Name: discrimination of seven immune cell subsets by two-fluorochrome flow cytometry
Uploaded: 2019-03-05T13:00:00.000+00:00
Duration: 10 min 58 s
Description: Watch this Scientific Journal Video about Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry at JoVE.com

This study was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases, &#60;https://www.niams.nih.gov/&#62;, award number P30-AR053503; The Stabler Foundation,&#160;www.stablerfoundation.org; National Institute of Allergy and Infectious Disease, www.niaid.nih.gov, T32AI007247; Nina Ireland Program for Lung Health (NIPLH), https://pulmonary.ucsf.edu/ireland/.

All studies of human materials were approved by the Johns Hopkins Institutional Review Board under the Health Insurance Portability and Accountability Act. Patient and control samples were de-identified. PBMCs and blood from healthy controls were obtained by informed consent.
NOTE: This protocol has been tested on freshly or frozen isolated peripheral blood cells and whole blood.
1. Cell Preparation
<ol>
	<li>Isolation of peripheral blood cells (PBMC) from whole blood
	<ol>
		<li>Draw blood in a 10 mL green-top tube containing sodium heparin. After the tube has been filled with blood, immediately invert the tube several times to prevent coagulation. 
		NOTE: Tubes containing other anticoagulant such as ethylenediaminetetraacetic acid (EDTA) or sodium citrate can be used with comparable results. If a different amount of blood is collected, the following steps in the protocol should be scaled accordingly.</li>
		<li>Carefully transfer drawn blood into a 50 mL conical tube. Dilute the blood with an equal amount of phosphate buffered saline (PBS) without calcium and magnesium.</li>
		<li>Add 15 mL of density gradient medium (e.g., Ficoll) to the bottom of a new 50 mL conical tube and carefully overlay the diluted blood on top of density gradient medium, avoiding any mixing between the density gradient medium and diluted blood. 
		NOTE: This is a critical step for a proper separation of PBMCs from red cells.</li>
		<li>Centrifuge at 400 x g for 30 min at room temperature (RT), with no brake to avoid disruption of the interface.</li>
		<li>After centrifugation, carefully aspirate the upper layer using a pipette and discard it, paying attention to not remove cells at the interface between the plasma and density gradient medium, that is where PBMCs stratifies. Collect as many cells as possible from the interface without touching the red cell pellet at the bottom of the 50 mL conical tube and transfer to a new 50 mL conical tube.</li>
		<li>Add PBS to bring the final volume to 25 mL and invert several times to mix. Centrifuge at 300 x g for 10 min at RT with the brake on to remove any density gradient medium contamination from the cell suspension.</li>
		<li>Carefully aspirate supernatant without disturbing cell pellet. Add PBS to bring the final volume to 25 mL and invert several times to mix. Centrifuge at 200 x g for 10 min at RT with the brake on to remove platelets.</li>
		<li>Carefully aspirate the supernatant without disturbing the cell pellet. Resuspend PBMCs in 1 mL of PBS/0.1% sodium azide. Sodium azide reduces capping, shedding, internalization of the antibodies, and increase cell recovery, but its toxicity can impair cell viability. For this reason, sodium azide should be avoided in all steps if the cells will be cultured for subsequent experiments. Cell isolation and staining without sodium azide gave similar results to staining performed in the presence of sodium azide. 
		&#8203;CAUTION: Sodium azide can cause death by affecting the central nervous system. Contact may cause burns to skin and eyes.</li>
		<li>Dilute the cells for counting by transferring 30 &#181;L of PBMCs in a 1.5 mL microcentrifuge tube. Then add 120 &#181;L of PBS and 150 &#181;L of Trypan blue to determine cell number and viability (1:10 cell dilution). Resuspend carefully.</li>
		<li>Transfer 10 &#181;L to a hemocytometer, count the cells accordingly to the used counting chamber and determine the number of viable cells. Viable cells = number of Trypan blue negative cells total x 10 (the dilution factor used in this protocol) x 104. 
		NOTE: On average, 7-15 x 106 of PBMCs should be collected from 10 mL of blood.</li>
		<li>Resuspend the cells at 10 x 106 per mL of PBS/0.1% sodium azide 
		NOTE: PBMC can be frozen and stored in liquid nitrogen for an extended period of time. However, expression of markers such as chemokine receptors can be altered by this procedure.</li>
	</ol>
	</li>
	<li>Preparation of cells from frozen PBMC 
	NOTE: Different freezing procedures can affect cell recovery and viability12. PBMCs for these experiments were frozen in specially formulated freezing media or fetal bovine serum (FBS)/10% dimethyl sulfoxide (DMSO) with similar results. 
	&#8203;CAUTION: DMSO can be slightly hazardous in case of inhalation (lung irritant), skin contact (irritant, permeator), of eye contact (irritant), of ingestion.
	<ol>
		<li>Remove frozen PBMC from liquid nitrogen and place on ice. Transfer the cryovial from the ice directly into the 37 &#176;C water bath. Keep the cryovial at water surface and gently shake the vials until a small ice pellet remain. Transfer the cryovial back on ice.</li>
		<li>Remove any water with a 70% ethanol sprayed wipe. Slowly add 1 mL of PBS/0.1% sodium azide at 4 &#176;C and carefully transfer the cell to a 15 mL conical tube. Slowly add cold PBS/0.1% sodium azide at 4 &#176;C to reach a final volume of 15 mL.</li>
		<li>Centrifuge at 300 x g for 10 min. Carefully remove the supernatant, resuspend the cells in 1 mL of PBS/0.1% sodium azide. 
		NOTE: The cells can also be resuspended in RPMI 10% FBS with similar results.</li>
		<li>Dilute the cell for counting by transferring 30 &#181;L of PBMCs in a 1.5 mL microcentrifuge tube. Then add 120 &#181;L of PBS and 150 &#181;L of Trypan blue to determine cell number and viability (1:10 cell dilution). Resuspend carefully.</li>
		<li>Transfer 10 &#181;L to a hemocytometer, count the cells accordingly to the used counting chamber and determine the number of viable cells. Viable cells = number of Trypan blue negative cells total x 10 (the dilution factor used in this protocol) x 104.</li>
		<li>Resuspend the cells at 10 x 106 per mL in PBS/0.1% sodium azide.</li>
	</ol>
	</li>
	<li>Preparation of cells from whole blood
	<ol>
		<li>Draw blood in a 10 mL green-top tube containing sodium heparin. After the tube has been filled with blood, immediately invert the tube several times to prevent coagulation. 
