Stochastic nucleosome disassembly mediated by remodelers and histone fragmentation

ORAL

Abstract

Nucleosome disassembly is a critical process during DNA replication and transcription. We construct and analyze monomeric and multimeric models of the stochastic disassembly of a single nucleosome. Our monomeric, model predicts the time needed for a number of histone-DNA contacts to spontaneously break, leading to dissociation of a non-fragmented histone from DNA. The dissociation process can be facilitated by DNA binding proteins or processing molecular motors that compete for contact sites. Eigenvalue analysis of the corresponding master equation allows us to evaluate histone detachment times under both spontaneous detachment and protein-facilitated processes. We find that competitive DNA binding of remodeling proteins can significantly reduce the typical detachment time but only if these remodelers have DNA-binding affinities comparable to those of histone-DNA contact sites. In the presence of processive motors, the histone detachment rate is shown to be proportional to the product of the histone single-bond dissociation constant and the speed of motor protein procession. Our simple intact-histone model is then extended to allow for multimeric nucleosome kinetics that reveal additional pathways of disassembly. In addition to a dependence of complete disassembly times on subunit-DNA contact energies, we show how histone subunit concentrations in bulk solution can mediate the disassembly process by rescuing partially disassembled nucleosomes. Moreover, our kinetic model predicts that remodeler binding can also bias certain pathways of nucleosome disassembly, with higher remodeler binding rates favoring intact-histone detachment.

* The authors acknowledge support from the Army Research Office through grant W911NF-18-1-0345 and the National Institutes of Health through grant R01HL146552.

Publication: preprint by the same title at arXiv:2309.02736 [q-bio.BM]

Presenters

  • Xiangting Li

    University of California, Los Angeles

Authors

  • Xiangting Li

    University of California, Los Angeles

  • Tom Chou

    University of California, Los Angeles