Toward Automation of Collision-Induced Unfolding Experiments through Online Size Exclusion Chromatography Coupled to Native Mass Spectrometry

Abstract

Ion mobility (IM)-based collision-induced unfolding (CIU) has gained increasing attention to probe gas-phase unfolding of proteins and their noncovalent complexes, notably for biotherapeutics. CIU detects subtle conformational changes of proteins and emerges as an attractive alternative to circumvent poor IM resolution. However, CIU still lacks in automation for buffer exchange and data acquisition, precluding its wide adoption. We present here an automated workflow for CIU experiments, from sample preparation to data interpretation using online size exclusion chromatography coupled to native IM mass spectrometry (SEC-CIU). Online automated SEC-CIU experiments offer several benefits over nanoESI-CIU, among which are (i) improved and fast desalting compared to manual buffer exchange used for classical CIU experiments; (ii) drastic reduction of the overall data collection time process; and (iii) maintaining the number of unfolding transitions. We then evaluate the potential of SEC-CIU to distinguish monoclonal antibody (mAb) subclasses, illustrating the efficiency of our method for rapid mAb subclass identification at both intact and middle levels. Finally, we demonstrate that CIU data acquisition time can be further reduced either by setting up a scheduled CIU method relying on diagnostic trap collision voltages or by implementing mAb-multiplexed SEC-CIU analyses to maximize information content in a single experiment. Altogether, our results confirm the suitability of SEC-CIU to automate CIU experiments, particularly for the fast characterization of next-generation mAb-based products.