A universal language for finding mass spectrometry data patterns

Damiani, Tito; Jarmusch, Alan K.; Aron, Allegra T.; Petras, Daniel; Phelan, Vanessa V.; Zhao, Haoqi Nina; Bittremieux, Wout; Acharya, Deepa D.; Ahmed, Mohammed M. A.; Bauermeister, Anelize; Bertin, Matthew J.; Boudreau, Paul D.; Borges, Ricardo M.; Bowen, Benjamin P.; Brown, Christopher J.; Chagas, Fernanda O.; Clevenger, Kenneth D.; Correia, Mario S. P.; Crandall, William J.; Crüsemann, Max; Fahy, Eoin; Fiehn, Oliver; Garg, Neha; Gerwick, William H.; Gilbert, Jeffrey R.; Globisch, Daniel; Gomes, Paulo Wender P.; Heuckeroth, Steffen; James, C. Andrew; Jarmusch, Scott A.; Kakhkhorov, Sarvar A.; Kang, Kyo Bin; Kessler, Nikolas; Kersten, Roland D.; Kim, Hyunwoo; Kirk, Riley D.; Kohlbacher, Oliver; Kontou, Eftychia E.; Liu, Ken; Lizama-Chamu, Itzel; Luu, Gordon T.; Luzzatto Knaan, Tal; Mannochio-Russo, Helena; Marty, Michael T.; Matsuzawa, Yuki; McAvoy, Andrew C.; McCall, Laura-Isobel; Mohamed, Osama G.; Nahor, Omri; Neuweger, Heiko; Niedermeyer, Timo H. J.; Nishida, Kozo; Northen, Trent R.; Overdahl, Kirsten E.; Rainer, Johannes; Reher, Raphael; Rodriguez, Elys; Sachsenberg, Timo T.; Sanchez, Laura M.; Schmid, Robin; Stevens, Cole; Subramaniam, Shankar; Tian, Zhenyu; Tripathi, Ashootosh; Tsugawa, Hiroshi; van der Hooft, Justin J. J.; Vicini, Andrea; Walter, Axel; Weber, Tilmann; Xiong, Quanbo; Xu, Tao; Pluskal, Tomáš; Dorrestein, Pieter C.; Wang, Mingxun

doi:10.1038/s41592-025-02660-z

Title: A universal language for finding mass spectrometry data patterns

Journal Article · Mon May 12 00:00:00 UTC 2025 · Nature Methods

DOI: https://doi.org/10.1038/s41592-025-02660-z · OSTI ID:2569376

^[1];

; Aron, Allegra T.; Petras, Daniel; Phelan, Vanessa V.; Zhao, Haoqi Nina; Bittremieux, Wout; Acharya, Deepa D.;

; Bauermeister, Anelize; Bertin, Matthew J.; Boudreau, Paul D.; Borges, Ricardo M.;

;

; Chagas, Fernanda O.; Clevenger, Kenneth D.; Correia, Mario S. P.;

; Crüsemann, Max more »

Czech Academy of Sciences (CAS), Prague (Czech Republic); et al.

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here, in this study, we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: US Department of Energy; USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22), Scientific User Facilities Division (SC-22.3 ); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science (BSS)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2569376

Journal Information:: Nature Methods, Journal Name: Nature Methods Journal Issue: 6 Vol. 22; ISSN 1548-7105; ISSN 1548-7091

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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