We compared the five different ways of fragmentation available on a tribrid mass spectrometer and optimized their collision energies with regard to optimal sequence coverage of cross-linked peptides. We created a library of bis(sulfosuccinimidyl)suberate (BS3/DSS) cross-linked precursors, derived from the tryptic digests of three model proteins (Human Serum Albumin, creatine kinase, and myoglobin). This enabled in-depth targeted analysis of the fragmentation behavior of 1065 cross-linked precursors using the five fragmentation techniques: collision-induced dissociation (CID), beam-type CID (HCD), electron-transfer dissociation (ETD), and the combinations ETciD and EThcD. EThcD gave the best sequence coverage for cross-linked m/z species with high charge density, while HCD was optimal for all others. We tested the resulting data-dependent decision tree against collision energy-optimized single methods on two samples of differing complexity (a mix of eight proteins and a highly complex ribosomal cellular fraction). For the high complexity sample the decision tree gave the highest number of identified cross-linked peptide pairs passing a 5% false discovery rate (on average ∼21% more than the second best, HCD). For the medium complexity sample, the higher speed of HCD proved decisive. Currently, acquisition speed plays an important role in allowing the detection of cross-linked peptides against the background of linear peptides. Enrichment of cross-linked peptides will reduce this role and favor methods that provide spectra of higher quality. Data are available via ProteomeXchange with identifier PXD006131.

xiView provides a common platform for the downstream analysis and visualisation of Crosslinking Mass Spectrometry data. It is independent of the search software used and its input is compliant with the relevant mass spectrometry data standards. It uses established visualisation techniques, notably Multiple Coordinated Views, to help the user explore the data and is designed to facilitate comparisons between different datasets.

Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of mass spectrometry (MS)-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently, such studies have also been published with noncleavable crosslinkers, suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the commonly used MS-cleavable crosslinker, disuccinimidyl sulfoxide (DSSO). Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS cleavability of the crosslinker, but improved peptide backbone fragmentation which reduces the ambiguity of peptide identifications. This also holds true for another commonly used MS-cleavable crosslinker, DSBU. We show furthermore that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped higher-energy collisional dissociation (HCD) method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

We present here a simple, user friendly and automated new quantitative cross-linking mass spectrometry (QCLMS) workflow comprising data-independent acquisition (DIA) for acquiring mass spectrometry data and Spectronaut, one of the leading DIA analysis tools. DIA crosslinking data outperforms DDA in reproducibility and accuracy of quantitation results. DIA-QCLMS tolerates complex backgrounds and through its automation recommends itself for routine application in the analysis of protein complex dynamics.

We present xiSPEC, a standard compliant, next-generation web-based spectrum viewer for visualizing, analyzing and sharing mass spectrometry data. Peptide-spectrum matches from standard proteomics and cross-linking experiments are supported. xiSPEC is to date the only browser-based tool supporting the standardized file formats mzML and mzIdentML defined by the proteomics standards initiative. Users can either upload data directly or select files from the PRIDE data repository as input. xiSPEC allows users to save and share their datasets publicly or password protected for providing access to collaborators or readers and reviewers of manuscripts. The identification table features advanced interaction controls and spectra are presented in three interconnected views: (i) annotated mass spectrum, (ii) peptide sequence fragmentation key and (iii) quality control error plots of matched fragments. Highlighting or selecting data points in any view is represented in all other views. Views are interactive scalable vector graphic elements, which can be exported, e.g. for use in publication. xiSPEC allows for re-annotation of spectra for easy hypothesis testing by modifying input data. xiSPEC is freely accessible at http://spectrumviewer.org and the source code is openly available on https://github.com/Rappsilber-Laboratory/xiSPEC.

We analyzed the backbone fragmentation behavior of tryptic peptides of a four-protein mixture and of E. coli lysate subjected to ultraviolet photodissociation (UVPD) at 213 nm on a commercially available UVPD-equipped tribrid mass spectrometer. We obtained 15 178 unique high-confidence peptide UVPD spectrum matches by recording a reference beam-type collision-induced dissociation (HCD) spectrum of each precursor, ensuring that our investigation includes a broad selection of peptides, including those that fragmented poorly by UVPD. Type a, b, and y ions were most prominent in UVPD spectra, and median sequence coverage ranged from 5.8% (at 5 ms laser excitation time) to 45.0% (at 100 ms). Overall, the sequence fragment intensity remained relatively low (median: 0.4% (5 ms) to 16.8% (100 ms) of total intensity), and the remaining precursor intensity, high. The sequence coverage and sequence fragment intensity ratio correlated with the precursor charge density, suggesting that UVPD at 213 nm may suffer from newly formed fragments sticking together due to noncovalent interactions. The UVPD fragmentation efficiency therefore might benefit from supplemental activation, as was shown for ETD. Aromatic amino acids, most prominently tryptophan, facilitated UVPD. This points to aromatic tags as possible enhancers of UVPD. Data are available via ProteomeXchange with identifier PXD018176 and on .

Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of MS-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently such studies have also been published with non-cleavable crosslinkers suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the most popular MS-cleavable crosslinker, DSSO. Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS-cleavability of the crosslinker, but improved peptide backbone fragmentation that allowed for more confident peptide identification. We also show that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped HCD method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

Crosslinking MS is currently transitioning from a routine tool in structural biology to enabling structural systems biology. MS-cleavable crosslinkers could substantially reduce the associated search space expansion by allowing an MS3-based approach for identifying crosslinked peptides. However, MS2-based approaches currently outperform approaches utilising MS3. We show here that MS3-trigger sensitivity and specificity were hampered algorithmically. Our four-step MS3-trigger algorithm greatly outperformed currently employed methods and comes close to reaching the theoretical limit.