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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Many intrinsically disordered proteins have been shown to participate in the formation of highly dynamic biomolecular condensates, a behavior important for numerous cellular processes. Here, we present a single-molecule imaging-based method for quantifying the dynamics by which proteins interact with each other in biomolecular condensates in live cells.

Abstract

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) have been considered critical in cellular organization and an increasing number of cellular functions. Characterizing LLPS in live cells is also important because aberrant condensation has been linked to numerous diseases, including cancers and neurodegenerative disorders. LLPS is often driven by selective, transient, and multivalent interactions between intrinsically disordered proteins. Of great interest are the interaction dynamics of proteins participating in LLPS, which are well-summarized by measurements of their binding residence time (RT), that is, the amount of time they spend bound within condensates. Here, we present a method based on live-cell single-molecule imaging that allows us to measure the mean RT of a specific protein within condensates. We simultaneously visualize individual protein molecules and the condensates with which they associate, use single-particle tracking (SPT) to plot single-molecule trajectories, and then fit the trajectories to a model of protein-droplet binding to extract the mean RT of the protein. Finally, we show representative results where this single-molecule imaging method was applied to compare the mean RTs of a protein at its LLPS condensates when fused and unfused to an oligomerizing domain. This protocol is broadly applicable to measuring the interaction dynamics of any protein that participates in LLPS.

Introduction

A growing body of work suggests that biomolecular condensates play an important role in cellular organization and numerous cellular functions, e.g., transcriptional regulation1,2,3,4,5, DNA damage repair6,7,8, chromatin organization9,10,11,12, X-chromosome inactivation13,14,15, and intracellular signaling16,17,18. In addition, the dysregulation of biomolecular condensates is implicated in many diseases, including cancers19,20,21 and neurodegenerative disorders22,23,24,25,26. Condensate formation is often driven by transient, selective, and multivalent protein-protein, protein-nucleic acid, or nucleic acid-nucleic acid interactions27. Under certain conditions, these interactions can lead to liquid-liquid phase separation (LLPS), a density transition that locally enriches specific biomolecules in membraneless droplets. Such multivalent interactions are often mediated by the intrinsically disordered regions (IDRs) of proteins1,28,29. Biophysical characterization of these interactions at the molecular level is critical to our understanding of numerous healthy and aberrant cellular functions, given the pervasiveness of condensates across them. Although techniques based on confocal fluorescence microscopy, e.g., fluorescence recovery after photobleaching (FRAP)30,31,32, have been widely used to qualitatively show that the molecular exchanges between condensates and the surrounding cellular environment are dynamic, quantifying the interaction dynamics of specific biomolecules within condensates is generally not possible using conventional confocal microscopy or single-molecule microscopy without specialized data analysis methods. The single-particle tracking (SPT) technique described in this protocol is based on live-cell single-molecule microscopy33 and provides a uniquely powerful tool to quantify the interaction dynamics between specific proteins within condensates. The readout of SPT for such measurement is the mean residence time of a protein of interest in the condensates.

The protocol can be broken down into two parts - data acquisition and data analysis. The first step of imaging data acquisition is to express in cells a protein of interest that is fused to a HaloTag34. This enables labeling of the protein of interest with two fluorophores, where a majority of the protein molecules are to be labeled with a non-photoactivatable fluorophore (e.g., JFX549 Halo ligand35) and a small fraction of them are to be labeled with a spectrally distinct, photoactivatable fluorophore (e.g., PA-JF646 Halo ligand36). This allows for the simultaneous acquisition of all condensate locations in the cell and the acquisition of single-molecule movies of the protein of interest binding and unbinding to the condensates. Meanwhile, the same type of cells are modified to stably express Halo-tagged H2B, a histone that is largely immobile on chromatin. The cells are then stained with the PA-JF646 Halo ligand to enable single-molecule imaging of H2B. As will be discussed in detail below, this experiment accounts for the contribution of photobleaching to enable precise quantification of the interaction dynamics of the protein of interest. Cells for imaging experiments must then be cultured on clean coverslips, stained with HaloTag ligand(s), and assembled into a live-cell imaging chamber. From there, the sample is imaged under highly inclined and laminated optical sheet (HILO) illumination on a total internal reflection fluorescence (TIRF) microscope capable of two-channel imaging and single-molecule detection. The emission is then split onto two cameras, one tracking condensate positions and one tracking single molecules. Acquisition is performed with a long integration time (on the order of hundreds of ms) to blur out freely-diffusing proteins and only capture proteins that are less mobile due to binding to stable structures in the cell37.

