Label-free and sensitive microRNA detection method based on the locked nucleic acid assisted fishing amplification strategy

化学 小RNA 核酸 计算生物学 纳米技术 色谱法 生物化学 基因 生物 材料科学
作者
Min-Xi Li,Yao Chen,Zeng‐Ping Chen,Ru‐Qin Yu
出处
期刊:Talanta [Elsevier]
卷期号:240: 123169-123169 被引量:2
标识
DOI:10.1016/j.talanta.2021.123169
摘要

Herein, a label free and sensitive miRNA detection method with enhanced practical applicability was developed based on the locked nucleic acid (LNA) assisted repeated fishing amplification strategy. The working mechanism of the proposed method is as follows: 1) a DNA probe (i.e, L-DNA) with LNA bases is immobilized onto the surface of a gold foil. The L-DNA hybridizes with the 3' terminus of the first strands of complementary deoxyribonucleic acid (cDNA) of the target miRNA in the test samples; 2) The protruding 5' terminus of the cDNA serves as a 'fishhook' to repeatedly fish the products of a hybridization chain reaction (HCR) out from a 'reaction tube'; 3) The HCR products can be unloaded from the gold foil into a 'product tube' through temperature-controlled dehybridization; 4) The concentration of the target miRNA is determined based on the fluorescence intensity generated by the addition of SYBR-Green I (SG) into the 'product tube'. The proposed platform was applied to the detection of miRNA-122 in cell lysate samples and obtained quantitative results with accuracy comparable to the quantitative reverse transcription PCR method (qRT-PCR). It is worth pointing out that the proposed platform achieved a limit of detection value of 2.9 fM for miRNA-122 by a simple but effective LNA-assisted repeated fishing amplification strategy instead of complicated enzyme-based amplification techniques. It is reasonable to expect that the proposed method provides a competitive alternative for designing practically applicable, cost-effective and label-free miRNA detection methods.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
SciGPT应助科研通管家采纳,获得10
刚刚
无花果应助科研通管家采纳,获得10
刚刚
积极的板栗完成签到 ,获得积分10
刚刚
咯咚完成签到 ,获得积分10
刚刚
ding应助科研通管家采纳,获得10
刚刚
CodeCraft应助科研通管家采纳,获得10
刚刚
今后应助科研通管家采纳,获得10
刚刚
研友_VZG7GZ应助科研通管家采纳,获得10
刚刚
完美世界应助科研通管家采纳,获得10
刚刚
科研通AI5应助科研通管家采纳,获得10
刚刚
maox1aoxin应助科研通管家采纳,获得30
刚刚
科研通AI5应助科研通管家采纳,获得10
刚刚
科研通AI5应助科研通管家采纳,获得10
刚刚
1秒前
领导范儿应助科研通管家采纳,获得10
1秒前
今后应助科研通管家采纳,获得10
1秒前
QXS发布了新的文献求助10
1秒前
1秒前
1秒前
1秒前
Liekkas发布了新的文献求助10
1秒前
可爱的函函应助bdvdsrwteges采纳,获得10
3秒前
木木雨发布了新的文献求助10
4秒前
鬲木发布了新的文献求助10
4秒前
mao12wang发布了新的文献求助10
4秒前
L坨坨完成签到 ,获得积分10
4秒前
耿强发布了新的文献求助10
4秒前
jmy发布了新的文献求助10
5秒前
科研小黑子完成签到,获得积分20
5秒前
5秒前
苏尔完成签到,获得积分10
5秒前
5秒前
浅墨完成签到 ,获得积分10
5秒前
mony完成签到,获得积分10
5秒前
6秒前
6秒前
huizi发布了新的文献求助10
6秒前
7秒前
菠萝冰棒发布了新的文献求助10
7秒前
7秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759