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Three-dimensional structure of the lithostathine protofibril, a protein involved in Alzheimer's disease.

ABSTRACT: Neurodegenerative diseases are characterized by the presence of filamentous aggregates of proteins. We previously established that lithostathine is a protein overexpressed in the pre-clinical stages of Alzheimer's disease. Furthermore, it is present in the pathognomonic lesions associated with Alzheimer's disease. After self-proteolysis, the N-terminally truncated form of lithostathine leads to the formation of fibrillar aggregates. Here we observed using atomic force microscopy that these aggregates consisted of a network of protofibrils, each of which had a twisted appearance. Electron microscopy and image analysis showed that this twisted protofibril has a quadruple helical structure. Three-dimensional X-ray structural data and the results of biochemical experiments showed that when forming a protofibril, lithostathine was first assembled via lateral hydrophobic interactions into a tetramer. Each tetramer then linked up with another tetramer as the result of longitudinal electrostatic interactions. All these results were used to build a structural model for the lithostathine protofibril called the quadruple-helical filament (QHF-litho). In conclusion, lithostathine strongly resembles the prion protein in its dramatic proteolysis and amyloid proteins in its ability to form fibrils.

SUBMITTER: Gregoire C

PROVIDER: S-EPMC125531 | biostudies-literature | 2001 Jul

REPOSITORIES: biostudies-literature

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Three-dimensional structure of the lithostathine protofibril, a protein involved in Alzheimer's disease.

Grégoire C C Marco S S Thimonier J J Duplan L L Laurine E E Chauvin J P JP Michel B B Peyrot V V Verdier J M JM

The EMBO journal 20010701 13

Neurodegenerative diseases are characterized by the presence of filamentous aggregates of proteins. We previously established that lithostathine is a protein overexpressed in the pre-clinical stages of Alzheimer's disease. Furthermore, it is present in the pathognomonic lesions associated with Alzheimer's disease. After self-proteolysis, the N-terminally truncated form of lithostathine leads to the formation of fibrillar aggregates. Here we observed using atomic force microscopy that these aggre ...[more]

PMID: 11432819

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Project description:Single Nucleotide Polymorphisms (SNPs) are an important source of human genome variability. Non-synonymous SNPs occurring in coding regions result in single amino acid polymorphisms (SAPs) that may affect protein function and lead to pathology. Several methods attempt to estimate the impact of SAPs using different sources of information. Although sequence-based predictors have shown good performance, the quality of these predictions can be further improved by introducing new features derived from three-dimensional protein structures.In this paper, we present a structure-based machine learning approach for predicting disease-related SAPs. We have trained a Support Vector Machine (SVM) on a set of 3,342 disease-related mutations and 1,644 neutral polymorphisms from 784 protein chains. We use SVM input features derived from the protein's sequence, structure, and function. After dataset balancing, the structure-based method (SVM-3D) reaches an overall accuracy of 85%, a correlation coefficient of 0.70, and an area under the receiving operating characteristic curve (AUC) of 0.92. When compared with a similar sequence-based predictor, SVM-3D results in an increase of the overall accuracy and AUC by 3%, and correlation coefficient by 0.06. The robustness of this improvement has been tested on different datasets and in all the cases SVM-3D performs better than previously developed methods even when compared with PolyPhen2, which explicitly considers in input protein structure information.This work demonstrates that structural information can increase the accuracy of disease-related SAPs identification. Our results also quantify the magnitude of improvement on a large dataset. This improvement is in agreement with previously observed results, where structure information enhanced the prediction of protein stability changes upon mutation. Although the structural information contained in the Protein Data Bank is limiting the application and the performance of our structure-based method, we expect that SVM-3D will result in higher accuracy when more structural date become available.

Project description:Alzheimer's disease is the most common form of dementia, characterized by two pathological hallmarks: amyloid-β plaques and neurofibrillary tangles. The amyloid hypothesis of Alzheimer's disease posits that the excessive accumulation of amyloid-β peptide leads to neurofibrillary tangles composed of aggregated hyperphosphorylated tau. However, to date, no single disease model has serially linked these two pathological events using human neuronal cells. Mouse models with familial Alzheimer's disease (FAD) mutations exhibit amyloid-β-induced synaptic and memory deficits but they do not fully recapitulate other key pathological events of Alzheimer's disease, including distinct neurofibrillary tangle pathology. Human neurons derived from Alzheimer's disease patients have shown elevated levels of toxic amyloid-β species and phosphorylated tau but did not demonstrate amyloid-β plaques or neurofibrillary tangles. Here we report that FAD mutations in β-amyloid precursor protein and presenilin 1 are able to induce robust extracellular deposition of amyloid-β, including amyloid-β plaques, in a human neural stem-cell-derived three-dimensional (3D) culture system. More importantly, the 3D-differentiated neuronal cells expressing FAD mutations exhibited high levels of detergent-resistant, silver-positive aggregates of phosphorylated tau in the soma and neurites, as well as filamentous tau, as detected by immunoelectron microscopy. Inhibition of amyloid-β generation with β- or γ-secretase inhibitors not only decreased amyloid-β pathology, but also attenuated tauopathy. We also found that glycogen synthase kinase 3 (GSK3) regulated amyloid-β-mediated tau phosphorylation. We have successfully recapitulated amyloid-β and tau pathology in a single 3D human neural cell culture system. Our unique strategy for recapitulating Alzheimer's disease pathology in a 3D neural cell culture model should also serve to facilitate the development of more precise human neural cell models of other neurodegenerative disorders.

Dataset Information

Three-dimensional structure of the lithostathine protofibril, a protein involved in Alzheimer's disease.

Publications

Three-dimensional structure of the lithostathine protofibril, a protein involved in Alzheimer's disease.

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