The first step of data analysis is using an established single-particle tracking (SPT) algorithm38,39 to localize individual protein molecules in each frame of the movie and assemble the localizations into a trajectory for each molecule over its detectable lifetime. The trajectories are then sorted into those representing molecules inside and those representing molecules outside the condensates by comparing the localizations of the molecules throughout their trajectories to the localizations of all the condensates at the corresponding times1.

Next, a survival curve (1 - CDF) is generated using the lengths of all the in-condensate trajectories. The apparent mean residence time of the molecules is then extracted by fitting the survival curve to the following two-component exponential model of protein binding,

figure-introduction-6098,

with A as the fraction of molecules non-specifically bound and with kobs,ns and kobs,s as the observed dissociation rates of the non-specifically bound and specifically bound molecules, respectively. Only kobs,s is considered from here onward. The dynamics of both protein dissociation, ktrue,s, and photobleaching of the fluorophore, kpb, contribute to kobs,s as

figure-introduction-6745;

thus, to isolate the effects of protein dissociation, the specific dissociation rate of H2B-Halo in the cell line mentioned prior is measured.

figure-introduction-7036

H2B is a protein that is stably integrated into chromatin and that experiences minimal dissociation in the time scale of a single-molecule movie acquisition37. Its specific dissociation rate is then equal to the photobleaching rate of the PA-JF646 Halo ligand, or

figure-introduction-7471.

The mean in-condensate residence time of the protein of interest, figure-introduction-7657, is then

figure-introduction-7785.

Representative results from Irgen-Gioro et al.40 are shown, where this protocol was applied to demonstrate that fusing an oligomerization domain to IDR results in longer residence times of the IDR in its condensates. This result suggests that the added oligomerization domain stabilizes the homotypic interactions of the IDR that drives LLPS. In principle, the same method with slightly modified protocols can be applied to characterize the homotypic or heterotypic interactions of any protein that participates in the formation of any types of condensates.

Protocol

1. Labeling of proteins in cells

  1. Express the protein of interest fused to HaloTag in the desired cell line.
  2. Stably express Halo-tagged H2B in the same type of cells as in 1.1 using transposons or viral transduction.

2. Preparation of coverslips

  1. Before using coverslips for cell culture, clean coverslips to remove autofluorescent contaminants.
    1. Mount 25 mm diameter, #1.5 coverslips on a ceramic staining rack and place into a polypropylene container.
    2. Completely immerse coverslips in a 1 M solution of KOH and sonicate for 1 h.
    3. Rinse coverslips three times with double-distilled water (ddH2O).
    4. Completely immerse coverslips in 100% ethanol and sonicate for 1 h.
    5. Completely immerse coverslips in 20% ethanol diluted with ddH2O and store at 4 °C until use.

3. Preparation of cells for microscopy

NOTE: Perform steps from this section in a biosafety cabinet to prevent contamination of the cells.

