Abstract
Bottom-up protein mass spectrometry aims for the identification and quantification of protein species by proxy of their proteolytic peptides. This dissertation presents methodological advances in three areas of protein mass spectrometry: acquisition methods, clinical appli- cations, and data analysis algorithms. The second chapter presents an optimized internal standard-triggered parallel reaction monitoring (OIS-PRM) method and demonstrates its application to study prognostic biomarkers in head and neck squamous cell carcinoma (HN- SCC). OIS-PRM uses intelligent scan scheduling and real-time monitoring of peptide elution profiles to reduce cycle-times and improve quantitative precision and accuracy. The assay measured NRF2 activation in both cell lines and formalin-fixed paraffin-embedded tumor samples, and it also quantified differences in T-cell marker expression between HPV-positive and HPV-negative tumors. The clinical applications demonstrated here may also help guide treatment decisions for HNSCC patients based on molecular signatures of NRF2 activity and inflammation. The third chapter introduces Pioneer and Altimeter, open-source tools for the analysis of data-independent acquisition (DIA) mass spectrometry data. Pioneer implements several innovations. These include an intensity-aware fragment indexing algorithm, robust spectral deconvolution using pseudo-Huber loss, and modeling of quadrupole transmission effects on fragment isotope patterns. Altimeter generates collision energy-specific spectral predictions using B-spline functions. This enables a single library to accommodate different instruments and methods. Across multiple benchmarks using different mass analyzers and experimental conditions, Pioneer demonstrates 3-15 times faster processing speeds and comparable or superior proteome coverage and quantitative precision compared to a state-of-the-art analysis tool, DIA-NN. Together, these tools improve DIA analyses and establish a new computational framework that can adapt to emerging experimental techniques.
Committee Chair
Benjamin Major
Committee Members
Dennis Goldfarb; Benjamin Garcia; Benjamin Major; Dennis Goldfarb; Gary Patti; Shamim Mollah; Timothy Holy
Degree
Doctor of Philosophy (PhD)
Author's Department
Biology & Biomedical Sciences (Computational & Systems Biology)
Document Type
Dissertation
Date of Award
5-5-2025
Language
English (en)
DOI
https://doi.org/10.7936/64fr-as23
Recommended Citation
Wamsley, Nathan, "Acquisition Algorithms for Protein Mass Spectrometry and Their Application to Clinical Proteomics" (2025). Arts & Sciences Theses and Dissertations. 3467.
The definitive version is available at https://doi.org/10.7936/64fr-as23