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Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows
Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data anal...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270371/ https://www.ncbi.nlm.nih.gov/pubmed/35803948 http://dx.doi.org/10.1038/s41467-022-31701-w |
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author | Matzinger, Manuel Vasiu, Adrian Madalinski, Mathias Müller, Fränze Stanek, Florian Mechtler, Karl |
author_facet | Matzinger, Manuel Vasiu, Adrian Madalinski, Mathias Müller, Fränze Stanek, Florian Mechtler, Karl |
author_sort | Matzinger, Manuel |
collection | PubMed |
description | Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results. |
format | Online Article Text |
id | pubmed-9270371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92703712022-07-10 Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows Matzinger, Manuel Vasiu, Adrian Madalinski, Mathias Müller, Fränze Stanek, Florian Mechtler, Karl Nat Commun Article Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results. Nature Publishing Group UK 2022-07-08 /pmc/articles/PMC9270371/ /pubmed/35803948 http://dx.doi.org/10.1038/s41467-022-31701-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Matzinger, Manuel Vasiu, Adrian Madalinski, Mathias Müller, Fränze Stanek, Florian Mechtler, Karl Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title | Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title_full | Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title_fullStr | Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title_full_unstemmed | Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title_short | Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
title_sort | mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270371/ https://www.ncbi.nlm.nih.gov/pubmed/35803948 http://dx.doi.org/10.1038/s41467-022-31701-w |
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