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SETAC Rome Non-Target Screening For Chemical Discovery

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SETAC Special Session: Solutions for emerging pollutants – Towards a holistic chemical quality status assessment in European freshwater resources
Non-target Screening for Holistic Chemical Monitoring and Compound Discovery: Open Science, Real-time and Retrospective Approaches
Emma L. Schymanski [1*], Reza Aalizadeh [2], Nikiforos Alygizakis [3], Juliane Hollender [4], Martin Krauss [5], Tobias Schulze [5], Jaroslav Slobodnik [3], Nikolaos S. Thomaidis [2] and Antony J. Williams [6]
[1] Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
[2] National and Kapodistrian University of Athens, Department of Chemistry, Athens, Greece.
[3] Environmental Institute, Koš, Slovak Republic
[4] Eawag: Swiss Federal Institute for Aquatic Science and Technology, Dübendorf, Switzerland
[5] UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
[6] National Centre for Computational Toxicity, US EPA, Research Triangle Park, Durham, NC, USA
*presenting author: emma.schymanski@uni.lu
Keywords: Non-target screening, Open Science, Mass Spectrometry, Monitoring
Non-target screening (NTS) with high resolution mass spectrometry (HR-MS) provides opportunities to discover chemicals, their dynamics and effects on the environment far beyond the current 45 “priority pollutants” or even “known” chemicals. Open science and the exchange of information (between for example scientists and regulatory authorities) has a critical role to play in the continuing evolution of NTS. Using a variety of case studies from Europe, this talk will highlight how open science activities such as MassBank.EU (https://massbank.eu), the NORMAN Suspect Exchange (http://www.norman-network.com/?q=node/236) and NORMAN Digital Sample Freezing Platform (http://norman-data.eu) as well as the US EPA CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard/) can support NTS. Further, it will show how initiatives such as near “real time” monitoring of the River Rhine and retrospective screening via so-called “digital freezing” platforms have opened up new potential for exploring the dynamics and distribution even of as-yet-unidentified chemicals. Collaborative European and international activities facilitate data exchange amongst analytical data scientists and enable quick, effective and reproducible provisional compound identification in digitally archived HR-MS data. This is leading to new ways of assessing and prioritizing the next generation of “emerging pollutants” in the environment, enabling a pro-active approach to environmental assessment unthinkable only a few years ago. Note: This abstract does not reflect US EPA policy.

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SETAC Rome Non-Target Screening For Chemical Discovery

