Advertisement

Analytical and Bioanalytical Chemistry

, Volume 411, Issue 4, pp 835–851 | Cite as

Using prepared mixtures of ToxCast chemicals to evaluate non-targeted analysis (NTA) method performance

  • Jon R. SobusEmail author
  • Jarod N. Grossman
  • Alex Chao
  • Randolph Singh
  • Antony J. Williams
  • Christopher M. Grulke
  • Ann M. Richard
  • Seth R. Newton
  • Andrew D. McEachran
  • Elin M. Ulrich
Research Paper

Abstract

Non-targeted analysis (NTA) methods are increasingly used to discover contaminants of emerging concern (CECs), but the extent to which these methods can support exposure and health studies remains to be determined. EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT) was launched in 2016 to address this need. As part of ENTACT, 1269 unique substances from EPA’s ToxCast library were combined to make ten synthetic mixtures, with each mixture containing between 95 and 365 substances. As a participant in the trial, we first performed blinded NTA on each mixture using liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS). We then performed an unblinded evaluation to identify limitations of our NTA method. Overall, at least 60% of spiked substances could be observed using selected methods. Discounting spiked isomers, true positive rates from the blinded and unblinded analyses reached a maximum of 46% and 65%, respectively. An overall reproducibility rate of 75% was observed for substances spiked into more than one mixture and observed at least once. Considerable discordance in substance identification was observed when comparing a subset of our results derived from two separate reversed-phase chromatography methods. We conclude that a single NTA method, even when optimized, can likely characterize only a subset of ToxCast substances (and, by extension, other CECs). Rigorous quality control and self-evaluation practices should be required of labs generating NTA data to support exposure and health studies. Accurate and transparent communication of performance results will best enable meaningful interpretations and defensible use of NTA data.

Graphical abstract

Keywords

ENTACT Non-targeted analysis ToxCast Exposome 

Notes

Acknowledgements

The authors thank Annette Guiseppi-Elie, Jennifer Orme-Zavaleta, and Russell Thomas for supporting ENTACT; Katherine Coutros for her assistance in acquiring ToxCast substances, Kamel Mansouri for his role in developing and implementing MS-Ready processing algorithms; Risa Sayre for her assistance in comparing spiked substances against compounds in Agilent reference libraries; and Sarah Laughlin, Aurelie Marcotte, Dawn Mills, James McCord, Mark Strynar, and Carol Ball (Agilent Technologies) for their contributions to the methods used for sample analysis and data processing. The authors further thank James McCord and Mark Strynar for their thoughtful reviews of this manuscript.

Funding information

The United States Environmental Protection Agency (U.S. EPA), through its Office of Research and Development (ORD), funded and managed the research described here. Partial support for this work was provided by an award from ORD’s Pathfinder Innovation Program. The work has been subjected to Agency administrative review and approved for publication. Randolph Singh and Andrew McEachran were supported by an appointment to the Internship/Research Participation Program at the Office of Research and Development, U.S. Environmental Protection Agency, administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and EPA.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Disclaimer

The views expressed in this paper are those of the authors and do not necessarily represent the views or policies of the U.S. EPA.

Supplementary material

216_2018_1526_MOESM1_ESM.pdf (1.9 mb)
ESM 1 (PDF 1947 kb)
216_2018_1526_MOESM2_ESM.xlsx (11.6 mb)
ESM 2 (XLSX 11865 kb)
216_2018_1526_MOESM3_ESM.sdf (1.7 mb)
ESM 3 (SDF 1717 kb)
216_2018_1526_MOESM4_ESM.sdf (891 kb)
ESM 4 (SDF 890 kb)
216_2018_1526_MOESM5_ESM.sdf (270 kb)
ESM 5 (SDF 269 kb)

