Name: isolation of cd4+ t-cells and analysis of circulating t-follicular helper (ctfh) cell subsets from peripheral blood using 6-color flow cytometry
Uploaded: 2019-01-07T14:00:00
Description: Watch this Scientific Journal Video about Isolation of CD4+ T-cells and Analysis of Circulating T-follicular Helper cTfh Cell Subsets from Peripheral Blood Using 6-color Flow Cytometry at JoVE.com

The work was supported by a grant from Leukaemia UK to ETB and MJA.

Blood samples were obtained from normal subjects (NS) (n = 12) as well as patients with marginal zone lymphoma (MZL) (n = 7) and other types of B-cell non-Hodgkin&#39;s lymphoma (BNHL) (6 FL patients, 2 lymphoplasmacytic lymphoma patients and 1 low-grade B-cell non-Hodgkin&#39;s lymphoma not otherwise specified patient). Patients were recruited from the hematology clinics at Leicester Royal Infirmary after having given informed, written consent, with ethical approval in place for all studies. Ethical approval was obtaine...

<ol>
	<li>Vinuesa, C. G., Linterman, M. A., Yu, D., MacLennan, I. C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Follicular+Helper+T+Cells.">Follicular Helper T Cells.</a> Annual Review of Immunology. 34 (1), 335-368 (2016).</li><li>Nurieva, R. 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=Bcl6+Mediates+the+Development+of+T+Follicular+Helper+Cells.">Bcl6 Mediates the Development of T Follicular Helper Cells.</a> Science. 325 (5943), 1001-1005 (2009).</li><li>Breitfeld, D., 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=Follicular+B+Helper+T+Cells+Express+Cxc+Chemokine+Receptor+5,+Localize+to+B+Cell+Follicles,+and+Support+Immunoglobulin+Production.">Follicular B Helper T Cells Express Cxc Chemokine Receptor 5, Localize to B Cell Follicles, and Support Immunoglobulin Production.</a> The Journal of Experimental Medicine. 192 (11), 1545-1552 (2000).</li><li>Linterman, M. 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=Follicular+helper+T+cells+are+required+for+systemic+autoimmunity.">Follicular helper T cells are required for systemic autoimmunity.</a> The Journal of Experimental Medicine. 206 (3), 561-576 (2009).</li><li>Bindea, G., 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=Spatiotemporal+Dynamics+of+Intratumoral+Immune+Cells+Reveal+the+Immune+Landscape+in+Human+Cancer.">Spatiotemporal Dynamics of Intratumoral Immune Cells Reveal the Immune Landscape in Human Cancer.</a> Immunity. 39 (4), 782-795 (2013).</li><li>Gu-Trantien, C., 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=CD4++follicular+helper+T+cell+infiltration+predicts+breast+cancer+survival.">CD4+ follicular helper T cell infiltration predicts breast cancer survival.</a> The Journal of Clinical Investigation. 123 (7), 2873-2892 (2013).</li><li>Am&#233;-Thomas, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+intratumoral+follicular+helper+T+cells+in+follicular+lymphoma:+role+in+the+survival+of+malignant+B+cells.">Characterization of intratumoral follicular helper T cells in follicular lymphoma: role in the survival of malignant B cells.</a> Leukemia. 26 (5), 1053-1063 (2012).</li><li>Bossaller, 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=ICOS+Deficiency+Is+Associated+with+a+Severe+Reduction+of+CXCR5+CD4+Germinal+Center+Th+Cells.">ICOS Deficiency Is Associated with a Severe Reduction of CXCR5+CD4 Germinal Center Th Cells.</a> The Journal of Immunology. 177 (7), 4927-4932 (2006).</li><li>Morita, 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=Human+Blood+CXCR5+CD4++T+Cells+Are+Counterparts+of+T+Follicular+Cells+and+Contain+Specific+Subsets+that+Differentially+Support+Antibody+Secretion.">Human Blood CXCR5+CD4+ T Cells Are Counterparts of T Follicular Cells and Contain Specific Subsets that Differentially Support Antibody Secretion.</a> Immunity. 34 (1), 108-121 (2011).</li><li>Locci, 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=Human+circulating+PD-1+CXCR3-CXCR5++memory+Tfh+cells+are+highly+functional+and+correlate+with+broadly+neutralizing+HIV+antibody+responses.">Human circulating PD-1+CXCR3-CXCR5+ memory Tfh cells are highly functional and correlate with broadly neutralizing HIV antibody responses.</a> Immunity. 39 (4), 758-769 (2013).</li><li>He, 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=Circulating+Precursor+CCR7loPD-1hi+CXCR5++CD4++T+Cells+Indicate+Tfh+Cell+Activity+and+Promote+Antibody+Responses+upon+Antigen+Reexposure.">Circulating Precursor CCR7loPD-1hi CXCR5+ CD4+ T Cells Indicate Tfh Cell Activity and Promote Antibody Responses upon Antigen Reexposure.</a> Immunity. 39 (4), 770-781 (2013).</li><li>Schmitt, N., Bentebibel, S. -. E., Ueno, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotype+and+functions+of+memory+Tfh+cells+in+human+blood.">Phenotype and functions of memory Tfh cells in human blood.</a> Trends in Immunology. 