Name: Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
Uploaded: 2024-01-05T14:35:00
Description: Watch this Scientific Journal Video about Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells at JoVE.com

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.

1. Labeling of proteins in cells
<ol>
	<li>Express the protein of interest fused to HaloTag in the desired cell line.</li>
	<li>Stably express Halo-tagged H2B in the same type of cells as in 1.1 using transposons or viral transduction.</li>
</ol>
2. Preparation of coverslips
<ol>
	<li>Before using coverslips for cell culture, clean coverslips to remove autofluorescent contaminants.
	<ol>
		<li>Mount 25 mm diameter, #1.5 coverslips on a ceramic staining rack an...

Live Cell Single-Molecule Imaging-Based Quantification of Protein Interactions

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...

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,
<img align="center" alt="Equation 1" src="/files/ftp_upload/66169/66169eq01.jpg" style="margin: auto;" />,
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
<img alt="Equation 2" src="/files/ftp_upload/66169/66169eq02.jpg" style="margin: auto;" />;
thus, to isolate the effects of protein dissociation, the specific dissociation rate of H2B-Halo in the cell line mentioned prior is measured.
<img alt="Equation 3" src="/files/ftp_upload/66169/66169eq03.jpg" style="margin: auto;" />
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
<img alt="Equation 4" src="/files/ftp_upload/66169/66169eq04.jpg" style="margin: auto;" />.
The mean in-condensate residence time of the protein of interest, <img alt="Equation 5" src="/files/ftp_upload/66169/66169eq05.jpg" style="margin: auto;" />, is then
<img alt="Equation 6" src="/files/ftp_upload/66169/66169eq06.jpg" style="margin: auto;" />.
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.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.1 &#181;m TetraSpeck microsphere</td>
			<td>Invitrogen</td>
			<td>T7279</td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>25 mm Diameter, #1.5 Coverslips</td>
			<td>Marienfeld Superior</td>
			<td>111650</td>
			<td>Preparation of coverslips</td>
		</tr>
		<tr>
			<td>593/40 nm bandpass filter</td>
			<td>Semrock</td>
			<td>FF01-593/40-25</td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>676/37 nm bandpass filter</td>
			<td>Semrock</td>
			<td>FF01-676/37-25</td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>6-Well TC Plate</td>
			<td>Genesee</td>
			<td>25-105MP</td>
			<td>Preparation of cells for microscopy</td>
		</tr>
		<tr>
			<td>Cell Line: U-2 OS</td>
			<td>ATCC</td>
			<td>HTB-96</td>
			<td>Labeling of proteins in cells</td>
		</tr>
		<tr>
			<td>ConvertASCII_SlowTracking_css3 
			.m</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Chong et al., 2018</td>
		</tr>
		<tr>
			<td>Coverglass Staining Rack</td>
			<td>Thomas</td>
			<td>24957</td>
			<td>Preparation of coverslips</td>
		</tr>
		<tr>
			<td>Deuterated Janelia Fluor 549 (JFX549)</td>
			<td>Janelia Research Campus</td>
			<td></td>
			<td>Preparation of cells for microscopy</td>
		</tr>
		<tr>
			<td>DMEM, Low Glucose</td>
			<td>Gibco</td>
			<td>10-567-022</td>
			<td>Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep</td>
		</tr>
		<tr>
			<td>Eclipse Ti2-E Inverted Microscope</td>
			<td>Nikon</td>
			<td></td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>Ethanol 200 Proof</td>
			<td>Lab Alley</td>
			<td>EAP200-1GAL</td>
			<td>Preparation of coverslips</td>
		</tr>
		<tr>
			<td>evalSPT</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Drosopoulos et al., 2020</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>Cytiva</td>
			<td>SH30396.03</td>
			<td>Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep</td>
		</tr>
		<tr>
			<td>Fiji</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data</td>
		</tr>
		<tr>
			<td>Ikon Ultra CCD Camera</td>
			<td>Andor</td>
			<td>X-13723</td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>Longpass dichroic beamsplitter</td>
			<td>Semrock</td>
			<td>Di02-R635-25x36</td>
			<td>Single-molecule imaging: Red/Far Red beamsplitter</td>
		</tr>
		<tr>
			<td>LUN-F Laser Unit</td>
			<td>Nikon</td>
			<td></td>
			<td>Single-molecule imaging: 405/488/561/640</td>
		</tr>
		<tr>
			<td>MatTek glass-bottom dish</td>
			<td>MatTek</td>
			<td>P35G-1.5-20-C</td>
			<td>Preparation of cells for microscopy: 35 mm, #1.5 coverslip dish for cell culture.</td>
		</tr>
		<tr>
			<td>NIS-Elements</td>
			<td>Nikon</td>
			<td></td>
			<td>Single-molecule imaging: Microscope acquisition software</td>
		</tr>
		<tr>
			<td>nucleus and cluster mask_v2.txt</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Chong et al., 2018</td>
		</tr>
		<tr>
			<td>Penicillin-Streptomycin</td>
			<td>Gibco</td>
			<td>15-140-122</td>
			<td>Labeling of proteins in cells: Growth media used: DMEM with 5% fetal bovine serum, 1% penstrep</td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline</td>
			<td>Thermo Fisher Scientific</td>
			<td>18912014</td>
			<td>Labeling of proteins in cells</td>
		</tr>
		<tr>
			<td>Photoactivatable Janelia Fluor 646 (PA-JF646)</td>
			<td>Janelia Research Campus</td>
			<td></td>
			<td>Preparation of cells for microscopy</td>
		</tr>
		<tr>
			<td>PLOT_ResidenceHist_css.m</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Chong et al., 2018</td>
		</tr>
		<tr>
			<td>Potassium Hydroxide</td>
			<td>Mallinckrodt Chemicals</td>
			<td>6984-06</td>
			<td>Preparation of coverslips</td>
		</tr>
		<tr>
			<td>pretracking_comb.txt</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Chong et al., 2018</td>
		</tr>
		<tr>
			<td>SLIMfast</td>
			<td></td>
			<td></td>
			<td>Analysis of single-molecule imaging data: Available in Teves et al., 2016</td>
		</tr>
		<tr>
			<td>Stage-top incubation system</td>
			<td>Tokai Hit</td>
			<td></td>
			<td>Single-molecule imaging: For live-cell imaging</td>
		</tr>
		<tr>
			<td>TwinCam dual emission image splitter</td>
			<td>Cairn Research</td>
			<td></td>
			<td>Single-molecule imaging</td>
		</tr>
		<tr>
			<td>Ultrasonic Cleaner</td>
			<td>Branson</td>
			<td>5800</td>
			<td>Preparation of coverslips</td>
		</tr>
	</tbody>
</table>

