We acknowledge the scientific and technical assistance of the INGM Imaging Facility, in particular, C. Cordiglieri and A. Fasciani, and the INGM FACS sorting facility in particular M.C Crosti (Istituto Nazionale di Genetica Molecolare &#39;Romeo ed Enrica Invernizzi&#39; (INGM), Milan, Italy). We acknowledge M. Giannaccari for his technical informatic support. This work was funded by the following grants: Fondazione Cariplo (Bando Giovani, grant nr 2018-0321) and Fondazione AIRC (grant nr MFAG 29165) to F.M. Ricerca Finalizzata, (grant nr GR-2018-12365280), Fondazione AIRC (grant nr 2022 27066), Fondazione Cariplo (grant nr 2019-3416), Fondazione Regionale per la Ricerca Biomedica (FRRB CP2_12/2018,) Piano Nazionale di Ripresa e Resilienza (PNRR) (grant nr G43C22002620007) and Progetti di Rilevante Interesse Nazionale (PRIN) (grant nr 2022PKF9S) to B.B.

The use of human samples for research purposes was approved by the Ethics Committees of the Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) C&#224; Granda Ospedale Maggiore Policlinico (Milan), and informed consent was obtained from all subjects (authorization numbers: 708_2020). The protocol is organized into three primary sections: immunofluorescence execution, image acquisition, and image analysis. On average, it necessitates 4 working days to be completed (Figure 1).
1. Immunofluorescence preparation
NOTE: This immunofluorescence protocol can be easily customized for various cell types and protein targets by adjusting the fixation and permeabilization conditions. Immunofluorescence preparation typically takes less than 3 days to be completed, with the duration of primary antibody incubation varying based on antibody quality and the target protein (Figure 1).
<ol>
	<li>Sample preparation
	<ol>
		<li>Isolate human peripheral blood mononuclear cells (PBMCs) through a density gradient centrifugation via a medium of approximately 1.077 g/mL density according to the manufacturer&#39;s instructions (Table of Materials).</li>
		<li>Isolate CD4+ T cells from PBMCs with magnetic beads, following the manufacturer&#39;s instructions (Table of Materials).</li>
		<li>Stain cells with antibodies for CD4, CD45RA, and CD45RO (Table of Materials) and proceed with FACS-sorting of na&#239;ve CD4+ T cells as CD4+/CD45RA+/CD45RO- cells, as described elsewhere29,30. 
		NOTE: See the Table of Materials for specifications of the FACS sorter used in this protocol.</li>
		<li>Induce the differentiation of na&#239;ve CD4+ T cells into T helper 1 (TH1 CD4+ cells) as described in 29. Briefly, culture 1.5 x 106 cells/mL of FACS-sorted na&#239;ve CD4+ T cells in TH1 medium stimulating them with anti-CD3/anti-CD28 magnetic beads at a 1:1 ratio. Count the cells and split them when they reach 1.5 &#215; 106 cells/mL every 2-3 days (see Table 1 for TH1 medium composition).</li>
		<li>Evaluate the secretion of effector function cytokines after 7 days of differentiation, as described in 29.</li>
	</ol>
	</li>
	<li>Cell fixation and permeabilization 
	NOTE: All these procedures were described in 30,31 with minor adaptations.
	<ol>
		<li>To ensure optimal cell adhesion, treat glass coverslips (10 mm, thickness 1.5 H) with coating solution (Table 1) as follows:
		<ol>
			<li>Clean the glass coverslips by initially washing them with distilled water (ddH2O), followed by a rinse with 70% ethanol (EtOH), and allowing them to air dry.</li>
			<li>Place the washed coverslips in a 24-multiwell plate for steps 1.2.1.3-1.3.</li>
			<li>Apply a drop of 200 &#181;L of coating solution onto the glass coverslip. After 5 min, remove the drop and let it air dry.</li>
			<li>Wash the coverslips by applying a drop of 200 &#181;L of ddH2O. After 5 min, remove the drop and air dry.</li>
			<li>Repeat 3 x steps 1.2.1.3-1.2.1.4.</li>
		</ol>
		</li>
		<li>Resuspend na&#239;ve CD4+ T cells and TH1 CD4+ cells in 1x phosphate-buffered saline (PBS) at 2 &#215; 106 cells/mL concentration. 
		NOTE: The indicated&#160;concentration is advised specifically for small cells such as human primary T lymphocytes. For adherent cells, glass coating treatment is unnecessary. Instead, proceed directly with growing the cells on the glass surface using the appropriate cell culture medium.</li>
		<li>Apply a 200 &#181;L drop of the cell suspension onto the glass cover slip. Allow the cells to seed at room temperature (RT) for 30 min; then, remove the drop.</li>
		<li>Fix the cells with freshly filtered 3% paraformaldehyde (PFA solution, Table 1) for 10 min at RT.</li>
		<li>Wash the glass coverslip with TPBS (Table 1) for 3 x 5 min at RT.</li>
		<li>Remove TPBS and add permeabilization solution (Table 1) for 10 min at RT.</li>
		<li>Discard the permeabilization solution and incubate the sample in storage solution (Table 1) from 1 h to overnight (ON) at 4 &#176;C. 
		NOTE: At this stage, the protocol can be safely halted, and the glass cover slips can be preserved in storage solution in a 24-multiwell plate for 3-4 weeks.</li>
	</ol>
	</li>
	<li>Immunofluorescence
	<ol>
		<li>(Optional) Remove the coverslip from the 24-multiwell plate and rapidly freeze on dry ice for 30 s, thaw at RT, and then wash the glass coverslip in a prefilled well with storage solution.</li>
		<li>(Optional) Repeat 3 x step 1.3.1.</li>
		<li>Wash in permeabilization solution for 5 min at RT. Next, wash for 2 x 5 min with TPBS at RT.</li>
		<li>Incubate in 0.1 N HCl for 12 min at RT.</li>
		<li>Perform two quick washes in 1x PBS. 
		NOTE: The specified cell permeabilization conditions, including freeze and thaw steps and HCl treatment, are optimal for staining nuclear components in cells characterized by densely packed chromatin. However, when dealing with cells characterized by less compacted chromatin, it is advisable to reduce or avoid these steps. Additionally, for targeting cytoplasmic components, consider reducing or eliminating HCl treatment.</li>
		<li>Incubate the cells with primary antibody (BRD4, 1:500, or SUZ12, 1:100) diluted in antibody dilution buffer (Table 1) (200 &#181;L for each glass coverslip) ON at 4 &#176;C. 
		NOTE: Immunofluorescence can be performed by multiplexing more than one primary antibody depending on experimental needs, secondary antibodies, and detection systems.</li>
		<li>Wash 3 x 5 min with PBS-T (Table 1) at RT with mild shaking.</li>
		<li>Incubate the cells with secondary antibody diluted in antibody dilution buffer (200 &#181;L for each glass coverslip) for 1 h at RT. 
		NOTE: Choose the secondary antibody that best suits the experimental needs and the available detection systems. Ensure that each secondary antibody targets the species from which the primary antibody is derived. Additionally, select fluorophores that are compatible with the microscope&#39;s filters and light source. It is crucial to avoid spectral overlap between the chosen fluorophore and the emission spectrum of the nuclear stain.</li>
		<li>Wash 3 x 5 min with PBS-T at RT with mild shaking.</li>
		<li>Stain with 1 ng/mL of 4&#39;,6-diamidino-2-phenylindole (DAPI) diluted in 1x PBS for 5 min at RT. 
		NOTE: Alternative dyes can be used for nuclear staining as long as they do not overlap with the emission spectrum of secondary antibodies.</li>
		<li>Perform several quick washes in 1x PBS.</li>
		<li>Mount the glass coverslip on a microscopy slide with antifade mounting media.</li>
	</ol>
	</li>
</ol>
2. Image acquisition
NOTE: The duration of image acquisition depends on the instrument and selected settings.
<ol>
	<li>Confocal microscope acquisition
	<ol>
