Developing Mass Spectrometry-based Omics and Proximity Labeling Methods to Unravel Mitochondrial Biology
Open Access DepositedMitochondria are essential organelles responsible for energy production, cellular metabolism, and signaling. Mitochondrial dysfunction is implicated in a wide range of diseases, including neurodegenerative diseases, cardiovascular disorders, metabolic syndromes, and cancer. However, the intricate molecular mechanisms governing mitochondrial biology remain elusive, largely due to the technical challenges of probing dynamic interactions within mitochondria and with other organelles and cellular components in living cells. Traditional biochemical approaches are often challenged by their low throughput and loss of the true physiological state of the dynamic mitochondrial protein networks after cell lysis. This dissertation focuses on developing and applying mass spectrometry (MS)-based omics and proximity labeling (PL) techniques to systematically investigate mitochondrial proteomes and protein interaction networks. Advanced MS enables high-throughput, unbiased identification and quantification of mitochondrial biomolecules. PL, when combined with MS, allows for selective labeling and identification of proteins in their native microenvironment, preserving their transient interactions and revealing their dynamic spatial and temporal remodeling. By integrating high-resolution MS analyses, PL techniques, and advanced sample preparation pipelines, our approaches capture dynamic changes in protein abundance, localization, and interactions under diverse physiological and pathological conditions. These methods pinpoint key regulators of mitochondrial function, illuminate inter-organelle communication, and deepen our understanding of the molecular events underlying mitochondrial dysfunction. Ultimately, this research paves the way for improved diagnostics and targeted therapeutic strategies to restore or modulate mitochondrial homeostasis in human disease. Chapter 1 of this dissertation introduces recent MS-based omics advances, with a particular focus on proteomics and metabolomics, as well as the latest developments in PL techniques. Additionally, it provides an overview of mitochondrial biology, mitochondrial diseases, and the specific objectives of this thesis. Chapter 2 describes the development of a thiol-cleavable biotin enrichment strategy to improve protein identification and biotinylation site analysis. By coupling TurboID PL in living cells with mass spectrometry, this approach reveals high spatial resolution of mitochondrial proteins, together with reduced streptavidin contamination, additional information on biotinylation site, and improved protein sequence coverage. Chapter 3 presents the effort to systematically evaluate biotinylation enrichment methods using a two-proteome model as well as developing a new automated workflow for PL proteomics. We comprehensively optimized various parameters involved in PL proteomics sample preparation. Using this optimized and automated workflow, we captured dynamic mitochondria-lysosome interactions upon mitochondrial damage, revealing time-dependent proteome remodeling and protein translocation. Chapter 4 describes a multi-omics approach integrating proteomics and metabolomics to explore patient-derived dermal fibroblasts with an ultra-rare mitochondrial disease variant. By revealing OXPHOS dysregulation and arginine biosynthesis deficiency, this study highlighted potential biomarkers underlying mitochondrial disease pathogenesis, supporting future clinical interventions and personalized therapeutic strategies to manage inherited mitochondrial disease. Chapter 5 details the pathogenetic origins of mitochondrial metabolic disorders and reviews recent MS-based metabolomic breakthroughs in profiling their remodeling. This chapter highlights how MS-driven insights into metabolomic biosignatures enhance diagnostic approaches, patient stratification, and targeted therapeutic strategies. Chapter 6 summarizes the work presented in this dissertation and provides future directions and improvements of MS-based PL techniques.
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