Longitudinal characterization of the brain proteomes for the tg2576 amyloid mouse model using shotgun based mass spectrometry.
Neurodegenerative disorders are often defined pathologically by the presence of protein aggregates, such as amyloid plaques composed of β-amyloid (Aβ) peptide in Alzheimer's disease. Such aggregates are the result of abnormal protein accumulation and may lead to neuronal dysfunction and cell death. In this study, APPSWE transgenic mice (Tg2576), which overexpress the Swedish mutated form of human amyloid precursor protein (APP), were used to study the brain proteome associated with amyloid plaque deposition. The major aim of the study was to map and compare the Tg2576 model brain proteome profiles during pathology progression using a shotgun approach based on label free quantification with mass spectrometry. Overall, 1085 proteins were identified and longitudinally quantified. Principal component analysis (PCA) showed the appearance of the pathology onset between twelve and fifteen months, correlating with sharp amyloid plaque accumulation within the same ages. Cluster analysis followed by protein-protein interaction analysis revealed an age-dependent decrease in mitochondrial protein expression. We identified 57 significantly affected mitochondrial proteins, several of which have been reported to alter expression in neurological diseases. We also found ten proteins that are upregulated early in the amyloid driven pathology progression with high confidence, some of which are directly involved in the onset of mitochondrial apoptosis and may represent potential markers for use in human neurological diseases prognosis. Our results further contribute to identifying common pathological pathways involved in both aging and progressive neurodegenerative disorders enhancing the understanding of disease pathogenesis.
Analytical Chemistry, Department of Chemistry-BMC, Uppsala University, and Department of Medical Sciences, Cancer Pharmacology and Computational Medicine, Uppsala University Academic Hospital, Box 599, SE-751 24 Uppsala, Sweden. ganna.shevchenko@kemi.uu.se
Ganna
G
Shevchenko
Magnus
M
Wetterhall
Jonas
J
Bergquist
Kina
K
Höglund
Lars I
LI
Andersson
Kim
K
Kultima
D000367:Age Factors; D000544:Alzheimer Disease / Q000175:diagnosis / Q000378:metabolism; D016564:Amyloid beta-Protein Precursor / Q000235:genetics / Q000378:metabolism*; D000818:Animals; D017209:Apoptosis; D015415:Biomarkers / Q000378:metabolism; D001921:Brain / Q000378:metabolism* / Q000473:pathology; D016000:Cluster Analysis; D018450:Disease Progression; D006801:Humans; D051379:Mice; D008822:Mice, Transgenic; D008928:Mitochondria / Q000378:metabolism / Q000473:pathology; D024101:Mitochondrial Proteins / Q000378:metabolism; D015999:Multivariate Analysis; D058225:Plaque, Amyloid / Q000378:metabolism / Q000473:pathology; D025341:Principal Component Analysis; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps; D020543:Proteome / Q000032:analysis* / Q000378:metabolism; D053719:Tandem Mass Spectrometry / Q000379:methods*; D013997:Time Factors
C545487:APP protein, human; D016564:Amyloid beta-Protein Precursor; D015415:Biomarkers; D024101:Mitochondrial Proteins; D020543:Proteome