		NOTE: Tubes containing other anticoagulant such as EDTA or sodium citrate can be used with comparable results. If a different amount of blood is collected, the following steps in the protocol should be scaled accordingly.</li>
		<li>Transfer 200 &#181;L of whole blood to a 12 mm x 75 mm capped tube, add 2 &#181;L of sodium azide and vortex gently for 2 s.</li>
	</ol>
	</li>
</ol>
2. Cell Staining
NOTE: Choosing pairs of fluorochromes with virtually no spectral overlap is important to reduce spread of data due to high spillover of a fluorochrome in the other fluorochrome detector. To achieve an optimal identification of al the cell subsets, fluorochromes with a high quantum yield should be used such as antibody pairs PE-BV421 and PE-APC.
<ol>
	<li>Staining of fresh and frozen PBMC
	<ol>
		<li>Transfer 100 &#181;L of PBMC (1 x 106 cells) to a 96-well V-bottom plate. 
		NOTE: Any number of cells lower than 1 x 106 can be used with similar results2.</li>
		<li>Centrifuge at 350 x g for 3 min at RT and carefully aspirate the supernatant without disturbing the cell pellet. Add to each well 100 &#181;L of PBS containing a live/dead fixable dye that reacts with free amine on proteins for 10 min to label dead cells.</li>
		<li>Prepare for each sample 30 &#181;L of a mix containing all the antibodies (anti-CD3. -CD56, TCR&#947;&#948; in fluorchrome A, and anti-CD4, CD8, CD19, CD14 in fluorchrome B). Concentration of antibodies are indicated in Table 1 and Table2. At this stage, titrated antibodies against different target molecules and in different fluorochromes can be added as well (e.g., Table 3). 
		NOTE: Antibodies concentration can vary depending on the manufacturer and lot number. Therefore, preliminary tests should be done to achieve the optimal signal. PBS, PBS/0.5% BSA, PBS/0.2% sodium azide or PBS/0.5% BSA/0.1% sodium azide were used with similar results to dilute antibodies2. Cell can also be stained in volumes different from 30 &#181;L to easily integrate this methodology to already existing staining protocols.</li>
		<li>Centrifuge at 350 x g for 3 min at RT and carefully aspirate the supernatant without disturbing the cell pellet. Add the antibody cocktail to each well and resuspend carefully without generating bubbles. Incubate for 30 min at RT in the dark. 
		NOTE: It is possible to stain the samples at 4 &#176;C with similar results.</li>
		<li>Add 150 &#181;L of staining buffer and centrifuge at 350 x g for 3 min at RT and carefully aspirate the supernatant without disturbing the cell pellet. Resuspend the cells in 200 &#181;L of PBS and acquire data on a flow cytometer. If staining volumes are changed, please ensure at least a 20-fold dilution of the original antibody mix used to wash the excess of antibodies. 
		NOTE: Stained cells can be fixed with in PBS/2% paraformaldehyde, kept in a refrigerator at 4 &#176;C overnight and then acquired on a flow cytometer the following day. 
		CAUTION: Paraformaldehyde is harmful if swallowed and can cause skin irritation</li>
	</ol>
	</li>
	<li>Staining of whole blood
	<ol>
		<li>To each 12 mm x 75 mm capped tube, add the cocktail of antibodies (anti-CD3. -CD56, TCR&#947;&#948; in fluorochrome A, and anti-CD4, CD8, CD19, CD14 in fluorochrome B) and incubate at RT for 30 min at RT in the dark. Concentration of antibodies are indicated in Table 4. At this stage, titrated antibodies against different target molecules and in different fluorochromes can be added as well. Antibody concentration can vary depending on the manufacturer and lot number. Therefore, preliminary tests should be done to achieve the optimal signal. 
		NOTE: It is possible to stain samples at 4 &#176;C with similar results.</li>
		<li>Centrifuge at 350 x g for 3 min at RT and carefully aspirate the supernatant without disturbing the cell pellet. Make a 1x solution of the red blood cell lysis buffer following manufacturer&#8217;s instructions. 
		NOTE: The lysis solution should be at RT before use.</li>
		<li>Add 2.0 mL of 1x red blood cell lysis buffer to each tube, cap well and invert several times to mix. Cover with foil and let sit for 15 min.</li>
		<li>Spin down at 300 x g for 5 min. Carefully aspirate the supernatant without disturbing the cell pellet.</li>
		<li>Add 2 mL of PBS and centrifuge at 300 x g for 5 min. 
		NOTE: At this point, the cell pellet should have a pale white coloration indicating a successful red blood cell lysis. Carefully aspirate the supernatant to not disturb the cell pellet and gently resuspend the cells in 200 &#181;L of PBS.</li>
		<li>Strain the cells through 12 mm x 75 mm tubes with 40 &#181;m filter caps to remove cell aggregates and acquire data on a flow cytometer.</li>
	</ol>
	</li>
</ol>
3. Antibody Titration
NOTE: Antibody titration is the most critical step for obtaining high-quality, reproducible data. Titration of anti-CD3, -CD8, -CD14, -CD19 and -TCR &#947;&#948; follows the standard procedure by which the concentration of antibody to optimally separate positive and negative peaks is derived by maximum staining index13,14. Dilutions at the peak or closer to the peak on the rising side of the stain index curve should be selected (Figure 1A-C). The anti-CD4 antibody is titrated to place the peak of the CD4 positive population between CD3 single positive populations and CD3+/CD8+ T cells, closer to the CD3 single positive signal to better discriminate the CD8dim populations (CD8+ &#947;&#948; T cells and NK T cells). Along the same line, CD56 titration aims to position NK CD56+ cells between the CD3+ and the CD3- population.
<ol>
	<li>Maximum stain index curve 
	NOTE: Titration of anti-CD3, -CD8, -CD14, -CD19 and -TCR &#947;&#948; follows the standard procedure by which the concentration of antibody to optimally separate positive and negative peaks is derived by a maximum staining index curve15. If antibodies against other markers are added to the panel, they also need to be titrated with a maximum staining index curve.
	<ol>
		<li>Prepare a 2-fold antibody dilution by filling 10 wells of a 96-well plate with 40 &#181;L of staining buffer. In the first well, increase the final volume to 80 &#181;L of staining buffer and add the antibody of interest at a concentration 4 times the concentration suggested by the manufacturer.</li>
		<li>Mix well and transfer 40 &#181;L to the second well. Mix well and repeat this step for the all the other wells.</li>
		<li>Stain 10 samples of PBMC or whole blood with 30 &#181;L of the 10 different 2-fold dilutions of antibodies following the protocol described before.</li>
