| Mass spectrometry-based proteomics is a constantly and rapidly evolving field of scientific research. Two of its most important components--data acquisition and data analysis---are no exception. The remarkable versatility of modem, hybrid mass spectrometers enables countless possibilities in terms of novel scan types, which can provide substantial benefits for certain types of analyses. Equally important, the complex, information-rich data generated by these mass spectrometers requires automated analysis in order to maximize identifications as well as provide reliable quantification. The research described herein documents the development and characterization of tools and methods designed to improve the performance of these technologies.;Chapter 1 is introduces mass spectrometry-based proteomics, with a focus on the relevant data acquisition and data analysis issues. Major historical developments, as well as future prospects, are discussed. Chapter 2 describes the implementation and characterization of a novel internal mass recalibration scheme for electron-transfer dissociation-enabled mass spectrometers. Its performance, which for orbitrap mass analysis provides low part-per-million mass errors for both precursors and products, is analyzed in comparison to standard external mass calibration and two similar, internal mass calibration approaches. Chapter 3 describes a novel data acquisition strategy for isobaric tag-based proteomic quantification (QuantMode). Though its straightforward application to tissues/biofluids and multiplexing capability (up to eight samples simultaneously) offer considerable advantages, isobaric tagging suffers from precursor interference--co-isolation of impurities that affect MS/MS--that has thus far severely limited its accuracy. QuantMode performs gas-phase purification to selectively enrich target analytes, drastically improving quantitative accuracy with only a minor loss of identifications. Chapter 4 describes the C&barbelow;oon OMSSA (Open Mass Spectrometry Search Algorithm) P&barbelow;roteomic A&barbelow;nalysis S&barbelow;oftware S&barbelow;uite (COMPASS): a synergistic collection of highly automated, free and open-source computational tools. The motivations for all of the modules in the suite are discussed, along with an analysis of the results they provided for two sample datasets. Whenever possible, the results are compared to the current de facto standard, the Trans-Proteomic Pipeline. |
