:High-content image acquisition is generally limited to cells grown in culture, requiring complex hardware and preset imaging modalities. Here we report an open source software package, OpenHiCAMM (Open Hi Content Acquisition for μManager), that provides a flexible framework for integration of generic microscope-associated robotics and image processing with sequential work-flows. As an example, we imaged Drosophila embryos, detecting the embryos at low resolution, followed by re-imaging the detected embryos at high resolution, suitable for computational analysis and screening. The OpenHiCAMM package is easy to use and adapt for automating complex microscope image tasks. It expands our abilities for high-throughput image-based screens to a new range of biological samples, such as organoids, and will provide a foundation for bioimaging systems biology.

| S-EPMC5993205 | biostudies-literature

Untargeted profiling of tracer-derived metabolites using stable isotopic labeling and fast polarity-switching LC-ESI-HRMS.

Project description:An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC-HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of (13)C9-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionization mode) corresponding to 139 metabolites were detected. The benefit of fast polarity switching was evident, with 32 and 58 of these metabolites having exclusively been detected in the positive and negative modes, respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived metabolites, the assignment of ion species and, thus, molecular weight was possible only by the use of complementary features of the two ion polarity modes. Statistical evaluation showed that treatment with DON increased or decreased the abundances of many detected metabolites.

| S-EPMC4255957 | biostudies-literature

Identification of Secondary Metabolites from <i>Aspergillus pachycristatus</i> by Untargeted UPLC-ESI-HRMS/MS and Genome Mining.

Project description:Aspergillus pachycristatus is an industrially important fungus for the production of the antifungal echinocandin B and is closely related to model organism A. nidulans. Its secondary metabolism is largely unknown except for the production of echinocandin B and sterigmatocystin. We constructed mutants for three genes that regulate secondary metabolism in A. pachycristatus NRRL 11440, and evaluated the secondary metabolites produced by wild type and mutants strains. The secondary metabolism was explored by metabolic networking of UPLC-HRMS/MS data. The genes and metabolites of A. pachycristatus were compared to those of A. nidulans FGSC A4 as a reference to identify compounds and link them to their encoding genes. Major differences in chromatographic profiles were observable among the mutants. At least 28 molecules were identified in crude extracts that corresponded to nine characterized gene clusters. Moreover, metabolic networking revealed the presence of a yet unexplored array of secondary metabolites, including several undescribed fellutamides derivatives. Comparative reference to its sister species, A. nidulans, was an efficient way to dereplicate known compounds, whereas metabolic networking provided information that allowed prioritization of unknown compounds for further metabolic exploration. The mutation of global regulator genes proved to be a useful tool for expanding the expression of metabolic diversity in A. pachycristatus.

| S-EPMC7071103 | biostudies-literature

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