		<li>Capture 3D images using a confocal microscope, setting a step size of 0.25 &#181;m in z and pixel size of 0.1-0.2 &#181;m. 
		NOTE: To achieve optimal light diffraction-limited resolution with our 63x 1.4 NA Oil objective, we set the pinhole size at 0.8 AU, 2x line average, and frame size 1024 &#215; 1024 pixels. The excitation laser as well as the channel acquisition sequence were selected deliberately to prevent interference or crosstalk between the fluorophores being used. However, the adjustment of parameters should be tailored to the specific microscope and specimen characteristics. See the Table of Materials for specifications of the confocal microscope used in this protocol.</li>
		<li>Acquire a consistent number of random fields to encompass approximately 50 cells per biological replicate.</li>
	</ol>
	</li>
</ol>
3. Image analysis
<ol>
	<li>Software installation
	<ol>
		<li>Download and install the last available version of Fiji from the official Fiji Download page (https://imagej.net/software/fiji/downloads).</li>
		<li>Install 3D Suite either via the Fiji update site or manually following the instructions on the 3D Suite website (https://mcib3d.frama.io/3d-suite-imagej/#download).</li>
		<li>Install GDSC (FindFoci) either via the Fiji update site or manually by following the instructions on the GitHub repository (https://github.com/aherbert/gdsc).&#160;</li>
	</ol>
	</li>
	<li>TIFF conversion
	<ol>
		<li>Download the &#34;convert_to_TIFF.py&#34; script (Supplemental File 1).</li>
		<li>Drag and drop the script on Fiji and run the code.</li>
		<li>In the panel that appears, browse to the path where the experiment is stored. The subfolder containing the converted TIFF files is created in the same experiment folder.</li>
	</ol>
	</li>
	<li>Initialize settings on 3D Manager.
	<ol>
		<li>Open the 3D Manager option panel by clicking on Plugins | 3DSuite | 3D Manager Options.</li>
		<li>Within the 3D Manager option window, select the checkboxes corresponding to the following measurements: Volume (unit), Mean Gray Value, Bounding box (pix), Std Dev Gray Value, Centroid (pix), and Centroid (unit).</li>
		<li>Tick the following options: Exclude objects on edges XY and Exclude objects on edges Z and click OK. 
		NOTE: This step needs to be done only once to initially configure the metrics that will be stored in the spatial and quantitative information files. The selected metrics are essential for ensuring proper pipeline functioning. Optional additional metrics can be included in this step, as further described in the Discussion section.</li>
	</ol>
	</li>
	<li>Set parameters on FindFoci GUI. 
	NOTE: This step needs to be done only once to configure the semi-automated pipeline with optimal parameters, which will then be incorporated into the scripts.
	<ol>
		<li>Open the test image. Duplicate the protein channel, including the stack (Ctrl + Shift + D), check the hyperstack checkbox, and specify the appropriate channel number within the Channels (c) box, and rename it accordingly.</li>
		<li>Launch the Fiji macro recorder by navigating to Plugins | Macros | Record.</li>
		<li>Open the FindFoci plugin (click on Plugins | GDSC | FindFoci | FindFoci GUI) and select the image to be analyzed from the &#34;Image&#34; dropdown menu.</li>
		<li>Set the parameters as follows (Figure 2A): Gaussian blur = 1.5; background method = SD above mean; background param = 9; search method = fraction of peak - background; search param = 0.7; peak method = relative above background; peak param = 0.2; minimum size = 5; max peaks = 1,000,000. 
		NOTE: The indicated parameters have been selected based on our case studies and may not be suitable for other staining procedures.</li>
		<li>To enhance foci identification, adjust the following parameters:
		<ol>
			<li>Gaussian blur defines the extent of smoothening to better segment foci. Keep it close to the foci diameter (pixel).</li>
			<li>Background param&#160;sets a threshold to distinguish the background from the foci signal. Increase the values to impose more stringent thresholds.</li>
			<li>Search param defines the percentage of fluorescence from the peak that is included in signal recognition. Decrease the values to include areas farther away from the fluorescence peak.</li>
			<li>Peak param&#160;determines the degree to which two signal peaks are considered continuous or separated. Decreasing the value will result in the separation of peaks.</li>
			<li>Max peaks&#160;specifies the maximum number of foci identifiable. Set high numbers to include all foci in the image.</li>
		</ol>
		</li>
		<li>Run FindFoci and copy the string that appears in the recorder window (Step 3.4.2, Figure 2B) that contains the selected parameters, excluding the quotation marks. For further information related to the settings, refer to the plugin manual instruction 22.</li>
	</ol>
	</li>
	<li>Nuclear protein quantification pipeline
	<ol>
		<li>Download the script &#34;nuclear_prot_q.py&#34; (Supplemental File 2).</li>
		<li>Drag and drop the script on Fiji and click run to execute the code.</li>
		<li>Follow the instructions within the displayed dialog box to process the images.
		<ol>
			<li>Nucleus channel: enter the number corresponding to the channel of DAPI (or any nuclear staining).</li>
			<li>Nucleus Gaussian Blur: enter the value of sigma needed to blur the image for segmentation. 
			NOTE: Maintain this parameter closer to the nucleus diameter (i.e., 5-6 &#181;m). Higher sigma values are indicated for inhomogeneous staining.</li>
			<li>Protein channel: enter the number corresponding to the channel of the staining of interest.</li>
			<li>FindFoci Parameter:&#160;paste the string obtained from the macro recording step in passage 3.4.6 (Figure 2B).</li>
			<li>(Optional) Quality control: check the quality of the segmented nuclei. This will pause the script and allow manual checking of each generated nuclear region of interest (ROI).</li>
			<li>Select an image directory: click the Browse button to navigate to the folder containing the TIFF&#160;files to be analyzed.</li>
		</ol>
		</li>
		<li>Once all boxes are compiled, click OK to continue the execution.</li>
		<li>If a nucleus is not correctly segmented and fails to meet quality requirements, delete or modify it as indicated in Figure 2C.
		<ol>
			<li>Check the ROI list in the ROIManager3D window; if the list is empty, select the merge window and click Quantify 3D to refresh the manager. Then, close the Quantify 3D result table. Select the nuclei channel and click Live-ROI to ON.</li>
			<li>Select the ROI belonging to the same nucleus and press Merge or press Delete in the case of undesired nuclei.</li>
			<li>Click select all and proceed with the analysis by clicking OK in the Mask check window.</li>
			<li>For results, look in the Quantification folder within the file path indicated in step 3.5.3.6, containing a txt file with records of the parameter used for the analysis.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Pipeline on Google Colab
	<ol>
		<li>Download the &#34;final_nuclear_protein_metrics.ipynb&#34; notebook (Supplemental File 3).</li>
		<li>Open the notebook on Google Colab (https://colab.research.google.com/).</li>
		<li>Upload all the folders containing the .csv files of each image field into a folder of preference in Google Drive.</li>
		<li>Indicate in the notebook the path of the folder where the result subfolders are stored and run all cells. When the code has finished compiling, the final spreadsheet file containing all the compiled data is created in the same folder where the .csv files were uploaded.</li>
	</ol>
	</li>
</ol>

