- Title
- Deep time-resolved proteomic and phosphoproteomic profiling of cigarette smoke-induced chronic obstructive pulmonary disease
- Creator
- Skerrett-Byrne, David
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2019
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Proteomics has become a mature scientific discipline across many fields and a critical means to understand the dynamic nature of disease states. Strikingly, there are now more than 83,995 citations featuring ‘proteomics’, many of which have arisen in the past 5-10 years. However, in stark contrast to most fields of research, in chronic obstructive pulmonary disease (COPD), proteomics remains an under-utilised research tool with only 202 citations featuring ‘COPD proteomics’ recorded to date (<0.25% of all papers). This is in spite of the severity of the disease with COPD listed as the third leading cause of death worldwide. In this thesis, we have sought to address this fundamental knowledge gap by undertaking a highly comprehensive, comparative and quantitative time resolved analysis of both the proteome and phosphoproteome of lung tissue using our well-characterised mouse model of cigarette smoke-induced COPD. Moreover, we have developed critical platforms for the analysis of endobronchial biopsies from patients through the analysis of samples from clinical cohorts encompassing healthy controls, healthy smokers, mild COPD and severe COPD patients. Key highlights from this body of work include the quantification of 7,324 proteins and 27,857 unique phoshopeptides across a 12-week time course of COPD progression in our mouse model. Strikingly, we have identified a critical window of protein dysregulation that occurs at the 8-week time point corresponding to the progression phase of the disease. Importantly, novel proteins implicated in this phase included heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC) and RNA-binding protein Musashi homolog 2 (MSI2), two key proteins involved in RNA synthesis and binding, and protein S100-A1 (S100A1), a calcium signalling protein with the propensity to signal through toll like receptor 4 (TLR4) andmodulate downstream inflammatory response pathways. In characterising alterations in phosphorylation associated with the induction and progression stages of COPD, our data have revealed 139 kinases responsible for the phosphorylation of serine, threonine and tyrosine residues. Moreover, from these data we have identified 14 druggable kinases that may be targeted to reduce the pathogenesis of COPD. Finally, through establishing a human COPD proteome we have developed a thorough inventory of dysregulated proteins that serve to characterise the progression of cigarette-smoke induced COPD in humans. Within this inventory we have highlighted activating transcription factor 6 (ATF6), x-box binding protein 1 (XBP1) and arachidonate 15-lipoxygenase (ALOX15) as potential contributors to oxidative stress, the unfolded protein response and advanced ageing-like phenotypic changes that are common to lung tissue following smoke exposure. Taken together, these data provide a large and valuable resource for molecular biologists working in the field of COPD. In this way the data presented in this thesis will aid in biomarker discover, direct the delineation of COPD classifications and inform therapeutic strategies towards better patient care for individuals experiencing the weight of this disease.
- Subject
- proteomics; phosphoproteomics; chronic obstructive pulmonary disease; therapeutic targets; biomarkers; kinases; bioinformatics; thesis by publication
- Identifier
- http://hdl.handle.net/1959.13/1409015
- Identifier
- uon:35918
- Rights
- Copyright 2019 David Skerrett-Byrne
- Language
- eng
- Full Text
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Thumbnail | File | Description | Size | Format | |||
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View Details Download | ATTACHMENT01 | Thesis | 15 MB | Adobe Acrobat PDF | View Details Download | ||
View Details Download | ATTACHMENT02 | Abstract | 426 KB | Adobe Acrobat PDF | View Details Download |