Application of a fast sorting algorithm to the assignment of mass spectrometric cross-linking data

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

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 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 was maintained high at ∼100. The estimated enrichment efficiency was improved by a factor of 4–5 (based on XL numbers) compared to enrichment via biotin and streptavidin. We were still able to detect cross-links from 0.25 μg cross-linked E. coli ribosomes in a background of 100 μg 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 mapping protein–protein interactions, investigating protein architectures in more depth, and helping to understand complex biological processes.

Exhaustively Identifying Cross-Linked Peptides with a Linear Computational Complexity

Chemical cross-linking coupled to mass spectrometry is a powerful tool to study protein-protein interactions and protein conformations. Two linked peptides are ionized and fragmented to produce a tandem mass spectrum. In such an experiment, a tandem mass spectrum contains ions from two peptides. The peptide identification problem becomes a peptide-peptide pair identification problem. Currently, most tools do not search all possible pairs due to the quadratic time complexity. Consequently, missed findings are unavoidable. In our previous work, we developed a tool named ECL to search all pairs of peptides exhaustively. Unfortunately, it is very slow due to the quadratic computational complexity, especially when the database is large. Furthermore, ECL uses a score function without statistical calibration, while researchers1-3 have proposed that it is inappropriate to directly compare uncalibrated scores because different spectra have different random score distributions. Here we propose an advanced version of ECL, named ECL2. It achieves a linear time and space complexity by taking advantage of the additive property of a score function. It can search a data set containing tens of thousands of spectra against a database containing thousands of proteins in a few hours. Comparison with other five state-of-the-art tools shows that ECL2 is much faster than pLink, StavroX, ProteinProspector, and ECL. Kojak is the only one that is faster than ECL2, but Kojak does not exhaustively search all possible peptide pairs. The comparison shows that ECL2 has the highest sensitivity among the state-of-the-art tools. The experiment using a large-scale in vivo cross-linking data set demonstrates that ECL2 is the only tool that can find the peptide-spectrum matches (PSMs) passing the false discovery rate/q-value threshold. The result illustrates that the exhaustive search and a well-calibrated score function are useful to find PSMs from a huge search space.

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca.

Comprehensive identification of disulfide bonds using non-specific proteinase K digestion and CID-cleavable crosslinking analysis methodology for Orbitrap LC/ESI-MS/MS data

Disulfide bonds are valuable constraints in protein structure modeling. The Cys-Cys disulfide bond undergoes specific fragmentation under CID and, therefore, can be considered as a CID-cleavable crosslink. We have recently reported on the benefits of using non-specific digestion with proteinase K for inter-peptide crosslink determination. Here, we describe an updated application of our CID-cleavable crosslink analysis software and our crosslinking analysis with non-specific digestion methodology for the robust and comprehensive determination of disulfide bonds in proteins, using Orbitrap LC/ESI-MS/MS data.

XL-MS: Protein cross-linking coupled with mass spectrometry

With the continuing trend to study larger and more complex systems, the application of protein cross-linking coupled with mass spectrometry (XL-MS) provides a varied toolkit perfectly suited to achieve these goals. By freezing the transient interactions through the formation of covalent bonds, XL-MS provides a vital insight into both the structure and organization of proteins in a wide variety of conditions. This review covers some of the established methods that underpin the field alongside the more recent developments that hold promise to further realize its potential in new directions.