Expanding the proteomics toolbox with intelligent data acquisition and genomic locus protein mapping

Abstract

Mass spectrometry-based proteomics has emerged as a cornerstone technology for understanding biological systems, yet significant computational and methodological challenges still exist. This dissertation aims to improve three important areas of need in proteomics: intelligent data acquisition methodologies, peptide identification efficiency, and scalability of methods for characterizing DNA-protein interactions. Chapter 2 addresses the computational demands of modern proteomics by implementing fragment ion indexing in the widely-used Comet search algorithm. Chapter 3 introduces real-time spectral library search (RTLS), an intelligent data acquisition method that leverages whole-proteome spectral libraries to guide instrument decision-making during acquisition. Finally, Chapter 4 presents DNA O-MAP, a scalable method for characterizing locus-specific chromatin interactions that overcomes limitations of existing approaches.