Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data

1,118 views

Published on

There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.

Published in: Science
  • Be the first to comment

The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data

  1. 1. The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data Antony J. Williams†, Andrew McEachran, Jon Sobus, Chris Grulke, Jennifer Smith, Michelle Krzyzanowski, Jordan Foster and Jeff Edwards National Center for Computational Toxicology U.S. Environmental Protection Agency, RTP, NC August 21-25, 2016 ACS Fall Meeting, Philadelphia, PA http://www.orcid.org/0000-0002-2668-4821 The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the U.S. EPA
  2. 2. Who is NCCT? • National Center for Computational Toxicology – part of EPA’s Office of Research and Development • Research driven by EPA’s Chemical Safety for Sustainability Research Program – Develop new approaches to evaluate the safety of chemicals – Integrate advances in biology, biotechnology, chemistry, exposure science and computer science • Goal - To identify chemical exposures that may disrupt biological processes and cause adverse outcomes. 1
  3. 3. Our Dashboard Applications • Some of our Web-based Applications 2
  4. 4. Introducing Our Latest Dashboard https://comptox.epa.gov 3 • >720,000 chemicals • >10 years assembling data
  5. 5. Bisphenol A 4
  6. 6. Physicochemical Properties 5
  7. 7. Bioassay Screening Data 6
  8. 8. Functional Use and Composition 7
  9. 9. Advanced MS Searches 8
  10. 10. Monoisotopic Mass Search 9
  11. 11. Monoisotopic Mass Search 10 Found 344 results for '215.096 ± 0.005 amu'
  12. 12. Formula Search 11
  13. 13. Formula Search 12 Found 8 results for 'C8H14ClN5'
  14. 14. Formula Searching Formulae matching Bisphenol A 13
  15. 15. Formula Search Results 14
  16. 16. Download to Excel 15
  17. 17. Download as SDF file 16
  18. 18. SDF file downloaded to desktop 17
  19. 19. Rank-Ordering of “Known-Unknowns” using ChemSpider 18
  20. 20. Comparing Performance 19 721k structures
  21. 21. Does the Dashboard Add Value? • Remember: – Focus on high quality data and curation – Data sources include EPA data sources and a focus on environmental chemistry • No “dilution” by chemical vendors 20
  22. 22. Dilution Example… Morphine Skeleton 21
  23. 23. Bisphenol A as an example ChemSpider: 1564 Structures 22
  24. 24. Bisphenol A as an example Dashboard: 215 Structures 23
  25. 25. Chemical Identification Dashboard vs ChemSpider Sorted by number of references (ChemSpider) or data sources (Dashboard) Monoisotopic Mass (+/- 0.005 amu) Search Position of compound sorted Source of List # of Compounds Search Tool Mean Position Median Position #1 #2 #3 #4 #5+ McEachran et al Wastewater 34 ChemSpider 1.8 1 28 5 0 0 1 Dashboard 1.3 1 31 2 0 0 1 Misc. NTA Compounds 13 ChemSpider 2 1 7 5 0 0 1 Dashboard 1.7 1 10 2 0 0 1 Bade et al (2016) 19 ChemSpider 2.1 1 11 2 5 0 1 Dashboard 1.6 1 12 3 3 1 0 Rager et al (2016) 24 ChemSpider 2.25 1 15 2 1 2 4 Dashboard 1.08 1 22 2 0 0 0
  26. 26. Dashboard vs ChemSpider Ranking Summary Mass-based Searching Formula Based Searching Dashboard ChemSpider Dashboard ChemSpider Cumulative Average Position 1.3 2.2 1.2 1.4 % in #1 Position 85% 70% 88% 80% • Selected peer-reviewed publications • 162 total individual chemicals in search
  27. 27. ChemSpider 6926 Results!!! 26 Tacedinaline Methyl Red C.I Disperse Yellow 3
  28. 28. Using Functional Use to Sort Candidates 27 Anti-cancer Drug Microbiological Indicator Dye Textile/Product Dye
  29. 29. Same top hits – different ranking 90 hits only versus 6926 hits 28 18 17 4Tacedinaline Methyl Red C.I Disperse Yellow 3
  30. 30. Dashboard: External Links to Analytical Methods 29
  31. 31. National Environmental Methods Index 30
  32. 32. RSC Analytical Abstracts 31
  33. 33. Integrated Google Chemical Searches 32
  34. 34. Google Chemical Searches Enhanced with Query Terms 33
  35. 35. Non-Targeted Analysis Research - 1 Dust Sample - Negative Ionization Mode - 300 Extracted “Molecular Features” 1) Prioritize “Molecular Features” 2) Correctly assign formulas 3) Correctly assign structures 4) Determine chemical sources 5) Predict chemical concentrations C17H19NO3 12 µg/g (1) (2) (3) (4) (5) What is contained in house dust, waste streams etc???
  36. 36. Previous Work with Suspect-Screening The dashboard is being enhanced to support Non-targeted Analysis
  37. 37. Future Work • Presently researching rank-ordering based on other criteria – Pubmed • Additional links to methods – CDC NIOSH • Links to Mass Spec databases – Thermo’s mzCloud, Massbank. Metlin etc. • Consider predicting metabolites and degradants • Searching based on “MS-ready” structures 36
  38. 38. “MS Ready” structures • Many compounds are salts – searches should be on the “neutral form” • Need to search for adducts (+Na, +K, +NH4), decarboxylation, loss of water etc. 37
  39. 39. Conclusions • Dashboard support for MS is focused on NTA research – related to chemical exposure • Dashboard outperforms ChemSpider for ranking chemicals of environmental concern • New searches developed with Non-targeted Analysis in mind - new rank-ordering approaches in development 38
  40. 40. Acknowledgements EPA NCCT Chris Grulke Jeff Edwards Ann Richard Jordan Foster Jennifer Smith Andrew McEachran* Michelle Krzyzanowski EPA NERL Jon Sobus * = ORISE Participant

×