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用于直接检测循环微小RNA的蛋白质电催化

Protein electrocatalysis for direct sensing of circulating microRNAs.

作者信息

Labib Mahmoud, Khan Nasrin, Berezovski Maxim V

机构信息

Department of Chemistry, University of Ottawa , 10 Marie Curie, Ottawa, Ontario K1N 6N5, Canada.

出版信息

Anal Chem. 2015 Jan 20;87(2):1395-403. doi: 10.1021/ac504331c. Epub 2014 Dec 26.

Abstract

MicroRNAs (miRNAs) are potentially useful biomarkers for diagnosis, classification, and prognosis of many diseases, including cancer. Herein, we developed a protein-facilitated electrocatalytic quadroprobe sensor (Sens(PEQ)) for detection of miRNA signature of chronic lymphocytic leukemia (CLL) in human serum. The developed signal-ON sensor provides a compatible combination of two DNA adaptor strands modified with four methylene blue molecules and electrocatalysis using glucose oxidase in order to enhance the overall signal gain. This enhanced sensitivity provided the response necessary to detect the low-abundant serum miRNAs without preamplification. The developed Sens(PEQ) is exquisitely sensitive to subtle π-stack perturbations and capable of distinguishing single base mismatches in the target miRNA. Furthermore, the developed sensor was employed for profiling of three endogenous miRNAs characteristic to CLL, including hsa-miR-16-5p, hsa-miR-21-5p, and hsa-miR-150-5p in normal healthy serum, chronic lymphocytic leukemia Rai stage 1 (CLL-1), and stage 3 (CLL-3) sera, using a non-human cel-miR-39-3p as an internal standard. The sensor results were verified by conventional SYBR green-based quantitative reverse-transcription polymerase chain reaction (RT-qPCR) analysis.

摘要

微小RNA(miRNA)是包括癌症在内的多种疾病诊断、分类和预后的潜在有用生物标志物。在此,我们开发了一种蛋白质辅助电催化四探针传感器(Sens(PEQ)),用于检测人血清中慢性淋巴细胞白血病(CLL)的miRNA特征。所开发的信号开启型传感器将两条用四个亚甲蓝分子修饰的DNA衔接链与使用葡萄糖氧化酶的电催化作用进行了兼容组合,以增强整体信号增益。这种增强的灵敏度提供了在无需预扩增的情况下检测低丰度血清miRNA所需的响应。所开发的Sens(PEQ)对细微的π-堆积扰动极其敏感,并且能够区分靶标miRNA中的单碱基错配。此外,所开发的传感器用于分析CLL特有的三种内源性miRNA,包括正常健康血清、慢性淋巴细胞白血病Rai 1期(CLL-1)和3期(CLL-3)血清中的hsa-miR-16-5p、hsa-miR-21-5p和hsa-miR-150-5p,使用非人类的cel-miR-39-3p作为内标。传感器结果通过传统的基于SYBR Green的定量逆转录聚合酶链反应(RT-qPCR)分析进行了验证。

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