Identification and Quantification of Extracellular Vesicles: Comparison of SDS-PAGE Analysis and Biosensor Analysis with QCM and IDT Chips

Biosensors Pub Date : 2024-07-27 DOI:10.3390/bios14080366
Yaw-Jen Chang, Wen-Tung Yang, Cheng-Hsuan Lei
{"title":"Identification and Quantification of Extracellular Vesicles: Comparison of SDS-PAGE Analysis and Biosensor Analysis with QCM and IDT Chips","authors":"Yaw-Jen Chang, Wen-Tung Yang, Cheng-Hsuan Lei","doi":"10.3390/bios14080366","DOIUrl":null,"url":null,"abstract":"This study presents and compares two methods for identifying the types of extracellular vesicles (EVs) from different cell lines. Through SDS-PAGE analysis, we discovered that the ratio of CD63 to CD81 in different EVs is consistent and distinct, making it a reliable characteristic for recognizing EVs secreted by cancer cells. However, the electrophoresis and imaging processes may introduce errors in the concentration values, especially at lower concentrations, rendering this method potentially less effective. An alternative approach involves the use of quartz crystal microbalance (QCM) and electroanalytical interdigitated electrode (IDT) biosensors for EV type identification and quantification. The QCM frequency shift caused by EVs is directly proportional to their concentration, while electroanalysis relies on measuring the curvature of the I−V curve as a distinguishing feature, which is also proportional to EV concentration. Linear regression lines for the QCM frequency shift and the electroanalysis curvature of various EV types are plotted separately, enabling the estimation of the corresponding concentration for an unknown EV type on the graphs. By intersecting the results from both biosensors, the unknown EV type can be identified. The biosensor analysis method proves to be an effective means of analyzing both the type and concentration of EVs from different cell lines.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"74 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosensors","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.3390/bios14080366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This study presents and compares two methods for identifying the types of extracellular vesicles (EVs) from different cell lines. Through SDS-PAGE analysis, we discovered that the ratio of CD63 to CD81 in different EVs is consistent and distinct, making it a reliable characteristic for recognizing EVs secreted by cancer cells. However, the electrophoresis and imaging processes may introduce errors in the concentration values, especially at lower concentrations, rendering this method potentially less effective. An alternative approach involves the use of quartz crystal microbalance (QCM) and electroanalytical interdigitated electrode (IDT) biosensors for EV type identification and quantification. The QCM frequency shift caused by EVs is directly proportional to their concentration, while electroanalysis relies on measuring the curvature of the I−V curve as a distinguishing feature, which is also proportional to EV concentration. Linear regression lines for the QCM frequency shift and the electroanalysis curvature of various EV types are plotted separately, enabling the estimation of the corresponding concentration for an unknown EV type on the graphs. By intersecting the results from both biosensors, the unknown EV type can be identified. The biosensor analysis method proves to be an effective means of analyzing both the type and concentration of EVs from different cell lines.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
细胞外囊泡的鉴定和定量:SDS-PAGE 分析与 QCM 和 IDT 芯片生物传感器分析的比较
本研究介绍并比较了两种识别不同细胞系细胞外囊泡 (EV) 类型的方法。通过 SDS-PAGE 分析,我们发现不同 EVs 中 CD63 与 CD81 的比例是一致且不同的,这使其成为识别癌细胞分泌的 EVs 的可靠特征。不过,电泳和成像过程可能会导致浓度值出现误差,尤其是在浓度较低的情况下,因此这种方法可能不太有效。另一种方法是使用石英晶体微天平(QCM)和电分析电极间(IDT)生物传感器来识别和量化 EV 类型。由 EV 引起的 QCM 频率偏移与 EV 浓度成正比,而电分析则依靠测量 I-V 曲线的曲率作为鉴别特征,该曲率也与 EV 浓度成正比。QCM 频率偏移和各种 EV 类型的电分析曲率的线性回归线分别绘制,这样就能在图形上估算出未知 EV 类型的相应浓度。将两个生物传感器的结果相交,就能确定未知的电动汽车类型。事实证明,生物传感器分析方法是分析来自不同细胞系的 EV 类型和浓度的有效手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Electrochemical Impedance Spectroscopy-Based Microfluidic Biosensor Using Cell-Imprinted Polymers for Bacteria Detection Ultrasensitive Electrochemical Biosensors Based on Allosteric Transcription Factors (aTFs) for Pb2+ Detection Salmonella Detection in Food Using a HEK-hTLR5 Reporter Cell-Based Sensor Paper-Based Microfluidic Device for Extracellular Lactate Detection Recent Electrochemical Advancements for Liquid-Biopsy Nucleic Acid Detection for Point-of-Care Prostate Cancer Diagnostics and Prognostics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1