Proteomes are very complex with a large number of unique proteoforms spread across a wide concentration dynamic range. This means that an MS-based platform with highly efficient separation and highly sensitive detection of proteoforms is required. Capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has been suggested as one such platform. When coupled to offline liquid chromatography-based fractionation, CZE-MS/MS has proven to be invaluable to the TDP community.In Chapter 2, the first optimization of dynamic pH junction-based sample stacking for TDP is provided along with one of the first comparisons of reversed-phase liquid chromatography coupled to mass spectrometry (RPLC-MS) and CZE-MS/MS. Optimization of dynamic pH junction is performed with a standard protein mixture, and this platform was ultimately applied to an Eschericia coli (E. coli) whole cell lysate. This resulted in the largest TDP dataset for single-shot CZE-MS/MS. The comparison of RPLC-MS/MS and CZE-MS/MS also included analysis of an E. coli cell lysate and resulted in high numbers of identifications and highlighted the various pros and cons of each method.In Chapter 3, two dimensional LC fractionation (size exclusion chromatography (SEC) and RPLC) was coupled to CZE-MS/MS for deep TDP of E. coli cells. This study resulted in the largest TDP dataset, at the time, for E. coli, identifying 5700 proteoforms and 850 proteins. We were also able to identify and localize various interesting PTMs and estimate protein abundances using a spectral counting method. From this study it was clear thatour platform was comparable to other RPLC-MS/MS methods for deep TDP in terms of number of proteoform identifications and total instrument time.In Chapter 4, we applied our TDP platform to two isogenic colorectal cancer (CRC) cell lines, SW480 and SW620, from primary and metastatic tumors. Genetic changes have been known for a long time to affect CRC progression but this was the first proteoform-level deep TDP study of CRC metastasis. In total, we identified over 23000 proteoforms and over 2000 proteins, for the largest TDP dataset of any cell type and was a 400% increase in terms of identifications over previous deep TDP studies. We used a special database searching tool to identify single amino acid variants (SAAVs) for the largest dataset of proteoforms containing SAAVs. Quantitative analysis identified 460 proteoforms with significant differences in abundance between SW480 and SW620. Several of these proteoforms were also phosphorylated which could further impact disease progression and outcome for a specific patient phenotype and could serve as biomarkers for deciding how to treat a patient or for drug development.In Chapter 5, both activated ion electron transfer dissociation (AI-ETD) and ultraviolet photodissociation (UVPD) at 213 nm were coupled to CZE for deep TDP of E. coli and zebrafish brain samples, respectively. Optimized CZE-AI-ETD and CZE-UVPD resulted in large numbers of proteoform identifications, and many important modifications were identified and localized using these effective fragmentation techniques. This included N-terminal acetylation, methylation, S-thiolation, disulfide bonds, and lysine succinylation.In Chapter 6, a variety of insights into the future of TDP are provided. This includes important applications for TDP, such as personalized medicine, drug development, embryonic development, and pathogen identification. Also, a few advancements to the TDP workflow that may have increased focus on in the future are mentioned.
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