References

  1. 1.
    Phillips KA, Yau A, Favela KA, Isaacs KK, McEachran A, Grulke C, et al. Suspect screening analysis of chemicals in consumer products. Environ Sci Technol. 2018;52(5):3125–35.  https://doi.org/10.1021/acs.est.7b04781.CrossRefGoogle Scholar
  2. 2.
    Biryol D, Nicolas CI, Wambaugh J, Phillips K, Isaacs K. High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization. Environ Int. 2017;108:185–94.  https://doi.org/10.1016/j.envint.2017.08.004.CrossRefGoogle Scholar
  3. 3.
    Newton SR, McMahen RL, Sobus JR, Mansouri K, Williams AJ, McEachran AD, et al. Suspect screening and non-targeted analysis of drinking water using point-of-use filters. Environ Pollut. 2018;234:297–306.  https://doi.org/10.1016/j.envpol.2017.11.033.CrossRefGoogle Scholar
  4. 4.
    Rager JE, Strynar MJ, Liang S, McMahen RL, Richard AM, Grulke CM, et al. Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. Environ Int. 2016;88:269–80.  https://doi.org/10.1016/j.envint.2015.12.008.CrossRefGoogle Scholar
  5. 5.
    Alygizakis NA, Samanipour S, Hollender J, Ibanez M, Kaserzon S, Kokkali V, et al. Exploring the potential of a global emerging contaminant early warning network through the use of retrospective suspect screening with high-resolution mass spectrometry. Environ Sci Technol. 2018.  https://doi.org/10.1021/acs.est.8b00365.
  6. 6.
    Gerona RR, Schwartz JM, Pan J, Friesen MM, Lin T, Woodruff TJ. Suspect screening of maternal serum to identify new environmental chemical biomonitoring targets using liquid chromatography-quadrupole time-of-flight mass spectrometry. J Expo Sci Environ Epidemiol. 2018;28(2):101–8.  https://doi.org/10.1038/jes.2017.28.CrossRefGoogle Scholar
  7. 7.
    Colby JM, Thoren KL, Lynch KL. Suspect screening using LC-QqTOF is a useful tool for detecting drugs in biological samples. J Anal Toxicol. 2018.  https://doi.org/10.1093/jat/bkx107.
  8. 8.
    Moritz F, Janicka M, Zygler A, Forcisi S, Kot-Wasik A, Kot J, et al. The compositional space of exhaled breath condensate and its link to the human breath volatilome. J Breath Res. 2015;9(2):027105.  https://doi.org/10.1088/1752-7155/9/2/027105.CrossRefGoogle Scholar
  9. 9.
    Andra SS, Austin C, Wright RO, Arora M. Reconstructing pre-natal and early childhood exposure to multi-class organic chemicals using teeth: towards a retrospective temporal exposome. Environ Int. 2015;83:137–45.  https://doi.org/10.1016/j.envint.2015.05.010.CrossRefGoogle Scholar
  10. 10.
    Rubert J, Leon N, Saez C, Martins CP, Godula M, Yusa V, et al. Evaluation of mycotoxins and their metabolites in human breast milk using liquid chromatography coupled to high resolution mass spectrometry. Anal Chim Acta. 2014;820:39–46.  https://doi.org/10.1016/j.aca.2014.02.009.CrossRefGoogle Scholar
  11. 11.
    Wild CP. Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomark Prev. 2005;14(8):1847–50.  https://doi.org/10.1158/1055-9965.EPI-05-0456.CrossRefGoogle Scholar
  12. 12.
    Rappaport SM, Smith MT. Epidemiology. Environment and disease risks. Science. 2010;330(6003):460–1.  https://doi.org/10.1126/science.1192603. CrossRefGoogle Scholar
  13. 13.
    Andra SS, Austin C, Patel D, Dolios G, Awawda M, Arora M. Trends in the application of high-resolution mass spectrometry for human biomonitoring: an analytical primer to studying the environmental chemical space of the human exposome. Environ Int. 2017;100:32–61.  https://doi.org/10.1016/j.envint.2016.11.026.CrossRefGoogle Scholar
  14. 14.
    Schymanski EL, Singer HP, Slobodnik J, Ipolyi IM, Oswald P, Krauss M, et al. Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis. Anal Bioanal Chem. 2015;407(21):6237–55.  https://doi.org/10.1007/s00216-015-8681-7.CrossRefGoogle Scholar
  15. 15.
    Sobus JR, Wambaugh JF, Isaacs KK, Williams AJ, McEachran AD, Richard AM, et al. Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA. J Expo Sci Environ Epidemiol. 2017.  https://doi.org/10.1038/s41370-017-0012-y.
  16. 16.