  1. Plate cells on cleaned coverslips. Perform 2 days before imaging if the Halo-tagged protein is to be transiently expressed. Perform 1 day before imaging if the Halo-tagged protein is stably or endogenously expressed.
    1. Use sterile forceps to place coverslips in a 6-well plate (one coverslip/well per cell sample) and allow residual ethanol to evaporate.
    2. Plate each well with an appropriate number of cells to achieve 70% confluency by the time of imaging. Plate an additional well with cells stably expressing H2B-Halo with the same target confluency.
    3. Follow this step only if transiently expressing the Halo-tagged protein of interest. Incubate cells for 24 h at 37 °C and 5% CO2. Then, transfect the cells with the plasmid encoding the tagged protein of interest using appropriate transfection reagents and following the manufacturer's guidelines.
    4. Incubate the cells for 24 h at 37 °C and 5% CO2.
  2. Stain the cells expressing the Halo-tagged protein of interest with both a non-photoactivatable Halo ligand (e.g., JFX549) and a photoactivatable Halo ligand (e.g., PA-JF646). Stain cells expressing H2B-Halo with only the photoactivatable Halo ligand.
    NOTE: Concentrations of Halo ligands listed here should be used as a starting point; the optimal concentration will depend on the expression level and in-condensate local concentration of the protein of interest.
    1. For each cell sample expressing the Halo-tagged protein of interest, dilute 100 nM JFX549 Halo ligand35 and 20 nM PA-JF646 Halo ligand36 in 500 µL of appropriate cell media. For each sample expressing H2B-Halo, dilute only 20 nM PA-JF646 Halo ligand in 500 µL of appropriate cell media.
    2. For each well, aspirate existing media, add 2 mL of 1x PBS, then aspirate PBS (this is referred to as a "rinse" for the remainder of the protocol), and replace with media containing the appropriate Halo ligands.
    3. Incubate for 1 h at 37 °C and 5% CO2.
    4. Rinse with PBS four times and replace with fresh media containing no Halo ligands.
    5. Incubate for 15 min at 37 °C and 5% CO2.
    6. Repeat steps 3.2.4 and 3.2.5 three times (four rinse-incubation cycles total).
    7. Use sterile forceps to transfer the coverslip with cells to a cell-culture coverslip chamber compatible with the microscope stage.
    8. Add phenol red-free media to the chamber and proceed to imaging. Incubate the samples not immediately being imaged at 37 °C and 5% CO2 until needed.

4. Single-molecule imaging

NOTE: Independent experiments measuring the residence times of both H2B and the protein of interest should be conducted across multiple (≥3) days to generate statistically significant results. Before imaging cell samples on the microscope, align the two cameras using 0.1 µm stained microspheres (Table of Materials) or a similar calibration standard.

  1. Prepare the microscope.
    1. Turn on the microscope and the computer that controls the microscope.
    2. Turn on live-cell incubation components (heater and CO2) on the microscope and set it to 37 °C and 5% CO2. Allow the system to equilibrate.
    3. Put a drop of the appropriate oil onto a 100x TIRF oil immersion objective on the microscope and load the cell sample onto the microscope stage.
  2. Identify a cell to image.
    1. Image the cell sample under brightfield illumination and adjust the z-position until the cells are in focus.
    2. Identify a cell that exhibits morphology characteristics of healthy cells.
    3. Crop the field of view (FOV) so that it only captures the target cell nucleus.
    4. Use laser illumination and adjust the TIRF angle until HILO illumination41 with optimal signal-to-noise ratio of single molecules is achieved.
  3. Image H2B-Halo in live cells.
    NOTE: The laser powers used in this section are specific to this experiment and included as an example. Appropriate laser powers should be chosen according to the criteria listed in the discussion.
    1. Set up an acquisition configuration as follows. Set the exposure time as 500 ms. During each 500 ms exposure, excite PA-JF646 labeled H2B-Halo molecules with a 9.1 mW, 640 nm beam. During the dead time between frames (158.01 µs on the imaging system used here), photoactivate the molecules with a 111 µW, 405 nm beam.
    2. Capture 2000 frames continuously under these settings. Gradually increase the 405 nm beam's power over the course of the acquisition when the number of photoactivated molecules becomes insufficient.
  4. Image the Halo-tagged protein of interest in live cells.
    1. Use a long-pass dichroic mirror to split emission wavelengths between two cameras, one to detect PA-JF646 and the other to detect JFX549. Use appropriate emission filters in front of the cameras.
    2. Use the same acquisition configuration described in 4.3.1 with the following modification. Add an additional JFX549 channel to track locations of the Halo-tagged protein condensates over time. Every 10 s, acquire one frame (500 ms, 2.1 mW, 561 nm excitation) in the JFX549 channel while keeping the acquisition of the PA-JF646 channel. This will cause bleedthrough into the PA-JF646 channel, which will be taken care of in the post-acquisition data analysis.
    3. Capture 2000 frames continuously under these settings. Gradually increase the 405 nm beam's power over the course of the acquisition when the number of photoactivated molecules becomes insufficient.

5. Analysis of single-molecule imaging data

NOTE: The parameters used throughout section 5 are specific to this experiment and included as an example. Appropriate parameters should be chosen according to the criteria listed in the discussion.