Analysis Workflow of Nuclear Protein Staining in Human Primary Cells

<ol>
	<li>Aboelnour, E., Bonev, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Decoding+the+organization,+dynamics,+and+function+of+the+4D+genome.">Decoding the organization, dynamics, and function of the 4D genome.</a> Dev Cell. 56 (11), 1562-1573 (2021).</li><li>Erdel, F., Rippe, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Formation+of+chromatin+subcompartments+by+phase+separation.">Formation of chromatin subcompartments by phase separation.</a> Biophys J. 114 (10), 2262-2270 (2018).</li><li>Henninger, J. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-mediated+feedback+control+of+transcriptional+condensates.">RNA-mediated feedback control of transcriptional condensates.</a> Cell. 184 (1), 207-225 (2021).</li><li>Guo, Y. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pol+II+phosphorylation+regulates+a+switch+between+transcriptional+and+splicing+condensates.">Pol II phosphorylation regulates a switch between transcriptional and splicing condensates.</a> Nature. 572 (7770), 543-548 (2019).</li><li>Bhat, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+genome+organization+around+nuclear+speckles+drives+mRNA+splicing+efficiency.">3D genome organization around nuclear speckles drives mRNA splicing efficiency.</a> bioRxiv. , (2023).</li><li>Spector, D. L., Lamond, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nuclear+speckles.">Nuclear speckles.</a> Cold Spring Harb Perspect Biol. 3 (2), a000646 (2011).</li><li>Kilic, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phase+separation+of+53BP1+determines+liquid-like+behavior+of+DNA+repair+compartments.">Phase separation of 53BP1 determines liquid-like behavior of DNA repair compartments.</a> EMBO J. 38 (16), e101379 (2019).</li><li>Parker, M. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+class+of+disordered+elements+controls+DNA+replication+through+initiator+self-assembly.">A new class of disordered elements controls DNA replication through initiator self-assembly.</a> Elife. 8, e48562 (2019).</li><li>Feric, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coexisting+liquid+phases+underlie+nucleolar+subcompartments.">Coexisting liquid phases underlie nucleolar subcompartments.</a> Cell. 165 (7), 1686-1697 (2016).</li><li>Yoneda, M., Nakagawa, T., Hattori, N., Ito, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+nucleolus+from+a+liquid+droplet+perspective.">The nucleolus from a liquid droplet perspective.</a> J Biochem. 170 (2), 153-162 (2021).</li><li>Alberti, S., Carra, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nucleolus:+A+liquid+droplet+compartment+for+misbehaving+proteins.">Nucleolus: A liquid droplet compartment for misbehaving proteins.</a> Curr Biol. 29 (19), R930-R932 (2019).</li><li>Strom, A. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phase+separation+drives+heterochromatin+domain+formation.">Phase separation drives heterochromatin domain formation.</a> Nature. 547 (7662), 241-245 (2017).</li><li>Sanulli, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HP1+reshapes+nucleosome+core+to+promote+phase+separation+of+heterochromatin.">HP1 reshapes nucleosome core to promote phase separation of heterochromatin.</a> Nature. 575 (7782), 390-394 (2019).</li><li>Hyman, A. A., Weber, C. A., Julicher, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Liquid-liquid+phase+separation+in+biology.">Liquid-liquid phase separation in biology.</a> Annu Rev Cell Dev Biol. 30, 39-58 (2014).</li><li>Feric, M., Misteli, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phase+separation+in+genome+organization+across+evolution.">Phase separation in genome organization across evolution.</a> Trends Cell Biol. 31 (8), 671-685 (2021).</li><li>Mitrea, D. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+for+physical+characterization+of+phase-separated+bodies+and+membrane-less+organelles.">Methods for physical characterization of phase-separated bodies and membrane-less organelles.</a> J Mol Biol. 430 (23), 4773-4805 (2018).</li><li>Fetter, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Endogenous+gene+tagging+with+fluorescent+proteins.">Endogenous gene tagging with fluorescent proteins.</a> Methods Mol Biol. 1239, 231-240 (2015).</li><li>Alberti, S., Gladfelter, A., Mittag, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Considerations+and+challenges+in+studying+liquid-liquid+phase+separation+and+biomolecular+condensates.">Considerations and challenges in studying liquid-liquid phase separation and biomolecular condensates.</a> Cell. 176 (3), 419-434 (2019).</li><li>Galbraith, C. G., Galbraith, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Super-resolution+microscopy+at+a+glance.">Super-resolution microscopy at a glance.</a> J Cell Sci. 124 (10), 1607-1611 (2011).</li><li>Scalisi, S., Ahmad, A., D'Annunzio, S., Rousseau, D., Zippo, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+analysis+of+PcG-associated+condensates+by+stochastic+optical+reconstruction+microscopy+(STORM).">Quantitative analysis of PcG-associated condensates by stochastic optical reconstruction microscopy (STORM).</a> Methods Mol Biol. 2655, 183-200 (2023).</li><li>Shihan, M. H., Novo, S. G., Le Marchand, S. J., Wang, Y., Duncan, M. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+method+for+quantitating+confocal+fluorescent+images.">A simple method for quantitating confocal fluorescent images.</a> Biochem Biophys Rep. 25, 100916 (2021).</li><li>Herbert, A. D., Carr, A. M., Hoffmann, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FindFoci:+a+focus+detection+algorithm+with+automated+parameter+training+that+closely+matches+human+assignments,+reduces+human+inconsistencies+and+increases+speed+of+analysis.">FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis.</a> PLoS One. 9 (12), e114749 (2014).</li><li>Ollion, J., Cochennec, J., Loll, F., Escude, C., Boudier, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TANGO:+a+generic+tool+for+high-throughput+3D+image+analysis+for+studying+nuclear+organization.">TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.</a> Bioinformatics. 29 (14), 1840-1841 (2013).</li><li>Sabari, B. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coactivator+condensation+at+super-enhancers+links+phase+separation+and+gene+control.">Coactivator condensation at super-enhancers links phase separation and gene control.</a> Science. 361 (6400), 3958 (2018).</li><li>Jang, M. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+bromodomain+protein+Brd4+is+a+positive+regulatory+component+of+P-TEFb+and+stimulates+RNA+polymerase+II-dependent+transcription.">The bromodomain protein Brd4 is a positive regulatory component of P-TEFb and stimulates RNA polymerase II-dependent transcription.</a> Mol Cell. 19 (4), 523-534 (2005).</li><li>Pasini, D., Bracken, A. P., Jensen, M. R., Denchi, E. L., Helin, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Suz12+is+essential+for+mouse+development+and+for+EZH2+histone+methyltransferase+activity.">Suz12 is essential for mouse development and for EZH2 histone methyltransferase activity.</a> EMBO J. 23 (20), 4061-4071 (2004).</li><li>Margueron, R., Reinberg, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Polycomb+complex+PRC2+and+its+mark+in+life.">The Polycomb complex PRC2 and its mark in life.</a> Nature. 469 (7330), 343-349 (2011).</li><li>Peng, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brd4+regulates+the+homeostasis+of+CD8(+)+T-lymphocytes+and+their+proliferation+in+response+to+antigen+stimulation.">Brd4 regulates the homeostasis of CD8(+) T-lymphocytes and their proliferation in response to antigen stimulation.</a> Front Immunol. 12, 728082 (2021).</li><li>Marasca, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LINE1+are+spliced+in+non-canonical+transcript+variants+to+regulate+T+cell+quiescence+and+exhaustion.">LINE1 are spliced in non-canonical transcript variants to regulate T cell quiescence and exhaustion.</a> Nat Genet. 54 (2), 180-193 (2022).</li><li>Marasca, F., Cortesi, A., Bodega, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+COMBO+chrRNA-DNA-ImmunoFISH.">3D COMBO chrRNA-DNA-ImmunoFISH.</a> Methods Mol Biol. 2157, 281-297 (2021).</li><li>Marasca, F., Cortesi, A., Manganaro, L., Bodega, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+Multicolor+DNA+FISH+tool+to+study+nuclear+architecture+in+human+primary+cells.">3D Multicolor DNA FISH tool to study nuclear architecture in human primary cells.</a> J Vis Exp. (155), (2020).</li><li>Jakob, B., Splinter, J., Durante, M., Taucher-Scholz, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Live+cell+microscopy+analysis+of+radiation-induced+DNA+double-strand+break+motion.">Live cell microscopy analysis of radiation-induced DNA double-strand break motion.</a> Proc Natl Acad Sci U S A. 106 (9), 3172-3177 (2009).</li></ol>

