a flow cytometry assay to identify immune cell subsets in peripheral blood mononuclear cells

A Flow Cytometry Assay to Identify Immune Cell Subsets in Peripheral Blood Mononuclear Cells

To prepare the PBMCs for staining, transfer 100 microliters of each sample to a 96-well V-bottom plate. Centrifuge the plate at 350 times g for three minutes at room temperature. Carefully, aspirate the supernatant without disturbing the cell pellet. To each well, add 100 microliters of PBS containing a live/dead fixable dye that reacts with free amine on proteins, and resuspend the PBMC mixture carefully.
Subsequently, allow the plate to sit for 10 minutes at room temperature for labeling of dead cells. For each sample, prepare 30 microliters of a mix containing all seven antibodies. At this stage, titrated antibodies against different target molecules and in different fluorochromes can be added as well. Centrifuge the 96-well plate at 350 times g for three minutes at room temperature, 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 minutes at room temperature in the dark. After 30 minutes, add 150 microliters of staining buffer to each well, and centrifuge the plate at 350 times g for three minutes at room temperature. Carefully aspirate the supernatant without disturbing the cell pellet, and resuspend the cells in 200 microliters of PBS. The cells are now ready for flow cytometry analysis.
To begin this two-fluorochrome, seven-marker gating strategy, select the lymphocyte gate and create a dot-plot with one of the two fluorochromes used in this protocol on each axis. Gate on CD8-positive T cells, identified as CD3 and CD8 double-positive cells at the top-right corner of the dot-plot. Exclude the dim CD8 population, which might contain NK T cells. Gate on CD4-positive T cells, identified as the population in between CD8-positive T cells and the CD3 single-positive populations.
Gate on gamma-delta T cells, identified as high CD3 cells. Subdivide gamma-delta T cells to CD8-positive and CD8-negative. Gate on NK cells, identified as the population in between CD3-positive and CD3-negative cells. Subdivide the NK cells to CD8-positive and CD8-negative Gate on B cells, identified as the CD3-negative, CD19-positive population on the lower right corner of the dot-plot.
Select the monocyte gate and create a dot-plot with one of the two fluorochromes used in this protocol on each axis. Gate on the CD3-negative, CD14-positive population.

