Development of ion mobility mass spectrometry deconvolution strategies for use in data-independent acquisition proteomics.

Modern mass spectrometers are among the most sensitive and suitable analytical tools for high-throughput protein characterization. However, limitations in ion mobility (IM) and mass spectrometry (MS) resolving powers can limit the success of MS-based proteomics approaches. This work highlights the development of IM-MS deconvolution techniques and their utilization with commercial data processing software to improve results from IM-enhanced data-independent acquisition (HDMSᴱ) proteomics strategies. Chemometric deconvolution and post-IM/collision-induced dissociation (postIM/CID) MS were used to extract “pure component” IM profiles and construct CID mass spectra of IM-MS unresolved species. Collision-energy resolved and broadband IM-MS deconvolution strategies were developed and used for successful characterization of simulated complex mixtures and biological samples, respectively. As described in Chapter Two, utilizing m/z-isolation in a novel collision-energy resolved approach, a multicomponent IM unresolved peak was deconvoluted to construct fully resolved individual IM peaks.A broadband data acquisition approach (i.e., without the use of m/z-isolation) for improved IM-MS deconvolution is presented in Chapter Three where it is demonstrated that broadband IM-MS deconvolution provides time-saving and sensitivity advantages over the scan mode approach. Elimination of the ion isolation step also expands the applicability of IM-MS deconvolution to HDMSᴱ acquisition. Ultra-performance liquid chromatography (UPLC) was used with HDMSᴱ for high-throughput bottom-up proteomics analysis of rat brain tissue. The combined use of broadband IM-MS deconvolution and commercial HDMSᴱ data processing software allowed more efficient precursor and product ion detections and improved proteins’ sequence coverages. The use of data-dependent acquisition (DDA) and HDMSᴱ for high-throughput MS-based investigations of rat brain tissue is presented in Chapter Four. Infrared laser ablation microsampling was used to extract spatially localized rat brain samples for subsequent bottom-up proteomics analysis using both DDA and HDMSᴱ strategies. The use of HDMSᴱ acquisition for bottom-up proteomics of laser ablated rat brain samples provided greater numbers of peptides and proteins detected than DDA. Finally, in Chapter Five, potential future research directions are presented and discussed.