    Richard AM, Judson RS, Houck KA, Grulke CM, Volarath P, Thillainadarajah I, et al. ToxCast chemical landscape: paving the road to 21st century toxicology. Chem Res Toxicol. 2016;29(8):1225–51.  https://doi.org/10.1021/acs.chemrestox.6b00135.CrossRefGoogle Scholar
  17. 17.
    Ulrich EM, Sobus JR, Grulke CM, Richard AM, Newton SR, Strynar MJ, Mansouri K, Williams AJ. EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT): genesis, design, and initial findings. Anal Bioanal Chem. 2018.  https://doi.org/10.1007/s00216-018-1435-6.
  18. 18.
    Williams AJ, Grulke CM, Edwards J, McEachran AD, Mansouri K, Baker NC, et al. The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. J Cheminform. 2017;9(1):61.  https://doi.org/10.1186/s13321-017-0247-6. CrossRefGoogle Scholar
  19. 19.
    McEachran AD, Mansouri K, Grulke CM, Schymanski EL, Ruttkies C, Williams AJ. “MS-Ready” structures for non-targeted high resolution mass spectrometry screening studies. J Cheminform. 2018;10(1):45.  https://doi.org/10.1186/s13321-018-0299-2. CrossRefGoogle Scholar
  20. 20.
    McEachran AD, Sobus JR, Williams AJ. Identifying known unknowns using the US EPA’s CompTox Chemistry Dashboard. Anal Bioanal Chem. 2017;409(7):1729–35.  https://doi.org/10.1007/s00216-016-0139-z.CrossRefGoogle Scholar
  21. 21.
    Sobus JR, DeWoskin RS, Tan YM, Pleil JD, Phillips MB, George BJ, et al. Uses of NHANES biomarker data for chemical risk assessment: trends, challenges, and opportunities. Environ Health Perspect. 2015;123(10):919–27.  https://doi.org/10.1289/ehp.1409177.CrossRefGoogle Scholar
  22. 22.
    McEachran AD, Mansouri K, Newton SR, Beverly BEJ, Sobus JR, Williams AJ. A comparison of three liquid chromatography (LC) retention time prediction models. Talanta. 2018;182:371–9.  https://doi.org/10.1016/j.talanta.2018.01.022.CrossRefGoogle Scholar
  23. 23.
    Ruttkies C, Schymanski EL, Wolf S, Hollender J, Neumann S. MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J Cheminform. 2016;8:3.  https://doi.org/10.1186/s13321-016-0115-9.CrossRefGoogle Scholar
  24. 24.
    Allen F, Pon A, Wilson M, Greiner R, Wishart D. CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra. Nucleic Acids Res. 2014;42(Web Server issue):W94–9.  https://doi.org/10.1093/nar/gku436.CrossRefGoogle Scholar
  25. 25.
    Allen F, Pon A, Greiner R, Wishart D. Computational prediction of electron ionization mass spectra to assist in GC/MS compound identification. Anal Chem. 2016;88(15):7689–97.  https://doi.org/10.1021/acs.analchem.6b01622.CrossRefGoogle Scholar
  26. 26.
    Schymanski EL, Jeon J, Gulde R, Fenner K, Ruff M, Singer HP, et al. Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol. 2014;48(4):2097–8.  https://doi.org/10.1021/es5002105.CrossRefGoogle Scholar
  27. 27.
    Straub RF, Voyksner RD. Negative ion formation in electrospray mass spectrometry. J Am Soc Mass Spectrom. 1993;4(7):578–87.  https://doi.org/10.1016/1044-0305(93)85019-T.CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2019

Authors and Affiliations

  • Jon R. Sobus
    • 1
    Email author return OK on get
  • Jarod N. Grossman
    • 2
    • 3
  • Alex Chao
    • 2
  • Randolph Singh
    • 4
  • Antony J. Williams
    • 5
  • Christopher M. Grulke
    • 5
  • Ann M. Richard
    • 5
  • Seth R. Newton
    • 1
  • Andrew D. McEachran
    • 4
  • Elin M. Ulrich
    • 1
  1. 1.U.S. Environmental Protection Agency, Office of Research and DevelopmentNational Exposure Research LaboratoryResearch Triangle ParkUSA
  2. 2.Student Contractor, U.S. Environmental Protection Agency, Office of Research and DevelopmentNational Exposure Research LaboratoryResearch Triangle ParkUSA
  3. 3.Agilent Technologies Inc.Santa ClaraUSA
  4. 4.Oak Ridge Institute for Science and Education (ORISE) ParticipantResearch Triangle ParkUSA
  5. 5.U.S. Environmental Protection Agency, Office of Research and DevelopmentNational Center for Computational ToxicologyResearch Triangle ParkUSA

Personalised recommendations