Smart Cutter: An Efficient Strategy for Increasing the Coverage of Chemical Cross-Linking Analysis.

Abstract

Chemical cross-linking combined with mass spectrometry (CXMS) has emerged as a powerful tool to study protein structure, conformation, and protein-protein interactions (PPIs). Until now, most cross-linked peptides were generated by using commercial cross-linkers, such as DSS, BS3, and DSSO, which react with the primary amino groups of the lysine residues of proteins. However, trypsin, the most commonly used proteolytic enzyme, cannot cleave the C-terminus of a linked lysine, making the obtained cross-linked peptides longer than common peptides and unfavorable for MS identification and data searching. Herein, we propose an in situ sequential digestion strategy using enzymes with distinct cleavage specificity, named as smart cutter, to generate cross-linked peptides with suitable length so that the identification coverage could improve. Through the application of such a strategy to DSS cross-linked E. coli lysates, additional cross-linked sites (1.3-fold increase) obtained in comparison with those obtained by trypsin-trypsin digestion (2879 vs 1255). Among the different digestion combinations, AspN-trypsin performed the best, with 64% (673/1059) of the cross-linked sites complementary to trypsin-trypsin digestion, which is beneficial to ensure the depth for studying protein structure and PPIs. Taking the 60 kDa chaperonin protein as an example, more than twice the cross-linked sites (30 vs 14) were identified to enrich the protein structure information. In addition, compared to the published protein interaction network for E. coli ( http://www.bacteriome.org ), 91 potential PPIs were discovered with our strategy, of which 65 have not covered by trypsin-trypsin digestion. Therefore, these results illustrate the great significance of smart-cutter-based CXMS for the revelation of protein structure as well as finding new PPIs.