Lithium suppresses Aß pathology by inhibiting translation in an adult Drosophila model of Alzheimer's disease.

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 (Aß) 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 Aß42 accumulation led to increased mortality and neuronal dysfunction in the adult flies. Furthermore, we showed that lithium reduced Aß42 protein, but not mRNA, and was able to rescue Aß42-induced toxicity. In the current study, we investigated the mechanism/s by which lithium modulates Aß42 protein levels and Aß42 induced toxicity in the fly model. We found that lithium caused a reduction in protein synthesis in Drosophila and hence the level of Aß42. At both the low and high doses tested, lithium rescued the locomotory defects induced by Aß42, 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.

Ageing increases vulnerability to aß42 toxicity in Drosophila.

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 Aß42 transgene in neurons at different adult ages and measuring the effects on Aß42 levels and associated pathological phenotypes. Acute induction of Arctic Aß42 in young adult flies resulted in rapid expression and clearance of mRNA and soluble Arctic Aß42 protein, but in irreversible expression of insoluble Arctic Aß42 peptide. Arctic Aß42 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 Aß42 peptide and associated toxicity, and this correlated with an age-dependent reduction in proteasome activity. Equalising Aß42 protein at different ages shortened lifespan in correlation with the duration of exposure to the peptide, suggesting that Aß42 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 Aß42 toxicity. Indeed older flies were more vulnerable to chronic Aß42 toxicity even with a much lower lifetime exposure to the peptide. Finally, the persistence of insoluble Aß42 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.

Inhibition of GSK-3 ameliorates Abeta pathology in an adult-onset Drosophila model of Alzheimer's disease.

Abeta 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 Abeta42 specifically in adult neurons, to avoid developmental effects. Abeta42 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 Abeta42 in adult neurons increased GSK-3 activity, and inhibition of GSK-3 (either genetically or pharmacologically by lithium treatment) rescued Abeta42 toxicity. Abeta42 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 Abeta42. The GSK-3-mediated effects on Abeta42 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, Abeta42 levels were reduced upon GSK-3 inhibition, pointing to a direct role of GSK-3 in the regulation of Abeta42 peptide level, in the absence of APP processing. Our study points to the need both to identify the mechanisms by which GSK-3 modulates Abeta42 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.

Analysis of iTRAQ data using Mascot and Peaks quantification algorithms.

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.