A Mechanistic Model of PCR for Accurate Quantification of Quantitative PCR Data

被引:77
作者
Boggy, Gregory J. [1 ]
Woolf, Peter J. [1 ]
机构
[1] Univ Michigan, Dept Chem Engn, Ann Arbor, MI 48109 USA
来源
PLOS ONE | 2010年 / 5卷 / 08期
基金
美国国家卫生研究院;
关键词
REAL-TIME PCR; POLYMERASE-CHAIN-REACTION; SIGMOIDAL MODEL;
D O I
10.1371/journal.pone.0012355
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Quantitative PCR (qPCR) is a workhorse laboratory technique for measuring the concentration of a target DNA sequence with high accuracy over a wide dynamic range. The gold standard method for estimating DNA concentrations via qPCR is quantification cycle (C-q) standard curve quantification, which requires the time-and labor-intensive construction of a C-q standard curve. In theory, the shape of a qPCR data curve can be used to directly quantify DNA concentration by fitting a model to data; however, current empirical model-based quantification methods are not as reliable as C-q standard curve quantification. Principal Findings: We have developed a two-parameter mass action kinetic model of PCR (MAK2) that can be fitted to qPCR data in order to quantify target concentration from a single qPCR assay. To compare the accuracy of MAK2-fitting to other qPCR quantification methods, we have applied quantification methods to qPCR dilution series data generated in three independent laboratories using different target sequences. Quantification accuracy was assessed by analyzing the reliability of concentration predictions for targets at known concentrations. Our results indicate that quantification by MAK2-fitting is as reliable as C-q standard curve quantification for a variety of DNA targets and a wide range of concentrations. Significance: We anticipate that MAK2 quantification will have a profound effect on the way qPCR experiments are designed and analyzed. In particular, MAK2 enables accurate quantification of portable qPCR assays with limited sample throughput, where construction of a standard curve is impractical.
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