Characterization of Novel Cellular Systems Using Labelfree Quantitative Proteomics
Date of Award
Chemistry and Biochemistry
Panayiotis O. Vacratsis
Alternate reproductive tactics, Daphnia pulex, data-independent acquisition, Ion mobility, Proteomics, Spinal muscular atrophy
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Proteomics involves the systematic identification of the protein complement within an array of biological systems. Quantitative proteomics is an extension of proteomics that aims to characterize the changes in protein abundance between different sample states. Mass spectrometry, which measures the mass of ionized molecules in the gas phase, is the predominant analytical tool featured in quantitative proteomic studies. As more genomes are becoming annotated and publicly available, mass spectrometry-based approaches to proteomics have increased in feasibility. Furthermore, the orthogonal detection of all precursor ions and precursor ion fragments, known as data independent acquisition mass spectrometry, has allowed for high-throughput instruments to identify low and high abundant proteins without bias. Data-independent acquisition, in combination with ion mobility, has encouraged the enhancement of protein resolution by further separating ions based on their size, shape and charge. Together, the technological innovations of today’s mass spectrometers and advancement of genomic libraries has extended the boundaries for deeper proteome coverage. The option of using label-free standards for quantitative applications in proteomics is a non-invasive and cost-effective method for measuring protein abundance. However, early label-free strategies suffered from poor resolution and sensitivity issues when analyzing complex mixtures during quantitative studies. By optimizing the use of data-independent acquisition mass spectrometry and ion mobility separation, label-free strategies have joined the toolbox of reliable proteomic platforms for conducting quantitative analysis. In the following thesis, we present the successful application of using data-independent acquisition mass spectrometry employing orthogonal ion mobility separation to three unique biological systems including Daphnia pulex with the supplementation of using label-free quantitative techniques to explore the protein alterations in the seminal plasma of Chinook salmon, and the synaptosomes of a SMA mouse model. For the Daphnia pulex profiling study, our optimized methods have progressed sample preparation methods for the Daphnia model system and suggests label free mass spectrometry techniques will be applicable in utilizing the Daphnia model in assays that monitor aquatic health dynamics. With regard to the Chinook salmon project, we elucidated statistically significant protein abundance differences between hooknose and jack male tactics. Proteins involved in membrane remodeling, proteolysis, hormonal transport, redox regulation, immunomodulation, and ATP metabolism were among the proteins reproducibly identified at different levels and represent putative factors influencing sperm competition between jack and hooknose males. This study represents the largest seminal plasma proteome from teleost fish and the first reported for Chinook salmon. Lastly, Label-free quantitative proteomics on isolated synaptosomes from spinal cords of a SMA mouse model identified 2030 protein groups. Statistical data analysis revealed 65 specific alterations in the proteome of the central synapses at the early onset stage of disease. Functional analysis of the dysregulated proteins indicated a significant enrichment of proteins associated with mitochondrial dynamics, cholesterol biogenesis, and protein clearance. These pathways represent potential targets for therapy development with the goal of providing stability to the central synapses, thereby preserving neuronal integrity in the context of SMA disease.
Gombar, Robert, "Characterization of Novel Cellular Systems Using Labelfree Quantitative Proteomics" (2020). Electronic Theses and Dissertations. 8361.