Alamán-Zárate, M.G. orcid.org/0009-0007-0587-534X, Rady, B.J. orcid.org/0000-0003-4763-4070, Ledermann, R. et al. (10 more authors) (2025) A software tool and strategy for peptidoglycomics, the high-resolution analysis of bacterial peptidoglycans via LC-MS/MS. Communications Chemistry, 8 (1). 91. ISSN 2399-3669
Abstract
Peptidoglycan is an essential component of the bacterial cell envelope—a mesh-like macromolecule that protects the bacterium from osmotic stress and its internal turgor pressure. The composition and architecture of peptidoglycan is heterogeneous and changes as bacteria grow, divide, and respond to their environment. Though peptidoglycan has long been studied via LC-MS/MS, the analysis of this data remains challenging as peptidoglycan’s unusual composition and branching can’t be handled by proteomics software. Here we describe user-friendly open-source tools and a web interface for building peptidoglycan databases, performing MS searches, and predicting the MS/MS fragmentation of muropeptides. We then use Rhizobium leguminosarum to describe a step-by-step strategy for the high-resolution analysis of peptidoglycan. The unprecedented detail of R. leguminosarum’s peptidoglycan composition (>250 muropeptides) reveals even the subtlest remodelling between growth conditions. These new and easier to use tools enable more systematic analyses of peptidoglycan dynamics.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Cheminformatics; Glycomics; Mass spectrometry; Peptides; Proteomics |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Chemical, Materials and Biological Engineering The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) > Department of Animal and Plant Sciences (Sheffield) |
Funding Information: | Funder Grant number BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL BB/W013800/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Apr 2025 10:23 |
Last Modified: | 02 Apr 2025 10:23 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1038/s42004-025-01490-6 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:225098 |