The quantitative polymerase chain reaction (qPCR) is an assay of target nucleic acid concentration. Clinical applications of quantitative PCR include measurement of HIV viral load, measurement of bacterial infection, and cancer diagnosis and prognosis. Widespread usage of qPCR, however, is restricted by limited experimental throughput, assay-to-assay variability, and methods of interpreting data that are either cumbersome or lack robustness.
This thesis introduces two advances that simplify both the analysis and design of qPCR assays. The first advance, a two parameter mass action kinetic model of PCR (MAK2) was developed for fitting qPCR data in order to quantify target concentration using a single qPCR assay. MAK2-fitting was experimentally validated on three independently generated qPCR datasets and found to quantify data as accurately as the gold-standard method, quantification cycle (Cq) standard curve quantification.
The second advance presented, multiplex-MAK2 analysis of monochrome multiplex qPCR (MMQPCR) data, was developed for automated quantification of both targets in duplex qPCR assays without target-specific DNA probes. The MMQPCR assay and multiplex-MAK2-fitting were tested experimentally on a two-dimensional dilution series with known amounts of two synthetic DNA targets. Results indicate that the two-target MMQPCR assay can accurately measure both targets when the target concentration ratio is at least 10:1, and that multiplex-MAK2 quantifies data with similar accuracy to quantification by Cq standard curve. Results obtained from experimental validation using two genetic DNA targets from a microbial coculture further support these conclusions. The results of these experiments suggest that duplex qPCR assays can be performed that are as simple, inexpensive, and accurate as monoplex qPCR assays, yet provide twice as much information.
Overall, this work demonstrates the benefits of using biophysics-based qPCR methods. This thesis first provides an overview of the biophysical framework from which current qPCR methods are analyzed. Next, there is an in depth discussion of the analysis methods currently used to analyze qPCR data. The MAK2 model is then derived from first principles and experimentally validated. Multiplex-MAK2-fitting of qPCR data is described and experimentally validated. The thesis concludes with applications of the developed technologies and possible directions for further development of biophysics-based qPCR methods.Ph.D.Chemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/84653/1/gboggy_1.pd