R.V. has a scientific collaboration with the startup T-One Therapeutics Srl; B.B. and F.M. are co-founders of the startup T-One Therapeutics Srl; E.P. is currently employed by T-One Therapeutics Srl; all the other authors declare they have no competing interests.

In this study, we present a method for performing immunofluorescence experiments on nuclear proteins in human T lymphocytes. This method offers flexibility for use with various cell types through minor modifications in fixation and permeabilization steps, as described previously30,31. 
Our imaging workflow builds upon established techniques outlined in the literature, specifically FindFoci and 3D Suite22,</...

The organization of the eukaryotic genome is governed by multiple layers of epigenetic modifications1, coordinating several nuclear functions that can occur within specialized compartments called nuclear bodies or condensates2. Within these structures, processes such as transcription initiation3, RNA processing4,5,6, DNA repair7,8, ribosome biogenesis9,10,11, and heterochromatin regulation12,13 take place. The regulation of nuclear bodies adjusts over both spatial and temporal dimensions to accommodate cellular requirements, guided by principles of phase separation14,15. Consequently, these bodies function as transient factories where functional components assemble and disassemble, undergoing changes in size and spatial distribution. Hence, understanding the characteristics of nuclear proteins by microscopy, including their propensity to form bodies and their spatial arrangement in different cellular conditions, offers valuable insights into their functional roles. Fluorescence microscopy is a widely used method for studying nuclear proteins, allowing their detection through fluorescent antibodies or directly expressing targets with a fluorescent protein reporter16,17.
In this context, nuclear bodies appear as bright foci or puncta, with a notable degree of sphericity, making them easily distinguishable from the surrounding environment16,18. Super-resolution techniques like STORM and PALM, by providing improved resolution (up to 10 nm)19, enable more precise characterization of the structure and composition of specific condensates20. However, their accessibility is limited by equipment expenses and the specialized skills needed for data analysis. Therefore, confocal microscopy remains popular due to its favorable balance between resolution and wider usage. Such popularity is facilitated by the inherent removal of out-of-focus light, which diminishes the requirement for extensive post-processing procedures for accurate segmentation, its widespread availability in research institutes, its effective acquisition time, and sample preparation that is typically efficient. However, accurately measuring protein distribution, assembly, or diffusion using immunofluorescence assays across diverse cellular conditions poses challenges, as many existing methods lack guidance on selecting suitable parameters for proteins with varying distribution patterns21. Moreover, handling the resulting large data volume can be daunting for users with limited experience in data analysis, potentially compromising the biological significance of the results.
To address these challenges, we introduce a detailed step-by-step protocol for immunofluorescence preparation and data analysis, aiming to provide an unbiased method for quantifying protein staining with various organization patterns (Figure 1). This semi-automated pipeline is designed for users with limited expertise in computational and imaging analysis. It combines the functionalities of two established Fiji plugins: FindFoci22 and 3D suite23. By integrating the precise foci identification capability of FindFoci with the object identification and segmentation features in 3D space offered by 3D suite, our approach generates two CSV files per channel for each field of acquisition. These files contain complementary information that facilitates the calculation of metrics suitable for various types of signal distribution, such as the count of foci per cell, the distance of foci from the nuclear centroid, and the inhomogeneity coefficient (IC), which we have introduced for diffuse protein staining. In addition, we acknowledge that data extrapolation can be time-consuming for users with limited data handling skills. To streamline this process, we provide a Python script that automatically compiles all collected measurements into a single file for each experiment. Users can execute this script without the need to install any programming language software. We provide an executable code on Google Colab, a cloud-based platform that allows the writing of Python scripts directly in the browser. This ensures that our method is intuitive and readily accessible for immediate use.
We demonstrate the effectiveness of our protocol in analyzing and quantifying alterations in signal distribution of two nuclear proteins: Bromodomain-containing protein 4 (BRD4) and Suppressor of zeste-12 (SUZ12). BRD4 is a well-documented coactivator protein within the Mediator complex known to form condensates associated with polymerase II-dependent transcriptional initiation24,25. SUZ12 is a protein component of the Polycomb Repressive Complex 2 (PRC2) responsible for regulating the deposition of H3K27me3 histone modification26,27. These proteins exhibit different patterns within two distinct cell types: freshly isolated human CD4+ na&#239;ve T cells, which are quiescent and exhibit slow rates of transcriptional activity, and in vitro differentiated TH1 CD4+ cells, which are specialized, proliferating effector cells showing increased transcription28.