		<li>Acquire data with a flow cytometer and plot the signal from each dilution (Figure 1A).</li>
		<li>Gate on the negative and positive populations for each antibody concentration. Increasing concentration of antibodies can lead to a higher background. Therefore, resize the negative gate accordingly.</li>
		<li>For each antibody concentration, extract information about the median and standard deviation for the fluorescent intensity of the negative population, and the median for the fluorescent intensity of the positive population. Calculate for each antibody concentration the stain index with this formula: (median fluorescent intensity of the positive population &#8212; median fluorescent intensity of the negative population) &#247; (2 x standard deviation of the fluorescent intensity of the negative population) (Figure 1B).</li>
		<li>Plot the stain index vs. the antibody concentration expressed as fraction of the antibody dilution (e.g., 1:10 dilution = 0.1), and identify the concentration of antibody with the maximum stain index value (Figure 1C).</li>
	</ol>
	</li>
	<li>Anti-CD4 and -CD56 antibody titration 
	NOTE: Anti-CD4 and -CD56 antibodies titration relies on previous titration the other markers in the two-fluorochrome panel. For the anti-CD4 antibody the titration aims at placing the anti-CD4 signal between the double CD8+/CD3+ signal and the CD3 single positive population (Figure 1D).
	<ol>
		<li>Titrate the anti-CD4 and CD56 antibodies with a 2-fold dilution strategy as described before, adding additional concentrations in between to finely identify the range of concentration that allow to separate CD4+&#160;T cells and NK cells from the other cell populations.</li>
		<li>Titrate the anti-CD4 antibody by placing the anti-CD4 signal between the double CD8+/CD3+ signal and the CD3 single positive population (Figure 1D). 
		NOTE: Special care should be done to clearly separate CD4+ T cells from CD8+ dim populations.</li>
		<li>Titrate the anti-CD56 antibody following a strategy similar to the anti-CD4 antibody titration, by placing NK cells between the CD3-negative and the CD3-positive populations.</li>
	</ol>
	</li>
</ol>
4. Gating Strategy
<ol>
	<li>Identify lymphocytic and monocytic cell populations and remove dead cells and most of the residual red blood cells from the analysis.
	<ol>
		<li>Select the entire population containing lymphocytes and monocytes based on forward vs side scatter area (FSC-A vs SSC-A). Remove cell aggregates from the analysis via forward scatter height vs forward scatter width (FSC-H vs FSC-W) and side scatter height vs side scatter width (SSC-H vs SSC-W).</li>
		<li>Use a live/dead discrimination marker to exclude bright positive dead cells and residual red blood cells from the analysis. Gate on lymphocytes and monocytes based on the different FSC-A and SSC-A profile.</li>
	</ol>
	</li>
	<li>Two-fluorochrome seven-marker gating strategy of the lymphocytic populations. 
	NOTE: Within the CD3 positive subgroup, CD4+, CD8+ and &#947;&#948; T cells can be separated using antibodies that solely target CD4, CD8 and the &#947;&#948; receptor. In a comparable way, within the CD3 negative subgroup, B cells, NK cells and monocytes can be uniquely identified using antibodies against CD19, CD56 and CD14, respectively.
	<ol>
		<li>Select the lymphocyte gate and create a dot plot with on each axis one of two fluorochromes used in this protocol (Figure 2B).</li>
		<li>Gate on CD8+ T cells identified as CD3+/CD8+ double positive cells at the top right corner of the dot-plot (Figure 2B). Exclude the dim CD8 population which might contain NKT cells. Gate on CD4+ T cells identified as population in between CD8+ T cells and the CD3 single positive populations. Gate on &#947;&#948; T cells identified as high CD3 cells. Subdivide &#947;&#948; T cells in CD8 positive and CD8 negative.</li>
		<li>Gate on NK cells identified as the population in between CD3-positive and CD3-negative cells. Subdivide NK cells in CD8 positive and CD8 negative. Gate on B cells identified as CD3-negative CD19+ population on the right lower corner of the dot plot.</li>
		<li>Select the monocyte gates and create a dot plot with on each axis one of two fluorochromes used in this protocol (Figure 2C). Gate on the CD3-/CD14+ population.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Bendall, S. C., Nolan, G. P., Roederer, M., Chattopadhyay, P. 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+deep+profiler's+guide+to+cytometry.">A deep profiler's guide to cytometry.</a> Trends in Immunology. 33 (7), 323-332 (2012).</li><li>Boin, 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=Flow+cytometric+discrimination+of+seven+lineage+markers+by+using+two+fluorochromes.">Flow cytometric discrimination of seven lineage markers by using two fluorochromes.</a> PLoS ONE. 12 (11), (2017).</li><li>Zola, H., 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> Leukocyte and Stromal Cell Molecules: The CD Markers. , (2007).</li><li>Lambert, C., Genin, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CD3+bright+lymphocyte+population+reveal+&#947;&#948;+T+cells.">CD3 bright lymphocyte population reveal &#947;&#948; T cells.</a> Cytometry Part B: Clinical Cytometry. 61 (1), 45-53 (2004).</li><li>Ginaldi, L., 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=Differential+expression+of+T+cell+antigens+in+normal+peripheral+blood+lymphocytes:+a+quantitative+analysis+by+flow+cytometry.">Differential expression of T cell antigens in normal peripheral blood lymphocytes: a quantitative analysis by flow cytometry.</a> Journal of Clinical Pathology. 49 (7), 539-544 (1996).</li><li>Park, J., Han, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-color+Multitarget+Flow+Cytometry+Using+Monoclonal+Antibodies+Labeled+with+Different+Intensities+of+the+Same+Fluorochrome.">Single-color Multitarget Flow Cytometry Using Monoclonal Antibodies Labeled with Different Intensities of the Same Fluorochrome.</a> Annals of Laboratory Medicine. 32 (3), 171-176 (2012).</li><li>Mansour, I., 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=Triple+labeling+with+two-color+immunoflorescence+using+one+light+source:+A+useful+approach+for+the+analysis+of+cells+positive+for+one+label+and+negative+for+the+other+two.">Triple labeling with two-color immunoflorescence using one light source: A useful approach for the analysis of cells positive for one label and negative for the other two.</a> Cytometry. 11 (5), 636-641 (1990).