Complete Mapping of Complex Disulfide Patterns with Closely-Spaced Cysteines by In-Source Reduction and Data-Dependent Mass Spectrometry

Abstract

Mapping of disulfide bonds is an essential part of protein characterization to ensure correct cysteine pairings. For this, mass spectrometry (MS) is the most widely used technique due to fast and accurate characterization. However, MS-based disulfide mapping is challenged when multiple disulfide bonds are present in complicated patterns. This includes the presence of disulfide bonds in nested patterns and closely spaced cysteines. Unambiguous mapping of such disulfide bonds typically requires advanced MS approaches. In this study, we exploited in-source reduction (ISR) of disulfide bonds during the electrospray ionization process to facilitate disulfide bond assignments. We successfully developed a LC-ISR-MS/MS methodology to use as an online and fully automated partial reduction procedure. Postcolumn partial reduction by ISR provided fast and easy identification of peptides involved in disulfide bonding from nonreduced proteolytic digests, due to the concurrent detection of disulfide-containing peptide species and their composing free peptides. Most importantly, intermediate partially reduced species containing only a single disulfide bond were also generated, from which unambiguous assignment of individual disulfide bonds could be done in species containing closely spaced disulfide bonds. The strength of this methodology was demonstrated by complete mapping of all four disulfide bonds in lysozyme and all 17 disulfide bonds in human serum albumin, including nested disulfide bonds and motifs of adjacent cysteine residues.