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Mass spectrometry searches using MASST

Nature Biotechnology volume 38, pages 23–26 (2020)Cite this article

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To the Editor — We introduce a web-enabled mass spectrometry (MS) search engine, named Mass Spectrometry Search Tool (MASST; https://masst.ucsd.edu). By enabling searches of all small-molecule tandem MS (MS/MS) data in public metabolomics repositories, we posit that MASST will unlock these resources for clinical, environmental and natural product applications.

Introduced in 1990, a tool for discovering related protein or gene sequences named Basic Local Alignment Search Tool (BLAST) enabled researchers to query entire public sequence data repositories through a web interface (WebBLAST; https://blast.ncbi.nlm.nih.gov/Blast.cgi)1. WebBLAST is one of the most widely cited and used bioinformatics tools because it permits any researcher to answer simple questions, such as ‘is a protein or DNA sequence common or rare?’. In the early days of public gene and protein databases, metadata, which include descriptions of sample, population or technical details, were limited. No deposition standards existed, except for the Short Read Archive and European Nucleotide Archive, which include experimental details for sequencing, instrumental details and sample description, such as the source of a sample. The current status of much MS data in the public domain is reminiscent of the DNA databanks of the 1990s. To increase usage and unlock the potential of openly available MS resources, we set out to build an infrastructure to enable WebBLAST for MS.

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Fig. 1: MASST search, reporting and match visualization.

Data availability

All data used for testing and validating MASST are deposited in GNPS/MassIVE. MASST is a web-based application that is embedded in GNPS, which is a community service in which all public data are public. All data underlying figures present in the Supplementary Note are included as Supplementary Data 1 and 2. We cannot provide server installation, software engineers or administrator support for individual installations of MASST. The MASST platform is built as a workflow on top of the web repository workflow platform ProteoSAFe (https://github.com/CCMS-UCSD/ProteoSAFe). Each step of the MASST query is written in Python. Web rendering of the results is displayed by ProteoSAFe in the browser.

Code availability

For those who wish to build out MASST and recruit their own programmers, software engineers and system administrators, we have deposited the code at github (https://github.com/CCMS-UCSD/GNPS_Workflows/tree/master/search_single_spectrum). The standalone MASST query interface is written in Python and Flask with a web front end written in HTML and JavaScript. It is open source (https://github.com/mwang87/GNPS_MASST) and released under an LGPL-3 license.

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Acknowledgements

Conversion of data from different repositories was supported by R03 CA211211 on reuse of metabolomics data. The development of a user-friendly interface was in part supported by Gordon and Betty Moore Foundation through grant GBMF7622. The UC San Diego Center for Microbiome Innovation supported the campus wide SEED grant awards for data collection that enabled the development of much of this infrastructure. A.K.J. thanks the American Society for Mass Spectrometry for the 2018 Postdoctoral Career Development Award. We acknowledge C. O’Donovan and K. Haug for help with navigating the MetaboLights data repository. J.V.D.H. was supported by a ASDI eScience grant (ASDI.2017.030) from the Netherlands eScience Center (NLeSC). E.I.Z. and L.L.-B. were supported by NIH grants AI081923 and AI113923. A.M.C.R., K.E.K., S.P.P., J.L.K., M.J.B. and P.C.D. were supported by NSF grant IOS-1656475. A.B. was supported by National Institute of Justice Award 2015-DN-BX-K047. F.V. was supported by the Department of Navy, Office of Naval Research Multidisciplinary University Research Initiative (MURI) Award, award number N00014-15-1-2809. D.P. was supported by the German Research Foundation (DFG) with grant PE 2600/1. Additional support for data acquisition and data storage was provided by P41 GM103484 Center for Computational Mass Spectrometry, Instrument support though NIH S10RR029121. R.L. is supported by NIH grants R01DK106419, 5P42ES010337 and 5UL1TR001442, and NIH K01DK116917 to J.D.W. The development of the web interface and harmonization with Qiita was in part supported by the Sloan Foundation.

