Published March 5, 2018 | Version v1
Journal article Open

RNA polymerase II clustering through CTD phase separation

  • 1. Max Planck Institute for Biophysical Chemistry, Department of Molecular Biology, Am Fassberg 11, 37077 Göttingen, Germany
  • 2. Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA.
  • 3. Max Planck Institute for Biophysical Chemistry, Department of NMR-based Structural Biology, Am Fassberg 11, 37077 Göttingen, Germany
  • 4. German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075 Göttingen, Germany


PALM imaging

Six movies of ~ 50,000 frames were acquired for each condition at 30 ms/frame. The axial drift was corrected in real time with a perfect focus system. A cylindrical lens was added to the system to induce astigmatism in the point-spread function (PSF) of the optical setup. 300,000 detections were collected on average per movie. Single molecule detection and localization was performed with a modified version of the multiple-target tracking algorithm. The 3D position of single detection was inferred from the lateral elongation of the PSF. The lateral drift of the sample was corrected by using fluorescent beads (TetraSpeck microspheres). To correct for blinking of the Dendra2 fluorophore, detections in a disk of 30 nm and adjacent in time were grouped and averaged.

Nuclei and nucleoli were automatically detected and segmented for further processing. .

The triangulation of the areas was performed with a custom python script and we used the ADS R package to estimate the four spatial statistics. In order to estimate the standard deviation and standard error associated with these measurements we performed a bootstrapping analysis of the data set. We randomly selected 10,000 detections from each original data set a 100 times and feed these sub sampled data set to the R script computing the spatial statistics.


Single-molecule imaging (spaSPT)

After overnight growth, cells were labeled with 50 nM PA-JF549 for ~15-30 min and washed twice (one wash: medium removed; PBS wash; replenished with fresh medium). At the end of the final wash, the medium was changed to phenol red-free medium keeping all other aspects of the medium the same (and adding back a-amanitin). Single-molecule imaging was performed on a custom-built Nikon TI microscope equipped with a 100x/NA 1.49 oil-immersion TIRF objective (Nikon apochromat CFI Apo TIRF 100x Oil), EM-CCD camera (Andor iXon Ultra 897; frame-transfer mode; vertical shift speed: 0.9 μs; -70°C), a perfect focusing system to correct for axial drift and motorized laser illumination (Ti-TIRF, Nikon), which allows an incident angle adjustment to achieve highly inclined and laminated optical sheet illuminatio. An incubation chamber maintained a humidified 37°C atmosphere with 5% CO2 and the objective was also heated to 37°C. Excitation was achieved using a 561 nm (1 W, Genesis Coherent) laser for PA-JF549. The excitation laser was modulated by an acousto-optic tunable filter (AA Opto-Electronic, AOTFnC-VIS-TN) and triggered with the camera TTL exposure output signal. The laser light was coupled into the microscope by an optical fiber and then reflected using a multi-band dichroic (405 nm/488 nm/561 nm/633 nm quad-band, Semrock) and then focused in the back focal plane of the objective. Fluorescence emission light was filtered using a single band-pass filter placed in front of the camera using the following filters : Semrock 593/40 nm bandpass filter. The microscope, cameras, and hardware were controlled through NIS-Elements software (Nikon).

We recorded single-molecule tracking movies using our previously developed technique, stroboscopic photo-activation Single-Particle Tracking (spaSPT). Briefly, 1 ms 561 nm excitation (100% AOTF) of PA-JF549 was delivered at the beginning of the frame to minimize motion-blurring; 405 nm photo-activation pulses were delivered during the camera integration time (~447 μs) to minimize background and their intensity optimized to achieve a mean density of ~1 molecule per frame per nucleus. 30,000 frames were recorded per cell per experiment. The camera exposure time was 7 ms resulting in a frame rate of approximately 134 Hz (7 ms + ~447 μs per frame).

spaSPT data was analyzed (localization and tracking) and converted into trajectories using a custom-written Matlab implementation of the MTT-algorithm and the following settings: Localization error: 10-6.25; deflation loops: 0; Blinking (frames): 1; max competitors: 3; max D (mm2/s): 20.

We recorded ~9-10 cells per replicate and performed three independent replicates on three different days. Specifically, across three replicates we imaged 29 cells for Halo-RPB1-25R and obtained 448,362 trajectories with 690,682 unique displacements at a mean density of 1.2 localizations per frame. Similarly, we imaged 30 cells for Halo-RPB1-52R and obtained 324,928 trajectories with 498,503 unique displacements at a mean density of 0.9 localizations per frame.



All data is available in CSV-files

For the SPT analysis, the file format is readible by the web-version of Spot-On. The CSV format consists of comma-separated values and contains headers.

Here the “frame” column contains the frame number in which the molecule was detected. The “t” column contains the timestamp. The “trajectory” column contains the trajectory number. For example, trajectory number 1 was only detected in frame 13 after which it disappeared. In contrast, trajectory number 4 was detected in frames 20, 21 22, 23 and 24. Finally, the “x” and “y” columns contain the x,y coordinates of the localization in units of micrometers (μm).



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