35 (9), 436-442 (2014).</li><li>Simpson, N., 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=Expansion+of+circulating+T+cells+resembling+follicular+helper+T+cells+is+a+fixed+phenotype+that+identifies+a+subset+of+severe+systemic+lupus+erythematosus.">Expansion of circulating T cells resembling follicular helper T cells is a fixed phenotype that identifies a subset of severe systemic lupus erythematosus.</a> Arthritis and Rheumatism. 62 (1), 234-244 (2010).</li><li>Wang, 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=High+frequencies+of+activated+B+cells+and+T+follicular+helper+cells+are+correlated+with+disease+activity+in+patients+with+new-onset+rheumatoid+arthritis.">High frequencies of activated B cells and T follicular helper cells are correlated with disease activity in patients with new-onset rheumatoid arthritis.</a> Clinical and Experimental Immunology. 174 (2), 212-220 (2013).</li><li>Ueno, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+Circulating+T+Follicular+Helper+Cell+Subsets+in+Health+and+Disease.">Human Circulating T Follicular Helper Cell Subsets in Health and Disease.</a> Journal of Clinical Immunology. 36, 34-39 (2016).</li><li>Maecker Holden, T., Trotter, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+cytometry+controls,+instrument+setup,+and+the+determination+of+positivity.">Flow cytometry controls, instrument setup, and the determination of positivity.</a> Cytometry Part A. 69 (9), 1037-1042 (2006).</li><li>Jia, Y., 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=Impaired+Function+of+CD4++T+Follicular+Helper+(Tfh)+Cells+Associated+with+Hepatocellular+Carcinoma+Progression.">Impaired Function of CD4+ T Follicular Helper (Tfh) Cells Associated with Hepatocellular Carcinoma Progression.</a> PLOS ONE. 10 (2), 0117458 (2015).</li><li>Byford, E. T., Carr, M., Ladikou, E., Ahearne, M. J., Wagner, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Circulating+Tfh1+(cTfh1)+cell+numbers+and+PD1+expression+are+elevated+in+low-grade+B-cell+non-Hodgkin's+lymphoma+and+cTfh+gene+expression+is+perturbed+in+marginal+zone+lymphoma.">Circulating Tfh1 (cTfh1) cell numbers and PD1 expression are elevated in low-grade B-cell non-Hodgkin's lymphoma and cTfh gene expression is perturbed in marginal zone lymphoma.</a> PLOS ONE. 13 (1), 0190468 (2018).</li><li>Annunziato, 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=Phenotypic+and+functional+features+of+human+Th17+cells.">Phenotypic and functional features of human Th17 cells.</a> Journal of Experimental Medicine. 204 (8), 1849-1861 (2007).</li><li>Duan, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotype+and+function+of+CXCR5+CD45RA-CD4++T+cells+were+altered+in+HBV-related+hepatocellular+carcinoma+and+elevated+serum+CXCL13+predicted+better+prognosis.">Phenotype and function of CXCR5+CD45RA-CD4+ T cells were altered in HBV-related hepatocellular carcinoma and elevated serum CXCL13 predicted better prognosis.</a> Oncotarget. 6 (42), 44239-44253 (2015).</li><li>Zhang, X., 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=Circulating+CXCR5+CD4+helper+T+cells+in+systemic+lupus+erythematosus+patients+share+phenotypic+properties+with+germinal+center+follicular+helper+T+cells+and+promote+antibody+production.">Circulating CXCR5+CD4+helper T cells in systemic lupus erythematosus patients share phenotypic properties with germinal center follicular helper T cells and promote antibody production.</a> Lupus. 24 (9), 909-917 (2015).</li><li>Sage, P. T., Francisco, L. M., Carman, C. V., Sharpe, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+receptor+PD-1+controls+follicular+regulatory+T+cells+in+the+lymph+nodes+and+blood.">The receptor PD-1 controls follicular regulatory T cells in the lymph nodes and blood.</a> Nature Immunology. 14 (2), 152-161 (2013).</li><li>Sage, P. T., Alvarez, D., Godec, J., von Andrian, U. H., Sharpe, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Circulating+T+follicular+regulatory+and+helper+cells+have+memory-like+properties.">Circulating T follicular regulatory and helper cells have memory-like properties.</a> The Journal of Clinical Investigation. 124 (12), 5191-5204 (2014).</li><li>Sage, P. T., Tan, C. L., Freeman, G. J., Haigis, M., Sharpe, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Defective+TFH+Cell+Function+and+Increased+TFR+Cells+Contribute+to+Defective+Antibody+Production+in+Aging.">Defective TFH Cell Function and Increased TFR Cells Contribute to Defective Antibody Production in Aging.</a> Cell Reports. 12 (2), 163-171 (2015).</li><li>Yu, N., 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=CD4+CD25+CD127low/-+T+Cells:+A+More+Specific+Treg+Population+in+Human+Peripheral+Blood.">CD4+CD25+CD127low/- T Cells: A More Specific Treg Population in Human Peripheral Blood.</a> Inflammation. 35 (6), 1773-1780 (2012).</li></ol>

