DOI: 10.17044/scilifelab.14815802
title: Data for ''RecA finds homologous DNA by reduced dimensionality search’

description: ### Dataset description<br>The data here is provided to support the publication 'RecA finds homologous DNA by reduced dimensionality search’. The supporting data is largely of two types: (1) Image sequences from automated widefield microscopy of live cells in a microfluidic device, and (2) STED superresolution images of fixed and immunostained cells <br><br>For automated widefield microscopy, the 'data' folder contains the raw microscopy images, together with the output from the image processing pipeline - stabilised and cropped phase channel ('PreprocessedPhase' directory) and segmentation mask done on the 'PreprocessedPhase' images ('SegmentedChannels' contains a single mask of growth channels, 'SegmentedPhase' has cell segmentation output for each frame of the 'PreprocessedPhase').<br><br>Our custom image processing pipeline referred to above is found in the folder 'image_analysis_code/ImAnalysis'.<br><br>The 'plotting_code' directory contains subdirectories with the figure number and panel. In each subdirectory there is a code used to generate the panel. To run those scripts, the paths pointing at the data in the scripts will have to be changed to match the location of the 'data' directory on the machine at which the script is executed.<br><br>The 'image_analysis_code' directory has to be added to the MATLAB path in order for the code to work.<br><br>The images and data from selected cells in each relevant experiment is stored in a .mat file with the name starting with 'Tt'. This structure can be loaded into the Matlab workspace and the images, segmentation outlines, and the DSB annotation (if relevant) can be accessed.<br><br>comments:<br>Fig. S2c script 'plot_spots_and_sace_table.m' uses 'detectSpotsSingleCell' function that relies on the path hardcoded in expInfoObj structure. The path in 'detectSpotsSingleCell' line 311 of the function will have to be modified to match the directory with the microscope images. Same for Fig. S5f, function 'detectFilamentsSingleCell' has to be modified on line 203<br><br>The code was developed and run using Matlab R2020b, python3.8.5, pytorch1.5.1, some plots require Matlab gramm library or OriginPro 2020.<br><br><br>### experiments, short descriptions, and folders structure<br>(the names of the experiments were automatically generated by the BIOVIA electronic lab notebook software)<br><br>EXP-20-BV3202 - DSB repair measurements in ParB cells<br>exp2 exp5, exp6, exp7<br><br>EXP-20-BV3206 - control - DSB repair measurements in cells without chromosomal cut-site<br>exp1, exp3 exp4<br><br>EXP-20-BV3207 - DSB repair measurements in recA-SYFP2 background<br>exp1, exp5, exp6<br><br>EXP-20-BV3209 - control - DSB repair in strain with recG and ruvC deletions<br>exp1<br><br>EXP-20-BV3210 - DSB measurements in mutants - focus on automatic spot counting<br>exp1 (wt), exp3 (recA), exp4 (recB), exp5 (wt), exp6 (recA), exp7 (recB), exp8 (wt)<br><br>EXP-20-BV3214 - DAPI staining of chromosome<br>exp7<br><br>EXP-20-BV3219 - fast (20s/frame) imaging of RecA-SYFP2 during DSB repair<br>exp3<br><br>EXP-20-BV3220 - malI experiments during DSB<br>exp2, exp3, exp4 - malO at -45 kb (yahA)<br>exp5, exp6 - malO at 170 kb (ybbD)<br>exp7, exp9 - malO at ygaY<br><br>EXP-20-BV3221 - control - measuring number of RecA filaments in cells with recB deletion (vs wt strain on the same chip)<br>exp1, exp2<br><br>EXP-20-BV3224 - control - measuring DSB repair dynamics in the RecA-alfa background<br>exp1, exp2<br><br>EXP-21-BT2884 - control - measuring DSB repair dynamics in a strain with malO-cs (instead of ParS-cs)<br>therun, exp2<br><br>EXP-21-BV3233 - control - measuring repair dynamics in a strain with pars-cs-malO<br>exp2<br>List of figures and experiments<br><br>Figure 1:<br>a - EXP-20-BV3210<br>b - n/a<br>c - EXP-20-BV3202<br>d - EXP-20-BV3202,EXP-20-BV3206,EXP-20-BV3210<br>e - EXP-20-BV3202<br>f - EXP-20-BV3202<br>g - EXP-20-BV3202<br><br>Figure 2:<br>a - EXP-20-BV3220<br>b - n/a<br>c - EXP-20-BV3220<br>d - EXP-20-BV3220<br>e - EXP-20-BV3220<br><br>Figure 3:<br>a - EXP-20-BV3207<br>b - EXP-20-BV3219<br>c - EXP-20-BV3207<br>f - EXP-20-BR5273<br>g - EXP-20-BR5273<br>h - EXP-20-BR5273<br>i - EXP-20-BR5273<br>j - EXP-20-BR5273<br><br>Figure 4:<br>a - n/a<br>b - EXP-20-BV3202, EXP-20-BV3207, EXP-20-BV3220<br><br>Figure ED1:<br>a - EXP-20-BV3210<br><br>Figure ED2:<br>a - EXP-20-BV3210<br>b - EXP-20-BV3206, EXP-20-BV3210<br>c - EXP-20-BV3210<br>d - EXP-20-BV3202<br>e - EXP-20-BV3202<br>f - EXP-20-BV3209<br><br>Figure ED3:<br>a - EXP-21-BT2884<br>b - EXP-21-BV3233<br><br>Figure ED4:<br>a - EXP-20-BV3220<br>b - EXP-20-BV3220<br>c - EXP-20-BV3220<br>d - EXP-20-BV3220<br>e - none<br><br>Figure ED5:<br>a - EXP-20-BV3207<br>b - n/a<br>c - EXP-20-BV3207<br>d - EXP-20-BV3207<br>e - EXP-20-BV3207<br>f - EXP-20-BV3221<br>g - EXP-20-BV3202, EXP-20-BV3207, EXP-20-BV3224<br>h - EXP-20-BV3207<br>i - EXP-20-BV3207<br><br>Figure ED6: <br>a - EXP-20-BR5273<br>b - n/a<br>c - EXP-20-BR5273<br>d - EXP-20-BR5273<br>e - EXP-20-BR5273<br>f - EXP-20-BR5273<br>g - EXP-20-BR5273<br>h - EXP-20-BR5273<br>i - EXP-20-BR5273<br>k - EXP-20-BR5273<br><br>Figure ED7: <br>EXP-20-BR5273<br><br>Figure ED8:<br>EXP-20-BV3214<br>