<table><tbody><tr><td>1.5 mL Safe-Lock Tubes</td><td>Eppendord</td><td>#0030121503</td><td>Protocol section 1</td></tr><tr><td>10 mL Serological pipettes</td><td>VWR</td><td>#612-3700</td><td>Protocol section 1</td></tr><tr><td>20 &amp;micro;L barrier pipette tip</td><td>Thermo Scientific</td><td>#2149P-HR</td><td>Protocol section 1</td></tr><tr><td>50 mL Polypropylene Conical Tube</td><td>Falcon</td><td>#352070</td><td>Protocol section 1</td></tr><tr><td>200 &amp;micro;L barrier pipette tip</td><td>Thermo Scientific</td><td>#2069-HR</td><td>Protocol section 1</td></tr><tr><td>antifade solution - ProlongGlass - mountingmedia</td><td>Invitrogen</td><td>#P36984</td><td>Step 1.3.12</td></tr><tr><td>BSA (Bovine Serum Albumin)</td><td>Sigma</td><td>#A7030</td><td>Step 1.3.6., 1.3.8.</td></tr><tr><td>CD4&lt;sup&gt;+ &lt;/sup&gt;T Cell Isolation Kit</td><td>Miltenyi Biotec</td><td>#130-096-533</td><td>Step 1.1.2.</td></tr><tr><td>DAPI (4,6-diamidino-2-phenylindole)</td><td>Invitrogen</td><td>Cat#D1306</td><td>Step 1.3.10.</td></tr><tr><td>Dry ice</td><td></td><td></td><td>Step 1.3.1.</td></tr><tr><td>Dynabeads Human T-activator anti-CD3/anti-CD28 bead</td><td>Life Technologies</td><td>#1131D</td><td>magnetic beads step 1.1.4.</td></tr><tr><td>EtOH</td><td>Carlo Erba</td><td>#4146320</td><td>Step 1.2.1.1.</td></tr><tr><td>FACSAria SORP</td><td>BD Bioscences</td><td></td><td>Step 1.1.3. Equipped with BD FACSDiva Software version 8.0.3</td></tr><tr><td>FBS (Fetal Bovine Serum)</td><td>Life Technologies</td><td>#10270106</td><td>Step 1.1.4</td></tr><tr><td>FICOLL PAQUE PLUS</td><td>Euroclone</td><td>GEH17144003F32</td><td>Step 1.1.1.</td></tr><tr><td>FIJI Version 2.14.0</td><td>-</td><td>-</td><td>Protocol section 3</td></tr><tr><td>Glass coverslip (10 mm, thickness 1.5 H)</td><td>Electron Microscopy Sciences</td><td>#72298-13</td><td>Step 1.2.1.</td></tr><tr><td>Glycerol</td><td>Sigma</td><td>#G5516</td><td>Step 1.2.7-1.3.1.</td></tr><tr><td>Goat anti-Rabbit AF568 secondary antibody</td><td>Invitrogen</td><td>A11036</td><td>Step 1.3.8.</td></tr><tr><td>HCl</td><td>Sigma</td><td>#320331</td><td>Step 1.3.4.</td></tr><tr><td>human neutralizing anti-IL-4</td><td>Miltenyi Biotec</td><td>Cat#130-095-753</td><td>Step 1.1.4.</td></tr><tr><td>human recombinant IL-12</td><td>Miltenyi Biotec</td><td>Cat#130-096-704</td><td>Step 1.1.4.</td></tr><tr><td>human recombinant IL-2</td><td>Miltenyi Biotec</td><td>Cat#130-097-744</td><td>Step 1.1.4.</td></tr><tr><td>Leica TCS SP5 Confocal microscope</td><td>Leica Microsystems</td><td>-</td><td>Protocol section 2, Equipped with HCX PL APO 63x, 1.40 NA oil immersion objective, with an additional 3x zoom. Pinhole size : 0.8 AU. Line average 2&amp;times;. Frame size 1024&amp;times;1024 pixel.</td></tr><tr><td>MEM Non-Essential Amino Acids Solution</td><td>Life Technologies</td><td>#11140035</td><td>Step 1.1.4.</td></tr><tr><td>Microscope Slides</td><td>VWR</td><td>#631-1552</td><td>Step 1.3.12.</td></tr><tr><td>Mouse monoclonal anti-Human CD4 APC-Cy7 (RPA-T4 clone)</td><td>BD Bioscience</td><td>#557871</td><td>Step 1.1.3.</td></tr><tr><td>Mouse monoclonal anti-Human CD45RA PECy5 (5H9 clone)</td><td>BD Bioscience</td><td>#552888</td><td>Step 1.1.3.</td></tr><tr><td>Mouse monoclonal anti-Human CD45RO APC (UCHL1 clone)</td><td>Miltenyi Biotec</td><td>#130-113-546</td><td>Step 1.1.3.</td></tr><tr><td>Multiwell 24 well</td><td>Falcon</td><td>#353047</td><td>Protocol section 1</td></tr><tr><td>Normal Goat Serum</td><td>Invitrogen</td><td>PCN5000</td><td>Step 1.3.6., 1.3.8.</td></tr><tr><td>PBS</td><td>Life Technologies</td><td>#14190094</td><td>Protocol section 1</td></tr><tr><td>Penicillin/Streptomycin solution</td><td>Life Technologies</td><td>#15070063</td><td>Step 1.1.4.</td></tr><tr><td>PFA</td><td>Sigma</td><td>#P6148</td><td>Step 1.2.4.</td></tr><tr><td>poly-L-lysine</td><td>Sigma</td><td>#P8920</td><td>1.2.1.</td></tr><tr><td>Primary antibody - BRD4</td><td>Abcam</td><td>#ab128874</td><td>Step 1.3.6.</td></tr><tr><td>Primary antibody - SUZ12</td><td>Cel Signalling</td><td>mAb #3737</td><td>Step 1.3.6.</td></tr><tr><td>RPMI 1640 W/GLUTAMAX-I</td><td>Life Technologies</td><td>#61870010</td><td>Step 1.1.4.</td></tr><tr><td>Sodium Pyruvate</td><td>Life Technologies</td><td>#11360039</td><td>Step 1.1.4.</td></tr><tr><td>Triton X-100</td><td>Sigma</td><td>#T8787</td><td>Step 1.2., 1.3.</td></tr><tr><td>TWEEN 20</td><td>Sigma</td><td>#P9416</td><td>Step 1.3.</td></tr><tr><td>Tweezers</td><td>-</td><td>-</td><td>Protocol section 1</td></tr></tbody></table>

a versatile pipeline for analyzing dynamic changes in nuclear bodies in a variety of cell types

Various nuclear processes, such as transcriptional control, occur within discrete structures known as foci that are discernable through the immunofluorescence technique. Investigating the dynamics of these foci under diverse cellular conditions via microscopy yields valuable insights into the molecular mechanisms governing cellular identity and functions. However, performing immunofluorescence assays across different cell types and assessing alterations in the assembly, diffusion, and distribution of these foci present numerous challenges. These challenges encompass complexities in sample preparation, determination of parameters for analyzing imaging data, and management of substantial data volumes. Moreover, existing imaging workflows are often tailored for proficient users, thereby limiting accessibility to a broader audience.
In this study, we introduce an optimized immunofluorescence protocol tailored for investigating nuclear proteins in different human primary T cell types that can be customized for any protein of interest and cell type. Furthermore, we present a method for unbiasedly quantifying protein staining, whether they form distinct foci or exhibit a diffuse nuclear distribution.
Our proposed method offers a comprehensive guide, from cellular staining to analysis, leveraging a semi-automated pipeline developed in Jython and executable in Fiji. Furthermore, we provide a user-friendly Python script to streamline data management, publicly accessible on a Google Colab notebook. Our approach has demonstrated efficacy in yielding highly informative immunofluorescence analyses for proteins with diverse patterns of nuclear organization across different&#160;contexts.

