Integration Of Quantitative And Functional Proteomics To Explore The Global Functional Landscape Of Post-Translational Modifications

Abstract

Proteomics explores global-scale protein functions, with post-translational modifications (PTMs) expanding proteome complexity and functionality. Significant advancements in mass spectrometry (MS)-based quantitative proteomics have expanded the scope of PTM pathways. Meanwhile, functional proteomics bridges the annotation gap by linking uncharacterized proteins with biological functions. These two fields facilitate the exploration of the vast physiological function landscape of proteins and PTMs and aid in identifying disease-specific protein targets for the early detection and curation of diseases.This research integrated the MS data analysis from quantitative proteomics and functional proteomics approaches and develop innovative bioinformatic strategies to interpret the functional landscape of PTM pathways in three aspects: up-stream enzymatic regulatory mechanisms that are responsible for adding and removing PTMs, comprehensive inventory and annotation analysis of PTM targets, and down-stream prediction of functional impacts of PTMs in protein structural stability and activities. First, to discover the up-stream enzymatic activities of a critical PTM pathway – ubiquitination, we constructed a quantitative ubiquitylome analysis algorithm and a stand-alone Python software package called UbE3-APA which is based on an interaction database for E3 ligase and ubiquitin sites to analyze the dynamics of ubiquitylome from MS-based quantitative proteomics data. The algorithm revealed the E3 ligase activity profiles of multiple global ubiquitylome studies effectively under various genetic and metabolic conditions. The algorithm developed in this project as well as a similar algorithm we developed in the Kinase Activity Profiling Analysis (KAPA) may be generally applicable to other PTM enzyme activity profiling analyses. Next, to comprehensively catalog an essential and yet under-studied oxygen-sensing posttranslational modification pathway – proline hydroxylation, we developed an online database and website platform, HypDB (https://hypdb.site), for hydroxyproline sites collection and functional annotation, while sharing the knowledge with the community. In the data collecting section, we evaluated the confidence of site-localization for identified sites and quantified their stoichiometry with corresponding MS spectra. And in the annotation section, we integrated multiple functional databases and developed bioinformatic strategies to study the enrichment of the hydroxyproline proteome in cellular pathways, structural domains, and tissue distributions at the levels of both the protein and modification site. All identified sites with annotation results were capsuled into HypDB websites, where its downloadable hydroxyproline spectra library allowed systematic data-independent DIA data analysis. Lastly, to understand the potential functional impacts of PTM in downstream pathways and protein activities, we developed bioinformatics strategies to identify the functional hydroxyproline proteome by integrated analysis of quantitative functional proteomics datasets. Our bioinformatic workflow explored the evolution conservation, protein turnover, and thermal stability profiles of hydroxyproline proteome in multiple species and different cell lines. Through individual and integrated analysis, we not only have a deeper understanding of the role of the global proline hydroxylation on protein structural stability under different conditions but also revealed significantly regulated hydroxyproline sites and substrate proteins that may serve as key targets in oxygen and metabolic sensing mechanisms in cellular activities. Collectively, this series of studies generate applicable models and novel knowledge in interpreting the functional network influenced by different PTMs.