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All procedures involving sample collection have been performed in accordance with the institute&#39;s IRB guidelines.
NOTE: This protocol has been tested on freshly or frozen isolated peripheral blood cells and whole blood.
1. Cell Staining
NOTE: Choosing pairs of fluorochromes with virtually no spectral overlap is important to reduce the spread of data due to the high spillover of a fluorochrome in the other fluorochrome detector. To achieve an optimal identification of all 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&#8203;
	<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 results.</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 phosphate-buffered saline (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 fluorochrome A, and anti-CD4, CD8, CD19, CD14 in fluorochrome B). The concentrations of antibodies are indicated in Table 1 and Table 2. 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% bovine serum albumin (BSA), PBS/0.2% sodium azide or PBS/0.5% BSA/0.1% sodium azide were used with similar results to dilute antibodies. Cells can also be stained in volumes different from 30 &#181;L to easily integrate this methodology into 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 antibodies. 
		NOTE: Stained cells can be fixed within 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>
</ol>
2. 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 index. 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 curve. 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 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 the 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 a fraction of the antibody dilution (e.g., 1:10 dilution = 0.1), and identify the concentration of the antibody with the maximum stain index value (Figure 1C).</li>
	</ol>
	</li>
	<li>Anti-CD4 and -CD56 antibody titration 
	NOTE: Anti-CD4 and -CD56 antibody titration relies on the previous titration of 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 allows to separate CD4+ 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>
3. 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 profiles.</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>
Table 1: Antibody panel used for the two-fluorochrome immune-cell staining of PBMC (BV421-PE combination).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Target</td>
			<td>Clone</td>
			<td>Fluorochrome</td>
			<td>Vendor</td>
			<td>Concentration</td>
			<td>Purpose</td>
		</tr>
		<tr>
			<td>CD3</td>
			<td>UCHT1</td>
			<td>BV421</td>
			<td>BD</td>
			<td>1/20</td>
			<td>Lineage</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>NCAM16.2</td>
			<td>BV421</td>
			<td>BD</td>
			<td>1/900</td>
			<td></td>
		</tr>
		<tr>
			<td>TCR&#947;&#948;</td>
			<td>B1</td>
			<td>BV421</td>
			<td>Bio</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CD4</td>
			<td>RPA-T4</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/450</td>
			<td></td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>RPA-T8</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/20</td>
			<td></td>
		</tr>
		<tr>
			<td>CD14</td>
			<td>M5E2</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/15</td>
			<td></td>
		</tr>
		<tr>
			<td>CD19</td>
			<td>HIB19</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/300</td>
			<td></td>
		</tr>
		<tr>
			<td>Dead cells</td>
			<td></td>
			<td>L/D Blue</td>
			<td>LT</td>
			<td>1/300</td>
			<td>Live/Dead discrimination</td>
		</tr>
		<tr>
			<td colspan="6">BD = BD Biosciences, Bio = BioLegend, LT = Life Technologies</td>
		</tr>
	</tbody>
</table>
Table 2: Antibody panel used for the two-fluorochrome immune-cell staining of PBMC (APC-PE combination).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Target</td>
			<td>Clone</td>
			<td>Fluorochrome</td>
			<td>Vendor</td>
			<td>Concentration</td>
			<td>Purpose</td>
		</tr>
		<tr>
			<td>CD3</td>
			<td>UCHT1</td>
			<td>APC</td>
			<td>BD</td>
			<td>1/20</td>
			<td>Lineage</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>NCAM16.2</td>
			<td>APC</td>
			<td>BD</td>
			<td>1/60</td>
			<td></td>
		</tr>
		<tr>
			<td>TCR&#947;&#948;</td>
			<td>B1</td>
			<td>APC</td>
			<td>Bio</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CD4</td>
			<td>RPA-T4</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/450</td>
			<td></td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>RPA-T8</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/20</td>
			<td></td>
		</tr>
		<tr>
			<td>CD14</td>
			<td>M5E2</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/15</td>
			<td></td>
		</tr>
		<tr>
			<td>CD19</td>
			<td>HIB19</td>
			<td>PE</td>
			<td>BD</td>
			<td>1/300</td>
			<td></td>
		</tr>
		<tr>
			<td>Dead cells</td>
			<td></td>
			<td>L/D Blue</td>
			<td>LT</td>
			<td>1/300</td>
			<td>Live/Dead discrimination</td>
		</tr>
		<tr>
			<td colspan="6">BD = BD Biosciences, Bio = BioLegend, LT = Life Technologies</td>
		</tr>
	</tbody>
</table>