The outlined protocol in this method facilitates the visualization and quantification of alterations in nuclear protein staining within human primary T cells, and it can be customized for diverse cell types and protein targets. As case studies, we conducted and analyzed the staining of BRD4 and SUZ12 in na&#239;ve and TH1 CD4+ cells.
BRD4 displays a well-dotted staining pattern in both quiescent na&#239;ve and differentiated TH1 CD4+...

Author Spotlight: Comprehensive Epigenetic Analysis for Investigating Human Cellular Plasticity and Environmental Adaptation Using Immunofluorescence Assays

This method describes an immunofluorescence protocol and quantification pipeline for evaluating protein distribution with varied nuclear organization patterns in human T lymphocytes. This protocol provides step-by-step guidance, starting from sample preparation and continuing through the execution of semi-automated analysis in Fiji, concluding with data handling by a Google Colab notebook.

A Versatile Pipeline for Analyzing Dynamic Changes in Nuclear Bodies in a Variety of Cell Types

Various nuclear processes, such as transcriptional control, occur within discrete structures known as foci that are discernable through the ...

a-versatile-pipeline-for-analyzing-dynamic-changes-nuclear-bodies

Research

JoVE Journal

Genetics

438 Views.  Istituto Nazionale di Genetica Molecolare "Romeo ed Enrica Invernizzi" (INGM). Onze belangrijkste onderzoeksinteresse is een epigenetisch mechanisme dat de menselijke cellulaire elasticiteit en aanpassing aan het milieu reguleert. Ik concentreer me momenteel op het bestuderen van hoe veranderingen in chromatisatie binnen een nucleair condensaat drie pathologische cellulaire aandoeningen zijn. Ik geloof dat het bestuderen van de biofysische eigenschappen van chromatisatie een nieuw veld opent en unieke mogelijkheden biedt voor het ontwik...

Video: Auteur in de schijnwerpers: uitgebreide epigenetische analyse voor het onderzoeken van menselijke cellulaire plasticiteit en aanpassing aan het milieu met behulp van immunofluorescentietesten

Long-term Live-cell Imaging to Assess Cell Fate in Response to Paclitaxel

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over the past decade, new and innovative technologies have greatly enhanced the practicality of live-cell imaging. Cells can now be kept in focus and continuously imaged over several days while maintained under 37 &#176;C and 5% CO2 cell culture conditions. Moreover, multiple fields of view representing different experimental conditions can be acquired simultaneously, thus providing high-throughput experimental data. Live-cell imaging provides a significant advantage over fixed-cell imaging by allowing for the direct visualization and temporal quantitation of dynamic cellular events. Live-cell imaging can also identify variation in the behavior of single cells that would otherwise have been missed using population-based assays. Here, we describe live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel. We demonstrate methods to visualize whether mitotically arrested cells die directly from mitosis or slip back into interphase. We also describe how the fluorescent ubiquitination-based cell cycle indicator (FUCCI) system can be used to assess the fraction of interphase cells born from mitotic slippage that are capable of re-entering the cell cycle. Finally, we describe a live-cell imaging method to identify nuclear envelope rupture events.

Live-cell imaging provides a wealth of information on single cells or whole populations that is unattainable by fixed cell imaging alone. Here, live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel are described.

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over ...

Cancer Research

Photobleaching Assays (FRAP &amp; FLIP) to Measure Chromatin Protein Dynamics in Living Embryonic Stem Cells

Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) enable the study of protein dynamics in living cells with good spatial and temporal resolution. Here we describe how to perform FRAP and FLIP assays of chromatin proteins, including H1 and HP1, in mouse embryonic stem (ES) cells. In a FRAP experiment, cells are transfected, either transiently or stably, with a protein of interest fused with the green fluorescent protein (GFP) or derivatives thereof (YFP, CFP, Cherry, etc.). In the transfected, fluorescing cells, an intense focused laser beam bleaches a relatively small region of interest (ROI). The laser wavelength is selected according to the fluorescent protein used for fusion. The laser light irreversibly bleaches the fluorescent signal of molecules in the ROI and, immediately following bleaching, the recovery of the fluorescent signal in the bleached area - mediated by the replacement of the bleached molecules with the unbleached molecules - is monitored using time lapse imaging. The generated fluorescence recovery curves provide information on the protein's mobility. If the fluorescent molecules are immobile, no fluorescence recovery will be observed. In a complementary approach, Fluorescence Loss in Photobleaching (FLIP), the laser beam bleaches the same spot repeatedly and the signal intensity is measured elsewhere in the fluorescing cell. FLIP experiments therefore measure signal decay rather than fluorescence recovery and are useful to determine protein mobility as well as protein shuttling between cellular compartments. Transient binding is a common property of chromatin-associated proteins. Although the major fraction of each chromatin protein is bound to chromatin at any given moment at steady state, the binding is transient and most chromatin proteins have a high turnover on chromatin, with a residence time in the order of seconds. These properties are crucial for generating high plasticity in genome expression1. Photobleaching experiments are therefore particularly useful to determine chromatin plasticity using GFP-fusion versions of chromatin structural proteins, especially in ES cells, where the dynamic exchange of chromatin proteins (including heterochromatin protein 1 (HP1), linker histone H1 and core histones) is higher than in differentiated cells2,3.

Photobleaching Assays FRAP & FLIP to Measure Chromatin Protein Dynamics in Living Embryonic Stem Cells

We describe photobleaching methods including Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) to monitor chromatin protein dynamics in embryonic stem (ES) cells. Chromatin protein dynamics, which is considered to be one of the means to study chromatin plasticity, is enhanced in pluripotent cells.

Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Loss In Photobleaching (FLIP) enable the study of protein dynamics in living cells with ...

