摘要
单通道电生理检测方法是目前研究蛋白纳米孔传输性质的一种有效手段,但该方法需要将待检测的纳米孔分子加入水溶液中,对于一些难以制备的微量样品很难高效快速地获得实验结果。针对上述问题,本研究对现有单通道电生理检测系统与方法进行改进,通过减小实验体系体积来增加纳米孔分子浓度,将蛋白纳米孔α-溶血素(α-hemolysin)进入脂质膜的几率提高了500倍,从而有效增加了纳米孔通道信号被检测到的可能性,提高了单通道电生理检测方法的实验效率与检测灵敏度。并进一步利用纳米孔α-溶血素对微量T7 DNA进行实时监测,证实了改造后的系统在微量DNA分子检测中的可靠性,为使用纳米孔对难以获得的珍稀微量样品的检测提供了技术基础。
Single-channel electrophysiology is a state-of-the-art method to effectively study quantitative properties of protein nanopores. However, this method requires the addition of the nanopore molecule into the aqueous solution before the required experimental signals can be detected. Thus, it is challenging to obtain results efficiently for some trace samples that are difficult to be prepared in solution. The work aimed to resolve these aforementioned problems and provide improved schemes for the existing single-channel electrophysiological detection system. By reducing the volume of the experimental system and increasing the concentration of nanopore molecules, the insertion probability of nanopore molecules into the lipid membrane significantly increased by 500-fold. Hence,our methods effectively enhanced the detection probability of the pore channel signals as well as the efficiency and sensitivity of single-channel electrophysiological detection. Furthermore, the study applied the modified system for real-time monitoring of trace T7 DNA, confirming the reliability of the modified system in the detection of trace DNA molecules, which set up a technical foundation for the application of nanopores in sensing rare, trace, or less accessible samples.
作者
于晗
刘美君
费帆
沈轶
Daniel M Czajkowsky
Yu Han;Liu Meijun;Fei Fan;Shen Yi;Daniel M Czajkowsky(School of Biomedical Engineering,Shanghai Jiaotong University,Shanghai,200240)
出处
《基因组学与应用生物学》
CAS
CSCD
北大核心
2021年第1期442-447,共6页
Genomics and Applied Biology
基金
国家自然科学基金(31670722,81627801)
上海市科学技术委员会项目(17JC1400804,18142202100)
中国科学院微观界面物理与探测重点实验室项目(CASKL-IPT1702)共同资助。
关键词
蛋白纳米孔
单通道电生理检测
微量生物样品检测
Protein nanopores
Single-channel electrophysiological detection
Trace biological sample detection
作者简介
通信作者:Daniel M Czajkowsky,dczaj@sjtu.edu.cn。
