DOI: 10.5061/dryad.jsxksn0g5
title: Dynamic 1D search and processive nucleosome translocations by RSC and ISW2 chromatin remodelers

description: Eukaryotic gene expression is linked to chromatin structure and nucleosome
 positioning by ATP-dependent chromatin remodelers that establish and
 maintain nucleosome-depleted regions (NDRs) near transcription
 start-sites. Conserved yeast RSC and ISW2 remodelers exert antagonistic
 effects on nucleosomes flanking NDRs, but the temporal dynamics of
 remodeler search, engagement and directional nucleosome mobilization for
 promoter accessibility are unknown. Using optical tweezers and 2-color
 single-particle imaging, we investigated the Brownian diffusion of RSC and
 ISW2 on free DNA and sparse nucleosome arrays. RSC and ISW2 rapidly scan
 DNA by one-dimensional hopping and sliding respectively, with dynamic
 collisions between remodelers followed by recoil or apparent co-diffusion.
 Static nucleosomes block remodeler diffusion resulting in remodeler recoil
 or sequestration. Remarkably, both RSC and ISW2 use ATP hydrolysis to
 translocate mono-nucleosomes processively at ~30 bp/sec for surprising
 distances on extended linear DNA. Processivity and opposing push-pull
 directionalities of nucleosome translocation shown by RSC and ISW2 shape
 the distinctive landscape of promoter chromatin.
description: Raw data of single molecule diffusion
 on naked DNA or on nucleosome arrays was collected on DNA stretched using
 dual optical tweezers and imaged for fluorescence using point scanning
 confocal microscopy. Initial raw data is in the form of an h5 file, which
 contains correlated metadata. However, due to the very large initial file
 sizes, we have chosen to upload images of kymographs (as tiff files) used
 for single particle tracking along with the respective single particle
 trajectories for both the red and green channel (as csv files).
 Frame-rates and pixel sizes are the same for all kymographs (0.0424 s and
 0.1 mm
 respectively). Single particle tracking was performed using LUMICKS Pylake
 Kymotracker as described in the methods section of our associated
 manuscript. Analysis of the
 resulting single particle trajectories (csv files) can be performed as
 follows, using the provided Matlab source code. The result of this
 analysis are parameter files for each single particle trajectory detected
 within each kymograph. These parameter files contain amongst other
 parameters the generalized diffusion coefficient. Further processing of
 these files produces summary files for each condition: “DValuesList.csv”:
 mean diffusion coefficient values per diffusive class [i.e. non-diffusive,
 low-diffusion, high-diffusion], “DwellTimeList.csv”: list of dwell-times
 in a diffusive state after transitioning into that diffusive class,
 “Parameter_Summary.csv”: relevant parameters used for the analysis [i.e.
 frame-rate, rolling-window size, threshold values differentiating
 diffusive classes], and “StatePercentagesPerTrajectory.csv”: percentage of
 time spent in a given diffusive class per trajectory. 1.     Run
 “c01_smoothKymo.m” and select the folder containing the csv files (this
 needs to be done twice in the case of two-color channels, once for the
 data in the red channel and once for the data in the green channel). This
 step smooths the tracking data, which will be the input for subsequent
 analysis. 2.     Run the
 rolling-window analysis.  This must be run once for data in the red
 channel and a second time for data in the green channel.  Rather than
 selecting the folder of interest as was done in step 1, this step was
 designed to feed in all data folders for a given remodeler. Select the
 folder containing all data folders. These sub-data folders must have
 “_csvfiles” at the end of the folder name to be detected for batch
 processing. a.    
 For data in the red color channel: run
 “c02_1_noPlot_Rollingwindow_CalculateParameters_Plot_AllCSV_VER2.m” b.     For data in the green color channel: run “c02_2_ALT_noPlot_Rollingwindow_Nucleosomes.m” 3.     Finally, in the same was a was done in step 2, run: “c03noplotCompute_DStates_fromcsv_NakedDNA_stringentsliceminimum.m” to create summary information for the condition of interest. Functions used in this analysis are provided in the source code folder. When running the scripts, please select change folder so that the functions can be found. Note: @msdanalyzer was used for calculating diffusion coefficients. This Matlab package needs to be downloaded and added to the same folder as the functions provided in order to run. Nadine Tarantino, Jean-Yves Tinevez, Elizabeth Faris Crowell, Bertrand Boisson, Ricardo Henriques, Musa Mhlanga, Fabrice Agou, Alain Israël, and Emmanuel Laplantine. TNF and IL-1 exhibit distinct ubiquitin requirements for inducing NEMO-IKK supramolecular structures. J Cell Biol (2014) vol. 204 (2) pp. 231-45 An example of the complete analysis is provided for the following data set: nucleosome array  ISW2  ATP  20211117_example_csvfiles The resulting analysis is added as subfolders of the respective color channels, with each subsequent analysis creating a new subfolder.
description: Matlab (2021 or newer)
description: # Dynamic 1D Search and Processive Nucleosome Translocations by RSC and
 ISW2 Chromatin Remodelers'a0 Raw data of single molecule diffusion on
 naked DNA or on nucleosome arrays was collected on DNA stretched using
 dual optical tweezers and imaged for fluorescence using point scanning
 confocal microscopy. Initial raw data is in the form of an h5 file, which
 contains correlated metadata. However, due to the very large initial file
 sizes, we have chosen to upload images of kymographs (as tiff files) used
 for single particle tracking along with the respective single particle
 trajectories for both the red and green channel (as csv files).
