Suppr超能文献

用于无标记伏安法检测MS2噬菌体的多孔硅膜修饰电极。

Porous silicon membrane-modified electrodes for label-free voltammetric detection of MS2 bacteriophage.

作者信息

Reta Nekane, Michelmore Andrew, Saint Christopher, Prieto-Simón Beatriz, Voelcker Nicolas H

机构信息

Future Industries Institute, Mawson Lakes, South Australia 5095, Australia.

Future Industries Institute, Mawson Lakes, South Australia 5095, Australia; School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, South Australia 5095, Australia.

出版信息

Biosens Bioelectron. 2016 Jun 15;80:47-53. doi: 10.1016/j.bios.2016.01.038. Epub 2016 Jan 14.

Abstract

A proof of concept for the label-free detection of bacteriophage MS2, a model indicator of microbiological contamination, is validated in this work as a porous silicon (pSi) membrane-based electrochemical biosensor. PSi membranes were used to afford nanochannel architectures. The sensing mechanism was based on the nanochannel blockage caused by MS2 binding to immobilized capture antibodies. This blockage was quantified by measuring the oxidation current of the electroactive species reaching the electrode surface, by means of differential pulse voltammetry (DPV). The immunosensor showed a limit of detection of 6 pfu/mL in buffer, allowing the detection of MS2 to levels commonly found in real-world applications, and proved to be unaffected by matrix effects when analyzing MS2 in reservoir water. This platform enables the straightforward, direct and sensitive detection of a broad range of target analytes and constitutes a promising approach towards the development of portable electronic point of sample analysis devices.

摘要

作为一种基于多孔硅(pSi)膜的电化学生物传感器,本文验证了用于无标记检测噬菌体MS2(一种微生物污染的模型指示物)的概念验证。使用pSi膜构建纳米通道结构。传感机制基于MS2与固定化捕获抗体结合导致的纳米通道堵塞。通过差分脉冲伏安法(DPV)测量到达电极表面的电活性物质的氧化电流,对这种堵塞进行定量。该免疫传感器在缓冲液中的检测限为6 pfu/mL,能够检测到实际应用中常见水平的MS2,并且在分析水库水中的MS2时不受基质效应的影响。该平台能够直接、灵敏地检测多种目标分析物,是开发便携式电子样本分析设备的一种有前景的方法。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验