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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Xi'an Jiaotong University
2020
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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. |
format | Online Article Text |
id | pubmed-7193079 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Xi'an Jiaotong University |
record_format | MEDLINE/PubMed |
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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