Dataset Information

Fast and highly efficient affinity enrichment of Azide-A-DSBSO cross-linked peptides.

ABSTRACT: Cross-linking mass spectrometry is an increasingly used, powerful technique to study protein-protein interactions or to provide structural information. Due to sub-stochiometric reaction efficiencies, cross-linked peptides are usually low abundant. This results in challenging data evaluation and the need for an effective enrichment. Here we describe an improved, easy to implement, one-step method to enrich azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide (DSBSO) cross-linked peptides using dibenzocyclooctyne (DBCO) coupled Sepharose�� beads. We probed this method using recombinant Cas9 and E. coli ribosome. For Cas9, the number of detectable cross-links was increased from ~100 before enrichment to 580 cross-links after enrichment. To mimic a cellular lysate, E. coli ribosome was spiked into a tryptic HEK background at a ratio of 1:2 �� 1:100. The number of detectable unique cross-links maintained high at ~100. The estimated enrichment efficiency was improved by factor 4 -5 (based on XL numbers) compared to enrichment via biotin and streptavidin. We were still able to detect cross-links from 0.25 ��g cross-linked E. coli ribosome in a background of 100 ��g tryptic HEK peptides, indicating a high enrichment sensitivity. In contrast to conventional enrichment techniques, like SEC, the time needed for preparation and MS measurement is significantly reduced. This robust, fast and selective enrichment method for azide-tagged linkers will contribute to map protein-protein interactions, investigate protein architectures in more depth and help to understand complex biological processes.

INSTRUMENT(S): Orbitrap Fusion Lumos, Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

SUBMITTER: Manuel Matzinger

LAB HEAD: Karl Mechtler

PROVIDER: PXD016963 | Pride | 2020-05-11

REPOSITORIES: Pride

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Publications

Fast and Highly Efficient Affinity Enrichment of Azide-A-DSBSO Cross-Linked Peptides.

Matzinger Manuel M Kandioller Wolfgang W Doppler Philipp P Heiss Elke H EH Mechtler Karl K

Journal of proteome research 20200416 5

Cross-linking mass spectrometry is an increasingly used, powerful technique to study protein-protein interactions or to provide structural information. Due to substochiometric reaction efficiencies, cross-linked peptides are usually low abundance. This results in challenging data evaluation and the need for an effective enrichment. Here we describe an improved, easy to implement, one-step method to enrich azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide (DSBSO) cross-linked peptides usi ...[more]

PMID: 32250121

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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.

Dataset Information

Fast and highly efficient affinity enrichment of Azide-A-DSBSO cross-linked peptides.

Publications

Fast and Highly Efficient Affinity Enrichment of Azide-A-DSBSO Cross-Linked Peptides.

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