by Keyword: Precursor protein
Molina-Fernandez, R, Picon-Pages, P, Barranco-Almohalla, A, Crepin, G, Herrera-Fernandez, V, Garcia-Elias, A, Fanlo-Ucar, H, Fernandez-Busquets, X, Garcia-Ojalvo, J, Oliva, B, Munoz, FJ, (2022). Differential regulation of insulin signalling by monomeric and oligomeric amyloid beta-peptide Brain Commun 4, fcac243
Alzheimer's disease and Type 2 diabetes are pathological processes associated to ageing. Moreover, there are evidences supporting a mechanistic link between Alzheimer's disease and insulin resistance (one of the first hallmarks of Type 2 diabetes). Regarding Alzheimer's disease, amyloid beta-peptide aggregation into beta-sheets is the main hallmark of Alzheimer's disease. At monomeric state, amyloid beta-peptide is not toxic but its function in brain, if any, is unknown. Here we show, by in silico study, that monomeric amyloid beta-peptide 1-40 shares the tertiary structure with insulin and is thereby able to bind and activate insulin receptor. We validated this prediction experimentally by treating human neuroblastoma cells with increasing concentrations of monomeric amyloid. beta-peptide 1-40. Our results confirm that monomeric amyloid beta-peptide 1-40 activates insulin receptor autophosphorylation, triggering downstream enzyme phosphorylarions and the glucose Transporter 4 translocation to the membrane. On the other hand, neuronal insulin resistance is known to be associated to Alzheimer's disease since early stages. We thus modelled the docking of oligomeric amyloid peptide 1-40 to insulin receptor. We found that oligomeric amyloid. beta-peptide 1-40 blocks insulin receptor, impairing its activation. It was confirmed in vitro by observing the lack of insulin receptor autophosphorylation, and also the impairment of insulin-induced intracellular enzyme activations and the glucose Transporter 4 translocation to the membrane. By biological system analysis, we have carried out a mathematical model recapitulating the process that turns amyloid beta-peptide binding to insulin receptor from the physiological to the pathophysiological regime. Our results suggest that monomeric amyloid beta-peptide 1-40 contributes to mimic insulin effects in the brain, which could be good when neurons have an extra requirement of energy beside the well-known protective effects on insulin intracellular signalling, while its accumulation and subsequent oligomerization blocks the insulin receptor producing insulin resistance and compromising neuronal metabolism and protective pathways.
JTD Keywords: A-beta, Aggregation, Akt, Alzheimer's disease, Alzheimers-disease, Amyloid beta-peptide, Brain, Design, Insulin, Insulin resistance, Precursor protein, Protein-protein docking, Receptor, Resistance, Site
Seuma, M, Faure, AJ, Badia, M, Lehner, B, Bolognesi, B, (2021). The genetic landscape for amyloid beta fibril nucleation accurately discriminates familial Alzheimer's disease mutations Elife 10, e63364
Plaques of the amyloid beta (A beta) peptide are a pathological hallmark of Alzheimer's disease (AD), the most common form of dementia. Mutations in A beta also cause familial forms of AD (fAD). Here, we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of A beta. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in A beta, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in A beta.
JTD Keywords: aggregation, kinetics, oligomers, onset, rates, state, Aggregation, Alzheimer's, Amyloid, Computational biology, Deep mutagenesis, Genetics, Genomics, Kinetics, Nucleation, Oligomers, Onset, Precursor protein, Rates, S. cerevisiae, State, Systems biology