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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
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author Hu, Jiaojiao
Sun, Huiyong
Hao, Haiping
Zheng, Qiuling
author_facet Hu, Jiaojiao
Sun, Huiyong
Hao, Haiping
Zheng, Qiuling
author_sort Hu, Jiaojiao
collection PubMed
description 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.
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spelling pubmed-71930792020-05-05 Prediction of fibril formation by early-stage amyloid peptide aggregation Hu, Jiaojiao Sun, Huiyong Hao, Haiping Zheng, Qiuling J Pharm Anal Short Communication 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. Xi'an Jiaotong University 2020-04 2019-12-13 /pmc/articles/PMC7193079/ /pubmed/32373391 http://dx.doi.org/10.1016/j.jpha.2019.12.002 Text en © 2019 Xi'an Jiaotong University. Production and hosting by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Short Communication
Hu, Jiaojiao
Sun, Huiyong
Hao, Haiping
Zheng, Qiuling
Prediction of fibril formation by early-stage amyloid peptide aggregation
title Prediction of fibril formation by early-stage amyloid peptide aggregation
title_full Prediction of fibril formation by early-stage amyloid peptide aggregation
title_fullStr Prediction of fibril formation by early-stage amyloid peptide aggregation
title_full_unstemmed Prediction of fibril formation by early-stage amyloid peptide aggregation
title_short Prediction of fibril formation by early-stage amyloid peptide aggregation
title_sort prediction of fibril formation by early-stage amyloid peptide aggregation
topic Short Communication
url 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
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