Improving the Characterization of Two-State DNA Transition Rates through a Frequency Response-based Analysis

Abstract

Characterizing DNA transition rates is essential in multiple domains, including molecular diagnostics and biotechnology. This study employs a custom-built measuring setup, based on periodic temperature perturbation, to determine these kinetics. However, such measurements are inherently noisy and labor-intensive, necessitating the development of a robust method to ensure accurate and reliable extraction of kinetic parameters from non-ideal data. Therefore, this thesis presents an automated, computational framework, using Fourier transforms and first-order system identification, to process raw datasets and determine values and uncertainties of the DNA’s kinetic parameters. By integrating a multitemperature design, the kinetic data were used to derive key thermodynamic parameters and to validate findings against theoretical models. Furthermore, current measurement procedures were analyzed and signal-to-noise limitations were identified, along with strategies for their mitigation. Results confirm a linear relationship between DNA concentration and the inverse of its relaxation rate (1/τ). This relationship contains a clear temperature dependence, observed as an up-shift in the equilibrium profile. From this relationship, the transition rates of the DNA molecule were extracted, with the off-rates (koff) showing a greater temperature dependence than the on-rates (kon): 160% versus 9.3% increase over a 3°C increment. This framework is not limited to DNA research and can be generalized to other two-state systems