AEM Accepts, published online ahead of print on 18 April 2008

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Appl. Environ. Microbiol. doi:10.1128/AEM.02743-07
Copyright (c) 2008, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

Development and experimental validation of a predictive threshold cycle (Ct) equation for quantification of virulence and marker genes using high-throughput nanoliter PCR on OpenArrays^TM

Robert D. Stedtfeld, Samuel W. Baushke, Dieter M. Tourlousse, Sarah M. Miller, Tiffany M. Stedtfeld, Erdogan Gulari, James M. Tiedje, and Syed A. Hashsham^*

Department of Civil and Environmental Engineering, Center for Microbial Ecology, Department of Crop and Soil Science, Michigan State University, East Lansing, MI-48824; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI-48109

^* To whom correspondence should be addressed. Email: Hashsham{at}egr.msu.edu.

Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (Ct) equation was developed to calculate starting copies based on experimental Ct. The empirical equation was developed with SYBR Green detection in nanoliter QPCR chambers (OpenArray^TM) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R² = 0.816) was observed between predicted and experimental Ct based on the organism's genome size, GC content, amplicon length, and stability of primer 3' end. The performance of the predictive Ct equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, primer success rate was dependent on GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive Ct equation is expected to reduce the extent of validation necessary when developing QPCR arrays for a large number of pathogens or other targets.