Aβ peptide accumulation is thought to be the primary event in the pathogenesis of Alzheimer's disease (AD), with downstream neurotoxic effects including the hyperphosphorylation of tau protein. Glycogen synthase kinase-3 (GSK-3) is increasingly implicated as playing a pivotal role in this amyloid cascade. We have developed an adult-onset Drosophila model of AD, using an inducible gene expression system to express Arctic mutant Aβ42 specifically in adult neurons, to avoid developmental effects. Aβ42 accumulated with age in these flies and they displayed increased mortality together with progressive neuronal dysfunction, but in the apparent absence of neuronal loss. This fly model can thus be used to examine the role of events during adulthood and early AD aetiology. Expression of Aβ42 in adult neurons increased GSK-3 activity, and inhibition of GSK-3 (either genetically or pharmacologically by lithium treatment) rescued Aβ42 toxicity. Aβ42 pathogenesis was also reduced by removal of endogenous fly tau; but, within the limits of detection of available methods, tau phosphorylation did not appear to be altered in flies expressing Aβ42. The GSK-3–mediated effects on Aβ42 toxicity appear to be at least in part mediated by tau-independent mechanisms, because the protective effect of lithium alone was greater than that of the removal of tau alone. Finally, Aβ42 levels were reduced upon GSK-3 inhibition, pointing to a direct role of GSK-3 in the regulation of Aβ42 peptide level, in the absence of APP processing. Our study points to the need both to identify the mechanisms by which GSK-3 modulates Aβ42 levels in the fly and to determine if similar mechanisms are present in mammals, and it supports the potential therapeutic use of GSK-3 inhibitors in AD.

The greatest risk factor for Alzheimer's disease (AD) is age, and changes in the ageing nervous system are likely contributors to AD pathology. Amyloid beta (Aβ) accumulation, which occurs as a result of the amyloidogenic processing of amyloid precursor protein (APP), is thought to initiate the pathogenesis of AD, eventually leading to neuronal cell death. Previously, we developed an adult-onset Drosophila model of AD. Mutant Aβ42 accumulation led to increased mortality and neuronal dysfunction in the adult flies. Furthermore, we showed that lithium reduced Aβ42 protein, but not mRNA, and was able to rescue Aβ42-induced toxicity. In the current study, we investigated the mechanism/s by which lithium modulates Aβ42 protein levels and Aβ42 induced toxicity in the fly model. We found that lithium caused a reduction in protein synthesis in Drosophila and hence the level of Aβ42. At both the low and high doses tested, lithium rescued the locomotory defects induced by Aβ42, but it rescued lifespan only at lower doses, suggesting that long-term, high-dose lithium treatment may have induced toxicity. Lithium also down-regulated translation in the fission yeast Schizosaccharomyces pombe associated with increased chronological lifespan. Our data highlight a role for lithium and reduced protein synthesis as potential therapeutic targets for AD pathogenesis.

Age is the major risk factor for many neurodegenerative diseases, including Alzheimer's Disease (AD), for reasons that are not clear. The association could indicate that the duration or degree of exposure to toxic proteins is important for pathology, or that age itself increases susceptibility to protein toxicity. Using an inducible Drosophila model of AD, we investigated these possibilities by varying the expression of an Aβ42 transgene in neurons at different adult ages and measuring the effects on Aβ42 levels and associated pathological phenotypes. Acute induction of Arctic Aβ42 in young adult flies resulted in rapid expression and clearance of mRNA and soluble Arctic Aβ42 protein, but in irreversible expression of insoluble Arctic Aβ42 peptide. Arctic Aβ42 peptide levels accumulated with longer durations of induction, and this led to a dose-dependent reduction in negative geotaxis and lifespan. For a standardised level of mRNA expression, older flies had higher levels of Arctic Aβ42 peptide and associated toxicity, and this correlated with an age-dependent reduction in proteasome activity. Equalising Aβ42 protein at different ages shortened lifespan in correlation with the duration of exposure to the peptide, suggesting that Aβ42 expression accumulates damage over time. However, the relative reduction in lifespan compared to controls was greater in flies first exposed to the peptide at older ages, suggesting that ageing itself also increases susceptibility to Aβ42 toxicity. Indeed older flies were more vulnerable to chronic Aβ42 toxicity even with a much lower lifetime exposure to the peptide. Finally, the persistence of insoluble Aβ42 in both young and old induced flies suggests that aggregated forms of the peptide cause toxicity in later life. Our results suggest that reduced protein turnover, increased duration of exposure and increased vulnerability to protein toxicity at later ages in combination could explain the late age-of-onset of neurodegenerative phenotypes.

The field of proteomics has been developing rapidly toward quantification of proteins. Despite the variety of experimental techniques available for peptide and protein labelling, there are few commercially available analytical tools with the ability to interpret data from any mass spectrometer. In this study, we compare two software packages, Mascot and Peaks, for the analysis of iTRAQ data from ESI-Q/TOF mass spectrometry. In the case of a six-protein mixture combined in a known proportion, the output of the Peaks algorithm deviated from the correct result by 14% on average, while the error of the Mascot quantification was nearly 200%. When the software were used to analyse iTRAQ data from a complex protein sample, the quantification results agreed within 20% for only 26% of the quantified proteins, showing significant differences in the two quantification algorithms. This comparison and analysis revealed major intricacies in peptide and protein quantification that must be taken into consideration for software development.

Age is the major risk factor for many neurodegenerative diseases, including Alzheimer's Disease (AD), for reasons that are not clear. The association could indicate that the duration or degree of exposure to toxic proteins is important for pathology, or that age itself increases susceptibility to protein toxicity. Using an inducible Drosophila model of AD, we investigated these possibilities by varying the expression of an Ab42 transgene in neurons at different adult ages and measuring the effects on Ab42 levels and associated pathological phenotypes. Acute induction of Arctic Ab42 in young adult flies resulted in rapid expression and clearance of mRNA and soluble Arctic Ab42 protein, but in irreversible expression of insoluble Arctic Ab42 peptide. Arctic Ab42 peptide levels accumulated with longer durations of induction, and this led to a dose-dependent reduction in negative geotaxis and lifespan. For a standardised level of mRNA expression, older flies had higher levels of Arctic Ab42 peptide and associated toxicity, and this correlated with an age-dependent reduction in proteasome activity. Equalising Ab42 protein at different ages shortened lifespan in correlation with the duration of exposure to the peptide, suggesting that Ab42 expression accumulates damage over time. However, the relative reduction in lifespan compared to controls was greater in flies first exposed to the peptide at older ages, suggesting that ageing itself also increases susceptibility to Ab42 toxicity. Indeed older flies were more vulnerable to chronic Ab42 toxicity even with a much lower lifetime exposure to the peptide. Finally, the persistence of insoluble Ab42 in both young and old induced flies suggests that aggregated forms of the peptide cause toxicity in later life. Our results suggest that reduced protein turnover, increased duration of exposure and increased vulnerability to protein toxicity at later ages in combination could explain the late age-of-onset of neurodegenerative phenotypes.

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