Development of the Droplet Digital PCR Method for the Detection and Quantification of Erwinia pyrifoliae.

IF 1.8 3区 农林科学 Q2 PLANT SCIENCES
Lin He, Seong Hwan Kim, Jun Myoung Yu
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引用次数: 0

Abstract

Black shoot blight disease caused by Erwinia pyrifoliae has serious impacts on quality and yield in pear production in Korea; therefore, rapid and accurate methods for its detection are needed. However, traditional detection methods require a great deal of time and fail to achieve absolute quantification. In the present study, we developed a droplet digital polymerase chain reaction (ddPCR) method for the detection and absolute quantification of E. pyrifoliae using a pair of species-specific primers. The detection range was 103 - 107 copies/ml (DNA templates) and cfu/ml (cell culture templates). This new method exhibited good linearity and repeatability and was validated by absolute quantification of E. pyrifoliae DNA copies from samples of artificially inoculated immature pear fruits. Here, we present the first study of ddPCR assay for the detection and quantification of E. pyrifoliae. This method has potential applications in epidemiology and for the early prediction of black shoot blight outbreaks.

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液滴数字PCR检测与定量方法的建立。
梨黑梢疫病严重影响韩国梨的品质和产量。因此,需要快速准确的检测方法。然而,传统的检测方法需要耗费大量的时间,且无法做到绝对定量。在本研究中,我们建立了一种液滴数字聚合酶链反应(ddPCR)方法,利用一对物种特异性引物检测和绝对定量pyrifoliae。检测范围为103 ~ 107拷贝/ml (DNA模板)和cfu/ml(细胞培养模板)。该方法具有良好的线性和重复性,并通过对人工接种的梨幼果样品进行绝对定量验证。在这里,我们提出了第一个ddPCR检测和定量的研究。该方法在流行病学和疫病的早期预测中具有潜在的应用价值。
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来源期刊
Plant Pathology Journal
Plant Pathology Journal 生物-植物科学
CiteScore
4.90
自引率
4.30%
发文量
71
审稿时长
12 months
期刊介绍: Information not localized
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