Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
08 07 2022
08 07 2022
Historique:
received:
11
11
2021
accepted:
21
06
2022
entrez:
8
7
2022
pubmed:
9
7
2022
medline:
14
7
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 35803948
doi: 10.1038/s41467-022-31701-w
pii: 10.1038/s41467-022-31701-w
pmc: PMC9270371
doi:
Substances chimiques
Cross-Linking Reagents
0
Ribosomal Proteins
0
Lysine
K3Z4F929H6
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3975Subventions
Organisme : Austrian Science Fund FWF
ID : I 3686
Pays : Austria
Informations de copyright
© 2022. The Author(s).
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