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Optimized fragmentation schemes and data analysis strategies for proteome-wide cross-link identification

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  • Fan Liu

    (Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht
    Netherlands Proteomics Center
    Present address: Leibniz-Institut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, D-13125 Berlin, Germany)

  • Philip Lössl

    (Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht
    Netherlands Proteomics Center)

  • Richard Scheltema

    (Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht
    Netherlands Proteomics Center)

  • Rosa Viner

    (Thermo Fisher Scientific)

  • Albert J. R. Heck

    (Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht
    Netherlands Proteomics Center)

Abstract

We describe optimized fragmentation schemes and data analysis strategies substantially enhancing the depth and accuracy in identifying protein cross-links using non-restricted whole proteome databases. These include a novel hybrid data acquisition strategy to sequence cross-links at both MS2 and MS3 level and a new algorithmic design XlinkX v2.0 for data analysis. As proof-of-concept we investigated proteome-wide protein interactions in E. coli and HeLa cell lysates, respectively, identifying 1,158 and 3,301 unique cross-links at ∼1% false discovery rate. These protein interaction repositories provide meaningful structural information on many endogenous macromolecular assemblies, as we showcase on several protein complexes involved in translation, protein folding and carbohydrate metabolism.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15473
    DOI: 10.1038/ncomms15473
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    Cited by:

    1. Jan Marten Schmidt & Ran Yang & Ashish Kumar & Olivia Hunker & Jan Seebacher & Franziska Bleichert, 2022. "A mechanism of origin licensing control through autoinhibition of S. cerevisiae ORC·DNA·Cdc6," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Jasjot Singh & Hadeer Elhabashy & Pathma Muthukottiappan & Markus Stepath & Martin Eisenacher & Oliver Kohlbacher & Volkmar Gieselmann & Dominic Winter, 2022. "Cross-linking of the endolysosomal system reveals potential flotillin structures and cargo," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. 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.
    4. Ying Zhu & Kerem Can Akkaya & Julia Ruta & Nanako Yokoyama & Cong Wang & Max Ruwolt & Diogo Borges Lima & Martin Lehmann & Fan Liu, 2024. "Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    5. S. M. Ayala Mariscal & M. L. Pigazzini & Y. Richter & M. Özel & I. L. Grothaus & J. Protze & K. Ziege & M. Kulke & M. ElBediwi & J. V. Vermaas & L. Colombi Ciacchi & S. Köppen & F. Liu & J. Kirstein, 2022. "Identification of a HTT-specific binding motif in DNAJB1 essential for suppression and disaggregation of HTT," Nature Communications, Nature, vol. 13(1), pages 1-25, December.

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