This protocol represents a simple and efficient way to analyze peripheral blood cTfh cells, enabling the detection of all relevant subsets identified in the literature thus far. Blood samples can be easily and efficiently obtained as part of standard out-patient clinics and serial samples can be collected in parallel with clinical data. In turn, this enables prospective studies evaluating cTfh subsets as biomarkers for disease progression or response to treatment. These studies would be particularly warranted in disease ...

T-follicular helper cells (Tfh) are a CD4+ T-cell subset that was initially characterized in lymphoid tissues1. These cells express PD-1 and CXCR5 surface receptors, secrete IL-21 and IL-4 and show nuclear expression of the transcription factor, BCL-62,3. As their name suggests, they are found in germinal centers and are essential for high affinity antibody production1.
Dysregulated Tfh responses have been implicated in disease pathogenesis, most notably autoimmune disease, where they promote the expansion of autoreactive B cells4. They also play a role in the tumor microenvironment of both solid5,6 and lymphoid cancers7. Conversely, genetic defects of surface proteins essential for Tfh function such as inducible T-cell costimulator (ICOS) result in human immunodeficiency syndromes8. CD4+ CXCR5+ cells in human peripheral blood are termed circulating T-follicular helper cells (cTfh) and are believed to be the memory compartment of Tfh cells in tissues9. The purpose of the method described here is the analysis of cTfh subsets following CD4+ cell isolation from peripheral blood samples.
Several cTfh subsets have been defined and the efficiency with which they provide B-cell help differs from one subset to another9,10,11,12. The relative proportions of these subsets are altered in a number of diseases, most prominently autoimmune disease in which there is almost always a relative increase in the more functional PD-1+/hi and/or cTfh2 or cTfh17 subsets in comparison to the less functional PD-1- and/or cTfh1 subsets12. The extent of these changes frequently associate with clinical parameters including disease activity and autoantibody titers, indicating a potential role of cTfh subset distribution as a prognostic biomarker in disease, which may reflect the activity of Tfh in lymphoid tissues9,12,13,14. Additionally, taking blood samples from participants is quick, safe and acceptable, and so allows serial monitoring for the analysis of disease progression or response to therapy.
The use of isolated CD4+ T-cells over traditional peripheral blood mononuclear cell (PBMNC) suspensions enables higher throughput flow cytometry experiments by reducing the time required to acquire a substantial number of cTfh cells for analysis. This is particularly helpful when sorting cells from rare cTfh subsets using flow activated cell sorting (FACS). To aid the efficiency, these suspensions can be cryopreserved to enable &#34;batching&#34; of samples to be used in the flow cytometry experiment. On testing, the CD4+ purity was not reduced by cryopreservation.
While different laboratories used different markers to categorise cTfh cells in the early stages of their discovery, the method presented here makes use of a unified scheme of two groups of cell-surface markers as proposed by Schmidt et al.12,15 to enable the simultaneous identification of cTfh and their nine recognized subsets in a single flow cytometry experiment.
As only cell surface markers are used, the cells do not require fixation or permeabilization, and thus can remain alive for downstream functional studies. This could be facilitated by cell sorting using FACS with the same antibody panel. This panel could be expanded to include other markers, allowing for the restrictions of the flow cytometer being used.
The analysis of multi-color flow cytometry experiments can be challenging due to the inherently subjective nature of gating on 2-dimensional dot plots, especially when cell populations do not have a clear bi-modal distribution in marker fluorescence, as is the case for cTfh cells and their subsets. For this reason, it is imperative to set up effective controls to reduce the artefacts to enable better resolution of populations and to set gating strategies confidently. As such, antibody panel design and the set-up of basic controls for a flow cytometry experiment, i.e., using compensation and FMO controls are outlined in Step 3.4.2 and 3.4.3,respectively.
All cTfh cells are defined as CD4+ CXCR5+ CD45RA-. The level of expression of the characteristic Tfh activation marker PD-1 can then be determined to identify the subsets of PD-1-, PD-1+ or PD-1hi cTfh cells. Then, using a combination of the chemokine receptors CXCR3 and CCR6, which are differentially expressed by traditional Th1,2 or 17 cells, cTfh can be characterized as cTfh1,2 or 17-like by a profile of CXCR3+ CCR6-, CXCR3- CCR6-, and CXCR3- CCR6+, respectively.
The antibody panel used by our laboratory is displayed in Table 1. The user may have to adapt their fluorophore selection to account for the laser and light filter configuration available on their local flow cytometer.
The following considerations influence the choice of fluorophores. Use bright fluorophores where possible. In particular, use the brightest available fluorophores on the dimmest (less highly expressed) markers. Dimmer markers include PD-1, CXCR3 and CCR6, and to a lesser extent, CXCR5. We specifically made use of the newer BB, BV and BUV fluorophores which provide excellent brightness and thus enable easier resolution of distinct populations of the cells.
Spread the fluorophore selection across the emission spectra as much as possible to minimize spectral overlap and thus the level of compensation required. A free, online tool that can be used to assist designing a flow cytometry panel can be found here: http://www.bdbioscienes.com/us/s/spectrumviewer. To save space on the emission spectrum, we employed a &#34;dump channel&#34; by using a viability dye with an emission wavelength that overlaps with that of APC-H7 (conjugated to CD45RA) to enable the detection (and exclusion) of both dead and/or CD45RA+ using a single detector.
Here, a protocol is presented for the isolation of peripheral blood CD4+ T-cells and their subsequent analysis by flow cytometry to determine the proportions of the different and recently described circulating subsets.

