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Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows

View ORCID ProfileManuel Matzinger, Adrian Vasiu, Mathias Madalinski, View ORCID ProfileFränze Müller, Florian Stanek, View ORCID ProfileKarl Mechtler
doi: https://doi.org/10.1101/2021.10.21.465295
Manuel Matzinger
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
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  • For correspondence: manuel.matzinger@imp.ac.at karl.mechtler@imp.ac.at
Adrian Vasiu
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
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Mathias Madalinski
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
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Fränze Müller
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
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Florian Stanek
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
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Karl Mechtler
1Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
2Institute of Molecular Biotechnology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
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  • For correspondence: manuel.matzinger@imp.ac.at karl.mechtler@imp.ac.at
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ABSTRACT

The field of 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, especially for newcomers, to decide for an appropriate analysis workflow. Therefore, we here present a large and flexible synthetic peptide library as reliable instrument to benchmark crosslinkers with different reactive sites as well as acquisition techniques and data analysis algorithms. 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. The library was used with the reagents DSSO, DSBU, CDI, ADH, DHSO and azide-a-DSBSO and data were analysed using the algorithms MeroX, MS Annika, XlinkX, pLink 2, MaxLynx and xiSearch. We thereby show that the correct algorithm and search setting choice is highly important to improve ID rate and FDR in combination with software and sample-complexity specific score cut-offs. When analysing DSSO data with MS Annika, we reach high identification rates of up to ∼70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a low real FDR of < 3 % at cross-link level and with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.

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Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • We expanded our study with additional data including MS2-MS2 and MS2-MS3 based acquisition strategies and added a direct benchmarking of FAIMS vs no FAIMS data. We improved our IMP-X-FDR tool by updating its functionality to work not only on unique residue pair but also on CSM level and added support for data from XiSearch. Furthermore, we added a more comprehensive discussion.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 08, 2022.
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Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows
Manuel Matzinger, Adrian Vasiu, Mathias Madalinski, Fränze Müller, Florian Stanek, Karl Mechtler
bioRxiv 2021.10.21.465295; doi: https://doi.org/10.1101/2021.10.21.465295
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Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows
Manuel Matzinger, Adrian Vasiu, Mathias Madalinski, Fränze Müller, Florian Stanek, Karl Mechtler
bioRxiv 2021.10.21.465295; doi: https://doi.org/10.1101/2021.10.21.465295

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