Abstract
Efforts to study the polymer physics of DNA confined in nanochannels have been stymied by a lack of consensus regarding its wall depletion length. We have measured this quantity in 38 nm wide, square silicon dioxide nanochannels for five different ionic strengths between 15 mM and 75 mM. Experiments used the Bionano Genomics Irys platform for massively parallel data acquisition, attenuating the effect of the sequence-dependent persistence length and finite-length effects by using nick-labeled E. coli genomic DNA with contour length separations of at least 30 µm (88 325 base pairs) between nick pairs. Over 5 × 106 measurements of the fractional extension were obtained from 39 291 labeled DNA molecules. Analyzing the stretching via Odijk’s theory for a strongly confined wormlike chain yielded a linear relationship between the depletion length and the Debye length. This simple linear fit to the experimental data exhibits the same qualitative trend as previously defined analytical models for the depletion length but now quantitatively captures the experimental data.
Original language | English (US) |
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Article number | 104901 |
Journal | Journal of Chemical Physics |
Volume | 149 |
Issue number | 10 |
DOIs | |
State | Published - Sep 14 2018 |
Bibliographical note
Funding Information:This work was supported by the National Institutes of Health (No. NIH R01-HG006851). Computational resources were provided in part by the Minnesota Supercomputing Institute. J.G.R. and H.C. are employees of Bionano Genomics, which is commercializing nanochannel genome mapping
Funding Information:
This work was supported by the National Institutes of Health (No. NIH R01-HG006851). Computational resources were provided in part by the Minnesota Supercomputing Institute. J.G.R. and H.C. are employees of Bionano Genomics, which is commercializing nanochannel genome mapping.
Publisher Copyright:
© 2018 Author(s).
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Measuring the wall depletion length of nanoconfined DNA (2018)
Bhandari, A. B., Reifenberger, J. G., Chuang, H.-M., Cao, H. & Dorfman, K., Data Repository for the University of Minnesota, 2018
DOI: 10.13020/D6QM51, http://hdl.handle.net/11299/200094
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