Table 3: Antibody panel used to stain frozen PBMC from a patient with multiple myeloma.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Target</td>
			<td>Clone</td>
			<td>Fluorochrome</td>
			<td>Catalog</td>
			<td>Vendor</td>
			<td>Concentration</td>
			<td>Purpose</td>
		</tr>
		<tr>
			<td>CD3</td>
			<td>UCHT1</td>
			<td>BV421</td>
			<td>562426</td>
			<td>BD</td>
			<td>1/20</td>
			<td>Lineage</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>NCAM16.2</td>
			<td>BV421</td>
			<td>562751</td>
			<td>BD</td>
			<td>1/900</td>
			<td></td>
		</tr>
		<tr>
			<td>TCR&#947;&#948;</td>
			<td>B1</td>
			<td>BV421</td>
			<td>331217</td>
			<td>Bio</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CD4</td>
			<td>RPA-T4</td>
			<td>PE</td>
			<td>555347</td>
			<td>BD</td>
			<td>1/450</td>
			<td></td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>RPA-T8</td>
			<td>PE</td>
			<td>555367</td>
			<td>BD</td>
			<td>1/20</td>
			<td></td>
		</tr>
		<tr>
			<td>CD14</td>
			<td>M5E2</td>
			<td>PE</td>
			<td>555398</td>
			<td>BD</td>
			<td>1/15</td>
			<td></td>
		</tr>
		<tr>
			<td>CD19</td>
			<td>HIB19</td>
			<td>PE</td>
			<td>555413</td>
			<td>BD</td>
			<td>1/300</td>
			<td></td>
		</tr>
		<tr>
			<td>CCR7</td>
			<td>G043H7</td>
			<td>AF647</td>
			<td>353217</td>
			<td>Bio</td>
			<td>1/30</td>
			<td>Differentiation</td>
		</tr>
		<tr>
			<td>CD45RA</td>
			<td>HI100</td>
			<td>APC-H7</td>
			<td>560674</td>
			<td>BD</td>
			<td>1/60</td>
			<td></td>
		</tr>
		<tr>
			<td>CCR4</td>
			<td>1G1</td>
			<td>PE-Cy7</td>
			<td>561034</td>
			<td>BD</td>
			<td>1/60</td>
			<td>Th subsets</td>
		</tr>
		<tr>
			<td>CCR6</td>
			<td>G034-E3</td>
			<td>BV605</td>
			<td>353419</td>
			<td>Bio</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CXCR3</td>
			<td>1C6/CXCR3</td>
			<td>AF488</td>
			<td>561730</td>
			<td>BD</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CD57</td>
			<td>NK-1</td>
			<td>PE-CF594</td>
			<td>562488</td>
			<td>BD</td>
			<td>1/900</td>
			<td>Activation/Exhaustion</td>
		</tr>
		<tr>
			<td>HLA-DR</td>
			<td>G46-6</td>
			<td>BV510</td>
			<td>563083</td>
			<td>BD</td>
			<td>1/30</td>
			<td></td>
		</tr>
		<tr>
			<td>CD16</td>
			<td>3G8</td>
			<td>BUV395</td>
			<td>563784</td>
			<td>BD</td>
			<td>1/30</td>
			<td>NK, Monocyte activation</td>
		</tr>
		<tr>
			<td colspan="2">Dead cells</td>
			<td>L/D Blue</td>
			<td>L-23105</td>
			<td>LT</td>
			<td>1/300</td>
			<td>Live/Dead discrimination</td>
		</tr>
	</tbody>
</table>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>CD3</td>
			<td>BD Biosciences</td>
			<td>562426</td>
			<td>Antibody for staining 
			RRID: AB_11152082</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>BD Biosciences</td>
			<td>562751</td>
			<td>Antibody for staining 
			RRID: AB_2732054</td>
		</tr>
		<tr>
			<td>TCRgd</td>
			<td>BD Biosciences</td>
			<td>331217</td>
			<td>Antibody for staining 
			RRID: AB_2562316</td>
		</tr>
		<tr>
			<td>CD4</td>
			<td>BD Biosciences</td>
			<td>555347</td>
			<td>Antibody for staining 
			RRID: AB_395752</td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>BD Biosciences</td>
			<td>555367</td>
			<td>Antibody for staining 
			RRID: AB_395770</td>
		</tr>
		<tr>
			<td>CD14</td>
			<td>BD Biosciences</td>
			<td>555398</td>
			<td>Antibody for staining 
			RRID: AB_395799</td>
		</tr>
		<tr>
			<td>CD19</td>
			<td>BD Biosciences</td>
			<td>555413</td>
			<td>Antibody for staining 
			RRID: AB_395813</td>
		</tr>
		<tr>
			<td>CD3</td>
			<td>BD Biosciences</td>
			<td>555335</td>
			<td>Antibody for staining 
			RRID: AB_398591</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>BD Biosciences</td>
			<td>555518</td>
			<td>Antibody for staining 
			RRID: AB_398601</td>
		</tr>
		<tr>
			<td>TCRgd</td>
			<td>BD Biosciences</td>
			<td>331211</td>
			<td>Antibody for staining 
			RRID: AB_1089215</td>
		</tr>
		<tr>
			<td>CCR7</td>
			<td>Biolegend</td>
			<td>353217</td>
			<td>Antibody for staining 
			RRID: AB_10913812</td>
		</tr>
		<tr>
			<td>CD45RA</td>
			<td>BD Biosciences</td>
			<td>560674</td>
			<td>Antibody for staining 
			RRID: AB_1727497</td>
		</tr>
		<tr>
			<td>CCR4</td>
			<td>BD Biosciences</td>
			<td>561034</td>
			<td>Antibody for staining 
			RRID: AB_10563066</td>
		</tr>
		<tr>
			<td>CCR6</td>
			<td>BD Biosciences</td>
			<td>353419</td>
			<td>Antibody for staining 
			RRID: AB_11124539</td>
		</tr>
		<tr>
			<td>CXCR3</td>
			<td>BD Biosciences</td>
			<td>561730</td>
			<td>Antibody for staining 
			RRID: AB_10894207</td>
		</tr>
		<tr>
			<td>CD57</td>
			<td>BD Biosciences</td>
			<td>562488</td>
			<td>Antibody for staining 
			RRID: AB_2737625</td>
		</tr>
		<tr>
			<td>HLA-DR</td>
			<td>BD Biosciences</td>
			<td>563083</td>
			<td>Antibody for staining 
			RRID: AB_2737994</td>
		</tr>
		<tr>
			<td>CD16</td>
			<td>BD Biosciences</td>
			<td>563784</td>
			<td>Antibody for staining 
			RRID: 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>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>

