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Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows

Author

Listed:
  • Manuel Matzinger

    (Vienna BioCenter (VBC))

  • Adrian Vasiu

    (Vienna BioCenter (VBC))

  • Mathias Madalinski

    (Vienna BioCenter (VBC))

  • Fränze Müller

    (Vienna BioCenter (VBC))

  • Florian Stanek

    (Vienna BioCenter (VBC))

  • Karl Mechtler

    (Vienna BioCenter (VBC)
    Vienna BioCenter (VBC))

Abstract

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

Suggested Citation

  • Manuel Matzinger & Adrian Vasiu & Mathias Madalinski & Fränze Müller & Florian Stanek & Karl Mechtler, 2022. "Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31701-w
    DOI: 10.1038/s41467-022-31701-w
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    References listed on IDEAS

    as
    1. Swantje Lenz & Ludwig R. Sinn & Francis J. O’Reilly & Lutz Fischer & Fritz Wegner & Juri Rappsilber, 2021. "Reliable identification of protein-protein interactions by crosslinking mass spectrometry," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    2. Rebecca Beveridge & Johannes Stadlmann & Josef M. Penninger & Karl Mechtler, 2020. "A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    3. Fan Liu & Philip Lössl & Richard Scheltema & Rosa Viner & Albert J. R. Heck, 2017. "Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification," Nature Communications, Nature, vol. 8(1), pages 1-8, August.
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