</li><li>Bocsi, J., Melzer, S., D&#228;hnert, I., T&#225;rnok, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=OMIP-023:+10-Color,+13+antibody+panel+for+in-depth+phenotyping+of+human+peripheral+blood+leukocytes.">OMIP-023: 10-Color, 13 antibody panel for in-depth phenotyping of human peripheral blood leukocytes.</a> Cytometry Part A. 85 (9), 781-784 (2014).</li><li>Van Dongen, J. J. 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=EuroFlow+antibody+panels+for+standardized+n-dimensional+flow+cytometric+immunophenotyping+of+normal,+reactive+and+malignant+leukocytes.">EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes.</a> Leukemia. 26 (9), 1908-1975 (2012).</li><li>Bradford, J. A., Buller, G., Suter, M., Ignatius, M., Beechem, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence-intensity+multiplexing:+Simultaneous+seven-marker,+two-color+immunophenotyping+using+flow+cytometry.">Fluorescence-intensity multiplexing: Simultaneous seven-marker, two-color immunophenotyping using flow cytometry.</a> Cytometry Part A. 61 (2), 142-152 (2004).</li><li>R&#252;hle, P. F., Fietkau, R., Gaipl, U. S., Frey, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+Modular+Assay+for+Detailed+Immunophenotyping+of+Peripheral+Human+Whole+Blood+Samples+by+Multicolor+Flow+Cytometry.">Development of a Modular Assay for Detailed Immunophenotyping of Peripheral Human Whole Blood Samples by Multicolor Flow Cytometry.</a> International Journal of Molecular Sciences. 17 (8), (2016).</li><li>H&#248;nge, B. L., Petersen, M. S., Olesen, R., M&#248;ller, B. K., Erikstrup, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimizing+recovery+of+frozen+human+peripheral+blood+mononuclear+cells+for+flow+cytometry.">Optimizing recovery of frozen human peripheral blood mononuclear cells for flow cytometry.</a> PLOS ONE. 12 (11), e0187440 (2017).</li><li>Roederer, 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=FACS+analysis+of+lymphocytes.">FACS analysis of lymphocytes.</a> Handbook of Experimental Immunology. 49, (1997).</li><li>Srivastava, P., Sladek, T. L., Goodman, M. N., Jacobberger, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Streptavidin-based+quantitative+staining+of+intracellular+antigens+for+flow+cytometric+analysis.">Streptavidin-based quantitative staining of intracellular antigens for flow cytometric analysis.</a> Cytometry. 13 (7), 711-721 (1992).</li><li>Maecker, H. T., 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=Selecting+fluorochrome+conjugates+for+maximum+sensitivity.">Selecting fluorochrome conjugates for maximum sensitivity.</a> Cytometry Part A. , (2004).</li><li>Noonan, K. A., 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=Adoptive+transfer+of+activated+marrow-infiltrating+lymphocytes+induces+measurable+antitumor+immunity+in+the+bone+marrow+in+multiple+myeloma.">Adoptive transfer of activated marrow-infiltrating lymphocytes induces measurable antitumor immunity in the bone marrow in multiple myeloma.</a> Science Translational Medicine. 7 (288), (2015).</li><li>Mahnke, Y. D., Beddall, M. H., Roederer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=OMIP-017:+Human+CD4++helper+T-cell+subsets+including+follicular+helper+cells.">OMIP-017: Human CD4+ helper T-cell subsets including follicular helper cells.</a> Cytometry Part A. 83 (5), 439-440 (2013).</li><li>Bonecchi, 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=Differential+Expression+of+Chemokine+Receptors+and+Chemotactic+Responsiveness+of+Type+1+T+Helper+Cells+(Th1s)+and+Th2s.">Differential Expression of Chemokine Receptors and Chemotactic Responsiveness of Type 1 T Helper Cells (Th1s) and Th2s.</a> The Journal of Experimental Medicine. 187 (1), 129-134 (1998).</li><li>Acosta-Rodriguez, E. V., 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=Surface+phenotype+and+antigenic+specificity+of+human+interleukin+17-producing+T+helper+memory+cells.">Surface phenotype and antigenic specificity of human interleukin 17-producing T helper memory cells.</a> Nature Immunology. 8 (6), 639-646 (2007).</li><li>Rivino, L., 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=Chemokine+Receptor+Expression+Identifies+Pre-T+Helper+(Th)1,+Pre-Th2,+and+Nonpolarized+Cells+among+Human+CD4++Central+Memory+T+Cells.">Chemokine Receptor Expression Identifies Pre-T Helper (Th)1, Pre-Th2, and Nonpolarized Cells among Human CD4+ Central Memory T Cells.</a> The Journal of Experimental Medicine. 200 (6), 725-735 (2004).</li><li>Ye, Z. -. 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=Differentiation+and+recruitment+of+Th9+cells+stimulated+by+pleural+mesothelial+cells+in+human+Mycobacterium+tuberculosis+infection.">Differentiation and recruitment of Th9 cells stimulated by pleural mesothelial cells in human Mycobacterium tuberculosis infection.</a> PloS One. 7 (2), e31710 (2012).</li><li>Speiser, D. 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=Human+CD8++T+cells+expressing+HLA-DR+and+CD28+show+telomerase+activity+and+are+distinct+from+cytolytic+effector+T+cells.">Human CD8+ T cells expressing HLA-DR and CD28 show telomerase activity and are distinct from cytolytic effector T cells.</a> European Journal of Immunology. 31 (2), 459-466 (2001).</li><li>Caruso, A., 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=Flow+cytometric+analysis+of+activation+markers+on+stimulated+T+cells+and+their+correlation+with+cell+proliferation.">Flow cytometric analysis of activation markers on stimulated T cells and their correlation with cell proliferation.</a> Cytometry. 27 (1), 71-76 (1997).</li><li>Brenchley, J. 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=Expression+of+CD57+defines+replicative+senescence+and+antigen-induced+apoptotic+death+of+CD8++T+cells.">Expression of CD57 defines replicative senescence and antigen-induced apoptotic death of CD8+ T cells.</a> Blood. 101 (7), 2711-2720 (2003).</li><li>Palmer, B. E., Blyveis, N., Fontenot, A. P., Wilson, C. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+and+Phenotypic+Characterization+of+CD57+CD4++T+Cells+and+Their+Association+with+HIV-1-Induced+T+Cell+Dysfunction.">Functional and Phenotypic Characterization of CD57+CD4+ T Cells and Their Association with HIV-1-Induced T Cell Dysfunction.</a> The Journal of Immunology. 175 (12), 8415-8423 (2005).</li><li>Focosi, D., Bestagno, M., Burrone, O., Petrini, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CD57++T+lymphocytes+and+functional+immune+deficiency.">CD57+ T lymphocytes and functional immune deficiency.</a> Journal of Leukocyte Biology. 87 (1), 107-116 (2010).</li></ol>

