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Pan, Dongqing; Brockrneyer, Andreas; Müller, Franziska; Musacchio, Andrea and Bange, Tanja (2018): Simplified Protocol for Cross-linking Mass Spectrometry Using the MS-Cleavable Cross-linker DSBU with Efficient Cross-link Identification. In: Analytical Chemistry, Vol. 90, No. 18: pp. 10990-10999

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Abstract

Chemical cross-linking combined with mass spectrometry (MS) is a powerful approach to identify and map protein-protein interactions. Its applications support computational modeling of three-dimensional structures and complement classical structural methodologies such as X-ray crystallography, NMR spectroscopy, and electron microscopy (EM). A plethora of cross-linkers, MS methods, and data analysis programs have been developed, but due to their methodological complexity application is currently reserved for specialized mass spectrometry laboratories. Here, we present a simplified single-step purification protocol that results in improved identifications of cross-linked peptides. We describe an easy-to-follow pipeline that combines the MS cleavable cross-linker DSBU (disuccinimidyl dibutyric urea), a Q-Exactive mass spectrometer, and the dedicated software MeroX for data analysis to make cross-linking MS accessible to structural biology and biochemistry laboratories. In experiments focusing on kinetochore subcomplexes containing 4-10 subunits (so-called KMN network), one-step peptide purification, and enrichment by size-exclusion chromatography yielded identification of 135-228 non-redundant cross-links (577-820 cross-linked peptides) from each experiment. Notably, half of the non-redundant cross-links identified were not lysine lysine cross links and involved side chains with hydroxy groups. The new pipeline has a comparable potential toward the identification of protein protein interactions as previously used pipelines based on isotope-labeled cross-linkers. A newly identified cross-link enabled us to improve our 3D-model of the KMN, emphasizing the power of cross-linking data for evaluation of low-resolution EM maps. In sum, our optimized experimental scheme represents a viable shortcut toward obtaining reliable cross-link data sets.

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