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Quantitative Modeling of Nucleosome Unwrapping from Both Ends.

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In eukaryotic cells, DNA is packaged into chromatin where nucleosomes are the basic packaging unit. Important cellular processes including gene expression, DNA replication, and DNA repair require nucleosomal DNA to… Click to show full abstract

In eukaryotic cells, DNA is packaged into chromatin where nucleosomes are the basic packaging unit. Important cellular processes including gene expression, DNA replication, and DNA repair require nucleosomal DNA to be unwrapped so that functional proteins can access their target sites, which otherwise are sterically occluded. A key question in this process is what the unwrapped conformations individual nucleosomes adopt within chromatin are. Here, we develop a concurrent nucleosome unwrapping model to address this question. We hypothesize that for a given end-to-end distance of the nucleosomal DNA, the nucleosomal DNA stochastically unwraps from the histone core from both ends independently and that this combination of unwrapping from both sides results in a significant increase in the average distance between the DNA extending from both sides of the nucleosomes. We test our model on recently published experiments using a DNA origami nanocaliper that quantifies nucleosome unwrapping and achieve good agreement between experiment and model prediction. We then investigate the DNA origami caliper distribution when attached to a hexasome (a nucleosome lacking an H2A/H2B dimer). A significant shift in the caliper angle distribution caused by the asymmetric structural features of the hexasome seen experimentally is consistent with the model. Our modeling approach may be more broadly useful to the interpretation of other studies of nucleosome dynamics, chromatin dynamics, and regulatory processes involving nucleosome unwrapping, as well as more generally to optimization of future DNA origami designs to probe mechanical properties of biomolecules.

Keywords: dna; nucleosome unwrapping; nucleosomal dna; dna origami; model; quantitative modeling

Journal Title: Biophysical journal
Year Published: 2019

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