Numerous chemical cross-linkers linkers have been developed over the last years, each with their own physical and chemical properties . The development of MS-cleavable linkers has further boosted the popularity of cross-linking mass spectrometry. These cross-linkers can be fragmented in MS/MS analysis to yield characteristic doublet peaks that correspond to the two cross-linked peptides . Several software packages have been developed for the identification of peptides from spectra containing cross-link information. Most of these tools are designed to identify non-cleavable cross-linkers. Tools aimed at cleavable cross-linkers are often specialised for use with one particular cross-linker, or rely on MS3 data, requiring a specific instrument to measure such data. Many cross-link spectra are chimeric spectra and contain fragment ions of both peptides, hampering peptide identification. Furthermore, since only a fraction of measured spectra contains cross-link information, selection of these spectra is crucial. Here, we present MS Annika, a new cross-linking search engine. The MS Annika algorithm consists of three stages: (1) Cross-link spectra selection based on several different identification modes; (2) Peptide identification using a modified version of the MS Amanda peptide identification algorithm ; and (3) Cross-link validation based on FDR calculation. We integrated MS Annika into Proteome Discoverer 2.3. An exporter utility enables the export of found cross-links to xiView to visualise the results . MS Annika can select cross-link spectra, identify, and verify the contained peptide sequences. MS Annika requires MS2 data only, therefore eliminating the need for MS3 capabilities in mass spectrometers. The search engine can be adapted in Proteome Discoverer to use a wide variety of cross-linkers, and is therefore very versatile. First results show that the algorithm can compete with comparable tools, such as MeroX  and XLinkX . On a sample E. coli data set, MS Annika found 3775 cross-link spectrum matches (CSMs) at 1% FDR. MeroX and XlinkX found 1459 and 3381 at the same false discovery rate, respectively.  A. Sinz, “Chemical cross-linking and mass spectrometry to map three-dimensional protein structures and protein-protein interactions,” Mass Spectrometry Reviews, vol. 25, no. 4, pp. 663–682, 2006.  C. E. Stieger et al., “Optimized Fragmentation Improves the Identification of Peptides Cross-Linked by MS-Cleavable Reagents,” J. Proteome Res., vol. 18, no. 3, pp. 1363–1370, Mar. 2019.  V. Dorfer et al., “MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra,” J. Proteome Res., vol. 13, no. 8, pp. 3679–3684, Aug. 2014.  M. J. Graham et al., “xiView: A common platform for the downstream analysis of Crosslinking Mass Spectrometry data,” bioRxiv, p. 561829, Feb. 2019.  M. Götze et al., “Automated Assignment of MS/MS Cleavable Cross-Links in Protein 3D-Structure Analysis,” J. Am. Soc. Mass Spectrom., vol. 26, no. 1, pp. 83–97, Jan. 2015.  F. Liu et al., “Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry,” Nature Methods, vol. 12, no. 12, pp. 1179–1184, Dec. 2015.
|Title of host publication||Proceedings of the 9th Symposium on Structural Proteomics (SSP2019)|
|Publication status||Published - 2019|
|Event||9th Symposium on Structural Proteomics (SSP2019) - Göttingen, Germany|
Duration: 3 Nov 2019 → 6 Nov 2019
|Conference||9th Symposium on Structural Proteomics (SSP2019)|
|Period||03.11.2019 → 06.11.2019|