Dynamic 1D search and processive nucleosome translocations by RSC and ISW2 chromatin remodelers
Creators: name: Kim, Jee Min
name: Carcamo, Claudia
name: Jazani, Sina
name: Xie, Zepei
name: Feng, Xinyu
name: Yamadi, Maryam
name: Poyton, Matthew
name: Holland, Katie
name: Grimm, Jonathan
name: Lavis, Luke
name: Ha, Taekjip
name: Wu, Carl
Publisher: name: Zenodo
Year: 2024
Subjects: Single Particle Tracking
Optical tweezers
chromatin remodelers
1D Diffusion

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: Matlab (2021 or newer)
Funding provided by: National Science FoundationCrossref Funder Registry ID: https://ror.org/021nxhr62Award Number: DGE-1746891
Funding provided by: National Institutes of HealthCrossref Funder Registry ID: https://ror.org/01cwqze88Award Number: GM132290-01
Funding provided by: National Institutes of HealthCrossref Funder Registry ID: https://ror.org/01cwqze88Award Number: T32 GM007445
Funding provided by: National Institutes of HealthCrossref Funder Registry ID: https://ror.org/01cwqze88Award Number: S10 OD025221
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.