DOI: 10.5281/zenodo.10572443
title: In vivo single-molecule imaging of RecB reveals efficient repair of DNA damage in Escherichia coli

description: This is the dataset for the BioRxiv pre-print: "In vivo single-molecule imaging of RecB reveals efficient repair of DNA damage in Escherichia coli".

This article has now been published, and the accompanying data can be found on the BioImage Archive repository.

ABSTRACT: Efficient DNA repair is crucial for maintaining genome integrity and ensuring cell survival. In Escherichia coli, RecBCD plays a crucial role in processing DNA ends following a DNA double-strand break (DSB) to initiate repair by homologous recombination. While RecBCD has been extensively studied in vitro, less is known about how it contributes to rapid and efficient repair in living bacteria. Here, we perform single-molecule microscopy to investigate DNA repair in real-time in E. coli. We quantify RecB single-molecule mobility and monitor the induction of the DNA damage response (SOS response) in individual cells. We show that RecB binding to broken DNA ends leads to efficient repair without SOS induction. In contrast, in a RecB mutant with modified activities leading to the activation of an alternative repair pathway, repair is less efficient and leads to high SOS induction. Our findings reveal how subtle alterations in RecB activity profoundly impact the efficiency of DNA repair in E. coli. 

DATASET DESCRIPTION:

See README.txt file for a throughout description of the dataset. 

In summary, this dataset contains:



Fluorescence microscopy images (OME-TIFF format) - in "Images_raw" subfolders;

Manually curated cell segmentation outputs from BACMMAN* (TIFF and .db formats) -in "BACMMAN_outputs" subfolders;

Configuration files used in BACMMAN* to perform the segmentation and the measurements (JSON format) - in in "BACMMAN_outputs" subfolders;

Cell segmentation files to perform tracking in MATLAB (HDF5 format) - in "Segmentation_files" subfolders;

Derived numerical data (CSV and MATLAB formats): measurements of SOS mean intensity for each segmented bacteria, nucleoid area for each segmented bacteria,  outputs from tracking with computed Dapp values - in "Quantification_results" subfolders;

Analysis scripts for single-particle tracking in E .coli (MATLAB format) - in "Analysis_scripts-Single-particle_tracking.zip" and also available at https://gitlab.com/MEKlab/tracking-in-e.coli/ 


*BACteria in Mother Maching Analyzer (BACMMAN; https://github.com/jeanollion/bacmman)

The main dataset folders are organized by genotype name and a short description (e.g. MEK707-RecB-HaloTag_SOS) . Within the main genotype folders, there are 4 data type subfolders: "Images_raw"; "BACMMAN_outputs"; "Segmentation_files"; "Quantification_results". Within these subfolders the data is categorized using a combination of the strain name, antibiotic treatment when applicable, and the dataset number (e.g.MEK707-cipro-04-Dataset-2).

The relationship between data and publication figures can be found in the "Dataset -publication_figures_relations.txt" file and in the main README.txt. 

Licences:     The license for reuse of the dataset is CC-BY 4.0     The license for reuse of single-particle tracking in E. coli analysis scripts is MIT