Blocking uncertain mispriming errors of PCR

Abstract

The polymerase chain reaction (PCR) plays a central role in genetic engineering and is routinely used in various applications, from biological and medical research to the diagnosis of viral infections. PCR is an extremely sensitive method for detecting target DNA sequences, but it is substantially error-prone. In particular, the mishybridization of primers to contaminating sequences can result in false positives for virus tests. The blocker method, also called the clamping method, has been developed to suppress mishybridization errors. However, its application is limited by the requirement that the contaminating template sequence must be known in advance. Here, we demonstrate that a mixture of multiple blocker sequences effectively suppresses the amplification of contaminating sequences even in the presence of uncertainty. The blocking effect was characterized by a simple model validated by experiments. Furthermore, the modeling allowed us to minimize the errors by optimizing the blocker concentrations. The results highlighted an inherent robustness of the blocker method, in that fine-tuning of the blocker concentrations is not necessary. Our method extends the applicability of PCR and other hybridization-based techniques, including genome editing, RNA interference, and DNA nanotechnology, by improving their fidelity. SignificanceThe applications of PCR are increasing day by day, and there is a need to suppress PCR errors to improve the accuracy of PCR-based techniques and broaden their applicability. The blocker method has been developed to substantially suppress mispriming. However, the method requires prior knowledge of the contaminating sequence, which limits its applicability. We successfully demonstrate that adding a combination of multiple blocker sequences can substantially suppress PCR errors, even when we have only partial information about the contaminating sequences. We also construct a biophysical model of the blocking effect, which allows us to find the optimal blocker combinations that minimize the PCR error. Since the method targets hybridization, it is readily applicable to a wide range of biotechnologies.