Abstract

The eukaryotic single-stranded DNA (ssDNA)-binding protein Replication Protein A (RPA) plays a crucial role in various DNA metabolic pathways, including DNA replication and repair, by dynamically associating with ssDNA. While the binding of a single RPA molecule to ssDNA has been thoroughly studied, the accessibility of ssDNA is largely governed by the bimolecular behavior of RPA, the biophysical nature of which remains unclear. In this study, we develop a three-step low-complexity ssDNA Curtains method, which, when combined with biochemical assays and a Markov chain model in non-equilibrium physics, allow us to decipher the dynamics of multiple RPA binding to long ssDNA. Interestingly, our results suggest that Rad52, the mediator protein, can modulate the ssDNA accessibility of Rad51, which is nucleated on RPA coated ssDNA through dynamic ssDNA exposure between neighboring RPA molecules. We find that this process is controlled by the shifting between the protection mode and action mode of RPA ssDNA binding, where tighter RPA spacing and lower ssDNA accessibility are favored under RPA protection mode, which can be facilitated by the Rfa2 WH domain and inhibited by Rad52 RPA interaction.

Here the authors study RPA, a key component in DNA replication and repair using single molecule DNA Curtains and Markov chain modelling. They reveal that the bimolecular nature of RPA dynamics on ssDNA is tuned by the Rad52 mediator to assist the loading of the Rad51 recombinase.

Details

Title
ssDNA accessibility of Rad51 is regulated by orchestrating multiple RPA dynamics
Author
Ding, Jiawei 1 ; Li, Xiangting 2   VIAFID ORCID Logo  ; Shen, Jiangchuan 3   VIAFID ORCID Logo  ; Zhao, Yiling 4 ; Zhong, Shuchen 5 ; Lai, Luhua 6   VIAFID ORCID Logo  ; Niu, Hengyao 3   VIAFID ORCID Logo  ; Qi, Zhi 1   VIAFID ORCID Logo 

 Peking University, Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 University of California, Department of Computational Medicine, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718) 
 Indiana University, Department of Molecular and Cellular Biochemistry, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X) 
 Peking University, Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University Health Science Center, Institute of Systems Biomedicine, School of Basic Medical Sciences, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 Peking University, BNLMS, College of Chemistry and Molecular Engineering, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 Peking University, Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, BNLMS, College of Chemistry and Molecular Engineering, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
Pages
3864
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2831683240
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.