  1. 1. 1 Non-target Screening for Holistic Chemical Monitoring and Compound Discovery: Open Science, Real-time and Retrospective Approaches Emma L. Schymanski Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg. Email: emma.schymanski@uni.lu Reza Aalizadeh, Nikiforos Aligizakis, Juliane Hollender, Martin Krauss, Tobias Schulze, Jaroslav Slobodnik, Nikolaos S. Thomaidis, Antony J. Williams Image © www.seanoakley.com/ The views expressed in this presentation are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. https://tinyurl.com/rome-solutions-nts
  2. 2. 2 What chemicals are out there? What to monitor? Numbers from Hollender, Schymanski, Singer & Ferguson, 2018, ES&T Feature, 51:20, 11505-11512. DOI: 10.1021/acs.est.7b02184 Chemical Space Knowns, Suspects and Unknowns *Estimate from MINE predictions of smaller datasets. Jeffryes et al. 2015. DOI: 10.1186/s13321-015-0087-1 **True number cannot be calculated. Non-target Screening of Complex Samples with HR-MS
  3. 3. 3 Non-target Screening for Chemical Monitoring Mod. from Hollender, Schymanski, Singer & Ferguson, 2018, ES&T Feature, 51:20, 11505-11512. DOI: 10.1021/acs.est.7b02184 Retrospective Retrospective Real-Time 1) Open Science 2) Real-Time & Retrospective Screening suspects Chemistry Dashboard Sampling AnalysisAnalysis Data Pre-Processing Prioritization Identification
  4. 4. 4 1) Open Science: MassBank EU https://github.com/MassBank/MassBank-data; https://github.com/MassBank/MassBank-web/; Rösch et al DOI 10.1021/acs.est.5b05186 http://massbank.eu/MassBank o MassBank.EU was founded late 2012, hosted at UFZ, Leipzig, Germany o >16,000 MS/MS spectra; 1,200 substances from NORMAN members o MassBank now has >46,000 spectra from 32 contributing institutes! o Thorough Github-based modernization in progress for traceability: o Tentative/unknown/literature spectra (Level Scheme) as SI for publications Schymanski et al DOI: 10.1021/es5002105
  5. 5. 5 NORMAN Suspect List Exchange o http://www.norman-network.com/?q=node/236 o 21 lists available … specialist collections to market lists • Integrated in NORMAN Databases & CompTox Chemistry Dashboard Schymanski, Aalizadeh et al. in prep; https://www.researchgate.net/project/Supporting-Mass-Spectrometry-Through-Cheminformatics
  6. 6. 6 NORMAN SusDat http://normandata.eu/normansusdat/ Schymanski, Aalizadeh et al. in prep.
  7. 7. 7 CompTox Chemistry Dashboard https://comptox.epa.gov/dashboard/chemical_lists/ … new lists are released all the time! http://normandata.eu/normansusdat/
  8. 8. 8 …All Combined in MetFrag https://msbi.ipb-halle.de/MetFragBeta/ AND https://comptox.epa.gov/dashboard/dsstoxdb/batch_search (MetFrag Export)
  9. 9. 9 …All Combined in MetFrag Example from: Schymanski & Williams, 2017, ES&T, 51 (10), pp 5357–5359. DOI: 10.1021/acs.est.7b01908
  10. 10. 10 Non-target Screening for Chemical Monitoring o Part 2: Real-Time and Retrospective Screening Retrospective Retrospective And Real-Time Sampling Analysis Data Pre-Processing Prioritization Identification Mod. from Hollender, Schymanski, Singer & Ferguson, 2018, ES&T Feature, 51:20, 11505-11512. DOI: 10.1021/acs.est.7b02184
  11. 11. 11 Real-time Monitoring of the Rhine River Hollender, Schymanski, Singer & Ferguson, 2018, ES&T Feature, 51:20, 11505-11512. DOI: 10.1021/acs.est.7b02184 Previously unknown chemicals detected due to “stand-out” patterns
  12. 12. 12 Real-time Monitoring of the Rhine River Hollender, Schymanski, Singer & Ferguson, 2018, ES&T Feature, 51:20, 11505-11512. DOI: 10.1021/acs.est.7b02184 Previously unknown chemicals detected due to “stand-out” patterns
  13. 13. 13 European (World-)Wide Exchange of Suspects Schymanski et al. 2015, ABC, DOI: 10.1007/s00216-015-8681-7; Wang et al 2016 Nature Biotechnology, DOI: 10.1038/nbt.3597 NORMAN Suspect List Exchange: http://www.norman-network.com/?q=node/236 Tentatively Identified Spectra: http://goo.gl/0t7jGp Hits in GNPS MassIVE datasets: TPs in skin: http://goo.gl/NmO4tx Surfactants: http://goo.gl/7sY9Pf
  14. 14. 14 Retrospective Screening: Emerging Suspects Alygizakis et al. 2018 ES&T, DOI: 10.1021/acs.est.8b00365 AND https://comptox.epa.gov/dashboard/chemical_lists/normanews Switzerland Mapimages©GoogleMaps NormaNEWS in Science: DOI: 10.1126/science.360.6389.616-d
  15. 15. 15 Interactive heatmap available at http://norman-data.eu/NORMAN-REACH NORMAN Digital Sample Freezing Platform Retrospective screening of REACH chemicals in Black Sea samples (various matrices)
  16. 16. 16 NORMAN Digital Sample Freezing Platform “Live” retrospective screening of known and unknown chemicals in European samples (various matrices) http://norman-data.eu/ AND Aligizakis et al, in prep.
  17. 17. 17 NORMAN Digital Sample Freezing Platform “Live” retrospective screening of known and unknown chemicals in European samples (various matrices) Future work: use results of unknowns to drive prioritization efforts http://norman-data.eu/ AND Aligizakis et al, in prep.
  18. 18. 18 Acknowledgements I Updates: https://www.researchgate.net/project/Supporting-Mass-Spectrometry-Through-Cheminformatics emma.schymanski@uni.lu Further Information: http://www.norman-network.com/?q=node/236 https://massbank.eu/MassBank/ https://github.com/MassBank/ https://comptox.epa.gov/dashboard/ http://normandata.eu/normansusdat/ http://norman-data.eu/ .eu EU Grant 603437 suspects Chemistry Dashboard
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  21. 21. 21 Creating High-Quality Mass Spectra Stravs, Schymanski, Singer and Hollender, 2013, Journal of Mass Spectrometry, 48, 89–99. DOI: 10.1002/jms.3131 Automatic MS and MS/MS Recalibration and Clean-up Remove interfering peaks Spectral Annotation with - Experimental Details - Compound Information https://github.com/MassBank/RMassBank/ http://bioconductor.org/packages/RMassBank/ 16,004 (61 %*) MS/MS spectra 1,269 (18 %*) substances *% of all open LC-MS/MS data
  22. 22. 22 Confidence Levels for Tentative Structures Schymanski, Jeon, Gulde, Fenner, Ruff, Singer & Hollender (2014) ES&T, 48 (4), 2097-2098. DOI: 10.1021/es5002105 o Annotation is the key to communicating information MS, MS2, RT, Reference Std. Level 1: Confirmed structure by reference standard Level 2: Probable structure a) by library spectrum match b) by diagnostic evidence Identification confidence N N N NHNH CH3 CH3 S CH3 OH MS, MS2, Library MS2 MS, MS2, Exp. data Example Minimum data requirements Level 4: Unequivocal molecular formula Level 5: Exact mass of interest C6H5N3O4 192.0757 MS isotope/adduct MS Level 3: Tentative candidate(s) structure, substituent, class MS, MS2, Exp. data
  23. 23. 23 NORMAN Suspect List Exchange o http://www.norman-network.com/?q=node/236 Schymanski, Aalizadeh et al. in prep; https://www.researchgate.net/project/Supporting-Mass-Spectrometry-Through-Cheminformatics ReferencesFull Lists

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