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FluoSurf neat 表面活性剂用于微滴数字PCR的应用介绍彩页

PCR技术已成为多个科学领域的基石,推动了诊断学、法医学、农业和生物技术等领域的重大进步。

微滴数字PCR(Droplet Digital PCR,简称ddPCR)是一种基于水-油乳液体系的数字PCR方法,其中反应单元是分散在油相中的微小水滴。样品被分割成数千至数百万个纳升(nL)级别的微滴,PCR反应在每个微滴内进行,其过程与在试管或微孔板中进行的反应完全相同。该技术的核心在于样品被高度分割,且这些分割单元的体积极小。ddPCR方法包含四个连续的步骤:

1、微滴生成:将DNA(或RNA)样品与PCR试剂(包括引物和荧光探针)混合后,利用微流控技术和专用表面活性剂,将混合物分割成数千至数百万个纳升级别的“油包水”微滴。

2、PCR扩增:每个微滴独立进行PCR扩增,相当于一个个微型试管。

3、微滴读取:扩增完成后,使用微滴读取仪对每个微滴进行逐一分析。通过测量每个微滴中的荧光信号,判断其中是否存在目标DNA(即“阳性”或“阴性”)。

4、数据分析:根据阳性微滴与阴性微滴的比例,利用泊松统计学(Poisson statistics)计算出原始样品中目标DNA的绝对含量。

这种样品分割方式实现了高精度和高灵敏度,能够对目标生物标志物进行极其精确的定量分析,使ddPCR成为稀有突变检测、基因表达分析以及拷贝数变异研究等应用领域的理想选择。

微滴数字PCR的介绍和应用的彩页,请点击 Here 下载。

PCR technology has become a cornerstone in various scientific fields, enabling significant advancements in diagnostics, forensics, agriculture, and biotechnology.

Droplet digital PCR, or ddPCR, is a digital PCR method implying a water-oil emulsion, where the partitions are tiny aqueous droplets dispersed in oil. The sample is divided into thousands to millions nanoliter-sized droplets and PCR reaction occurs inside each droplet exactly like in test tubes or microwells. Key aspects of this technique lie in the fact that the sample undergoes a massive partitioning, and in the very small size of these partitions. ddPCR method involves 4 different and consecutive steps:

1、Droplet generation: Once the DNA (or RNA) sample has been mixed with the PCR reagents, including primers and fluorescent probes, the mixture is divided into thousands to millions nanoliter sized water-in-oil droplets using microfluidics and specialized surfactants.

2、PCR amplification: Each droplet undergoes PCR amplification independently, essentially becoming a mini test tube.

3、Droplet reading: After amplification, droplets are analyzed one-by-one using a droplet reader. Fluorescence in each droplet is measured to determine if target DNA is present (positive) or absent (negative).

4、Data analysis: The ratio of positive to negative droplets is used to calculate the absolute quantity of target DNA in the original sample using Poisson statistics.

This partitioning of the sample allows for high precision and sensitivity, allowing the highly accurate quantification of biomarkers of interest and making ddPCR ideal for applications such as rare mutation detection, gene expression analysis, and copy number variation studies.

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