Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.
Manuel MatzingerAdrian VasiuMathias MadalinskiFränze MüllerFlorian StanekKarl MechtlerPublished in: Nature communications (2022)
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.
Keyphrases
- data analysis
- mass spectrometry
- amino acid
- liquid chromatography
- high resolution
- protein protein
- capillary electrophoresis
- small molecule
- high performance liquid chromatography
- electronic health record
- gas chromatography
- healthcare
- machine learning
- mental health
- binding protein
- high throughput
- patient reported outcomes
- artificial intelligence
- neural network