Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex

The field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce an algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. We compare our algorithm to other state-of-the-art crosslinking search engines commonly used in the field and conclude that MS Annika unifies high sensitivity, accurate FDR estimation and computational performance, outperforming competing tools. Application of this algorithm enabled us to employ a proteome-wide search of C. elegans nuclei samples, where we were able to uncover previously unknown protein interactions and conclude a comprehensive structural analysis that provides a detailed view of the Box C/D complex. Moreover, our algorithm will enable researchers to conduct similar studies that were previously unfeasible.

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Publication Details

Journal
Communications Chemistry
Published
2024-12-19
DOI
https://doi.org/10.1038/s42004-024-01386-x
Citations
7
Primary Topic
Enzyme Structure and Function
Type
article
Field-Weighted Citation Impact
0.82

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article

Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex

Fränze Müller, Karl Mechtler, Manuel Matzinger, Viktoria Dorfer et al.
7 citations
Communications Chemistry
Enzyme Structure and Function
0.82
article

Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex

Fränze Müller, Karl Mechtler, Manuel Matzinger, Viktoria Dorfer, Micha J. Birklbauer, Sowmya Sivakumar Geetha
article en
7 citations

Abstract

The field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce an algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. We compare our algorithm to other state-of-the-art crosslinking search engines commonly used in the field and conclude that MS Annika unifies high sensitivity, accurate FDR estimation and computational performance, outperforming competing tools. Application of this algorithm enabled us to employ a proteome-wide search of C. elegans nuclei samples, where we were able to uncover previously unknown protein interactions and conclude a comprehensive structural analysis that provides a detailed view of the Box C/D complex. Moreover, our algorithm will enable researchers to conduct similar studies that were previously unfeasible.

Communications ChemistryVol. 7(1)
Johannes Kepler University of Linz (AT), Institute of Molecular Biotechnology (AT), University of Vienna (AT), Gregor Mendel Institute of Molecular Plant Biology (AT), Austrian Academy of Sciences (AT), Research Institute of Molecular Pathology (AT), Max Perutz Labs (AT), Software Competence Center Hagenberg (Austria) (AT), University of Applied Sciences Upper Austria (AT), Vienna Biocenter (AT), Medical University of Vienna (AT)
Nvidia, Vienna Science and Technology Fund, Austrian Science Fund, Österreichische Forschungsförderungsgesellschaft
Zero hunger
Openalex Percentile: Top 25%
Enzyme Structure and Function
0.82
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