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

Matzinger, Manuel; Kandioller, Wolfgang; Doppler, Philipp; Heiß, Elke H.; Mechtler, Karl

doi:10.1101/2019.12.17.879601

Cited by 8 publications

(18 citation statements)

References 34 publications

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“…There have been several recent advances in enrichment and detection of crosslinked peptides by Crosslinking MS that suggest it will soon be able to map large portions of the cellular interactome in a single experiment 3,13,25 . This will open the door to detecting changes in these interactomes in different cellular states by quantification of the abundances of the detected crosslinks 2,26 .…”

Section: Discussionmentioning

confidence: 99%

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

et al. 2021

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Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

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Section: Discussionmentioning

confidence: 99%

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

et al. 2021

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“…Enrichment was performed by clicking crosslinked peptides to beads functionalized with dibenzocyclooctyne (DBCO) as previously described. 33…”

Section: Resultsmentioning

confidence: 99%

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows

Matzinger

Vasiu

Madalinski

et al. 2021

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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 anal-ysis 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 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 and MaxLynx. 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 extraordinary high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.Graphical abstract

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“…Table S7 shows the concrete information for all the datasets used in this paper: PXD014337 [8], PXD011861 [18], PXD016963 [19], PXD020014 [20] and PXD012546 [10].…”

Section: Data Descriptions Parameter Settings and Supporting Figuresmentioning

confidence: 99%

“…Real dataset comparison among Maxlynx, MeroX and ECL-PF. PXD011861[17], PXD016963[31] and PXD020014[32] are in vitro experimental datasets on an E.coli study. PXD012546[27] is a proteome-wide in vivo dataset on a drosophila melanogaster study.…”

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confidence: 99%

Exhaustive Cross-linking Search with Protein Feedback

Zhou

Dai

Lin

et al. 2022

Preprint

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Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic datasets and hybrid simulated datasets, ECL-PF achieved three-fold higher sensitivity over standard techniques. In experiments using real datasets, it also identified 91.6% more cross-link spectrum matches and 52.6% more unique cross-links.

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

Cited by 8 publications

References 34 publications

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows

Exhaustive Cross-linking Search with Protein Feedback

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