<table border="0" cellpadding="0" cellspacing="0" style="width:1037px;" width="1037">
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	</colgroup>
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">RosetteSep Human CD4+ T Cell Enrichment Cocktail</td>
			<td style="width:179px;">STEMCELL TECHNOLOGIES</td>
			<td style="width:119px;">15062</td>
			<td style="width:255px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ficoll-Paque PLUS</td>
			<td style="width:179px;">GE Healthcare Life Sciences</td>
			<td>17144003</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">BUV395 Mouse Anti-Human CD183&#160;Clone 1C6/CXCR3</td>
			<td style="width:179px;">BD Horizon</td>
			<td>565223</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">BV711 Mouse Anti-Human CD196 (CCR6)&#160;Clone 11A9</td>
			<td style="width:179px;">BD Horizon</td>
			<td>563923</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">BV421 Rat Anti-Human CXCR5 (CD185)&#160;Clone&#160;RF8B2</td>
			<td style="width:179px;">BD Horizon</td>
			<td>562747</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">BB515 Mouse Anti-Human CD4&#160;Clone &#160;RPA-T4</td>
			<td style="width:179px;">BD Horizon</td>
			<td>564419</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">PE Mouse Anti-Human CD279&#160;Clone MIH4</td>
			<td style="width:179px;">BD Pharmingen</td>
			<td>557946</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">APC-H7 Mouse Anti-Human CD45RA Clone&#160; HI100</td>
			<td style="width:179px;">BD Pharmingen</td>
			<td>560674</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">LIVE/DEAD Fixable Far Red Dead Cell Stain Kit, for 633 or 635 nm excitation</td>
			<td style="width:179px;">ThermoFisher Scientific</td>
			<td style="width:119px;">L34973</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">Brilliant Stain Buffer</td>
			<td style="width:179px;">BD Horizon</td>
			<td>563794</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">Anti-Mouse Ig, &#954;/Negative Control Compensation Particles Set</td>
			<td style="width:179px;">BD CompBead</td>
			<td>552843</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">FACS Aria II Flow Cytometer</td>
			<td style="width:179px;">BD Biosciences</td>
			<td>644832</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">FACSDiva 6.1.3</td>
			<td style="width:179px;">BD Biosciences</td>
			<td>643629</td>
			<td>Flow Cytometer Acquisition Software</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:485px;">FlowJo 10.2</td>
			<td style="width:179px;">Treestar Inc.</td>
			<td style="width:119px;"></td>
			<td>Flow Cytometry Data Analysis Software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-CXCR3 antibody</td>
			<td style="width:179px;">BD Horizon&#160;</td>
			<td style="width:119px;">565223</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-CCR6 antibody</td>
			<td style="width:179px;">BD Horizon&#160;</td>
			<td style="width:119px;">563923</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-CXCR5 antibody</td>
			<td style="width:179px;">BD Horizon&#160;</td>
			<td style="width:119px;">562747</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-CD4 antibody</td>
			<td style="width:179px;">BD Horizon&#160;</td>
			<td style="width:119px;">564419</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-PD-1 antibody</td>
			<td style="width:179px;">BD Pharmingen&#160;</td>
			<td style="width:119px;">557946</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Anti-CD45RA antibody</td>
			<td style="width:179px;">BD Pharmingen&#160;</td>
			<td style="width:119px;">560674</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:485px;">Viability Marker</td>
			<td style="width:179px;">ThermoFisher Scientific&#160;</td>
			<td style="width:119px;">L34973</td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

