An empirical approach to target DNA quantification in environmental samples using real-time polymerase chain reactions

Recent advances in molecular techniques have allowed for the routine examination of nucleic acids in environmental samples. Although current methodologies are very sensitive, accurate target DNA quantification from environmental samples remains challenging. To facilitate high-throughput DNA quantification from environmental samples, we developed a novel DNA quantification method based on a non-linear curve-fitting approach to extract additional information from quantitative PCR amplification curves and used the fitted parameters to develop multiple regression standard equations for target DNA quantification. A 3-parameter sigmoidal function performed superior to a 4-parameter Weibull function for generating the multiple regression standard equations. In a verification experiment, target DNA was quantified in a series of ‘unknown’ samples in three soils using this approach and the results were compared to target DNA values determined using corrected and uncorrected Ct-based (threshold cycle) methods. For each method, the deviations from the expected target DNA content were determined. Results clearly showed that over all DNA concentrations, target DNA content determined by the non-linear curve-fitting method was more accurate and more precise than values predicted by all other methods. Analysis of variance conducted on the predicted DNA contents also revealed fewer statistical artifacts with the non-linear curve fitting method compared to the conventional Ct-based methods. The novel approach described here is accurate, inexpensive, and very amenable for automation and high-throughput applications.