  1. Prepare raw imaging data for processing.
    1. For the data of the protein of interest, convert each channel from the raw imaging data file into an independent .tif file using ImageJ or similar image processing software. For the data of H2B, convert the single channel from the raw imaging data file into a .tif file in the same way.
      NOTE: Depending on the acquisition software being used, there can be empty frames in the condensate movie, as only one condensate-tracking frame is taken every 10 s. The empty frames should be populated with the most recent condensate frame (some acquisition software automatically does this). Additionally, if there is significant bleedthrough from the condensate (JFX549) channel into the single-molecule (PA-JF646) channel during those condensate-tracking frames, the corresponding single-molecule frames should be replaced with the most recent single-molecule frame.
    2. If there are any frames that need to be replaced in either movie due to the above reasons, replace them with the most recent frame from that movie by modifying (if necessary) and running pretracking_comb.txt, an ImageJ macro available in Chong et al.1, and following the prompts.
  2. Generate single-particle trajectories using an SPT software, e.g., SLIMfast39, a GUI implementation of the MTT algorithm38 available in Teves et al.42.
    1. Load the file from 5.1.2 containing the single-molecule movie in SLIMfast by clicking on Load > Imagestack.
    2. Set the parameters (localization error rate: 10-6; deflation loops: 3) for localization by clicking OPT > Sheet: Localization.
    3. Set the parameters (peak emission: 664 nm; lag time: 500 ms) for acquisition by clicking OPT > Sheet: Acquisition.
    4. Visualize the localizations of all the molecules in a single frame to ensure that the parameters chosen are appropriate (TEST LOC). If inappropriate, modify parameters in steps 5.2.2 and 5.2.3 and repeat this step.
    5. Generate a file containing the localizations of all the molecules in every frame (LOC ALL).
    6. Load the file from 5.2.5 in SLIMfast by clicking Load > Particle Data > SLIMfast.
    7. Set the parameters (maximum expected diffusion coefficient: 0.1 µm2/s; maximum number of competitors: 5) for trajectory generation by clicking OPT > Sheet: Tracking.
    8. Generate a file containing the trajectories of all the molecules (GEN TRAJ).
  3. Filter out the trajectories that are shorter than tmin, 2.5 s, using evalSPT39, available in Drosopoulos et al.43, to account for tracking errors that result in artificially short trajectories.
    1. Load the file from 5.2.8 into evalSPT (+ > file from 5.2.8 > OK).
    2. Set the parameters (min: 5 frames; max: maximum trajectory length for file from 5.2.8) to filter out the trajectories shorter than 2.5 s.
    3. Generate a file with all the filtered trajectories (EXPORT DATA).
  4. Follow this step for the trajectories of the protein of interest only. Sort the trajectories into those in the condensates and out of the condensates, then extract the mean in-condensate residence time.
    NOTE: All the codes for this section are available in Chong et al.1.
    1. Threshold all the frames of the movie acquired in the JFX549 channel to generate a time-lapse movie populated with the time-evolving binary mask highlighting condensate locations by running the ImageJ macro, nucleus, and cluster mask_v2.txt, and following the prompts.
    2. Reformat the single-molecule trajectories generated in 5.3.3. using the MATLAB script, ConvertASCII_SlowTracking_css3.m, and adjusting the filenames, paths, and parameters as necessary. (Parameters: Exposure, 0.5 s; Resolution, 0.16 µm/pixel).
    3. Sort trajectories based on the fraction of the lifetime a given molecule spends in a condensate, F, using the MATLAB script, categorization_v4.m, and adjusting the filenames and paths as necessary.
    4. Proceed using only in-condensate trajectories.
  5. Extract kobs,s and kpb and compute the corrected mean residence time, figure-protocol-12416.
    1. Extract kobs,s from the in-condensate protein of interest trajectories using the MATLAB script, PLOT_ResidenceHist_css.m, and adjusting filenames, paths, and parameters as necessary.
      (Parameters: Exposure, 0.5 s; StartFrameForFit, 5 frames).
    2. Extract kpb from the H2B trajectories using the MATLAB script, PLOT_ResidenceHist_css.m, and adjusting filenames, paths, and parameters as necessary.
      (Parameters: Exposure, 0.5 s; StartFrameForFit, 5 frames).
    3. Calculate the corrected mean residence time of the protein of interest specifically bound to its condensates, figure-protocol-13266, as
      figure-protocol-13369
      NOTE: Controls should be performed to verify that different exposure times that are long enough to blur out mobile particles, for example, 300 ms and 800 ms, still result in the same mean residence time of the protein of interest.