High CD4+ purity was achieved using the CD4+ isolation protocol, which was reliable across all blood samples tested by us (mean: 96.6%, SD: 2.38, n=31) (Figure 3).
Identification of cTfh (CD4+ CXCR5+ cells) in a representative normal subject is presented (Figure 4A). The proportion of total cTfh cells within C...

Watch this Scientific Journal Video about Isolation of CD4+ T-cells and Analysis of Circulating T-follicular Helper cTfh Cell Subsets from Peripheral Blood Using 6-color Flow Cytometry at JoVE.com

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.

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 ...

This method can help to demonstrate the differences between circulating T-follicular helper cell subsets in healthy and diseased states.The main advantages of this technique are that it's fast, that the samples can be batch-processed, and that the cells remain alive for downstream functional analysis.This technique facilitates the evaluation of circulating T-follicular helper subsets as biomarkers for disease progression as they correlate with markers of clinical severity.Helping with the demonstration of this procedure will be Dr.Lucia Pi

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Research

JoVE Journal

Biology

Isolation of CD4+ T cells from Mouse Lymph Nodes Using Miltenyi MACS Purification

Isolation of cells from the primary source is a necessary step in many more complex protocols. Miltenyi offers kits to isolate cells from several organisms including humans, non-human primates, rat and, as we describe here, mice. Magnetic bead-based cell separation allows for either positive selection (or cell depletion) as well as negative selection. Here, we demonstrate negative selection of untouched or na ve CD4+ helper T cells. Using this standard protocol we typically purify cells that are &#8805; 96% pure CD4+/CD3+. This protocol is used in conjunction with the protocol Dissection and 2-Photon Imaging of Peripheral Lymph Nodes in Mice published in issue 7 of JoVE, for purification of T cells and other cell types to adoptively transfer for imaging purposes. Although we did not demonstrate FACS analysis in this protocol video, it is highly recommended to check the overall purity of isolated cells using the appropriate antibodies via FACS. In addition, we demonstrate the non-sterile method of T cell isolation. If sterile cells are needed for your particular end-user application, be sure to do all of the demonstrated procedures in the tissue culture hood under standard sterile conditions. Thank you for watching and good luck with your own experiments!

Isolation of lymphocytes using the Miltenyi MACs kit is a reliable way to purify cells from whole lymphoid tissue homogenates. Cells purified using the Miltenyi system are typically &#8805; 96% pure. Here, we demonstrate the steps taken to isolate CD4+ T cells, one of the many kits offered by Miltenyi.

Isolation of cells from the primary source is a necessary step in many more complex protocols. Miltenyi offers kits to isolate cells from several ...