single-molecule measurement of protein interaction dynamics within biomolecular condensates

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.

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates

1 Our lab aims to understand the interaction behaviors<v>2 of intrinsically disordered protein regions 3 and how they play roles in transcriptional regulation 4 in healthy and diseased human cells. 5 In our lab, we develop and use novel 6 single molecule microscopy techniques 7 in combination with molecular biology, 8 biochemical and proteomic approaches 9 to study biomolecular condensates. 10 This protocol enables the quantification of the dynamics 11 by which a specific protein 12 binds to a particular type of condensate 13 in live human cells, 14 and is broadly applicable 15 to measuring the interaction dynamics of any protein 16 that participates in liquid-liquid phase separation.

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...

Watch this Scientific Journal Video about Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells at JoVE.com

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.

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) have been considered critical in cellular organization and an increasing number ...

single-molecule-measurement-protein-interaction-dynamics-within

Research

JoVE Journal

Biology

Halo-Ligand Staining of Cells for Protein Condensate-Interaction Studies Using Single-Molecule Imaging

1 After creating the cell lines<v>2 expressing the HaloTag protein of interest and Halo-H2B, 3 prepare the halo ligand staining reagent 4 separately for both of them. 5 Rinse the cells with two milliliters of PBS. 6 Add halo ligand containing media 7 and incubate them at 37 degrees Celsius 8 with 5%carbon dioxide for one hour.9 After removing the staining media, 10 rinse the cells four times with PBS 11 and incubate them with fresh media devoid of halo ligands. 12 After four such rinse incubation cycles, 13 transfer the cover slip with cells 14 to a microscope stage compatible chamber 15 with sterile forceps. 16 Add phenol red-free media to the chamber before imaging.

