Dataset Information

In vivo crosslinking and effective 2D enrichment for interactome studies of the nucleosome.

ABSTRACT: Cross-linking mass spectrometry has evolved as a powerful technique to study protein-protein interactions and to provide structural information over the past decades. Low reaction efficiencies, and complex matrices lead to challenging system wide crosslink analysis. In this study, we improved and streamlined an Azide-A-DSBSO based in vivo crosslinking workflow employing two orthogonal effective enrichment steps: Affinity enrichment and size exclusion chromatography (SEC). Combined, they allow an effective pulling of DSBSO containing peptides and remove the background of linear as well as mono-linked peptides. We found that the analysis of a single SEC fraction is effective to yield ~90% of all crosslinks, which is important whenever measurement time is limited, and sample throughput is crucial. Our workflow resulted in more than 5000 crosslinks from K562 cells and generated a comprehensive PPI network from whole cells as well as nuclear extracts. From 393 PPI found within the nucleus, 56 have not yet been reported in the STING database and are representing a valuable resource for investigating new molecular mechanisms and provide complementary data for future studies. We further show, that by applying DSBSO to nuclear extracts we yield more crosslinks on lower abundant proteins and showcase this on the DEAD-box RNA helicase DDX39B which is predominantly expressed in the nucleus. Our data indicates that DDX39B is present in monomeric and dimeric form together with DDX39A within the nuclear extracts analyzed.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell

DISEASE(S): Chronic Myelomonocytic Leukemia

SUBMITTER: Manuel Matzinger

LAB HEAD: Karl Mechtler

PROVIDER: PXD061173 | Pride | 2025-08-21

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	20240424_Eclipse_NEO4_FAIMS_PepMap50cm_pepmapTrap_Braeuer_MS_Hub_IMP_ID021_CubeB_WholeCell_DBCO10_Rep1.pdResult	Other
	20240424_Eclipse_NEO4_FAIMS_PepMap50cm_pepmapTrap_Braeuer_MS_Hub_IMP_ID021_CubeB_WholeCell_DBCO10_Rep1.raw	Raw
	20240424_Eclipse_NEO4_FAIMS_PepMap50cm_pepmapTrap_Braeuer_MS_Hub_IMP_ID021_CubeB_WholeCell_DBCO10_Rep2.pdResult	Other
	20240424_Eclipse_NEO4_FAIMS_PepMap50cm_pepmapTrap_Braeuer_MS_Hub_IMP_ID021_CubeB_WholeCell_DBCO10_Rep2.raw	Raw
	20240424_Eclipse_NEO4_FAIMS_PepMap50cm_pepmapTrap_Braeuer_MS_Hub_IMP_ID021_CubeB_WholeCell_DBCO10_Rep3.pdResult	Other

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Publications

In vivo crosslinking and effective 2D enrichment for proteome wide interactome studies.

Bräuer Philipp P Tirian Laszlo L Müller Fränze F Mechtler Karl K Matzinger Manuel M

Communications chemistry 20250813 1

Cross-linking mass spectrometry has evolved as a powerful technique to study protein-protein interactions and to provide structural information. Low reaction efficiencies, and complex matrices lead to challenging system wide crosslink analysis. We improved and streamlined an Azide-A-DSBSO based in vivo crosslinking workflow employing two orthogonal effective enrichment steps: Affinity enrichment and size exclusion chromatography (SEC). Combined, they allow an effective enrichment of DSBSO contai ...[more]

PMID: 40804100

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Project description:Over the past few decades cross-linking mass spectrometry (XLMS) has become a powerful tool for identification of protein-protein interactions and for gaining insight into the structures of proteins in living cells, tissues, and organelles. The development of new crosslinkers, enrichment strategies and data acquisition methods led to the establishment of numerous new software tools specifically for the analysis and interpretation of cross-linking data. We previously published one of these tools called MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable crosslinkers. In this publication we present an updated MS Annika and a new search algorithm that additionally supports processing of data from MS2-MS3-based approaches and identification of peptides from MS3 spectra. In the new MS2-MS3 search algorithm, MS3 spectra are matched to their corresponding precursor doublet peak in the MS2 scan to identify the crosslink modification and the monoisotopic peptide mass. This information is then used to adjust the MS3 spectra for search with MS Amanda, our in-house developed peptide search engine, to identify the cross-linked peptides. Peptides that are identified in the MS2 scan and one or more of the associated product MS3 scans are re-scored with a novel scoring function to reflect the increased confidence. Finally, the detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines that support MS3 crosslink identification. Three of the datasets were benchmark datasets of synthetic peptides that allow calculation of an experimentally validated FDR, and we show that MS Annika detects up to 4 times more true unique crosslinks than MaXLinker and up to 35% more than XlinkX while simultaneously yielding less false positive hits and therefore a more accurate FDR than the other two search engines. Additionally, for the other two datasets we could show that MS Annika finds between 74% to 2.5 times more crosslinks at 1% estimated FDR and reveals protein-protein interactions that are not detected by either XlinkX or MaXLinker.