 Frame-rates and pixel sizes are the same for all kymographs (0.0424 s and
 0.1 um respectively). Single particle tracking was performed using LUMICKS
 Pylake Kymotracker as described in the methods section of our associated
 manuscript. The uploaded data can be found in three parts as zip files:
 (1) naked DNA data: remodeler diffusion on naked lambda DNA (2) nucleosome
 array data: remodeler diffusion on nucleosome arrays (3)
 remodeler-remodeler data: diffusion of remodelers labeled in red and green
 diffusing on the same naked lambda DNA The csv files uploaded contain the
 following data as comma delimited columns (all in column 1 of the csv
 file): (1)Line index (this is the trajectory number) (2)Time (pixels): to
 convert to seconds 1 pixel = 0.0424 s (3)Coordinate (pixels): to convert
 to distance 1 pixel = 0.1 um (4)Time (s) (5)Position (um) (6)Counts
 (summed over 7 pixels): intensity of the molecule Tiff files can be used
 as they are or can be converted to jpeg using software such as FIJI ##
 Folders/Subfolders Main Folders: "naked DNA", "nucleosome
 array", "remodeler-remodeler". Each main folder name
 describes the experimental conditions that help identify the contained
 data with the section of the manuscript where the data is used. For
 example: all diffusion data of single remodelers collected on naked DNA is
 in the "naked DNA folder". For single remodelers on the
 nucleosome array, data is in the "nucleosome array" folder. For
 data of two remodelers on the same piece of naked DNA, the data is in the
 folder "remodeler-remodeler". Subfolders: Given the description
 of the contents of the main folders, the user will be able to understand
 which data is contained in the subfolders by the description included in
 the name of the subfolder. For example, in the "naked DNA" main
 folder, the subfolder "ISW2_1mMATP" includes data of ISW2
 diffusion in the presence of 1mM ATP. In the case of the "nucleosome
 array" main folder, the subfolder "ISW2" with subfolder
 "ATP" includes data on ISW2 diffusion in the presence of ATP on
 the nucleosome array. In the case of the "remodeler-remodeler"
 main folder, the subfolder "RSC-ISW2" includes data of where RSC
 and ISW2 are labeled in different colors and are diffusing on the same
 piece of DNA. ## Code/Software Source codes are written in Matlab Analysis
 of the resulting single particle trajectories (csv files) can be performed
 as follows, using the provided Matlab source code. The result of this
 analysis are parameter files for each single particle trajectory detected
 within each kymograph. These parameter files contain amongst other
 parameters the generalized diffusion coefficient. Further processing of
 these files produces summary files for each condition:
 '93DValuesList.csv'94: mean diffusion coefficient values per
 diffusive class [i.e. non-diffusive, low-diffusion, high-diffusion],
 '93DwellTimeList.csv'94: list of dwell-times in a diffusive
 state after transitioning into that diffusive class,
 '93Parameter_Summary.csv'94: relevant parameters used for the
 analysis [i.e. frame-rate, rolling-window size, threshold values
 differentiating diffusive classes], and
 '93StatePercentagesPerTrajectory.csv'94: percentage of time
 spent in a given diffusive class per trajectory. Run
 '93c01_smoothKymo.m'94 and select the folder containing the csv
 files (this needs to be done twice in the case of two-color channels, once
 for the data in the red channel and once for the data in the green
 channel). This step smooths the tracking data, which will be the input for
 subsequent analysis. 2.'a0'a0'a0'a0 Run the
 rolling-window analysis.'a0 This must be run once for data in the red
 channel and a second time for data in the green channel.'a0 Rather
 than selecting the folder of interest as was done in step 1, this step was
 designed to feed in all data folders for a given remodeler. Select the
 folder containing all data folders. These sub-data folders must have
 '93_csvfiles'94 at the end of the folder name to be detected for
 batch processing. a.'a0'a0'a0'a0 For data in the red
 color channel: run
 '93c02_1_noPlot_Rollingwindow_CalculateParameters_Plot_AllCSV_VER2.m'94 b.'a0'a0'a0'a0 For data in the green color channel: run '93c02_2_ALT_noPlot_Rollingwindow_Nucleosomes.m'94 3.'a0'a0'a0'a0 Finally, in the same was a was done in step 2, run: '93c03noplotCompute_DStates_fromcsv_NakedDNA_stringentsliceminimum.m'94 to create summary information for the condition of interest. Functions used in this analysis are provided in the source code folder. When running the scripts, please select change folder so that the functions can be found. Note: @msdanalyzer was used for calculating diffusion coefficients. This Matlab package needs to be downloaded and added to the same folder as the functions provided in order to run. Nadine Tarantino, Jean-Yves Tinevez, Elizabeth Faris Crowell, Bertrand Boisson, Ricardo Henriques, Musa Mhlanga, Fabrice Agou, Alain Isra'ebl, and Emmanuel Laplantine. TNF and IL-1 exhibit distinct ubiquitin requirements for inducing NEMO-IKK supramolecular structures. J Cell Biol (2014) vol. 204 (2) pp. 231-45 An example of the complete analysis is provided for the following data set: nucleosome array -&gt; ISW2 -&gt; ATP -&gt; 20211117_example_csvfiles The resulting analysis is added as subfolders of the respective color channels, with each subsequent analysis creating a new subfolder.