Single-Molecule Dynamics and Localization of DNA Repair Proteins in Cells

Insights into the control of RAD51 nucleoprotein filament dynamics from single-molecule studies

Genomic integrity depends on the RecA/RAD51 protein family. Discovered over five decades ago with the founder bacterial RecA protein, eukaryotic RAD51 is an ATP-dependent DNA strand transferase implicated in DNA double-strand break and single-strand gap repair, and in dealing with stressed DNA replication forks. RAD51 assembles as a nucleoprotein filament around single-stranded DNA to promote homology recognition in a duplex DNA and subsequent strand exchange. While the intrinsic dynamics of the RAD51 nucleoprotein filament has been extensively studied, a plethora of accessory factors control its dynamics. Understanding how modulators control filament dynamics is at the heart of current research efforts. Here, we describe recent advances in RAD51 control mechanisms obtained specifically using fluorescence-based single-molecule techniques.

Elucidating Recombination Mediator Function Using Biophysical Tools

Simple Summary

This review recapitulates the initial knowledge acquired with genetics and biochemical experiments on Recombination mediator proteins in different domains of life. We further address how recent in vivo and in vitro biophysical tools were critical to deepen the understanding of RMPs molecular mechanisms in DNA and replication repair, and unveiled unexpected features. For instance, in bacteria, genetic and biochemical studies suggest a close proximity and coordination of action of the RecF, RecR and RecO proteins in order to ensure their RMP function, which is to overcome the single-strand binding protein (SSB) and facilitate the loading of the recombinase RecA onto ssDNA. In contrary to this expectation, using single-molecule fluorescent imaging in living cells, we showed recently that RecO and RecF do not colocalize and moreover harbor different spatiotemporal behavior relative to the replication machinery, suggesting distinct functions. Finally, we address how new biophysics tools could be used to answer outstanding questions about RMP function.

Abstract

The recombination mediator proteins (RMPs) are ubiquitous and play a crucial role in genome stability. RMPs facilitate the loading of recombinases like RecA onto single-stranded (ss) DNA coated by single-strand binding proteins like SSB. Despite sharing a common function, RMPs are the products of a convergent evolution and differ in (1) structure, (2) interaction partners and (3) molecular mechanisms. The RMP function is usually realized by a single protein in bacteriophages and eukaryotes, respectively UvsY or Orf, and RAD52 or BRCA2, while in bacteria three proteins RecF, RecO and RecR act cooperatively to displace SSB and load RecA onto a ssDNA region. Proteins working alongside to the RMPs in homologous recombination and DNA repair notably belongs to the RAD52 epistasis group in eukaryote and the RecF epistasis group in bacteria. Although RMPs have been studied for several decades, molecular mechanisms at the single-cell level are still not fully understood. Here, we summarize the current knowledge acquired on RMPs and review the crucial role of biophysical tools to investigate molecular mechanisms at the single-cell level in the physiological context.

Particle Mobility Analysis Using Deep Learning and the Moment Scaling Spectrum

Quantitative analysis of dynamic processes in living cells using time-lapse microscopy requires not only accurate tracking of every particle in the images, but also reliable extraction of biologically relevant parameters from the resulting trajectories. Whereas many methods exist to perform the tracking task, there is still a lack of robust solutions for subsequent parameter extraction and analysis. Here a novel method is presented to address this need. It uses for the first time a deep learning approach to segment single particle trajectories into consistent tracklets (trajectory segments that exhibit one type of motion) and then performs moment scaling spectrum analysis of the tracklets to estimate the number of mobility classes and their associated parameters, providing rich fundamental knowledge about the behavior of the particles under study. Experiments on in-house datasets as well as publicly available particle tracking data for a wide range of proteins with different dynamic behavior demonstrate the broad applicability of the method.