Repository logo
 

Maximizing Proteome Recovery and Digestion Efficiency for High-Throughput Bottom-up Mass Spectrometry

dc.contributor.authorNickerson, Jessica
dc.contributor.copyright-releaseYesen_US
dc.contributor.degreeDoctor of Philosophyen_US
dc.contributor.departmentDepartment of Chemistryen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinerDajana Vuckovicen_US
dc.contributor.graduate-coordinatorPeng Zhangen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.thesis-readerJan Raineyen_US
dc.contributor.thesis-readerAlejandro Cohenen_US
dc.contributor.thesis-readerJames Fawcetten_US
dc.contributor.thesis-supervisorAlan A. Doucetteen_US
dc.date.accessioned2022-12-19T14:44:06Z
dc.date.available2022-12-19T14:44:06Z
dc.date.defence2022-12-09
dc.date.issued2022-12-16
dc.description.abstractWith current mass spectrometry and bioinformatics platforms, proteome analysis is at the forefront of characterizing complex biological systems. Through deep qualitative coverage combined with precise quantitation, proteomics represents a powerful tool in the pursuit of understanding disease-driving mechanisms and elucidating precise therapeutic approaches. However, the stringency of proteomics output is limited by the coverage and precision afforded by front-end preparation strategies. Much of the current proteomics literature relies on the maximum potential of state-of-the-art MS acquisition technologies without leveraging optimal front-end processing. Furthermore, many of the existing sample preparation strategies (reviewed in Chapter 1 of this thesis) impart a trade-off between recovery, digestion efficiency, and precision. The present thesis aims to evaluate the factors limiting front-end workflows and propose practical alternatives that maximize coverage, quantitative precision, and throughput. Organic solvent-based precipitation as a means of proteome purification has often been overlooked based on conflicting reports of efficiency. Following previous work from this group, Chapter 2 of this thesis assesses the rate-limiting variables associated with protein precipitation and demonstrates a rapid and robust approach to precipitation-based proteome recovery. Chapter 3 provides an evaluation of the repeatability of a precipitation-based bottom-up proteome workflow on the basis of sample coverage and the precision of peptide quantitation. Chapter 4 evaluates the potential of the enhanced precipitation approach towards multi-omics preparations. Bottom-up proteome strategies rely on robust enzymatic digestion with trypsin. Many common proteomics additives, however, impede the enzyme’s stability. Chapter 5 of this thesis characterizes the effects of several denaturing additives, demonstrating that these solubilizing agents are included at the expense of proteolytic efficiency. A wide variety of alternative digestion approaches have been described towards improved throughput over the conventional overnight incubation, although the limited validation reduces their potential for precise quantitation. Chapter 6 of this thesis characterizes the effects of elevated temperature in combination with the stabilizing effects of calcium ions towards a rapid approach to complete digestion while demonstrating the implications for bottom-up proteome analysis. Future studies, summarized in Chapter 7, suggest the application of the described rapid precipitation and enzymatic digestion to the development of targeted assays in large-scale clinical settings.en_US
dc.identifier.urihttp://hdl.handle.net/10222/82183
dc.language.isoen_USen_US
dc.subjectproteomicsen_US
dc.subjectsample preparationen_US
dc.subjectprotein precipitationen_US
dc.subjecttrypsin digestionen_US
dc.titleMaximizing Proteome Recovery and Digestion Efficiency for High-Throughput Bottom-up Mass Spectrometryen_US

Files

Original bundle

Now showing 1 - 5 of 35
Loading...
Thumbnail Image
Name:
JessicaLynnNickerson2022.pdf
Size:
5.92 MB
Format:
Adobe Portable Document Format
Description:
Main article
No Thumbnail Available
Name:
TableA2.1.xlsx
Size:
3.08 MB
Format:
Microsoft Excel XML
Description:
TableA2.1
No Thumbnail Available
Name:
TableA2.2.xlsx
Size:
2.51 MB
Format:
Microsoft Excel XML
Description:
TableA2.2
No Thumbnail Available
Name:
TableA2.3.xlsx
Size:
636.79 KB
Format:
Microsoft Excel XML
Description:
TableA2.3
No Thumbnail Available
Name:
TableA2.4.xlsx
Size:
613.86 KB
Format:
Microsoft Excel XML
Description:
TableA2.4

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: