Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

METLIN MS2 molecular standards database: a broad chemical and biological resource

Nature Methods volume 17, pages 953–954 (2020)Cite this article

Subjects

To the Editor — Tandem mass spectrometry (MS2) data provide high-confidence molecular identification of known molecules and preliminary characterization of novel, unknown molecules (unknowns). However, for databases to be an effective resource, broad chemical space coverage is necessary. Consequently, we have created METLIN (http://metlin.scripps.edu) a highly annotated and structurally diverse database of over 850,000 molecular standards. METLIN’s tandem mass spectral library numerically covers almost 1% of PubChem’s 93 million compounds, essentially a number that can be characterized as the known chemical space.

The combination of METLIN’s molecular standards and systematically acquired experimental data allows for the examination of the impact that MS2 data has on the identification of known molecules. For example, when METLIN is searched against precursor m/z values at varying parts per million (ppm) errors, the number of hits typically ranges from tens to hundreds of compounds. However, with the addition of MS2 data, the false positive rate can be minimized to only a few compounds. Beyond providing molecular identification through its multiple search capabilities (for example, MS2, batch, name and elemental composition), METLIN’s expansion will facilitate similarity searching. The similarity searching algorithm was originally developed to aid in the identification of unknowns and the discovery of novel molecules4 and operates by using fragment ion data to help align an unknown molecule to compounds with similar fragmentation data within a database to help further identify and characterize it4. METLIN’s fragment ion similarity searching and neutral loss similarity searching are applied in identifying endogenous metabolites, drugs and drug metabolites, as well as biotransformation products of xenobiotics5. METLIN facilitates both endogenous and exogenous compound identification. For example, it contains MS2 data for over 60,000 pyrimidine analogs and over 6,000 purine analogs (Fig. 1b), among others.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The METLIN MS2 database.

Data availability

The data in the METLIN database are available at http://metlin.scripps.edu. The data in other databases mentioned in this study were obtained from their websites (accessed in February 2020) or published papers: MoNA (https://mona.fiehnlab.ucdavis.edu/), mzCloud (https://www.mzcloud.org/), GNPS (https://gnps.ucsd.edu/)9, HMDB (https://hmdb.ca/)10 and NIST 17 (https://chemdata.nist.gov/).

References

  1. Guijas, C. et al. Anal. Chem. 90, 3156–3164 (2018).

    Article  CAS  Google Scholar 

  2. Tautenhahn, R. et al. Nat. Biotechnol. 30, 826–828 (2012).

    Article  CAS  Google Scholar 

  3. Kafader, J. O. et al. Nat. Methods 17, 391–394 (2020).

    Article  CAS  Google Scholar 

  4. Benton, H. P., Wong, D. M., Trauger, S. A. & Siuzdak, G. Anal. Chem. 80, 6382–6389 (2008).

    Article  CAS  Google Scholar 

  5. Flasch, M. et al. ACS Chem. Biol. 15, 970–981 (2020).

    Article  CAS  Google Scholar 

  6. Xue, J. et al. Anal. Chem. 92, 6051–6059 (2020).

    Article  CAS  Google Scholar 

  7. Quinn, R. A. et al. Nature 579, 123–129 (2020).

    Article  CAS  Google Scholar 

  8. Clayton, T. A., Baker, D., Lindon, J. C., Everett, J. R. & Nicholson, J. K. Proc. Natl Acad. Sci. USA 106, 14728–14733 (2009).

    Article  CAS  Google Scholar 

  9. Wang, M. et al. Nat. Biotechnol. 38, 23–26 (2020).

    Article  CAS  Google Scholar 

  10. Wishart, D. S. et al. Nucleic Acids Res. 46, D608–D617 (2018). D1.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was partially funded by US National Institutes of Health grants R35 GM130385 (G.S.), P30 MH062261 (G.S.), P01 DA026146 (G.S.) and U01 CA235493 (G.S.) and by Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory for the US Department of Energy, Office of Science, Office of Biological and Environmental Research, under contract number DE-AC02-05CH11231 (G.S.).

Author information

Author notes

  1. These authors contributed equally: Jingchuan Xue, Carlos Guijas.

Authors and Affiliations

  1. Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute, La Jolla, CA, USA

    Jingchuan Xue, Carlos Guijas, H. Paul Benton & Gary Siuzdak

  2. Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria

    Benedikt Warth

  3. Department of Molecular and Computational Biology, Scripps Research Institute, La Jolla, CA, USA

    Gary Siuzdak

Authors
  1. Jingchuan Xue
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carlos Guijas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. Paul Benton
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Benedikt Warth
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gary Siuzdak
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.X., C.G., H.P.B., B.W. and G.S. contributed to data collection, analysis, and manuscript writing. J.X. and C.G. share first authorship.

Corresponding author

Correspondence to Gary Siuzdak.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Editorial note: This article has been peer reviewed.

Source data

Source Data Fig. 1

Statistical Source Data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xue, J., Guijas, C., Benton, H.P. et al. METLIN MS2 molecular standards database: a broad chemical and biological resource. Nat Methods 17, 953–954 (2020). https://doi.org/10.1038/s41592-020-0942-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-020-0942-5

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research