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Identifying markers of exposure using a combination of in silico predictive tools and non-targeted analysis
Citation:
Boyce, M., K. Farvala, J. Sobus, A. Williams, A. Chao, J. Wambaugh, L. Lizarraga, AND G. Patlewicz. Identifying markers of exposure using a combination of in silico predictive tools and non-targeted analysis. American Chemical Society (ACS) Fall 2021 National Meeting, Virtual, NC, August 22 - 26, 2021. https://doi.org/10.23645/epacomptox.17430338
Impact/Purpose:
Presentation to the American Chemical Society (ACS) Fall 2021 National Meeting August 2021. Non-targeted analysis (NTA) strives to detect and identify a wide range of chemicals without preconceived target list or standards. Such efforts can be applied to and use a variety of exposure science efforts, including basic research into the technique (ENTACT), informatics tools (CompTox Chemicals Dashboard), complex mixtures (UVCBs) and pairing exposure to effects (EDA). Current high-throughput screening assays and read-across methods consider bioactivity of a specific "parent" compound. There is an immediate need to also consider bioactivity of multigenerational biological metabolites and environmental transformation/degradation products. Software exists to predict metabolites and transformation products, but it can be difficult to constrain predicted species to those which are most plausible. Using open-access models and NTA instrumentation, this product will develop and deliver an integrated workflow for predicting "daughter" species from parent compounds and confirming the presence of these species via high-resolution mass spectrometry. Current and future NTA research areas are also linked to larger scientific efforts within the exposure community at EPA.
Description:
Understanding the metabolic fate of a xenobiotic substance will inform its health risk and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analyses (NTA), which often aim to profile all compounds within a sample using high-resolution mass spectrometry (HRMS). Due to the complexity of data generated by NTA and lack of suitable mass spectrometry databases for chemical metabolites, in silico metabolite prediction tools can be used to construct suspect screening lists and guide metabolite identification. This coupling of in silico predictive tools with NTA facilitates the identification of markers of exposure. Herein, we demonstrate how in silico tools can be used to prepare a suspect screening list and guide the identification of 34 substances and their metabolites. These starting substances represent a diverse selection of pharmaceutical, agrochemical, and industrial chemicals selected from the Environmental Protection Agency (EPA) ToxCast Inventory. The compounds were metabolized in a high-throughput assay using primary hepatocytes and the resulting supernatant and lysate were analyzed via HRMS. Metabolite predictions from four software packages (TIMES, Nexus Meteor, BioTransformer, and QSAR Toolbox) were combined to serve as the suspect screening list, where the exact masses of the predicted metabolites were used to select features for fragmentation via tandem mass spectrometry (MS/MS). HRMS data were refined into a list of features using Agilent’s MassHunter Profinder and Mass Profiler Professional software, and the EPA’s NTA WebApp. The features and their corresponding fragmentation patterns were compared to spectra generated by Competitive Fragmentation Modeling for Metabolite Identification, and metabolite structures were assigned based on similarity ranking. The methods and results of this study provide a framework for using in silico prediction tools to guide NTA of metabolites. This abstract does not reflect EPA policy.
URLs/Downloads:
DOI: Identifying markers of exposure using a combination of in silico predictive tools and non-targeted analysis
ACS_2021_MWBOYCE_REVISED.PDF (PDF, NA pp, 1355.39 KB, about PDF)