Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring

Metadata Updated: January 18, 2020

There is a growing need in the field of exposure science for monitoring methods that rapidly screen environmental media for suspect contaminants. Measurement and analysis platforms, based on high resolution mass spectrometry (HRMS), now exist to meet this need. Here we describe results of a study that links HRMS data with exposure predictions from the U.S. EPA's ExpoCast™ program and in vitro bioassay data from the U.S. interagency Tox21 consortium. Vacuum dust samples were collected from 56 households across the U.S. as part of the American Healthy Homes Survey (AHHS). Sample extracts were analyzed using liquid chromatography time-of-flight mass spectrometry (LC–TOF/MS) with electrospray ionization. On average, approximately 2000 molecular features were identified per sample (based on accurate mass) in negative ion mode, and 3000 in positive ion mode. Exact mass, isotope distribution, and isotope spacing were used to match molecular features with a unique listing of chemical formulas extracted from EPA's Distributed Structure-Searchable Toxicity (DSSTox) database. A total of 978 DSSTox formulas were consistent with the dust LC–TOF/molecular feature data (match score ≥ 90); these formulas mapped to 3228 possible chemicals in the database. Correct assignment of a unique chemical to a given formula required additional validation steps. Each suspect chemical was prioritized for follow-up confirmation using abundance and detection frequency results, along with exposure and bioactivity estimates from ExpoCast and Tox21, respectively. Chemicals with elevated exposure and/or toxicity potential were further examined using a mixture of 100 chemical standards. A total of 33 chemicals were confirmed present in the dust samples by formula and retention time match; nearly half of these do not appear to have been associated with house dust in the published literature. Chemical matches found in at least 10 of the 56 dust samples include Piperine, N,N-Diethyl-m-toluamide (DEET), Triclocarban, Diethyl phthalate (DEP), Propylparaben, Methylparaben, Tris(1,3-dichloro-2-propyl)phosphate (TDCPP), and Nicotine. This study demonstrates a novel suspect screening methodology to prioritize chemicals of interest for subsequent targeted analysis. The methods described here rely on strategic integration of available public resources and should be considered in future non-targeted and suspect screening assessments of environmental and biological media.

This dataset is associated with the following publication: Rager, J.E., M. Strynar , S. Liang, R.L. McMahen, A. Richard , C.M. Grukle, J. Wambaugh , K. Isaacs , R. Judson , A. Williams , and J. Sobus. Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 88: 269-280, (2016).

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Public: This dataset is intended for public access and use. License: See this page for license information.

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References

https://doi.org/10.1016/j.envint.2015.12.008

Dates

Metadata Created Date September 26, 2016
Metadata Updated Date January 18, 2020

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date September 26, 2016
Metadata Updated Date January 18, 2020
Publisher U.S. EPA Office of Research and Development (ORD)
Unique Identifier A-dbs5-231
Maintainer
Jon Sobus
Maintainer Email
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Harvest Object Id 0da98e06-f090-4b71-93b6-673b58726d42
Harvest Source Id cf9b0004-f9fd-420e-bade-a86839e82acf
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Data Last Modified 2015-12-15
Program Code 020:095
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents https://doi.org/10.1016/j.envint.2015.12.008
Source Datajson Identifier True
Source Hash 62bfdb51b4080c4d8b647c4af877ac155db45c16
Source Schema Version 1.1

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