Source: Torchia, M. L. G., et al. <a href="https://app.jove.com/v/58955">Discrimination of Seven Immune Cell Subsets by Two-fluorochrome Flow Cytometry.</a> J. Vis. Exp. (2019)
This video demonstrates a flow cytometry-based technique using two fluorochromes to identify CD4+ and CD8+ T cells, &#947;&#948; T cells, B cells, natural killer (NK) cells, and monocytes in human peripheral blood mononuclear cells (PBMCs). Upon incubating the cells with fluorochrome-conjugated antibodies against the surface markers, the cell subsets are identified using an optimal flow cytometric gating strategy.

<img alt="Figure 1" src="/files/ftp_upload/21987/21987_Figure1.jpg" /> 
Figure 1: Representative antibody titration. (A) The dot plot shows CD8 expression on fresh PBMC stained with the indicated concentration of the antibody. (B) The table represents the median and standard deviation of fluorescent intensity of the CD8+, median fluorescent intensity CD8- population, and the derived stain index for each concentration tested. (<strong...

All procedures involving sample collection have been performed in accordance with the institute&#39;s IRB guidelines.
NOTE: This protocol has been tested ...

Take peripheral blood mononuclear cells or PBMCs, a mixed-cell population including lymphocytes and monocytes.
Add a fluorescent viability dye to discriminate dead cells, and a fluorescently labeled antibody cocktail to identify different cell types.
The fluorochrome &#160;A-conjugated antibodies bind to surface markers &#8212; CD3 on T cells, &#947;&#948; T cell receptor or TCR on &#947;&#948; T cells, and CD56 on natural killer or NK cells.
The fluorochrome B-conjugated antibodies bind to CD4 and CD8 on T cells, CD19 on B cells, and CD14 on monocytes.
Using flow cytometry, identify the live cell subsets.
While CD8+ and CD4+ T cells are CD3+, CD4+ cells lie between CD3 single-positive and CD3-CD8 double-positive cells.
&#947;&#948; T cells express &#947;&#948; TCRs and higher CD3 compared to CD4+ and CD8+ cells.
B cells and NK cells are CD3- but are identified by CD19 on B cells and CD56 on NK cells.
Monocytes are identified by CD14 expression.