Biology

High-resolution Imaging of Nuclear Dynamics in Live Cells under Uniaxial Tensile Strain

Extracellular mechanical strain is known to elicit cell phenotypic responses and has physiological relevance in several tissue systems. To capture the effect of applied extracellular tensile strain on cell populations in vitro via biochemical assays, a device has previously been designed which can be fabricated simply and is small enough to fit inside tissue culture incubators, as well as on top of microscope stages. However, the previous design of the polydimethylsiloxane substratum did not allow high-resolution subcellular imaging via oil-immersion objectives. This work describes a redesigned geometry of the polydimethylsiloxane substratum and a customized imaging setup that together can facilitate high-resolution subcellular imaging of live cells while under applied strain. This substratum can be used with the same, earlier designed device and, hence, has the same advantages as listed above, in addition to allowing high-resolution optical imaging. The design of the polydimethylsiloxane substratum can be improved by incorporating a grid which will facilitate tracking the same cell before and after the application of strain. Representative results demonstrate high-resolution time-lapse imaging of fluorescently labeled nuclei within strained cells captured using the method described here. These nuclear dynamics data give insights into the mechanism by which applied tensile strain promotes differentiation of oligodendrocyte progenitor cells.&#160;

Using a previously designed device to apply mechanical strain to adherent cells, this paper describes a redesigned substratum geometry and a customized apparatus for high-resolution single-cell imaging of strained cells with a 100x oil immersion objective.

Extracellular mechanical strain is known to elicit cell phenotypic responses and has physiological relevance in several tissue systems. To capture the ...

Bioengineering

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in live-cell imaging and high-throughput microscopy techniques. This led to a constant increase in the amount and complexity of the microscopy data for a single experiment. Because manual analysis of microscopy data is very time consuming, subjective, and prohibits quantitative analyses, automation of bioimage analysis is becoming almost unavoidable. We built an informatics workflow called Substructure Analyzer to fully automate signal analysis in bioimages from fluorescent microscopy. This workflow is developed on the user-friendly open-source platform Icy and is completed by functionalities from ImageJ. It includes the pre-processing of images to improve the signal to noise ratio, the individual segmentation of cells (detection of cell boundaries) and the detection/quantification of cell bodies enriched in specific cell compartments. The main advantage of this workflow is to propose complex bio-imaging functionalities to users without image analysis expertise through a user-friendly interface. Moreover, it is highly modular and adapted to several issues from the characterization of nuclear/cytoplasmic translocation to the comparative analysis of different cell bodies in different cellular sub-structures. The functionality of this workflow is illustrated through the study of the Cajal (coiled) Bodies under oxidative stress (OS) conditions. Data from fluorescence microscopy show that their integrity in human cells is impacted a few hours after the induction of OS. This effect is characterized by a decrease of coilin nucleation into characteristic Cajal Bodies, associated with a nucleoplasmic redistribution of coilin into an increased number of smaller foci. The central role of coilin in the exchange between CB components and the surrounding nucleoplasm suggests that OS induced redistribution of coilin could affect the composition and the functionality of Cajal Bodies.

We present a freely available workflow built for rapid exploration and accurate analysis of cellular bodies in specific cell compartments in fluorescence microscopy images. This user-friendly workflow is designed on the open-source software Icy and also uses ImageJ functionalities. The pipeline is affordable without knowledge in image analysis.

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in ...

Studying Proteolysis of Cyclin B at the Single Cell Level in Whole Cell Populations

Equal distribution of chromosomes between the two daughter cells during cell division is a prerequisite for guaranteeing genetic stability 1. Inaccuracies during chromosome separation are a hallmark of malignancy and associated with progressive disease 2-4. The spindle assembly checkpoint (SAC) is a mitotic surveillance mechanism that holds back cells at metaphase until every single chromosome has established a stable bipolar attachment to the mitotic spindle1. The SAC exerts its function by interference with the activating APC/C subunit Cdc20 to block proteolysis of securin and cyclin B and thus chromosome separation and mitotic exit. Improper attachment of chromosomes prevents silencing of SAC signaling and causes continued inhibition of APC/CCdc20 until the problem is solved to avoid chromosome missegregation, aneuploidy and malignant growths1.
Most studies that addressed the influence of improper chromosomal attachment on APC/C-dependent proteolysis took advantage of spindle disruption using depolymerizing or microtubule-stabilizing drugs to interfere with chromosomal attachment to microtubules. Since interference with microtubule kinetics can affect the transport and localization of critical regulators, these procedures bear a risk of inducing artificial effects 5.
To study how the SAC interferes with APC/C-dependent proteolysis of cyclin B during mitosis in unperturbed cell populations, we established a histone H2-GFP-based system which allowed the simultaneous monitoring of metaphase alignment of mitotic chromosomes and proteolysis of cyclin B 6.
To depict proteolytic profiles, we generated a chimeric cyclin B reporter molecule with a C-terminal SNAP moiety 6 (Figure 1). In a self-labeling reaction, the SNAP-moiety is able to form covalent bonds with alkylguanine-carriers (SNAP substrate) 7,8 (Figure 1). SNAP substrate molecules are readily available and carry a broad spectrum of different fluorochromes. Chimeric cyclin B-SNAP molecules become labeled upon addition of the membrane-permeable SNAP substrate to the growth medium 7 (Figure 1). Following the labeling reaction, the cyclin B-SNAP fluorescence intensity drops in a pulse-chase reaction-like manner and fluorescence intensities reflect levels of cyclin B degradation 6 (Figure 1). Our system facilitates the monitoring of mitotic APC/C-dependent proteolysis in large numbers of cells (or several cell populations) in parallel. Thereby, the system may be a valuable tool to identify agents/small molecules that are able to interfere with proteolytic activity at the metaphase to anaphase transition. Moreover, as synthesis of cyclin B during mitosis has recently been suggested as an important mechanism in fostering a mitotic block in mice and humans by keeping cyclin B expression levels stable 9,10, this system enabled us to analyze cyclin B proteolysis as one element of a balanced equilibrium 6.

Metaphase to anaphase transition is triggered through anaphase-promoting complex (APC/C)-dependent ubiquitination and subsequent destruction of cyclin B. Here, we established a system which, following pulse-chase labeling, allows monitoring cyclin B proteolysis in entire cell populations and facilitates the detection of interference by the mitotic checkpoint.

Equal distribution of chromosomes between the two daughter cells during cell division is a prerequisite for guaranteeing genetic stability 1. Inaccuracies ...

Nuclear Transport Assays in Permeabilized Mouse Cortical Neurons

Disruption of nucleocytoplasmic transport is increasingly implicated in the pathogenesis of neurodegenerative diseases. Moreover, there is a growing recognition of cell-specific differences in nuclear pore complex structure, prompting a need to adapt nuclear transport methods for use in neurons. Permeabilized cell assays, in which the plasma membrane is selectively perforated by digitonin, are widely used to study passive and active nuclear transport in immortalized cell lines but have not been applied to neuronal cultures. In our initial attempts, we observed the rapid loss of nuclear membrane integrity in primary mouse cortical neurons exposed to even low concentrations of digitonin. We hypothesized that neuronal nuclear membranes may be uniquely vulnerable to the loss of cytoplasmic support. After testing multiple approaches to improve nuclear stability, we observed optimal nuclear integrity following hypotonic lysis in the presence of a concentrated bovine serum albumin cushion. Neuronal nuclei prepared by this approach reliably import recombinant fluorescent cargo in an energy-dependent manner, facilitating analysis of nuclear import by high content microscopy with automated analysis. We anticipate that this method will be broadly applicable to studies of passive and active nuclear transport in primary neurons.