Single-Molecule Imaging of Halo-Tagged Proteins to Study Protein-Condensate Interactions

1 To begin, obtain ligand stain cells<v>2 expressing halo-tagged protein of interest and halo H2B. 3 After turning on the microscope system, 4 set the live cell incubation parameters 5 and let the system equilibrate. 6 Put a drop of the oil onto 7 a 100x TIRF objective on the microscope 8 and load the cell sample onto the microscope stage.9 To identify a morphologically healthy cell, 10 adjust the Z position 11 and image the cell sample under brightfield illumination. 12 Crop the field of view to capture the target cell nucleus. 13 Using laser illumination, adjust the TIRF angle 14 to achieve hilo illumination with an optimal 15 signal to noise ratio of a single molecule.16 Then, set the exposure time to 500 milliseconds. 17 During the dead time between frames, 18 photo activate the molecules 19 with a 111 microwatt 405 nanometer beam, 20 and during each exposure, excite H2B halo molecules 21 with a 9.1 milliwatt 640 nanometer beam. 22 Initiate image capturing for 2000 frames continuously 23 and gradually increase the power of the 405 nanometer beam 24 upon reduction of photo activated molecules.25 For a halo-tagged protein of interest, 26 split emission wavelengths between two cameras 27 using a long pass dichroic mirror. 28 To the same acquisition parameters demonstrated earlier, 29 add JFX549 channel to acquire one frame every 10 seconds 30 and capture 2000 frames continuously.

Analysis of Single-Molecule Imaging Data to Study Interactions of Halo-Tagged Proteins

1 To begin, perform live cell<v>2 single molecule imaging of HaloTag protein condensates. 3 Using ImageJ, convert each channel 4 from the raw imaging data file 5 into an independent TIFF file. 6 If necessary, run pre-tracking comb.text 7 and follow the prompts 8 to replace any frames with the most recent ones. 9 To load the single molecule of movie file in SlimFast, 10 click on load, followed by image stack. 11 Set the parameters for localization 12 and acquisition under respective option sheets.13 Visualize the localizations of all the molecules. 14 And using lock all, 15 generate a file containing the localizations 16 of all the molecules in every frame. 17 Next, go to load particle data 18 and select SlimFast to load the file 19 with localization and acquisition settings.20 Using option and sheet tracking, 21 adjust the parameters for trajectory generation. 22 Click on gen traj to generate a file 23 containing the trajectories of all the molecules. 24 Load the sheet tracked file into eval SPT 25 and set the parameters 26 to filter out the trajectories shorter than 2.5 seconds.27 Using export data, generate a file 28 with all the filtered trajectories. 29 Running the ImageJ macro, nucleus, 30 and cluster mask version two. text, 31 threshold all the frames of the movie acquired 32 in the JFX549 channel to generate a time lapse movie 33 populated with the time evolving binary mask 34 highlighting condensate locations.35 Using convert ASCII slow tracking CSS 3. M, 36 reformat the trajectories 37 and run categorization version 4. M 38 to sort them based on the lifetime 39 a molecule spends in a condensate.40 Next, using plot residence hist CSS. M, 41 extract the observed dissociation rate 42 of specifically bound molecules 43 and the photobleaching rate from the in condensate 44 protein of interest and the H2B trajectories. 45 Finally, calculate the corrected mean residence time 46 of the protein of interest, 47 specifically bound to its condensates.48 A frame from two-color single molecule movie 49 of TAF15 IDR-Halo-FTH1 shows signals 50 from the nucleus in both PA-JF646 and JFX549 channels. 51 Upon assembling and sorting, 52 a clear distinction was observed for the trajectories 53 of PA-JF646 detected molecules bound to the condensates. 54 The calculated mean residence times 55 after correction for photobleaching 56 were more for TAF15-Halo-FTH1 than Halo-TAF15.