133 조회수. 말초 혈액 단핵 세포에서 면역 세포 subset을 식별하기 위한 유세포 분석 분석

비디오: 말초 혈액 단핵 세포에서 면역 세포 subset을 식별하기 위한 유세포 분석 분석 - 실험

Obtaining Human Microglia from Adult Human Brain Tissue

Microglia are resident innate immune cells of the central nervous system (CNS). Microglia play a critical role during development, in maintaining homeostasis, and during infection or injury. Several independent research groups have highlighted the central role that microglia play in autoimmune diseases, autoinflammatory syndromes and cancers. The activation of microglia in some neurological diseases may directly participate in pathogenic processes. Primary microglia are a powerful tool to understand the immune responses in the brain, cell-cell interactions and dysregulated microglia phenotypes in disease. Primary microglia mimic in vivo microglial properties better than immortalized microglial cell lines. Human adult microglia exhibit distinct properties as compared to human fetal and rodent microglia. This protocol provides an efficient method for isolation of primary microglia from adult human brain. Studying these microglia can provide critical insights into cell-cell interactions between microglia and other resident cellular populations in the CNS including, oligodendrocytes, neurons and astrocytes. Additionally, microglia from different human brains may be cultured for characterization of unique immune responses for personalized medicine and a myriad of therapeutic applications.

This protocol is an efficient, cost effective and robust method of isolating primary microglia from live, adult, human brain tissue. Isolated primary human microglia can serve as a tool for studying cellular processes in homeostasis and disease.

성인 인간 뇌 조직에서 인간 마이크로글리아 획득

Microglia are resident innate immune cells of the central nervous system (CNS). Microglia play a critical role during development, in maintaining ...

연구

JoVE Journal

신경과학

Standardization of Transfer across Labs between Flow Cytometers for Detection of Lymphocytes in Japanese Encephalitis Vaccinated Children

An increasing number of laboratories need to collect data from multiple flow cytometers, especially for research projects performed across multiple centers. The challenges of using two flow cytometers in different labs include the lack of standardized materials, software compatibility issues, inconsistencies in instrument setup, and the use of different configurations for different flow cytometers. To establish a standardized flow cytometry experiment to achieve the consistency and comparability of experimental results across multiple centers, a rapid and feasible standardization method was established to transfer parameters across different flow cytometers. 
The methods developed in this study allowed the transfer of experimental settings and analysis templates between two flow cytometers in different laboratories for the detection of lymphocytes in Japanese encephalitis (JE)-vaccinated children. A consistent fluorescence intensity was obtained between the two cytometers using fluorescence standard beads to establish the cytometer settings. Comparable results were obtained in two laboratories with different types of instruments. Using this method, we can standardize analysis for evaluating the immune function of JE-vaccinated children in different laboratories with different instruments, diminish the differences in data and results among flow cytometers in multiple centers, and provide a feasible approach for the mutual accreditation of laboratory results. The standardization method of flow cytometer experiments will ensure the effective performance of research projects across multiple centers.

In this study, a method was developed to facilitate the transfer of experimental settings and analysis templates between two flow cytometers in two laboratories for the detection of lymphocytes in Japanese encephalitis-vaccinated children. The standardization method for the flow cytometer experiments will allow research projects to be effectively conducted in multiple centers.

일본 뇌염 예방 접종 아동의 림프구 검출을 위한 유세포 분석기 간 실험실 간 이동 표준화

An increasing number of laboratories need to collect data from multiple flow cytometers, especially for research projects performed across multiple ...

면역학 및 감염병학

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.

CD4의 격리+ T-세포 및 분석의 순환 T-follicular 도우미 (cTfh) 6 컬러 Flow Cytometry 주변 혈액을 사용 하 여에서 셀 하위 집합

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

A Flow Cytometry Assay to Identify Immune Cell Subsets in Peripheral Blood Mononuclear Cells

내레이션 대본

A Flow Cytometry Assay to Identify Immune Cell Subsets in Peripheral Blood Mononuclear Cells