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通过扩增效率依赖的 PCR 对核酸进行准确估计。

Accurate estimation of nucleic acids by amplification efficiency dependent PCR.

机构信息

Molecular Biology Section, AstraZeneca India Private Limited, Bangalore, Karnataka, India.

出版信息

PLoS One. 2012;7(8):e42063. doi: 10.1371/journal.pone.0042063. Epub 2012 Aug 17.

DOI:10.1371/journal.pone.0042063
PMID:22912684
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3422235/
Abstract

Accurate estimation of template--DNA or RNA by real time PCR is dependent on the amplification efficiency (F) of the reaction. The analytical equation describing the kinetics of PCR that is influenced by template re-annealing is formulated. It predicts the gradual reduction of F--from its initial value of 2, leading to template saturation. From an experimental standpoint, due to the exponential nature of the reaction a minute change in F can lead to a large error in the estimation of the initial template concentration. On the basis of individual variation in the amplification efficiency we have formulated a simple mathematical model and an MS Excel based data analysis software that allows accurate and automated quantification of initial template concentration. This method which does not require any normalisation with housekeeping genes was validated by transcript profiling of the genes in the TCA/glyoxylate cycle of E. coli. Consistent with published reports, we observed a precise and specific induction of the glyoxylate shunt genes when the bacteria was shifted from a six carbon glucose media to a two carbon source like acetate.

摘要

实时 PCR 中准确估计模板(DNA 或 RNA)取决于反应的扩增效率(F)。本文构建了一个描述受模板复性影响的 PCR 动力学的分析方程。该方程预测了 F 的逐渐降低——从其初始值 2 降低,导致模板饱和。从实验角度来看,由于反应的指数性质,F 的微小变化可能导致初始模板浓度估计的较大误差。基于扩增效率的个体差异,我们构建了一个简单的数学模型和一个基于 MS Excel 的数据分析软件,该软件允许对初始模板浓度进行准确和自动的定量。该方法不需要用管家基因进行任何归一化,通过大肠杆菌 TCA/乙醛酸循环基因的转录谱进行了验证。与已发表的报告一致,当细菌从六碳葡萄糖培养基转移到二碳源(如乙酸盐)时,我们观察到乙醛酸支路基因的精确和特异性诱导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/cd67b8503d8a/pone.0042063.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/a3c3426872bf/pone.0042063.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/00a300ca50db/pone.0042063.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/bed46624b5a7/pone.0042063.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/45f91e659e9b/pone.0042063.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/b52530733752/pone.0042063.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/cd67b8503d8a/pone.0042063.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/a3c3426872bf/pone.0042063.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/00a300ca50db/pone.0042063.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/bed46624b5a7/pone.0042063.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/45f91e659e9b/pone.0042063.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/b52530733752/pone.0042063.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3319/3422235/cd67b8503d8a/pone.0042063.g006.jpg

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