The authors have nothing to disclose.

The protocol presented here has been shown to be quite flexible and insensitive to changes in staining buffer, temperature and peripheral blood cell preparation due to the high expression of lineage markers on the cell surface. The most critical step for obtaining high-quality, reproducible data is antibody titration. Of note, since the titration of antibodies should always be performed during the setup of a flow cytometric panel, this step does not add extra bench-time to our two-fluorochrome approach. Titration of anti...

Flow cytometry is a technique that was developed to analyze multiple parameters on single particles at a rate of several thousand of events per second1. Examples of specimens analyzed by flow cytometry include, but are not limited to, cells, beads, bacteria, vesicles and chromosomes. A fluidic system directs particles at the interrogation point where each particle intersects its path with one or more lasers, and multiple parameters are recorded for further analysis. Forward and side scatters, generated by scattering of the pure laser light, are used to identify the target population and retrieve information about the relative size and internal complexity/granularity of particles, respectively. All the other parameters, that account for most of data in a flow cytometric analysis, are derived by fluorochrome-labeled probes that recognize and bind to specific targets on the particles of interest.
Flow cytometry is a primary tool for immunological studies to identify and characterize cell populations. To dissect the complexity of the immune system, multicolor panels are constantly evolving to expand the number of markers simultaneously recorded for deep immunophenotyping of cell populations1. This is leading to the development of more capable instruments and fluorochromes, with recent high-end flow cytometers exceeding 20 fluorescent parameters. This results in complex study design due to fluorochrome spectral overlap and in higher costs associated with custom antibody labelling and skilled operators. In several instances, complexity and costs are reduced by using separate panels of markers for different cell populations. This approach, however, is error prone, reduces the information in each panel, and can be difficult to apply to samples with limited number of cells. Moreover, increasing the number of markers precludes deep immunophenotyping on instruments with fewer fluorescent parameters. We previously developed a staining protocol to identify major human immune populations (CD4+ and CD8+ T cells, &#947;&#948; T cells, B cells, NK cells and monocytes) in peripheral blood mononuclear cells (PBMCs) by combining seven lineage markers using only two fluorochromes instead of the seven required using the traditional &#34;one fluorochrome-one marker&#34; approach (www.hcdm.org)2,3.&#160;Our initial report explored and validated the notion of combining seven markers in two fluorochromes for deep immunophenotyping. In this report, we present a step-by step protocol to isolate and stain peripheral blood cells, focusing on the practical aspect and troubleshooting steps to achieve a successful staining.&#160;
This protocol is based on the observation that lineage markers have a constant expression on the cell surface and that each cell population has an exclusive combination of lineage markers. In PBMCs, CD3 expression subdivides immune cells into two main categories: CD3-positive T lymphocytes and CD3-negative cells. Within the CD3 positive subgroup, CD4+, CD8+ and &#947;&#948; T cells can be separated using antibodies that solely target CD4, CD8 and the &#947;&#948; receptor. In a comparable way, within the CD3 negative subgroup, B cells, NK cells and monocytes can be uniquely identified using antibodies against CD19, CD56 and CD14, respectively. In a standard one fluorochrome-one marker approach, anti-CD3, -CD4, -CD8, -CD14, -CD19, -CD56 and -TCR &#947;&#948; antibodies are detected with seven different fluorochromes. Our approach combines anti-CD3, -CD56, and -TCR &#947;&#948; antibodies in one fluorochrome (labeled for convenience fluorochrome A) and anti-CD4, -CD8, -CD14 and -CD19 antibodies in a different fluorochrome (fluorochrome B). This is possible by a combination of antibody titration and differential antigen expression. Both CD4+ and CD8+ T cells are positive for the anti-CD3 antibody in fluorochrome A, but they can be separated in fluorochrome B maximizing the expression of the CD8 signal while placing, with an ad hoc titration, the CD4 signal in between the CD8 and the CD3 positive-CD4/CD8 double negative cells. &#947;&#948; T cells expresses higher level of CD3 than CD4 and CD8, and therefore they can be identified as CD3 high4. This signal is further boosted by labeling &#947;&#948; T cells in fluorochrome A with an anti-TCR &#947;&#948; antibodies, thus improving separation between CD3 low T cells and CD3 high &#947;&#948; T cells. B cells can be identified as CD3- in fluorochrome A and CD19+ in fluorochrome B. To separate CD3 negative NK cells from B cells, an anti-CD56 antibody was used in fluorochrome A as the anti-CD3. This is possible because CD56 expressed on NK cell at a much lower level than CD3 on T cells5. Finally, monocytes can be identified via a combination of forward-side scatter properties and expression of CD14 in fluorochrome B.
The idea of combining up to four markers using two fluorochromes has been already successfully attempted before6,7,8, and has been used in a clinical protocol to identify malignant lymphocytic populations9. A previous report also combined seven markers (with different specificity from the markers than we used in our protocol) using two fluorochromes, but this approach relied on a complex labelling of each antibody with varying amount of fluorochrome10. This is in contrast to our method which uses commercially available antibodies and can be adapted to the instrument configuration and can take advantage of the new generation of polymer fluorochromes.
The overall goal of this methodology is to expand the optical limits of most flow cytometers allowing for the recording of five additional markers to interrogate complex cell populations. As a consequence, advanced immunological analysis can be performed on affordable 6-10 fluorochrome flow cytometers, and 2-3 fluorochrome field instruments can achieve remarkable results in areas with limited resources. High-end instruments can also benefit from this approach by using extra fluorochromes to accomplish deeper flow cytometry analysis and to create modular flow cytometric panels targeting several lineages at the same time11. This can potentially reduce the number of panels used in modular immunophenotyping flow cytometry and reduce costs, errors and handling time. This approach is also very well suited in the case of clinical samples with limited number of cells.

<table><tbody><tr><td>CD3</td><td>BD Biosciences</td><td>562426</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_11152082</td></tr><tr><td>CD56</td><td>BD Biosciences</td><td>562751</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_2732054</td></tr><tr><td>TCRgd</td><td>BD Biosciences</td><td>331217</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_2562316</td></tr><tr><td>CD4</td><td>BD Biosciences</td><td>555347</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_395752</td></tr><tr><td>CD8</td><td>BD Biosciences</td><td>555367</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_395770</td></tr><tr><td>CD14</td><td>BD Biosciences</td><td>555398</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_395799</td></tr><tr><td>CD19</td><td>BD Biosciences</td><td>555413</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_395813</td></tr><tr><td>CD3</td><td>BD Biosciences</td><td>555335</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_398591</td></tr><tr><td>CD56</td><td>BD Biosciences</td><td>555518</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_398601</td></tr><tr><td>TCRgd</td><td>BD Biosciences</td><td>331211</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_1089215</td></tr><tr><td>CCR7</td><td>Biolegend</td><td>353217</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_10913812</td></tr><tr><td>CD45RA</td><td>BD Biosciences</td><td>560674</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_1727497</td></tr><tr><td>CCR4</td><td>BD Biosciences</td><td>561034</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_10563066</td></tr><tr><td>CCR6</td><td>BD Biosciences</td><td>353419</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_11124539</td></tr><tr><td>CXCR3</td><td>BD Biosciences</td><td>561730</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_10894207</td></tr><tr><td>CD57</td><td>BD Biosciences</td><td>562488</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_2737625</td></tr><tr><td>HLA-DR</td><td>BD Biosciences</td><td>563083</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_2737994</td></tr><tr><td>CD16</td><td>BD Biosciences</td><td>563784</td><td>Antibody for staining&lt;br/&gt; &lt;strong&gt;RRID&lt;/strong&gt;: AB_2744293</td></tr><tr><td>Dead cells</td><td>Life technologies</td><td>L-23105</td><td>Live/dead discrimination</td></tr><tr><td>Falcon 5 mL round-bottom polystyrene test tube with cell strainer snap cap</td><td>BD Bioscience</td><td>352235</td><td>to filter cell suspension before passing though the flow cytometer</td></tr><tr><td>Falcon 5 mL round-bottom polystyrene test tube</td><td>BD Bioscience</td><td>352001</td><td>to stain whole blood</td></tr><tr><td>Recovery Cell Culture Freezing Medium</td><td>Thermo fisher</td><td>12648010</td><td>Freezing cells</td></tr><tr><td>96-well V-bottom plate</td><td>Thermo fisher</td><td>249570</td><td>plate for staining</td></tr><tr><td>FACSAria IIu Cell Sorter</td><td>BD Biosciences</td><td></td><td>Flow cytometer</td></tr><tr><td>FCS Express 6</td><td>De Novo Software</td><td></td><td>FACS analysis</td></tr><tr><td>Graphpad Prism</td><td>GraphPad software</td><td></td><td>Data analysis</td></tr></tbody></table>

