Literature DB >> 35803152

A multiplexed electrochemical quantitative polymerase chain reaction platform for single-base mutation analysis.

Yang Wang1, Hong Sun2, Gaolian Xu3, Mengdi Guan4, Qingyang Zhang5, Zhiying Wang2, Zaizai Dong2, Wenhui Chen6, Xiaoxiao Yang6, Anbang Qiao6, Yubo Fan2, Xinxia Cai7, Zhou Chen8, Lingqian Chang9, Bo Wei10.   

Abstract

Detection of single-based mutation (SbM), which is of ultra-low abundance against wild-type alleles, are typically constrained by the level of multiplexing, sensitivity for single-base resolution and quantification accuracy. In this work, an electrochemical quantitative polymerase chain reaction (E-PCR) platform was developed for multiplexed and quantitative SbM analysis in limited and precious samples with single-nucleotide discrimination. A locked nucleic acid (LNA)-mediated multiplexed PCR system in a single, closed tube setup was firstly constructed to selectively amplify the SbM genes while suppressing the wild-type alleles. The amplicons were detected simultaneously through hybridization with the sequence-specific hairpin probes anchored on a reduced graphene oxide-gold nanoparticles functionalized electrode surface. With the inclusion of an LNA-mediated PCR step upstream of the electrochemical detection, we improved the limit of detection (LOD) by 2 orders of magnitude, down to an ultralow-level of 5 copies μL-1. The platform achieved an ultra-sensitive and specific detection with 0.05% against a background of 10, 000 copies of wild-type alleles. It is highly adaptive and has the potential to enable expanded multiplexed detection in parallel, thus providing a universal tool for multiplexed SbM identification.
Copyright © 2022 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  E-PCR platform; LNA-Mediated PCR; Multiplexed detection; Single-based mutation

Mesh:

Substances:

Year:  2022        PMID: 35803152     DOI: 10.1016/j.bios.2022.114496

Source DB:  PubMed          Journal:  Biosens Bioelectron        ISSN: 0956-5663            Impact factor:   12.545


  1 in total

1.  A Neural Sensor with a Nanocomposite Interface for the Study of Spike Characteristics of Hippocampal Neurons under Learning Training.

Authors:  Shihong Xu; Yu Deng; Jinping Luo; Yaoyao Liu; Enhui He; Yan Yang; Kui Zhang; Longze Sha; Yuchun Dai; Tao Ming; Yilin Song; Luyi Jing; Chengyu Zhuang; Qi Xu; Xinxia Cai
Journal:  Biosensors (Basel)       Date:  2022-07-21
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.