Visualizing Antigen Specific CD4+ T Cells using MHC Class II Tetramers

Major histocompatibility complex (MHC) class II tetramers allow the direct visualization of antigen specific CD4+ T cells by flow cytometry.  This method relies on the highly specific interaction between peptide loaded MHC and the corresponding T-cell receptor.  While the affinity of a single MHC/peptide molecule is low, cross-linking MHC/peptide complexes with streptavidin increases the avidity of the interaction, enabling their use as staining reagents.  Because of the relatively low frequencies of CD4+ T cells (~1 in 300,000 for a single specificity) this assay utilizes an in vitro amplification step to increase its threshold of detection.  Mononuclear cells are purified from peripheral blood by Ficoll underlay.  CD4+ cells are then separated by negative selection using biotinylated antibody cocktail and anti-biotin labeled magnetic beads.  Using adherent cells from the CD4- cell fraction as antigen presenting cells, CD4+ T cells are expanded in media by adding an antigenic peptide and IL-2.  The expanded cells are stained with the corresponding class II tetramer by incubating at 37 C for one hour and subsequently stained using surface antibodies such as anti-CD4, anti-CD3, and anti-CD25.  After labeling, the cells can be directly analyzed by flow cytometry.  The tetramer positive cells typically form a distinct population among the expanded CD4+ cells.  Tetramer positive cells are usually CD25+ and often CD4 high.  Because the level of background tetramer staining can vary, positive staining results should always be compared to the staining of the same cells with an irrelevant tetramer.  Multiple variations of this basic assay are possible.  Tetramer positive cells may be sorted for further phenotypic analysis, inclusion in ELISPOT or proliferation assays, or other secondary assays.  Several groups have also demonstrated co-staining using tetramers and either anti-cytokine or anti-FoxP3 antibodies.  

This procedure demonstrates the purification and in vitro expansion of antigen specific CD4+ T cells from whole peripheral blood and their visualization using MHC class II tetramers. Tetramers permit the direct visualization of T cells with a single antigen specificity and defined MHC class II restriction.

Major histocompatibility complex (MHC) class II tetramers allow the direct visualization of antigen specific CD4+ T cells by flow cytometry.  This method ...

Isolation and Culture of Pulmonary Endothelial Cells from Neonatal Mice

Endothelial cells provide a useful research model in many areas of vascular biology. Since its first isolation 1, human umbilical vein endothelial cells (HUVECs) have shown to be convenient, easy to obtain and culture, and thus are the most widely studied endothelial cells. However, for research focused on processes like angiogenesis, permeability or many others, microvascular endothelial cells (ECs) are a much more physiologically relevant model to study 2. Furthermore, ECs isolated from knockout mice provide a useful tool for analysis of protein function ex vivo. Several approaches to isolate and culture microvascular ECs of different origin have been reported to date 3-7, but consistent isolation and culture of pure ECs is still a major technical problem in many laboratories. Here, we provide a step-by-step protocol on a reliable and relatively simple method of isolating and culturing mouse lung endothelial cells (MLECs). In this approach, lung tissue obtained from 6- to 8-day old pups is first cut into pieces, digested with collagenase/dispase (C/D) solution and dispersed mechanically into single-cell suspension. MLECS are purified from cell suspension using positive selection with anti-PECAM-1 antibody conjugated to Dynabeads using a Magnetic Particle Concentrator (MPC). Such purified cells are cultured on gelatin-coated tissue culture (TC) dishes until they become confluent. At that point, cells are further purified using Dynabeads coupled to anti-ICAM-2 antibody. MLECs obtained with this protocol exhibit a cobblestone phenotype, as visualized by phase-contrast light microscopy, and their endothelial phenotype has been confirmed using FACS analysis with anti-VE-cadherin 8 and anti-VEGFR2 9 antibodies and immunofluorescent staining of VE-cadherin. In our hands, this two-step isolation procedure consistently and reliably yields a pure population of MLECs, which can be further cultured. This method will enable researchers to take advantage of the growing number of knockout and transgenic mice to directly correlate in vivo studies with results of in vitro experiments performed on isolated MLECs and thus help to reveal molecular mechanisms of vascular phenotypes observed in vivo.

Here, we describe a protocol for isolation and culture of murine pulmonary endothelial cells. This method comprises mechanic and enzymatic lung tissue dissociation as well as a 2-step purification process using anti-PECAM-1 and anti-ICAM-2 antibodies conjugated to magnetic beads, which produces a pure endothelial cell population of mostly microvascular origin.

Endothelial cells provide a useful research model in many areas of vascular biology. Since its first isolation 1, human umbilical vein endothelial cells ...

