(574a) Quantitative CFD-Enabled Analysis of DNA Fluorescence within a Convective PCR System Toward Fast and Simultaneous PCR and Melting Curve Analysis

Melting curve analysis (MCA) is a well-established fluorescence-based assessment of the DNA double helix state as a function of temperature. MCA is typically performed after polymerase chain reaction (PCR) amplification, where sequence-specific melting curves facilitate DNA identification in biomedical applications. Conventional systems lack thermal control ease and the capability to perform simultaneous PCR and MCA, thereby failing to deliver fast analysis and cost-effectiveness. In this regard, establishing Rayleigh–Bénard convection inside a cylindrical PCR chamber, known as isothermal convective PCR (cPCR), eliminates the need for hold times at each reaction step in conventional PCR. We have previously shown that a cylindrical cPCR chamber (8 mm height and 1.38 mm diameter) with fixed temperatures at top (~58 °C) and bottom (~96 °C) is highly repeatable in PCR assays relevant to pathogen detection and diagnostics. To further investigate, in this study, we aim to develop fast, cost-effective, and simultaneous PCR and MCA within cPCR systems for the first time. These are critical features that were desperately needed during the COVID-19 pandemic, where the turnaround for PCR tests was up to a few days. To achieve this goal, we need to investigate the fluorescence signal generated by intercalating dyes inserted into double-stranded DNA (dsDNA) within a cPCR chamber. In this matter, DNA helicity and concentration emerge as key parameters whose spatial distribution and interplay determine the resulting fluorescence in cPCR. However, the complex and nonsymmetric fluorescence distribution around the cylindrical chamber makes it challenging to experimentally retrieve precise information for MCA without any prior knowledge and understanding of its behavior.

Herein, we present a quantitative analysis of DNA fluorescence within a cPCR system using computational fluid dynamics (CFD) simulations (STAR-CCM+). First, the temperature and concentration distributions of the DNA species within the cPCR chamber are retrieved from the CFD simulation. Second, the DNA helicity of a specific DNA sequence is determined for each temperature using the web-based application uMelt. Hence, a 3D helicity-concentration distribution fingerprint can be obtained, which we convert to a performance index (PI) parameter representing the normalized expected fluorescence. This PI distribution offers more detailed information than a conventional melting curve, and it can be further evaluated to identify optimal regions to reliably obtain sequence-specific DNA meting curve profiles (MCPs) along the height of the chamber and from different viewing angles. The ability to retrieve such sequence-specific MCPs in cPCR is assessed considering the PCR analysis of different variants of a pathogen, such as Delta and Omicron in COVID-19. The preliminary numerical results demonstrate that the peak in the profiles (derivative of PI with respect to the height of the chamber) for the Delta and Omicron variants occur at heights of 0.57 mm and 0.41 mm from the bottom of the chamber, respectively, which indicates around 160 μm difference between the peaks. Their separation is sufficient enough to distinguish the behavior of the variants based on the resolution of our optical system, which is around 10 μm/pixel. Incorporating insights and results from this simulation study and the corresponding cPCR experiments will not only facilitate the validation of our computational approach, but it will further help us develop the required experimental methods to retrieve the desired MCPs. This will enable the fast and reliable execution of simultaneous PCR and MCA in cPCR systems, where unique fluorescence signatures retrieved during PCR facilitate determining the success of the reaction. Furthermore, these advances could potentially remove the requirement of post-processing and analysis steps, such as gel electrophoresis or traditional MCA, to confirm the identity of the PCR reaction products, leading to cheaper and more versatile PCR.