已发表论文

基于重组酶聚合酶扩增的生物传感器用于快速筛查人畜共患疾病

 

Authors Feng X , Liu Y, Zhao Y, Sun Z, Xu N , Zhao C, Xia W

Received 2 September 2023

Accepted for publication 21 October 2023

Published 6 November 2023 Volume 2023:18 Pages 6311—6331

DOI https://doi.org/10.2147/IJN.S434197

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor R.D.K. Misra

Abstract: Recent, outbreaks of new emergency zoonotic diseases have prompted an urgent need to develop fast, accurate, and portable screening assays for pathogen infections. Recombinase polymerase amplification (RPA) is sensitive and specific and can be conducted at a constant low temperature with a short response time, making it especially suitable for on-site screening and making it a powerful tool for preventing or controlling the spread of zoonoses. This review summarizes the design principles of RPA-based biosensors as well as various signal output or readout technologies involved in fluorescence detection, lateral flow assays, enzymatic catalytic reactions, spectroscopic techniques, electrochemical techniques, chemiluminescence, nanopore sequencing technologies, microfluidic digital RPA, and clustered regularly interspaced short palindromic repeats/CRISPR-associated systems. The current status and prospects of the application of RPA-based biosensors in zoonoses screening are highlighted. RPA-based biosensors demonstrate the advantages of rapid response, easy-to-read result output, and easy implementation for on-site detection, enabling development toward greater portability, automation, and miniaturization. Although there are still problems such as high cost with unstable signal output, RPA-based biosensors are increasingly becoming one of the most important means of on-site pathogen screening in complex samples involving environmental, water, food, animal, and human samples for controlling the spread of zoonotic diseases.
Keywords: recombinase polymerase amplification, biosensor, zoonoses, rapid detection, nanomaterials