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DNA looping by protamine follows a nonuniform spatial distribution

View ORCID ProfileRyan B. McMillan, Victoria D. Kuntz, Luka M. Devenica, Hilary Bediako, View ORCID ProfileAshley R. Carter
doi: https://doi.org/10.1101/2021.01.12.426418
Ryan B. McMillan
1Department of Physics, Amherst College, Amherst, MA 01002, USA
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Victoria D. Kuntz
1Department of Physics, Amherst College, Amherst, MA 01002, USA
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Luka M. Devenica
1Department of Physics, Amherst College, Amherst, MA 01002, USA
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Hilary Bediako
1Department of Physics, Amherst College, Amherst, MA 01002, USA
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Ashley R. Carter
1Department of Physics, Amherst College, Amherst, MA 01002, USA
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  • For correspondence: acarter@amherst.edu
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ABSTRACT

DNA looping plays an important role in cells in both regulating and protecting the genome. Often, studies of looping focus on looping by prokaryotic transcription factors like lac repressor or by structural maintenance of chromosomes (SMC) proteins such as condensin. Here, however, we are interested in a different looping method whereby multivalent cations (charge≥+3), such as protamine proteins, neutralize the DNA, causing it to form loops and toroids. We considered two previously proposed mechanisms for DNA looping by protamine. In the first mechanism, protamine stabilizes spontaneous DNA fluctuations, forming randomly distributed loops along the DNA. In the second mechanism, protamine binds and bends the DNA to form a loop, creating a distribution of loops that is biased by protamine binding. To differentiate between these mechanisms, we imaged both spontaneous and protamine-induced loops on short-length (≤ 1 μm) DNA fragments using atomic force microscopy (AFM). We then compared the spatial distribution of the loops to several model distributions. A random looping model, which describes the mechanism of spontaneous DNA folding, fit the distribution of spontaneous loops, but it did not fit the distribution of protamine-induced loops. Specifically, it overestimated the number of loops that form at the ends of the molecule and failed to predict a peak in the spatial distribution of loops at an intermediate location along the DNA. An electrostatic multibinding model, which was created to mimic the bind-and-bend mechanism of protamine, was a better fit of the distribution of protamine-induced loops. In this model, multiple protamines bind to the DNA electrostatically within a particular region along the DNA to coordinate the formation of a loop. We speculate that these findings will impact our understanding of protamine’s in vivo role for looping DNA into toroids and the mechanism of DNA condensation by multivalent cations more broadly.

SIGNIFICANCE DNA looping is important in a variety of both in vivo functions (e.g. gene regulation) and in vitro applications (e.g. DNA origami). Here, we sought a mechanistic understanding of DNA looping by multivalent cations (≥+3), which condense DNA into loops and toroids. One such multivalent cation is the protein protamine, which condenses DNA in sperm. We investigated the mechanism for loop formation by protamine and found that the experimental data was consistent with an electrostatic multibinding model in which two protamines bind electrostatically to the DNA within a 50-nm region to form a loop. This model is likely general to all multivalent cations and may be helpful in applications involving toroid formation or DNA nanoengineering.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://zenodo.org/record/4321605#.X_4WHdhKg2w

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted January 13, 2021.
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DNA looping by protamine follows a nonuniform spatial distribution
Ryan B. McMillan, Victoria D. Kuntz, Luka M. Devenica, Hilary Bediako, Ashley R. Carter
bioRxiv 2021.01.12.426418; doi: https://doi.org/10.1101/2021.01.12.426418
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DNA looping by protamine follows a nonuniform spatial distribution
Ryan B. McMillan, Victoria D. Kuntz, Luka M. Devenica, Hilary Bediako, Ashley R. Carter
bioRxiv 2021.01.12.426418; doi: https://doi.org/10.1101/2021.01.12.426418

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