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Prediction of fibril formation by early-stage amyloid peptide aggregation

Amyloid fibrils are found in systemic amyloidosis diseases such as Alzheimer’s disease, Parkinson’s disease, and type II diabetes. Currently, these diseases are diagnosed by observation of fibrils or plaques, which is an ineffective method for early diagnosis and treatment of disease. The goal of th...

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Detalles Bibliográficos
Autores principales: Hu, Jiaojiao, Sun, Huiyong, Hao, Haiping, Zheng, Qiuling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Xi'an Jiaotong University 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193079/
https://www.ncbi.nlm.nih.gov/pubmed/32373391
http://dx.doi.org/10.1016/j.jpha.2019.12.002
Descripción
Sumario:Amyloid fibrils are found in systemic amyloidosis diseases such as Alzheimer’s disease, Parkinson’s disease, and type II diabetes. Currently, these diseases are diagnosed by observation of fibrils or plaques, which is an ineffective method for early diagnosis and treatment of disease. The goal of this study was to develop a simple and quick method to predict the possibility and speed of fibril formation before its occurrence. Oligomers generated from seven representative peptide segments were first isolated and detected by ion-mobility mass spectrometry (IM-MS). Then, their assemblies were disrupted using formic acid (FA). Interestingly, oligomers that showed small ion intensity changes upon FA addition had rapid fibril formation. By contrast, oligomers that had large ion intensity changes generated fibrils slowly. Two control peptides (aggregation/no fibrils and no aggregation/no fibrils) did not show changes in their ion intensities, which confirmed the ability of this method to predict amyloid formation. In summary, the developed method correlated MS intensity ratio changes of peptide oligomers on FA addition with their amyloid propensities. This method will be useful for monitoring peptide/protein aggregation behavior and essential for their mechanism studies.