We have developed a reliable method of selective plasma membrane permeabilization of primary mouse cortical neurons for high content automated analysis of neuronal nucleocytoplasmic transport.

Disruption of nucleocytoplasmic transport is increasingly implicated in the pathogenesis of neurodegenerative diseases. Moreover, there is a growing ...

Neuroscience

Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion

Nuclear positioning within cells is important for multiple cellular processes in development and regeneration. The most intriguing example of nuclear positioning occurs during skeletal muscle differentiation. Muscle fibers (myofibers) are multinucleated cells formed by the fusion of muscle precursor cells (myoblasts) derived from muscle stem cells (satellite cells) that undergo proliferation and differentiation. Correct nuclear positioning within myofibers is required for the proper muscle regeneration and function. The common procedure to assess myoblast differentiation and myofiber formation relies on fixed cells analyzed by immunofluorescence, which impedes the study of nuclear movement and cell behavior over time. Here, we describe a method for the analysis of myoblast differentiation and myofiber formation by live cell imaging. We provide a software for automated nuclear tracking to obtain a high-throughput quantitative characterization of nuclear dynamics and myoblast behavior (i.e., the trajectory) during differentiation and fusion.

Skeletal muscle differentiation is a highly dynamic process, which particularly relies on nuclear positioning. Here, we describe a method to track nuclei movements by live cell imaging during myoblast differentiation and myotube formation and to perform a quantitative characterization of nuclei dynamics by extracting information from automatic tracking.

Nuclear positioning within cells is important for multiple cellular processes in development and regeneration. The most intriguing example of nuclear ...

Examination of Mitotic and Meiotic Fission Yeast Nuclear Dynamics by Fluorescence Live-cell Microscopy

Live-cell imaging is a microscopy technique used to examine cell and protein dynamics in living cells. This imaging method is not toxic, generally does not interfere with cell physiology, and requires minimal experimental handling. The low levels of technical interference enable researchers to study cells across multiple cycles of mitosis and to observe meiosis from beginning to end. Using fluorescent tags such as Green Fluorescent Protein (GFP) and Red Fluorescent Protein (RFP), researchers can analyze different factors whose functions are important for processes like transcription, DNA replication, cohesion, and segregation. Coupled with data analysis using Fiji (a free, optimized ImageJ version), live-cell imaging offers various ways of assessing protein movement, localization, stability, and timing, as well as nuclear dynamics and chromosome segregation. However, as is the case with other microscopy methods, live-cell imaging is limited by the intrinsic properties of light, which put a limit to the resolution power at high magnifications, and is also sensitive to photobleaching or phototoxicity at high wavelength frequencies. However, with some care, investigators can bypass these physical limitations by carefully choosing the right conditions, strains, and fluorescent markers to allow for the appropriate visualization of mitotic and meiotic events.

Here, we present live-cell imaging which is a non-toxic microscopy method that allows researchers to study protein behavior and nuclear dynamics in living fission yeast cells during mitosis and meiosis.

Live-cell imaging is a microscopy technique used to examine cell and protein dynamics in living cells. This imaging method is not toxic, generally does ...

Live Cell Imaging to Assess the Dynamics of Metaphase Timing and Cell Fate Following Mitotic Spindle Perturbations

Live cell time-lapse imaging is an important tool in cell biology that provides insight into cellular processes that might otherwise be overlooked, misunderstood, or misinterpreted by the fixed-cell analysis. While the fixed cell imaging and analysis is robust and sufficient to observe cellular steady-state, it can be limited in defining a temporal order of events at the cellular level and is ill-equipped to assess the transient nature of dynamic processes including mitotic progression. In contrast, live cell imaging is an eloquent tool that can be used to observe cellular processes at the single-cell level over time and has the capacity to capture the dynamics of processes that would otherwise be poorly represented in fixed cell imaging. Here we describe an approach to generate cells carrying fluorescently labeled markers of chromatin and microtubules and their use in live cell imaging approaches to monitor metaphase chromosome alignment and mitotic exit. We describe imaging-based techniques to assess the dynamics of spindle formation and mitotic progression, including the identification of cells at various stages in mitosis, identification&#160;and tracking of mitotic defects, and analysis of spindle dynamics and mitotic cell fate following the treatment with mitotic inhibitors.

Here we present a protocol to assess the dynamics of spindle formation and mitotic progression. Our application of time-lapse imaging enables the user to identify cells at various stages of mitosis, track and identify mitotic defects, and analyze spindle dynamics and mitotic cell fate upon exposure to anti-mitotic drugs.

Live cell time-lapse imaging is an important tool in cell biology that provides insight into cellular processes that might otherwise be overlooked, ...

Impact of Cytoskeleton on Nuclear Shape and Condensate Dynamics in Mouse Oocytes

Capturing Cytoskeleton-Based Agitation of the Mouse Oocyte Nucleus Across Spatial Scales

A major challenge in understanding the causes of female infertility is to elucidate mechanisms governing the development of female germ cells, named oocytes. Their development is marked by cell growth and subsequent divisions, two critical phases that prepare the oocyte for fusion with sperm to initiate embryogenesis. During growth, oocytes reorganize their cytoplasm to position the nucleus at the cell center, an event predictive of successful oocyte development in mice and humans and, thus, their embryogenic potential. In mouse oocytes, this cytoplasmic reorganization was shown to be driven by the cytoskeleton, the activity of which generates mechanical forces that agitate, reposition, and penetrate the nucleus. Consequently, this cytoplasmic-to-nucleoplasmic force transmission tunes the dynamics of nuclear RNA-processing organelles known as biomolecular condensates. This protocol provides an experimental framework to document, with high temporal resolution, the impact of the cytoskeleton on the nucleus across spatial scales in mouse oocytes. It details the imaging and image analysis steps and tools necessary to evaluate i) cytoskeletal activity in the oocyte cytoplasm, ii) cytoskeleton-based agitation of the oocyte nucleus, and iii) its effects on biomolecular condensate dynamics in the oocyte nucleoplasm. Beyond oocyte biology, the methods elaborated here can be adapted for use in somatic cells to similarly address cytoskeleton-based tuning of nuclear dynamics across scales.

Author Spotlight: Elucidating the Dynamics of Mechano-Transduction and Nuclear Agitation in Mouse Oocytes

This protocol provides an experimental framework to document the physical impact of the cytoskeleton on nuclear shape and the internal membrane-less organelles in the mouse oocyte system. The framework can be adapted for use in other cell types and contexts.

A major challenge in understanding the causes of female infertility is to elucidate mechanisms governing the development of female germ cells, named ...

A Versatile Pipeline for Analyzing Dynamic Changes in Nuclear Bodies in a Variety of Cell Types

Samenvatting

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