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通过数字高分辨率熔解提高数字PCR的定量能力。

Improving Quantitative Power in Digital PCR through Digital High-Resolution Melting.

作者信息

Aralar April, Yuan Yixu, Chen Kevin, Geng Yunshu, Ortiz Velez Daniel, Sinha Mridu, Lawrence Shelley M, Fraley Stephanie I

机构信息

Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.

Department of Pediatrics, Division of Neonatal-Perinatal Medicine, University of California, San Diego, La Jolla, California, USA.

出版信息

J Clin Microbiol. 2020 May 26;58(6). doi: 10.1128/JCM.00325-20.

Abstract

Applying digital PCR (dPCR) technology to challenging clinical and industrial detection tasks has become more prevalent because of its capability for absolute quantification and rare target detection. However, practices learned from quantitative PCR (qPCR) that promote assay robustness and wide-ranging utility are not readily applied in dPCR. These include internal amplification controls to account for false-negative reactions and amplicon high-resolution melt (HRM) analysis to distinguish true positives from false positives. Incorporation of internal amplification controls in dPCR is challenging because of the limited fluorescence channels available on most machines, and the application of HRM analysis is hindered by the separation of heating and imaging functions on most dPCR systems. We use a custom digital HRM platform to assess the utility of HRM-based approaches for mitigation of false positives and false negatives in dPCR. We show that detection of an exogenous internal control using dHRM analysis reduces the inclusion of false-negative partitions, changing the calculated DNA concentration up to 52%. The integration of dHRM analysis enables classification of partitions that would otherwise be considered ambiguous "rain," which accounts for up to ∼3% and ∼10% of partitions in intercalating dye and hydrolysis probe dPCR, respectively. We focused on developing an internal control method that would be compatible with broad-based microbial detection in dPCR-dHRM. Our approach can be applied to a number of DNA detection methods including microbial profiling and may advance the utility of dPCR in clinical applications where accurate quantification is imperative.

摘要

由于数字PCR(dPCR)技术具有绝对定量和检测稀有靶标的能力,将其应用于具有挑战性的临床和工业检测任务变得越来越普遍。然而,从定量PCR(qPCR)中学到的提高检测稳健性和广泛实用性的方法在dPCR中并不容易应用。这些方法包括用于解释假阴性反应的内部扩增对照,以及用于区分真阳性和假阳性的扩增子高分辨率熔解(HRM)分析。在dPCR中加入内部扩增对照具有挑战性,因为大多数仪器上可用的荧光通道有限,并且大多数dPCR系统上加热和成像功能的分离阻碍了HRM分析的应用。我们使用定制的数字HRM平台来评估基于HRM的方法在减轻dPCR中的假阳性和假阴性方面的实用性。我们表明,使用dHRM分析检测外源性内部控制可减少假阴性分区的纳入,使计算出的DNA浓度变化高达52%。dHRM分析的整合能够对否则会被视为模糊“雨”的分区进行分类,在嵌入染料和水解探针dPCR中,这分别占分区的约3%和约10%。我们专注于开发一种与dPCR-dHRM中广泛的微生物检测兼容的内部控制方法。我们的方法可以应用于包括微生物分析在内的多种DNA检测方法,并可能提高dPCR在需要准确定量的临床应用中的实用性。

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