title: Sequence-dependent biophysical modeling of DNA amplification.
abstract: A theoretical framework for prediction of the dynamic evolution of chemical species in DNA amplification reactions, for any specified sequence and operating conditions, is reported. Using the polymerase chain reaction (PCR) as an example, we developed a sequence- and temperature-dependent kinetic model for DNA amplification using first-principles biophysical modeling of DNA hybridization and polymerization. We compare this kinetic model with prior PCR models and discuss the features of our model that are essential for quantitative prediction of DNA amplification efficiency for arbitrary sequences and operating conditions. Using this model, the kinetics of PCR is analyzed. The ability of the model to distinguish between the dynamic evolution of distinct DNA sequences in DNA amplification reactions is demonstrated. The kinetic model is solved for a typical PCR temperature protocol to motivate the need for optimization of the dynamic operating conditions of DNA amplification reactions. It is shown that amplification efficiency is affected by dynamic processes that are not accurately represented in the simplified models of DNA amplification that form the basis of conventional temperature cycling protocols. Based on this analysis, a modified temperature protocol that improves PCR efficiency is suggested. Use of this sequence-dependent kinetic model in a control theoretic framework to determine the optimal dynamic operating conditions of DNA amplification reactions, for any specified amplification objective, is discussed.
authors.affiliation: Department of Chemical Engineering and Center for Advanced Process Decision-making, Carnegie Mellon University, Pittsburgh, Pennsylvania.
authors.forename: Karthikeyan
authors.initials: K
authors.lastname: Marimuthu
authors.affiliation: Division of Fundamental Research, PMC Advanced Technology, Mt. Laurel, New Jersey.
authors.forename: Chaoran
authors.initials: C
authors.lastname: Jing
authors.affiliation: Department of Chemical Engineering and Center for Advanced Process Decision-making, Carnegie Mellon University, Pittsburgh, Pennsylvania; Division of Fundamental Research, PMC Advanced Technology, Mt. Laurel, New Jersey. Electronic address: raj@pmc-group.com.
authors.forename: Raj
authors.initials: R
authors.lastname: Chakrabarti
mesh_terms: D001483:Base Sequence; D004247:DNA / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D004254:DNA Nucleotidyltransferases / Q000378:metabolism; D007700:Kinetics; D008954:Models, Biological; D009693:Nucleic Acid Hybridization; D016133:Polymerase Chain Reaction; D013696:Temperature
chemical_list: D004247:DNA; D004254:DNA Nucleotidyltransferases