美国加州大学Tilmann Weber团队研制了用于查找质谱数据模式的通用语言。这一研究成果发表在2025年5月12日出版的国际学术期刊《自然—方法学》上。

在这里，小组介绍了一种新的语言，质谱查询语言（MassQL），以及一个配套的软件生态系统，通过使社区能够使用一组表达性的定义质谱模式直接查询质谱数据来解决这些问题。通过现实世界的例子，MassQL提供了一个数据驱动的化学多样性定义，通过重新分析所有公开的非目标代谢组学数据，使许多学科的科学家能够做出新的发现。MassQL已广泛应用于多种开放的和商业的质谱分析工具中，为研究团体增强了质谱数据挖掘的能力、互操作性和可重复性。

据了解，尽管信息丰富，但绝大多数非靶向质谱数据未得到充分利用；大多数分析结果在发表后没有进行下游解释或再分析的主题。由于现有软件工具的灵活性和可扩展性有限，无法深入研究这些丰富的原始质谱数据集。

附：英文原文

Title: A universal language for finding mass spectrometry data patterns

Author: 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., Crsemann, 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

Issue&Volume: 2025-05-12

Abstract: 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 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.

DOI: 10.1038/s41592-025-02660-z

Source: https://www.nature.com/articles/s41592-025-02660-z