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United States Department of Agriculture

Agricultural Research Service

Research Project: MICROBIAL COMMUNITIES AND INTERACTIONS AND THEIR IMPACT ON FOOD SAFETY

Location: Molecular Characterization of Foodborne Pathogens

Title: A method for correcting standard-based real-time PCR DNA quantitation when the standard's polymerase reaction efficiency is significantly different from that of the unknown's

Authors
item Irwin, Peter
item Nguyen, Ly Huong
item Chen, Chin-Yi
item Uhlich, Gaylen
item Paoli, George

Submitted to: Analytical and Bioanalytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 11, 2012
Publication Date: February 12, 2012
Citation: Irwin, P.L., Nguyen, L.T., Chen, C., Uhlich, G.A., Paoli, G. 2012. A method for correcting standard-based real-time PCR DNA quantitation when the standard's polymerase reaction efficiency is significantly different from that of the unknown's. Analytical and Bioanalytical Chemistry. 402:2713-2725.

Interpretive Summary: Bacteria exist in complex microbial communities. Some microorganisms in these communities form complex structures or biofilms. When pathogens reside within these biological structures their detection can be masked. Part of our research project is to characterize the physical characteristics of such biological constructions from the standpoint of cell number. One method for doing this is to count the occurrence of certain genetic components, which are proportional to the number of cells present in a cell extract using quantitative, or real time, polymerase chain reaction (qPCR), which is an analytical method used to determine the number of copies of any particular gene per volume tested. To perform these analyses, DNA standards (various concentrations of known gene copy number) are measured and utilized to convert raw qPCR data associated with unknown test samples into concentration terms. However, the determination of a test sample’s DNA concentration assumes that the concentration dependence of the standard and unknown reactions are equivalent. Frequently, this criterion is not met. In this work we develop a simple mathematical method to generate an adjusted standard curve with a slope (change in PCR response with Log[dilution factor]) based upon at least three dilutions of the unknown test DNA solution and an intercept calculated from one-to-several of the standard DNA concentrations from which an ideal intercept is calculated. With this technique one should be able to determine the concentration of any DNA extract regardless of differences between unknowns and standards.

Technical Abstract: Standard-based real-time, or quantitative, polymerase chain reaction (qPCR) quantitation of an unknown sample’s DNA concentration (i.e., [DNA]-unk) assumes that the concentration dependence of the standard and unknown reactions (related to reaction efficiency, E) are equivalent. In our work with background food-borne organisms, which can interfere with pathogen detection, we have found that it is generally possible to achieve an acceptable E (= 1 ± 0.1) for standard solutions by optimizing the PCR conditions, primer sequence, template purity and amplicon lengths. However, this is frequently not true for the solutions containing unknown amounts of target DNA inasmuch as cell extracts are more chemically complex than the standards, which have been amplified 1E9- to 1E12-fold, as well as undergone a purification step. When significant differences in polymerase E occur, it is not possible to accurately estimate unknown target DNA concentration from the standard solution’s slope and intercept (from PCR response, or Ct, versus Log[DNA] data). What is needed is a standard-mediated intercept, which can be specifically coupled with an unknown solution’s PCR concentration dependence. In this work we develop a simple algorithm to generate a new standard curve with a slope (change in Ct with Log[Dilution]) based upon at least three dilutions of the unknown target DNA solution and an intercept calculated from one to several of the standard DNA concentrations. We were able to achieve this due to the predictable way in which observed and ideal Ct versus Log[DNA] slopes and intercepts deviate from one another.

Last Modified: 10/30/2014
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