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of different cell types in vitro and in vivo.1-5 Although there are literally thousands of publications using such dyes, some of the most commonly encountered cell tracking applications include monitoring of:
<ol>
	<li>stem and progenitor cell quiescence, proliferation and/or differentiation6-8</li>
	<li>antigen-driven membrane transfer9 and/or precursor cell proliferation3,4,10-18 and</li>
	<li>immune regulatory and effector cell function1,18-21.</li>
</ol>
Commercially available cell tracking dyes vary widely in their chemistries and fluorescence properties but the great majority fall into one of two classes based on their mechanism of cell labeling. "Membrane dyes", typified by PKH26, are highly lipophilic dyes that partition stably but non-covalently into cell membranes1,2,11. "Protein dyes", typified by CFSE, are amino-reactive dyes that form stable covalent bonds with cell proteins4,16,18. Each class has its own advantages and limitations. The key to their successful use, particularly in multicolor studies where multiple dyes are used to track different cell types, is therefore to understand the critical issues enabling optimal use of each class2-4,16,18,24.
The protocols included here highlight three common causes of poor or variable results when using cell-tracking dyes. These are:
<ol>
	<li>Failure to achieve bright, uniform, reproducible labeling. This is a necessary starting point for any cell tracking study but requires attention to different variables when using membrane dyes than when using protein dyes or equilibrium binding reagents such as antibodies.</li>
	<li>Suboptimal fluorochrome combinations and/or failure to include critical compensation controls. Tracking dye fluorescence is typically 102 - 103 times brighter than antibody fluorescence. It is therefore essential to verify that the presence of tracking dye does not compromise the ability to detect other probes being used.</li>
	<li>Failure to obtain a good fit with peak modeling software. Such software allows quantitative comparison of proliferative responses across different populations or stimuli based on precursor frequency or other metrics. Obtaining a good fit, however, requires exclusion of dead/dying cells that can distort dye dilution profiles and matching of the assumptions underlying the model with characteristics of the observed dye dilution profile.</li>
</ol>
Examples given here illustrate how these variables can affect results when using membrane and/or protein dyes to monitor cell proliferation.

Successful use of cell tracking dyes to monitor immune cell function and proliferation involves several critical steps. We describe methods for: 1) obtaining bright, uniform, reproducible label-ing with membrane dyes; 2) selecting fluorochromes and data acquisition conditions; and 3) choosing a model to quantify cell proliferation based on dye dilution.

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of ...

Techniques for the Analysis of Extracellular Vesicles Using Flow Cytometry

Extracellular Vesicles (EVs) are small, membrane-derived vesicles found in bodily fluids that are highly involved in cell-cell communication and help regulate a diverse range of biological processes. Analysis of EVs using flow cytometry (FCM) has been notoriously difficult due to their small size and lack of discrete populations positive for markers of interest. Methods for EV analysis, while considerably improved over the last decade, are still a work in progress. Unfortunately, there is no one-size-fits-all protocol, and several aspects must be considered when determining the most appropriate method to use. Presented here are several different techniques for processing EVs and two protocols for analyzing EVs using either individual detection or a bead-based approach. The methods described here will assist with eliminating the antibody aggregates commonly found in commercial preparations, increasing signal&#8211;to-noise ratio, and setting gates in a rational fashion that minimizes detection of background fluorescence. The first protocol uses an individual detection method that is especially well suited for analyzing a high volume of clinical samples, while the second protocol uses a bead-based approach to capture and detect smaller EVs and exosomes.

Many different methods exist for the measurement of extracellular vesicles (EVs) using flow cytometry (FCM). Several aspects should be considered when determining the most appropriate method to use. Two protocols for measuring EVs are presented, using either individual detection or a bead-based approach.

Extracellular Vesicles (EVs) are small, membrane-derived vesicles found in bodily fluids that are highly involved in cell-cell communication and help ...

Isolation and Characterization of Microvesicles from Peripheral Blood

The release of extracellular vesicles (EVs) including small endosomal-derived exosomes (Exos, diameter &#60; 100 nm) and large plasma membrane-derived microvesicles (MVs, diameter &#62; 100 nm) is a fundamental cellular process that occurs in all living cells. These vesicles transport proteins, lipids and nucleic acids specific for their cell of origin and in vitro studies have highlighted their importance as mediators of intercellular communication. EVs have been successfully isolated from various body fluids and especially EVs in blood have been identified as promising biomarkers for cancer or infectious diseases. In order to allow the study of MV subpopulations in blood, we present a protocol for the standardized isolation and characterization of MVs from peripheral blood samples. MVs are pelleted from EDTA-anticoagulated plasma samples by differential centrifugation and typically possess a diameter of 100 - 600 nm. Due to their larger size, they can easily be studied by flow cytometry, a technique that is routinely used in clinical diagnostics and available in most laboratories. Several examples for quality control assays of the isolated MVs will be given and markers that can be used for the discrimination of different MV subpopulations in blood will be presented.

Extracellular vesicles present in blood have been suggested as novel biomarkers for various diseases. Here, we present a protocol for the isolation of large plasma membrane-derived microvesicles from peripheral blood samples and their subsequent analysis by conventional flow cytometry and Western Blotting.

The release of extracellular vesicles (EVs) including small endosomal-derived exosomes (Exos, diameter &#60; 100 nm) and large plasma membrane-derived ...

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 ...

