Alzheimer’s disease (AD) is the most prevalent form of dementia affecting the elderly, and as the aging population increases the social and economic burden of AD grows substantially. Pathological hallmarks of AD include the accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles (NFTs), as well as significant neuron loss. Amyloid plaques consist of aggregated amyloid beta (Aβ) peptide, which is generated from the proteolytic processing of amyloid precursor protein (APP) in addition to several other peptides. While the processing of APP has been characterized, its primary physiological function and its involvement in AD pathology are poorly understood. Developing a greater understanding of the function of APP, and the molecular and cellular functions it is involved in or other proteins it is associated with, could provide insight into its role in AD pathology. To investigate the function of APP695, the neuronal isoform of APP, we used mass spectrometry to compare changes in protein expression and phosphorylation between APP-null B103 and APP695-expressing B103-695 rat neuroblastoma cells.
Mass spectrometry-based proteomics has become a powerful technique for the unbiased identification of proteins from complex mixtures. Quantitative proteomics using labeling techniques, such as stable isotope labeling by amino acids in cell culture (SILAC), allow relative quantitation of multiple samples at once. More recently, with advances in mass spectrometer technology, label-free quantitation has become a reliable quantitative proteomics approach. Additionally, mass spectrometry can be used for the analysis of post-translational modifications, such as phosphorylation, a dynamic modification involved in the regulation of many cellular processes. Phosphoproteomics identifies site-specific phosphorylation and surrounding sequence information, which can be used for consensus motif analysis to provide further information about potential changes in kinase activity. Identifying changes in phosphorylation and kinase activity also provides information about signaling pathways and functions that may be affected by APP695 expression. Comprehensive proteomic and phosphoproteomic datasets can be used to gain insight into the molecular mechanisms that may be regulated by APP695 expression, or involved in AD progression and pathology, leading to the development of novel therapeutic and preventative strategies for AD.
Proteomic and phosphoproteomic analysis of B103 and B103-695 cells identified several significant protein expression and phosphorylation changes that may be mediated by APP695-expression. Global-scale proteomic analysis identified increased expression of Ras and ƴ-synuclein in B103-695 cells, which was further validated in human AD brain tissue. Phosphoproteomic analysis showed increased phosphorylation of Histone H4 at Ser47, and led to the investigation of PCTAIRE-2 (Cdk17), and PCTAIRE-3 (Cdk18) expression, which were all shown to be increased in AD transgenic mouse tissue, culture primary rat neurons treated with Aβ, as well as mild cognitive impairment (MCI) and AD human brain tissue.
Label-free quantitative proteomics was used for the analysis of human brain tissue from the cortex of individuals affected by AD, MCI, Parkinson’s disease (PD), and progressive supranuclear palsy (PSP) compared to cognitively normal, control samples. A number of differentially expressed proteins were identified in AD, MCI, PD, and PSP tissue. Bioinformatic analysis of the comprehensive proteomic datasets from AD, MCI, PD, and PSP human brain tissue identified several proteins consistent with corresponding disease pathology and neurodegeneration, such as inflammatory proteins. While some of the molecular and cellular functions were unique among neurodegenerative diseases, there also appears to be overlap of affected functions, suggesting there may be a more common mechanism of neurodegeneration.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-7117 |
| Date | 19 November 2015 |
| Creators | Chaput, Dale |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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