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NEW METHODS TO QUANTIFY METHIONINE OXIDATION AND PROTEIN GLYCOSYLATION AND A DE NOVO GLYCOPEPTIDE DECOY GENERATOR
SHIPMAN, JOSHUA Thomas
SHIPMAN, JOSHUA Thomas
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Abstract
Protein post-translational modifications (PTMs) produce complex, heterogeneous species that can best be identified and analyzed using mass spectrometry (MS). The ever-growing number of protein bioetherapeutics need effective MS tools to characterize PTMs and ensure drug safety and efficacy. Methionine oxidation and glycosylation are two PTMs that can impact protein structure, stability and pharmokinetic properties. The highly spontaneous nature of methionine oxidation makes it challenging to analyze because biologically irrelevant oxidation can be introduced during sample preparation that is indiscriminable from oxidation that impacts protein function. Chapter Two of this dissertation applies a sample preparation strategy that elucidates how much oxidation is present in native protein samples to HIV-1 Env by developing a new data analysis strategy that can be applied to the multiple-methionine containing peptides found in the tryptic digests of the protein.
Protein glycosylation is another PTM typically analyzed with MS-based workflows. MS/MS characterization of glycopeptides provides useful site-specific information, but the highly heterogeneous nature of protein glycosylation produces datasets that require burdensome, time-consuming manual analysis. To aid researchers automated MS/MS software tools have been developed, but the algorithms used are still flawed and must be improved upon to match the accuracy made by experts in glycopeptide data analysis. The production of large sets of decoy glycopeptides can be used to reveal the deficiencies in automated scoring algorithms, but to date tools that produce decoy glycopeptides are limited to specific MS/MS fragmentation techniques. Introduced in Chapter Three is DecoyDeveloper, which produces fully sequenced decoy glycopeptides de novo; this tool is capable of providing the large volume of decoy glycopeptides necessary to improve automated algorithms in a format that is applicable to any fragmentation technique. DecoyDeveloper is open source and can be integrated into existing or newly developed tools, aiding in the improvement and validation of automated glycopeptide scoring software.
Another research field that greatly benefits from the mass spectrometry-based analysis of protein glycosylation is the discovery and quantitation of disease biomarkers, as the wealth of data can be used to identify differences between healthy and diseased individuals. While MS profiling of glycosylation has shown that glycans offer the sensitive, specific biomarkers that are needed, the translation into the clinical laboratory has failed due to the limitations of the analysis itself. We have developed a stream-lined method that can quantify glycan features in a manner that is conducive to high-throughput sample screening with the needs of the clinical laboratory in mind. The throughput of sample preparation, analysis, and data processing are all improved upon over conditional glycomics experiments, offering a method that can bridge the divide between discovery and clinical use of glycan based biomarkers.
Protein glycosylation is another PTM typically analyzed with MS-based workflows. MS/MS characterization of glycopeptides provides useful site-specific information, but the highly heterogeneous nature of protein glycosylation produces datasets that require burdensome, time-consuming manual analysis. To aid researchers automated MS/MS software tools have been developed, but the algorithms used are still flawed and must be improved upon to match the accuracy made by experts in glycopeptide data analysis. The production of large sets of decoy glycopeptides can be used to reveal the deficiencies in automated scoring algorithms, but to date tools that produce decoy glycopeptides are limited to specific MS/MS fragmentation techniques. Introduced in Chapter Three is DecoyDeveloper, which produces fully sequenced decoy glycopeptides de novo; this tool is capable of providing the large volume of decoy glycopeptides necessary to improve automated algorithms in a format that is applicable to any fragmentation technique. DecoyDeveloper is open source and can be integrated into existing or newly developed tools, aiding in the improvement and validation of automated glycopeptide scoring software.
Another research field that greatly benefits from the mass spectrometry-based analysis of protein glycosylation is the discovery and quantitation of disease biomarkers, as the wealth of data can be used to identify differences between healthy and diseased individuals. While MS profiling of glycosylation has shown that glycans offer the sensitive, specific biomarkers that are needed, the translation into the clinical laboratory has failed due to the limitations of the analysis itself. We have developed a stream-lined method that can quantify glycan features in a manner that is conducive to high-throughput sample screening with the needs of the clinical laboratory in mind. The throughput of sample preparation, analysis, and data processing are all improved upon over conditional glycomics experiments, offering a method that can bridge the divide between discovery and clinical use of glycan based biomarkers.
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2019-01-01
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University of Kansas
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