Sensitive Measurement of Mitophagy by Flow Cytometry Using the pH-dependent Fluorescent Reporter mt-Keima

Mitophagy is a process of selective removal of damaged or unnecessary mitochondria using autophagy machinery. Close links have been found between defective mitophagy and various human diseases, including neurodegenerative diseases, cancer, and metabolic diseases. In addition, recent studies have shown that mitophagy is involved in normal cellular processes, such as differentiation and development. However, the precise role of and molecular mechanisms underlying mitophagy require further study. Therefore, it is critical to develop a robust and convenient method for measuring changes in mitophagy activity. Here, we describe a detailed protocol for quantitatively assessing mitophagy activity through flow cytometry using the mitochondria-targeted fluorescent protein Keima (mt-Keima). This flow cytometry assay can analyze mitophagy activity more rapidly and sensitively than conventional microscopy- or immunoblotting-based methods. This protocol can be applied to analyze mitophagy activity in various cell types.

Mitophagy, the selective degradation of mitochondria, has been implicated in mitochondrial homeostasis and is deregulated in various human diseases. However, convenient experimental methods for measuring mitophagy activity are very limited. Here, we provide a sensitive assay for measuring mitophagy activity using flow cytometry.

Mitophagy is a process of selective removal of damaged or unnecessary mitochondria using autophagy machinery. Close links have been found between ...

Measurement of Mitochondrial Mass and Membrane Potential in Hematopoietic Stem Cells and T-cells by Flow Cytometry

A fine balance of quiescence, self-renewal, and differentiation is key to preserve the hematopoietic stem cell (HSC) pool and maintain lifelong production of all mature blood cells. In recent years cellular metabolism has emerged as a crucial regulator of HSC function and fate. We have previously demonstrated that modulation of mitochondrial metabolism influences HSC fate. Specifically, by chemically uncoupling the electron transport chain we were able to maintain HSC function in culture conditions that normally induce rapid differentiation. However, limiting HSC numbers often precludes the use of standard assays to measure HSC metabolism and therefore predict their function. Here, we report a simple flow cytometry assay that allows reliable measurement of mitochondrial membrane potential and mitochondrial mass in scarce cells such as HSCs. We discuss the isolation of HSCs from mouse bone marrow and measurement of mitochondrial mass and membrane potential post ex vivo culture. As an example, we show the modulation of these parameters in HSCs via treatment with a metabolic modulator. Moreover, we extend the application of this methodology on human peripheral blood-derived T cells and human tumor infiltrating lymphocytes (TILs), showing dramatic differences in their mitochondrial profiles, possibly reflecting different T cell functionality. We believe this assay can be employed in screenings to identify modulators of mitochondrial metabolism in various cell types in different contexts.

Here we describe a reliable method to measure mitochondrial mass and membrane potential in ex vivo cultured hematopoietic stem cells and T cells.

A fine balance of quiescence, self-renewal, and differentiation is key to preserve the hematopoietic stem cell (HSC) pool and maintain lifelong production ...

Immunophenotyping and Cell Sorting of Human MKs from Human Primary Sources or Differentiated In Vitro from Hematopoietic Progenitors

Megakaryocyte (MK) differentiation encompasses a number of endomitotic cycles that result in a highly polyploid (reaching even&#160;&#62;64N) and extremely large cell (40-60 &#181;m). As opposed to the fast-increasing knowledge in megakaryopoiesis at the cell biology and molecular level, the characterization of megakaryopoiesis by flow cytometry is limited to the identification of mature MKs using lineage-specific surface markers, while earlier MK differentiation stages remain unexplored. Here, we present an immunophenotyping strategy that allows the identification of successive MK differentiation stages, with increasing ploidy status, in human primary sources or in vitro cultures with a panel integrating MK specific and non-specific surface markers. Despite its size and fragility, MKs can be immunophenotyped using the above-mentioned panel and enriched by fluorescence-activated cell sorting under specific conditions of pressure and nozzle diameter. This approach facilitates multi-Omics studies, with the aim to better understand the complexity of megakaryopoiesis and platelet production in humans. A better characterization of megakaryopoiesis may pose fundamental in the diagnosis or prognosis of lineage-related pathologies and malignancy.

Immunophenotyping and Cell Sorting of Human MKs from Human Primary Sources or Differentiated In Vitro from Hematopoietic Progenitors

Here, we present an immunophenotyping strategy for the characterization of megakaryocyte differentiation, and show how that strategy allows the sorting of megakaryocytes at different stages with a fluorescence-activated cell sorter. The methodology can be applied to human primary tissues, but also to megakaryocytes generated in culture in vitro.