Stochastic unfolding of nanoconfined DNA: experiments, model and Bayesian analysis

TL;DR

This paper presents a comprehensive model and Bayesian analysis of DNA unfolding in nanochannels, enabling the extraction of physical parameters like unfolding force and friction coefficient from experimental data.

Contribution

It introduces a novel model for DNA unfolding that incorporates entropic forces and friction, combined with Bayesian inference to quantify physical parameters from experiments.

Findings

Unfolding force agrees with Flory theory estimates.

Friction coefficient matches theoretical predictions for cylindrical motion.

Validated friction estimates using DNA center-of-mass motion.

Abstract

Nanochannels provide means for detailed experiments on the effect of confinement on biomacromolecules, such as DNA. We here introduce a model for the complete unfolding of DNA from the circular to linear configuration. Two main ingredients are the entropic unfolding force as well as the friction coefficient for the unfolding process, and we describe the associated dynamics by a non-linear Langevin equation. By analyzing experimental data where DNA molecules are photo-cut and unfolded inside a nanochannel, our model allows us to extract values for the unfolding force as well as the friction coefficient for the first time. In order to extract numerical values for these physical quantities, we employ a recently introduced Bayesian inference framework. We find that the determined unfolding force is in agreement with estimates from a simple Flory type argument. The estimated friction coefficient is in agreement with theoretical estimates for motion of a cylinder in a channel. We further validate the estimated friction constant by extracting this parameter from DNA's center-of-mass motion before and after unfolding, yielding decent agreement.