Results

Here, we present representative results from Irgen-Gioro et al.40, where we used this SPT protocol to compare the interaction dynamics of two proteins in their respective self-assembled LLPS condensates. TAF15 (TATA-box binding protein associated factor 15) contains an IDR that can undergo LLPS upon overexpression in human cells. We hypothesized that fusing TAF15(IDR) to FTH1 (ferritin heavy chain 1), which forms a 24-subunit oligomer, would lead to more stable homotypic protein-protein interactio...

Discussion

The protocol as presented here is designed for systems like those investigated in Irgen-Gioro et al.40. Depending on the application, some components of the protocol can be modified, e.g., the method for generating fluorescently labeled cell lines, the fluorescent labeling system, and the style of coverslip used. Halo-tagging of a protein in a cell can be done using two strategies, depending on which is more suitable for a given experiment. 1) Exogenous expression: fusing the protein of interest t...

Disclosures

The authors have nothing to disclose.

Acknowledgements

This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1745301 (S.Y.), Pew-Stewart Scholar Award (S.C.), Searle Scholar Award (S.C.), the Shurl and Kay Curci Foundation Research Grant (S.C.), Merkin Innovation Seed Grant (S.C.), the Mallinckrodt Research Grant (S.C.), and the Margaret E. Early Medical Research Trust 2024 Grant (S.C.). S.C. is also supported by the NIH/NCI under Award Number P30CA016042.

Materials

NameCompanyCatalog NumberComments
0.1 µm TetraSpeck microsphereInvitrogenT7279Single-molecule imaging
25 mm Diameter, #1.5 CoverslipsMarienfeld Superior111650Preparation of coverslips
593/40 nm bandpass filterSemrockFF01-593/40-25Single-molecule imaging
676/37 nm bandpass filterSemrockFF01-676/37-25Single-molecule imaging
6-Well TC PlateGenesee25-105MPPreparation of cells for microscopy
Cell Line: U-2 OSATCCHTB-96Labeling of proteins in cells
ConvertASCII_SlowTracking_css3
.m		Analysis of single-molecule imaging data: Available in Chong et al., 2018
Coverglass Staining RackThomas24957Preparation of coverslips
Deuterated Janelia Fluor 549 (JFX549)Janelia Research CampusPreparation of cells for microscopy
DMEM, Low GlucoseGibco10-567-022Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep
Eclipse Ti2-E Inverted MicroscopeNikonSingle-molecule imaging
Ethanol 200 ProofLab AlleyEAP200-1GALPreparation of coverslips
evalSPTAnalysis of single-molecule imaging data: Available in Drosopoulos et al., 2020
Fetal Bovine SerumCytivaSH30396.03Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep
FijiAnalysis of single-molecule imaging data
Ikon Ultra CCD CameraAndorX-13723Single-molecule imaging
Longpass dichroic beamsplitterSemrockDi02-R635-25x36Single-molecule imaging: Red/Far Red beamsplitter
LUN-F Laser UnitNikonSingle-molecule imaging: 405/488/561/640
MatTek glass-bottom dishMatTekP35G-1.5-20-CPreparation of cells for microscopy: 35 mm, #1.5 coverslip dish for cell culture.
NIS-ElementsNikonSingle-molecule imaging: Microscope acquisition software
nucleus and cluster mask_v2.txtAnalysis of single-molecule imaging data: Available in Chong et al., 2018
Penicillin-StreptomycinGibco15-140-122Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep
Phosphate Buffered SalineThermo Fisher Scientific18912014Labeling of proteins in cells
Photoactivatable Janelia Fluor 646 (PA-JF646)Janelia Research CampusPreparation of cells for microscopy
PLOT_ResidenceHist_css.mAnalysis of single-molecule imaging data: Available in Chong et al., 2018
Potassium HydroxideMallinckrodt Chemicals6984-06Preparation of coverslips
pretracking_comb.txtAnalysis of single-molecule imaging data: Available in Chong et al., 2018
SLIMfastAnalysis of single-molecule imaging data: Available in Teves et al., 2016
Stage-top incubation systemTokai HitSingle-molecule imaging: For live-cell imaging
TwinCam dual emission image splitterCairn ResearchSingle-molecule imaging
Ultrasonic CleanerBranson5800Preparation of coverslips

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