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METLIN Database
Content
Descriptionrepository of chemical entity information as well as tandem mass spectrometry data
Contact
Research centerThe Scripps Research Institute
LaboratorySiuzdak laboratory at The Scripps Research Institute
Release date2005
Access
Websitemetlin.scripps.edu

The METLIN Metabolite and Chemical Entity Database[1][2][3] is the largest repository of experimental tandem mass spectrometry and neutral loss[4] data acquired from standards. The tandem mass spectrometry data on over 930,000 molecular standards (as of December, 2023)[5][6][7][8] is provided to facilitate the identification of chemical entities from tandem mass spectrometry experiments. In addition to the identification of known molecules, it is also useful for identifying unknowns[3] using its similarity searching technology.[9] All tandem mass spectrometry data comes from the experimental analysis of standards at multiple collision energies and in both positive and negative ionization modes.

METLIN[10] serves as a data management system to assist in metabolite and chemical entity identification by providing public access to its repository of comprehensive MS/MS and neutral loss data.[6][3][4] METLIN's annotated list of molecular standards include metabolites and other chemical entities, searching METLIN can be done based on a molecule's tandem mass spectrometry data, neutral loss masses, precursor mass, chemical formula, and structure within the METLIN website. Each molecule is linked to outside resources such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) for further reference and inquiry. The METLIN database was developed and is maintained solely by the Siuzdak laboratory at The Scripps Research Institute.

Constantly evolving

Since its initial implementation in the early 2000s,[2] the freely available METLIN website has collected comments and suggestions for improvements from users in the biotechnology, pharmaceutical and academic communities ultimately resulting in functionally useful technology for metabolomics as well as hundreds of thousands of other molecular entities.[6] The METLIN interface allows researchers to readily search the database and characterize metabolites and other compounds through features such as accurate mass, single and multiple fragment searching, neutral loss and full spectrum search capabilities. The similarity searching feature introduced in 2008[9] was designed to expedite the identification process of unknown molecules.

Also, METLIN has been used to create a novel multiple reaction monitoring (MRM) library of precursor to fragment ion transitions.[11] The METLIN-MRM transition repository for small-molecule quantitative tandem mass spectrometry was designed to facilitate data sharing across different instruments and laboratories.[11]

The METLIN database is implemented in the cloud to enable users throughout the world.[6][10] In addition to expanding the tandem mass spectrometry database, METLIN is designed to search tandem mass spectrometry data, precursor mass, chemical formulas, compound names among other search capabilities. METLIN has also been implemented with cognitive computing applications.[12] The tandem MS high-resolution ESI-QTOF MS/MS data on now over 930,000 distinct chemical entities, includes mass spectral collision-induced dissociation data at four different collision energies, in both positive and negative ionization modes.[6][8][13]

