Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment

Bibliographic Details
Title: Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment
Authors: Robin Schmid, Daniel Petras, Louis-Félix Nothias, Mingxun Wang, Allegra T. Aron, Annika Jagels, Hiroshi Tsugawa, Johannes Rainer, Mar Garcia-Aloy, Kai Dührkop, Ansgar Korf, Tomáš Pluskal, Zdeněk Kameník, Alan K. Jarmusch, Andrés Mauricio Caraballo-Rodríguez, Kelly C. Weldon, Melissa Nothias-Esposito, Alexander A. Aksenov, Anelize Bauermeister, Andrea Albarracin Orio, Carlismari O. Grundmann, Fernando Vargas, Irina Koester, Julia M. Gauglitz, Emily C. Gentry, Yannick Hövelmann, Svetlana A. Kalinina, Matthew A. Pendergraft, Morgan Panitchpakdi, Richard Tehan, Audrey Le Gouellec, Gajender Aleti, Helena Mannochio Russo, Birgit Arndt, Florian Hübner, Heiko Hayen, Hui Zhi, Manuela Raffatellu, Kimberly A. Prather, Lihini I. Aluwihare, Sebastian Böcker, Kerry L. McPhail, Hans-Ulrich Humpf, Uwe Karst, Pieter C. Dorrestein
Source: Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Publisher Information: Nature Portfolio, 2021.
Publication Year: 2021
Collection: LCC:Science
Subject Terms: Science
More Details: Abstract Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2041-1723
Relation: https://doaj.org/toc/2041-1723
DOI: 10.1038/s41467-021-23953-9
Access URL: https://doaj.org/article/c79c811ddd0b40428c0ef8e4c5a7fe4c
Accession Number: edsdoj.79c811ddd0b40428c0ef8e4c5a7fe4c
Database: Directory of Open Access Journals
More Details
ISSN:20411723
DOI:10.1038/s41467-021-23953-9
Published in:Nature Communications
Language:English