discrimination of seven immune cell subsets by two-fluorochrome flow cytometry

Immune cell characterization heavily relies on multicolor flow cytometry to identify subpopulations based on differential expression of surface markers. Setup of a classic multicolor panel requires high-end instruments, custom labeled antibodies, and careful study design to minimize spectral overlap. We developed a multiparametric analysis to identify major human immune populations (CD4+ and CD8+ T cells, &#947;&#948; T cells, B cells, NK cells and monocytes) in peripheral blood by combining seven lineage markers using only two fluorochromes. Our strategy is based on the observation that lineage markers are constantly expressed in a unique combination by each cell population. Combining this information with a careful titration of the antibodies allows investigators to record five additional markers, expanding the optical limit of most flow cytometers. Head-to-head comparison demonstrated that the vast majority of immune cell populations in peripheral blood can be characterized with comparable accuracy between our method and the classic &#34;one fluorochrome-one marker approach&#34;, although the latter is still more precise for identifying populations such as NKT cells and &#947;&#948; T cells. Combining seven markers using two fluorochromes allows for the analysis of complex immune cell populations and clinical samples on affordable 6-10 fluorochrome flow cytometers, and even on 2-3 fluorochrome field instruments in areas with limited resources. High-end instruments can also benefit from this approach by using extra fluorochromes to accomplish deeper flow cytometry analysis. This approach is also very well suited for screening several cell populations in the case of clinical samples with limited number of cells.

Setup and analysis of a flow cytometry experiment of human peripheral blood cells stained with seven lineage markers (anti-CD3, -CD4, -CD8, -CD14, -CD19, -CD56 and -TCR &#947;&#948; antibodies) using only two fluorochromes are presented.
Representative results are described for anti-CD8 and -CD56 antibody titration. For each antibody (in this example, anti-CD8), data from ten successive 2-fold dilutions were recorded to calculat...

Watch this Scientific Journal Video about Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry at JoVE.com

Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry

Here, we present a flow cytometric protocol to identify CD4+ and CD8+ T cells, &#947;&#948; T cells, B cells, NK cells and monocytes in human peripheral blood by using only two fluorochromes instead of seven. With this approach, five additional markers can be recorded on most flow cytometers.

Immune cell characterization heavily relies on multicolor flow cytometry to identify subpopulations based on differential expression of surface markers. ...

discrimination-seven-immune-cell-subsets-two-fluorochrome-flow

Research

JoVE Journal

Immunology and Infection

13.8K Views.  Medimmune, LLC. Here, we present a flow cytometric protocol to identify CD4+ and CD8+ T cells, γδ T cells, B cells, NK cells and monocytes in human peripheral blood by using only two fluorochromes instead of seven. With this approach, five additional markers can be recorded on most flow cytometers.

Video: Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry

Detection of Fluorescent Nanoparticle Interactions with Primary Immune Cell Subpopulations by Flow Cytometry

Engineered nanoparticles are endowed with very promising properties for therapeutic and diagnostic purposes. This work describes a fast and reliable method of analysis by flow cytometry to study nanoparticle interaction with immune cells. Primary immune cells can be easily purified from human or mouse tissues by antibody-mediated magnetic isolation. In the first instance, the different cell populations running in a flow cytometer can be distinguished by the forward-scattered light (FSC), which is proportional to cell size, and the side-scattered light (SSC), related to cell internal complexity. Furthermore, fluorescently labeled antibodies against specific cell surface receptors permit the identification of several subpopulations within the same sample. Often, all these features vary when cells are boosted by external stimuli that change their physiological and morphological state. Here, 50 nm FITC-SiO2 nanoparticles are used as a model to identify the internalization of nanostructured materials in human blood immune cells. The cell fluorescence and side-scattered light increase after incubation with nanoparticles allowed us to define time and concentration dependence of nanoparticle-cell interaction. Moreover, such protocol can be extended to investigate Rhodamine-SiO2 nanoparticle interaction with primary microglia, the central nervous system resident immune cells, isolated from mutant mice that specifically express the Green Fluorescent Protein (GFP) in the monocyte/macrophage lineage. Finally, flow cytometry data related to nanoparticle internalization into the cells have been confirmed by confocal microscopy.

Analysis of nanoparticle interaction with defined subpopulations of immune cells by flow cytometry.

Engineered nanoparticles are endowed with very promising properties for therapeutic and diagnostic purposes. This work describes a fast and reliable ...

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis

Monocytes are key contributors in various inflammatory disorders and alterations to these cells, including their subset proportions and functions, can have pathological significance. An ideal method for examining alterations to monocytes is whole blood flow cytometry as the minimal handling of samples by this method limits artifactual cell activation. However, many different approaches are taken to gate the monocyte subsets leading to inconsistent identification of the subsets between studies. Here we demonstrate a method using whole blood flow cytometry to identify and characterize human monocyte subsets (classical, intermediate, and non-classical). We outline how to prepare the blood samples for flow cytometry, gate the subsets (ensure contaminating cells have been removed), and determine monocyte subset expression of surface markers &#8212; in this example M1 and M2 markers. This protocol can be extended to other studies that require a standard gating method for assessing monocyte subset proportions and monocyte subset expression of other functional markers.

Here we present a protocol for characterizing monocyte subsets by whole blood flow cytometry. This includes outlining how to gate the subsets and assess their expression of surface markers and giving an example of the assessment of the expression of M1 (inflammatory) and M2 markers (anti-inflammatory).

Monocytes are key contributors in various inflammatory disorders and alterations to these cells, including their subset proportions and functions, can ...

Determination of Regulatory T Cell Subsets in Murine Thymus, Pancreatic Draining Lymph Node and Spleen Using Flow Cytometry

Our immune system consists of a number and variety of immune cells including regulatory T cells (Treg) cells. Treg cells can be divided into two subsets, thymic derived Treg (tTreg) cells and peripherally induced Treg (pTreg) cells. They are present in different organs of our body and can be distinguished by specific markers, such as Helios and Neuropilin 1. It has been reported that tTreg cells are functionally more suppressive than pTreg cells. Therefore, it is important to determine the proportion of both tTreg and pTreg cells when investigating heterogeneous cell populations. Herein, we collected thymic glands, pancreatic draining lymph nodes and spleens from normoglycemic non-obese diabetic mice to distinguish tTreg cells from pTreg cells using flow cytometry. We manually prepared single cell suspensions from these organs. Fluorochrome conjugated surface CD4, CD8, CD25, and Neuropilin 1 antibodies were used to stain the cells. They were kept in the fridge overnight. On the next day, the cells were stained with fluorochrome conjugated intracellular Foxp3 and Helios antibodies. These markers were used to characterize the two subsets of Treg cells. This protocol demonstrates a simple but practical way to prepare single cells from murine thymus, pancreatic draining lymph node and spleen and use them for subsequent flow cytometric analysis.