Author information

Authors and Affiliations

  1. Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA

    Mingxun Wang, Alan K. Jarmusch, Fernando Vargas, Alexander A. Aksenov, Julia M. Gauglitz, Kelly Weldon, Daniel Petras, Ricardo da Silva, Robert Quinn, Alexey V. Melnik, Justin J. J. van der Hooft, Andrés Mauricio Caraballo-Rodríguez, Louis Felix Nothias, Christine M. Aceves, Morgan Panitchpakdi, Elizabeth Brown, Nicole Sikora, Emmanuel O. Elijah, Emily C. Gentry, Amina Bouslimani, Madeleine Ernst & Pieter C. Dorrestein

  2. Ometa Labs LLC, San Diego, CA, USA

    Mingxun Wang

  3. Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA

    Fernando Vargas, Lara Labarta-Bajo & Elina I. Zúñiga

  4. Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA

    Kelly Weldon, Carolina S. Carpenter, Austin D. Swafford, Rohit Loomba, Rob Knight, Nuno Bandeira & Pieter C. Dorrestein

  5. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA

    Robert Quinn

  6. Bioinformatics Group, Wageningen University, Wageningen, The Netherlands

    Justin J. J. van der Hooft

  7. Faculty of Bioscience and Technology for Food, Agriculture, and Environment, University of Teramo, Teramo, TE, Italy

    Francesca Di Ottavio

  8. Department of Pharmacology, School of Medicine, University of California San Diego, La Jolla, CA, USA

    Shabnam Shalapour & Pieter C. Dorrestein

  9. Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA

    Kathleen E. Kyle & Jonathan L. Klassen

  10. Division of Medicinal Chemistry, Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT, USA

    Sara P. Puckett & Marcy J. Balunas

  11. Department of Medicine, University of California San Diego, San Diego, California, USA

    Jeramie D. Watrous

  12. Division of Gastroenterology, University of California San Diego, La Jolla, CA, USA

    Rohit Loomba

  13. Department of Pediatrics, University of California San Diego, La Jolla, CA, USA

    Rob Knight & Pieter C. Dorrestein

  14. Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA

    Rob Knight & Nuno Bandeira

  15. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA

    Nuno Bandeira

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Contributions

P.C.D. and M.W. came up with the concept of MASST. M.W. and N.B. performed the engineering to enable MASST. M.W., A.V.M., A.K.J., J.J.J.v.d.H., J.M.G., M.P., E.O.E., K.W., C.M.A., F.D.O., E.B., A.B., R.Q., M.C., N.S. and S.S. curated metadata. F.V., J.M.G., L.L.-B., K.W., E.B., A.A.A., R.Q., M.C. and C.S.C. generated data for the manuscript. E.C.G. synthesized the bile acids. P.C.D., M.W., D.P., J.D.W., M.J., L.F.N., J.M.G., E.I.Z., L.L.-B., K.E.K., S.P.P., A.M.C.R., A.V.M., F.V., K.W., A.A.A. and S.S. performed experiments and/or analysis for Box 1. P.C.D., D.P., L.F.N., J.J.J.v.d.H., J.M.G., A.A.A., A.M.C.R., F.V., K.W., A.B., F.D.O., M.E. and R.d.S. tested the MASST infrastructure and downloaded public data. P.C.D., N.B., E.I.Z., R.L., R.K., A.D.S., M.J.B. and J.L.K. provided supervision and funding for the project. P.C.D., A.K.J., D.P., J.J.v.d.H., M.E., J.M.G., A.A.A., A.M.C.R., R.K., J.L.K., L.F.N., N.B. and M.W. wrote and edited the manuscript.

Corresponding author

Correspondence to Pieter C. Dorrestein.

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Competing interests

M.W. is the founder of Ometa Labs LLC and consults for Sirenas, and P.C.D. is on the scientific advisory board of Sirenas.

Supplementary information

Supplementary Note

Supplementary Data for Supplementary Note Box Figure 1a

Underlying data for figure panel in the Supplementary Note.

Supplementary Data for Supplementary Note Box Figure 1c,d

Underlying data for figure panel in the Supplementary Note.

Supplementary Data for Supplementary Note Box Figure 2a

Underlying data for figure panel in the Supplementary Note.

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Wang, M., Jarmusch, A.K., Vargas, F. et al. Mass spectrometry searches using MASST. Nat Biotechnol 38, 23–26 (2020). https://doi.org/10.1038/s41587-019-0375-9

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