References

  1. ^ Xue, Jingchuan; Guijas, Carlos; Benton, H. Paul; Warth, Benedikt; Siuzdak, Gary (October 2020). "METLIN MS 2 molecular standards database: a broad chemical and biological resource". Nature Methods. 17 (10): 953–954. doi:10.1038/s41592-020-0942-5. ISSN 1548-7105. PMC 8802982. PMID 32839599.
  2. ^ a b Smith CA, O'Maille G, Want EJ, Qin C, Trauger SA, Brandon TR, et al. (December 2005). "METLIN: a metabolite mass spectral database". Therapeutic Drug Monitoring. 27 (6): 747–51. doi:10.1097/01.ftd.0000179845.53213.39. PMID 16404815. S2CID 14774455.
  3. ^ a b c Guijas C, Montenegro-Burke JR, Domingo-Almenara X, Palermo A, Warth B, Hermann G, et al. (March 2018). "METLIN: A Technology Platform for Identifying Knowns and Unknowns". Analytical Chemistry. 90 (5): 3156–3164. doi:10.1021/acs.analchem.7b04424. PMC 5933435. PMID 29381867.
  4. ^ a b Aisporna, Aries; Benton, H. Paul; Chen, Andy; Derks, Rico J. E.; Galano, Jean Marie; Giera, Martin; Siuzdak, Gary (2022-03-02). "Neutral Loss Mass Spectral Data Enhances Molecular Similarity Analysis in METLIN". Journal of the American Society for Mass Spectrometry. 33 (3): 530–534. doi:10.1021/jasms.1c00343. ISSN 1044-0305. PMC 10131246. PMID 35174708. S2CID 246902725.
  5. ^ Giera, Martin; Yanes, Oscar; Siuzdak, Gary (2022-01-04). "Metabolite discovery: Biochemistry's scientific driver". Cell Metabolism. 34 (1): 21–34. doi:10.1016/j.cmet.2021.11.005. hdl:1887/3250578. ISSN 1550-4131. PMID 34986335. S2CID 245729571.
  6. ^ a b c d e Xue J, Guijas C, Benton HP, Warth B, Siuzdak G (August 2020). "2 molecular standards database: a broad chemical and biological resource". Nature Methods. 17 (10): 953–954. doi:10.1038/s41592-020-0942-5. PMC 8802982. PMID 32839599.
  7. ^ Guijas, Carlos; To, Andrew; Montenegro-Burke, J. Rafael; Domingo-Almenara, Xavier; Alipio-Gloria, Zaida; Kok, Bernard P.; Saez, Enrique; Alvarez, Nicole H.; Johnson, Kristen A.; Siuzdak, Gary (August 2022). "Drug-Initiated Activity Metabolomics Identifies Myristoylglycine as a Potent Endogenous Metabolite for Human Brown Fat Differentiation". Metabolites. 12 (8): 749. doi:10.3390/metabo12080749. ISSN 2218-1989. PMC 9415469. PMID 36005620.
  8. ^ a b "The Analytical Scientist Innovation Awards 2023". The Analytical Scientist. 2023-12-12. Retrieved 2023-12-14.
  9. ^ a b Benton HP, Wong DM, Trauger SA, Siuzdak G (August 2008). "XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization". Analytical Chemistry. 80 (16): 6382–9. doi:10.1021/ac800795f. PMC 2728033. PMID 18627180.
  10. ^ a b Tautenhahn R, Cho K, Uritboonthai W, Zhu Z, Patti GJ, Siuzdak G (September 2012). "An accelerated workflow for untargeted metabolomics using the METLIN database". Nature Biotechnology. 30 (9): 826–8. doi:10.1038/nbt.2348. PMC 3666346. PMID 22965049.
  11. ^ a b Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Ivanisevic, Julijana; Thomas, Aurelien; Sidibé, Jonathan; Teav, Tony; Guijas, Carlos; Aisporna, Aries E.; Rinehart, Duane; Hoang, Linh; Nordström, Anders (September 2018). "XCMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules". Nature Methods. 15 (9): 681–684. doi:10.1038/s41592-018-0110-3. ISSN 1548-7105. PMC 6629029. PMID 30150755.
  12. ^ Majumder, Erica L.-W.; Billings, Elizabeth M.; Benton, H. Paul; Martin, Richard L.; Palermo, Amelia; Guijas, Carlos; Rinschen, Markus M.; Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Tagtow, Bradley A.; Plumb, Robert S. (2021-01-22). "Cognitive analysis of metabolomics data for systems biology". Nature Protocols. 16 (3): 1376–1418. doi:10.1038/s41596-020-00455-4. ISSN 1754-2189. OSTI 1774918. PMC 10357461. PMID 33483720. S2CID 231687415.
  13. ^ Heim, Wilasinee; Aisporna, Aries; Hoang, Linh; Benton, H. Paul; Siuzdak, Gary (2023), Ivanisevic, Julijana; Giera, Martin (eds.), "METLIN Tandem Mass Spectrometry and Neutral Loss Databases for the Identification of Microbial Natural Products and Other Chemical Entities", A Practical Guide to Metabolomics Applications in Health and Disease: From Samples to Insights into Metabolism, Learning Materials in Biosciences, Cham: Springer International Publishing, pp. 105–124, doi:10.1007/978-3-031-44256-8_5, ISBN 978-3-031-44256-8, retrieved 2024-03-01
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