Herein, we present a protocol to prepare single cells from murine thymus, pancreatic draining lymph node and spleen to further study these cells using flow cytometry. In addition, this protocol was used for determining the subsets of regulatory T cells using flow cytometry.

Our immune system consists of a number and variety of immune cells including regulatory T cells (Treg) cells. Treg cells can be divided into two subsets, ...

High-Dimensionality Flow Cytometry for Immune Function Analysis of Dissected Implant Tissues

The success of implanting laboratory-grown tissue or a medical device in an individual is subject to the immune response of the recipient host. Considering an implant as a foreign body, a hostile and dysregulated immune response may result in the rejection of the implant, while a regulated response and regaining of homeostasis can lead to its acceptance. Analyzing the microenvironments of implants dissected out under in vivo or ex vivo&#160;settings can help in understanding the pattern of immune response, which can ultimately help in developing new generations of biomaterials. Flow cytometry is a well-known technique for characterizing immune cells and their subsets based on their cell surface markers. This review describes a protocol based on manual dicing, enzymatic digestion, and filtration through a cell strainer for the isolation of uniform cell suspensions from dissected implant tissue. Further, a multicolor flow cytometry staining protocol has been explained, along with steps for initial cytometer settings to characterize and quantify these isolated cells by flow cytometry.

Isolation of cells from dissected implants and their characterization by flow cytometry can significantly contribute to understanding the pattern of immune response against implants. This paper describes a precise method for the isolation of cells from dissected implants and their staining for flow cytometric analysis.

The success of implanting laboratory-grown tissue or a medical device in an individual is subject to the immune response of the recipient host. ...

Bioengineering

Flow Cytometric Characterization of Murine B Cell Development

Extensive studies have characterized the development and differentiation of murine B cells in secondary lymphoid organs. Antibodies secreted by B cells have been isolated and developed into well-established therapeutics. Validation of murine B cell development, in the context of autoimmune prone mice, or in mice with modified immune systems, is a crucial component of developing or testing therapeutic agents in mice and is an appropriate use of flow cytometry. Well established B cell flow cytometric parameters can be used to evaluate B cell development in the murine peritoneum, bone marrow, and spleen, but a number of best practices must be adhered to. In addition, flow cytometric analysis of B cell compartments should also complement additional readouts of B cell development. Data generated using this technique can further our understanding of wild type, autoimmune prone mouse models as well as humanized mice that can be used to generate antibody or antibody-like molecules as therapeutics.

We describe herein a simple analysis of the heterogeneity of the murine immune B cell compartment in the peritoneum, spleen, and bone marrow tissues by flow cytometry. The protocol can be adapted and extended to other mouse tissues.

Extensive studies have characterized the development and differentiation of murine B cells in secondary lymphoid organs. Antibodies secreted by B cells ...

Isolation of Uterine Innate Lymphoid Cells for Analysis by Flow Cytometry

Described here is a simple method to isolate and phenotype mouse group 1 uterine innate lymphoid cells (g1 uILCs) from individual pregnant uterus by flow cytometry. The protocol describes how to set up time mating to obtain multiple synchronous dams, the mechanical and enzymatic digestion of the pregnant uterus, the staining of single-cell suspensions, and a FACS strategy to phenotype and discriminate g1 uILCs. Although this method inevitably loses the spatial information of cellular distribution within the tissue, the protocol has been successfully applied to determine uILC heterogeneity, their response to maternal and foetal factors affecting pregnancy, their gene expression profile, and their functions.

This is a method to isolate uterine lymphoid cells from both pregnant and non-pregnant mice. This method can be used for multiple downstream applications such as FACS phenotyping, cell sorting, functional assays, RNA-seq, and proteomics. The protocol here demonstrates how to phenotype group 1 uterine innate lymphoid cells by flow cytometry.

Described here is a simple method to isolate and phenotype mouse group 1 uterine innate lymphoid cells (g1 uILCs) from individual pregnant uterus by flow ...

Flow Cytometry Analysis of Immune Cell Subsets within the Murine Spleen, Bone Marrow, Lymph Nodes and Synovial Tissue in an Osteoarthritis Model

Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases, affecting patients suffering from pain and physical limitations. Recent evidence indicates a potential inflammatory component of the disease, with both T-cells and monocytes/macrophages potentially associated with the pathogenesis of OA. Further studies postulated an important role for subsets of both inflammatory cell lineages, such as Th1, Th2, Th17, and T-regulatory lymphocytes, and M1, M2, and synovium-tissue-resident macrophages. However, the interaction between the local synovial and systemic inflammatory cellular response and the structural changes in the joint is unknown. To fully understand how T-cells and monocytes/macrophages contribute towards OA, it is important to be able to quantitively identify these cells and their subsets simultaneously in synovial tissue, secondary lymphatic organs and systemically (the spleen and bone marrow). Nowadays, the different inflammatory cell subsets can be identified by a combination of cell-surface markers making multi-color flow cytometry a powerful technique in investigating these cellular processes. In this protocol, we describe detailed steps regarding the harvest of synovial tissue and secondary lymphatic organs as well as generation of single cell suspensions. Furthermore, we present both an extracellular staining assay to identify monocytes/macrophages and their subsets as well as an extra- and intra-cellular staining assay to identify T-cells and their subsets within the murine spleen, bone marrow, lymph nodes and synovial tissue. Each step of this protocol was optimized and tested, resulting in a highly reproducible assay that can be utilized for other surgical and non-surgical OA mouse models.

Here, we describe a detailed and reproducible flow cytometry protocol to identify monocyte/macrophage and T-cell subsets using both extra- and intracellular staining assays within the murine spleen, bone marrow, lymph nodes and synovial tissue, utilizing an established surgical model of murine osteoarthritis.

Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases, affecting patients suffering from pain and physical limitations. Recent ...

Medicine

Analysis of Cell Suspensions Isolated from Solid Tissues by Spectral Flow Cytometry

Flow cytometry has been used for the past 40 years to define and analyze the phenotype of lymphoid and other hematopoietic cells. Initially restricted to the analysis of a few fluorochromes, currently there are dozens of different fluorescent dyes, and up to 14-18 different dyes can be combined at a time. However, several limitations still impair the analytical capabilities. Because of the multiplicity of fluorescent probes, data analysis has become increasingly complex due to the need of large, multi-parametric compensation matrices. Moreover, mutant mouse models carrying fluorescent proteins to detect and trace specific cell types in different tissues have become available, so the analysis (by flow cytometry) of auto-fluorescent cell suspensions obtained from solid organs is required. Spectral flow cytometry, which distinguishes the shapes of emission spectra along a wide range of continuous wavelengths, addresses some of these problems. The data is analyzed with an algorithm that replaces compensation matrices and treats auto-fluorescence as an independent parameter. Thus, spectral flow cytometry should be capable of discriminating fluorochromes with similar emission peaks and can provide a multi-parametric analysis without compensation requirements.
This protocol describes the spectral flow cytometry analysis, allowing for a 21-parameter (19 fluorescent probes) characterization and the management of an auto-fluorescent signal, providing high resolution in minor population detection. The results presented here show that spectral flow cytometry presents advantages in the analysis of cell populations from tissues difficult to characterize in conventional flow cytometry, such as the heart and the intestine. Spectral flow cytometry thus demonstrates the multi-parametric analytical capacity of high-performing conventional flow cytometry without the requirement for compensation and enables auto-fluorescence management.

