Article open access publication

Stochastic unfolding of nanoconfined DNA: Experiments, model and Bayesian analysis.

The Journal of Chemical Physics, AIP Publishing, ISSN 0021-9606

Volume 149, 21, 2018

DOI:10.1063/1.5051319, Dimensions: pub.1110383991, PMID: 30525714,



  1. (1) University of Southern Denmark, grid.10825.3e, SDU
  2. (2) Chalmers University of Technology, grid.5371.0
  3. (3) University of Gothenburg, grid.8761.8
  4. (4) Lund University, grid.4514.4







Nanochannels provide a means for detailed experiments on the effect of confinement on biomacromolecules, such as DNA. Here we introduce a model for the complete unfolding of DNA from the circular to linear configuration. Two main ingredients are the entropic unfolding force and 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. We provide publically available software for performing the required image and Bayesian analysis.

Research Categories

Links & Metrics

NORA University Profiles

University of Southern Denmark

Danish Open Access Indicator

2018: Realized

Research area: Science & Technology

Danish Bibliometrics Indicator

2018: Level 2

Research area: Science & Technology

Dimensions Citation Indicators

Times Cited: 4

Relative Citation ratio (RCR): 0.83

Open Access Info

Green, Submitted