This article describes spectral cytometry, a new approach in flow cytometry that uses the shapes of emission spectra to distinguish fluorochromes. An algorithm replaces compensations and can treat auto-fluorescence as an independent parameter. This new approach allows for the proper analysis of cells isolated from solid organs.

Flow cytometry has been used for the past 40 years to define and analyze the phenotype of lymphoid and other hematopoietic cells. Initially restricted to ...

Biology

Isolation of CD4+ T-cells and Analysis of Circulating T-follicular Helper (cTfh) Cell Subsets from Peripheral Blood Using 6-color Flow Cytometry

Aberrant T-follicular helper (Tfh) cell activity is detectable in autoimmune conditions and their presence is associated with clinical outcomes when the lymph node microenvironment in B-cell non-Hodgkin&#39;s lymphoma is analyzed. Subsets of circulating T-follicular helper cells (cTfh), the circulating memory compartment of Tfh cells in the blood, are also perturbed in disease and therefore represent potential novel predictive biomarkers. Peripheral blood-based testing is advantageous because it is relatively non-invasive and allows simple serial monitoring.This article describes a method for isolating CD4+ T-cells from human blood, and further analysis by flow-cytometry to enumerate cTfh cells and the proportions of their various subsets (cTfhPD-1-/+/hi, cTfh1,2,17 and cTfh1/17). The level of these subsets was then compared between normal subjects and patients with lymphoma. We found that the method was robust enough to obtain reliable results from routinely collected patient material. The technique we describe for the analysis can be easily adapted to cell sorting and downstream applications such as RT-PCR.

Isolation of CD4+ T-cells and Analysis of Circulating T-follicular Helper cTfh Cell Subsets from Peripheral Blood Using 6-color Flow Cytometry

Here, a protocol for the isolation and characterization of CD4+ T-cell subsets from human peripheral blood is described. Purified CD4+ T-cells are analyzed by flow cytometry to determine proportions of T-follicular helper cell subsets.

Aberrant T-follicular helper (Tfh) cell activity is detectable in autoimmune conditions and their presence is associated with clinical outcomes when the ...

Flow Cytometry and Fluorescence-Activated Cell Sorting (FACS): Isolation of Splenic B Lymphocytes

Source: Perchet Thibaut1,2,3, Meunier Sylvain1,2,3, Sophie Novault4, Rachel Golub1,2,3 
1 Unit for Lymphopoiesis, Department of Immunology, Pasteur Institute, Paris, France 
2 INSERM U1223, Paris, France 
3 Universit&#233; Paris Diderot, Sorbonne Paris Cit&#233;, Cellule Pasteur, Paris, France 
4 Flow Cytometry Platfrom, Cytometry and Biomarkers UtechS, Center for Translational Science, Pasteur Institute, Paris, France
The overall function of the immune system is to defend the body against infectious organisms and other invaders. White blood cells, or leukocytes, are the key players of the immune system. Upon infection, they are activated and initiate an immune response. Leukocytes can be divided into various sub-populations (e.g., myeloid cells, lymphocytes, dendritic cells) based on different parameters that can be biological, physical, and/or functional (e.g., size, granularity, and secretion). One way to characterize leukocytes is through their surface proteins, which are mainly receptors. Each leukocyte population expresses a specific combination of receptors (e.g., cytotoxic, activating, migration receptors) that can define subsets among populations. As the immune system encompasses a wide range of cell populations, it is essential to characterize them to decipher their participation in the immune response.
Flow cytometry (FC or FCM) is a widely used method for analyzing the expression of cell surface and intracellular molecules, characterizing and defining different cell types in a heterogenous cell mixture. Flow cytometers are composed of three main sub-systems: fluidics, optics, and electronics. The fluidics system transports the cells in a stream such that they pass in front of a laser one by one. The optics system consists of light sources (lasers) to illuminate the particles, optical filters to direct the resulting light, and fluorescent signals to appropriate detectors. Finally, the electronics system converts the detected light signals into electronic signals that can be processed by the computer. As an individual cell passes in front of the laser beam, it scatters light. A detector in front of the beam measures forward scatter (FS) and several detectors to the side measure side scatter (SC). The FS correlates with cell size and SC is proportional to the granularity of the cells. In this manner, cell populations can often be distinguished based on differences in their size and granularity alone.
In addition to analyzing a cell&#39;s size, shape, and complexity, flow cytometry is widely used for detecting the expression of cell surface receptors (1). This is accomplished by using fluorochrome-labelled monoclonal antibodies which bind to known cell-specific receptors. Upon excitation, these bound fluorochromes emit a light of specific wavelength, called emission wavelength, which can be detected and scored. Fluorescence measurements provide quantitative and qualitative data about fluorochrome-labeled cell surface receptors. Hematologists were first to use FC for the therapeutic follow up of immune cell populations (2). Now, it is used for a wide range of applications such as immunophenotyping, cell viability, gene expression, cell counting, and GFP analysis.
FACS (Fluorescent Activated Cell Sorter) is a specialized type of flow cytometry, which sorts a population of cells into subpopulation using fluorescent labelling. Just like conventional flow cytometry, first FS, SC, and fluorescent data are collected. Then, the machine applies a charge (negative or positive) and an electrostatic deflection system (electromagnets) facilitates the collection of charged droplets containing cells into appropriate tubes.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/10494/10494fig1.jpg" /> 
Figure 1: Schematic representation of FACS. Sample (1) is aspirated in the FACS (2) and passed in front of the laser (3). Cell fluorescence is sensed by fluorescence detectors (4). Finally, cells are incorporated in droplets and the cells of interest are deflected by deflection plates (5) and collected in a collection tube (6). The remaining cells go into the trash (7). <a href="https://www.jove.com/files/ftp_upload/10494/10494fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The sorting aspect of the FACS presents many advantages. Many tests can help understand the role of specific cells in immune system, such as analyses of gene expression like RT-qPCR, cell cycle, or cytokine secretion. However, cells should be purified upstream to obtain clear and specific results. Here, FACS comes in useful and the desired cells can be sorted with great purity, yielding highly reliable and reproducible results. FACS can also be used to sort cells based on nuclear or other intracellular staining and according to the presence, absence, and density of surface receptors. FACS is now a standard technique for the purification of subpopulations of cells and has the ability sort up to four populations simultaneously.
This lab exercise demonstrates how to isolate splenic leukocytes and then how to specifically sort B lymphoid cells from the splenic leukocyte cell mixture using FACS.