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 obtained by Leicestershire, Northamptonshire and Rutland Research Ethics Committee 1, reference 06/Q2501/122 for patient samples and the Health Research Authority (HRA) NRES Committee East Midlands-Derby, reference 14/EM/1176 for normal subjects.
1. Isolation of CD4+ T-cells from Whole Peripheral Blood
<ol>
	<li>Take fresh peripheral blood (2 to 15 mL) into K2EDTA tubes by standard venipuncture and process as soon as possible to maintain maximum viability. 
	NOTE: Use standard laboratory personal protective equipment (coat, gloves, glasses) and carry out the work in a class II Biosafety Cabinet.</li>
	<li>Bring the blood and all necessary reagents (CD4+ enrichment cocktail, 2% fetal bovine serum/phosphate buffered saline (FBS/PBS), density gradient media, and freezing medium if cryopreserving cells) to room temperature.</li>
	<li>Mix the blood with a commercially available cocktail of antibodies for the enrichment of human CD4+ T Cells. Use 50 &#181;L of the reagent for every 1 mL of blood. Use a 50 mL conical polypropylene tube for 5 to 15 mL of blood. 
	&#8203;NOTE: If using 2 to 4 mL of blood, perform this step in a 14 mL conical polypropylene tube.</li>
	<li>Incubate the mixture at room temperature for 20 min.</li>
	<li>Dilute the mixture with an equal volume of 2% FBS/PBS</li>
	<li>Layer this diluted mixture on top of the density gradient media slowly to avoid disturbing the interface and proceed to centrifugation immediately to avoid diffusion of the blood into the density gradient medium.
	<ol>
		<li>For 2 to 3 mL of blood, use 3 mL of density gradient medium in a 14 mL conical polypropylene tube, but for 4 mL of blood, use 4 mL of density gradient medium in a 14 mL conical polypropylene tube and for 5 to 15 mL blood, use 15 mL of density gradient medium in a 50 mL conical polypropylene tube.</li>
	</ol>
	</li>
	<li>Centrifuge the layered mixture for 20 min at 1,200 x g with the brake off at 20 &#176;C. 
	NOTE: A temperature below ambient may result in the contamination with red blood cells and granulocytes. A lower speed will cause the CD4+ isolation process to fail. Leaving the break engaged will decrease cell yield. Use a bench top centrifuge with rotors that can be closed to avoid aerosols.</li>
	<li>Remove the enriched CD4+ cell layer from the interface using a Pasteur pipette. 
	NOTE: The enriched cell layer will resemble a standard &#34;buffy coat&#34; of white cloudy cells, but as only CD4+ cells are present, this will naturally be smaller and more difficult to see.</li>
	<li>Add 2% FBS/PBS to the CD4+ cells up to a total volume of 10 mL and then wash twice with 2% FBS/PBS by centrifuging for 10 min at 400 x g during each wash.</li>
	<li>Resuspend the pellet in 2% FBS/PBS and count the cells stained with a vital dye (trypan blue) to determine the cell numbers and viability.</li>
	<li>Optional step: resuspend 5 x 105 to 1 x 106&#160;cells in freezing medium (10% dimethyl sulfoxide in FBS) in 1 mL aliquots. 
	NOTE: Levels of some surface markers may be altered by cryo-preservation and thawing. It is, therefore, very important that all samples are processed consistently. In order to minimize the differences in analytical variables, the samples were cryo-preserved and batched for analysis in this study.</li>
</ol>
2. Flow Cytometry
<ol>
	<li>Thaw the cryopreserved CD4+ cells quickly in a water bath at 37 &#176;C and wash once in pre-warmed medium (RPMI 1640 + L-glutamine supplemented with 10% FBS and 1x penicillin-streptomycin).</li>
	<li>Add the cells to 9 mL of medium, centrifuge for 5 min at 400 x g and remove the supernatant.</li>
	<li>Resuspend the cells in 1% bovine serum albumin (BSA) in PBS (50 &#181;L) so that each condition to be tested uses between 5 x 105 and 1 x 106 cells.</li>
	<li>Mix the cells with Staining Buffer (50 &#181;L). 
	NOTE: Brilliant Stain Buffer prevents various staining artefacts that may interfere with data analysis when two or more BV or BUV stains are used simultaneously owing to inherent chemical properties of these dyes. In single or unstained conditions, the 50 &#181;L of brilliant stain buffer can be substituted for 50 &#181;L of 1% BSA/PBS.</li>
	<li>Add the antibodies to cells (as per the &#34;volume used&#34; column in Table 1) and incubate on ice in the dark for 30 min.</li>
	<li>Wash the cells twice in 1% BSA/PBS by centrifuging for 3 min at 600 x g during each wash.</li>
	<li>Resuspend in 1% BSA/PBS (400 &#181;L) and transfer to a flow cytometry acquisition tube.</li>
	<li>Vortex the cells gently before acquiring data on a flow cytometer:</li>
</ol>
3. Flow Cytometry Controls and Set-up
<ol>
	<li>Using an unstained sample, set photodiode voltages so that lymphocytes can be separated from obvious debris and dead cells (events with high side scatter (SSC) area and low forward scatter (FSC) area)16. Using single stained samples, set photomultiplier (PMT) voltages so that positive fluorescence can be discerned from background fluorescence while making sure that all events fall within the detectable scale. 
	NOTE: An improvement would be to plot CV against PMT voltage for each PMT using dimly fluorescent beads to find the minimum voltage for optimum resolution (The &#34;Peak 2&#34; method19).</li>
	<li>Account for spectral overlap by generating a compensation matrix using single stains with capture beads. Add commercially available compensation beads (60 &#181;L), and negative control beads (60 &#181;L) to 1% BSA/PBS (100 &#181;L), and vortex. 
	NOTE: The capture beads used must match the host species and IgG isotype of the antibody being used. The compensation matrix should be re-calculated if the lot number of any tandem dyes changes, as they can display considerable variability in their emission spectra between lots.</li>
	<li>Add a single antibody (20 &#181;L) and vortex.</li>
	<li>Incubate at room temperature in the dark for 30 min.</li>
	<li>Centrifuge at 200 x g for 10 min and discard the supernatant.</li>
	<li>Resuspend in 1%BSA/PBS (500 &#181;L) and vortex.</li>
	<li>Acquire the sample with a flow cytometer using the designated compensation matrix generator in the acquisition software according to the manufacturer&#39;s instructions.</li>
	<li>Use FMO controls to guide the placement of gates for positive marker fluorescence to account for dye spill over, which is the main source of background fluorescence in experiments using &#8805;4 colours16. Follow the general cell-surface staining protocol as described in Step 3, but for each condition, omit one of the fluorophores from the staining step (where CD45RA is omitted, also omit the live/dead stain). Acquire 100,000 lymphocytes for each condition.</li>
	<li>Set the gate positivity at &#8804;0.5% of cells. See Figure 2 for an illustrated example of FMO controls.</li>
</ol>
4. Data Analysis
<ol>
	<li>Employ the flow cytometer&#39;s acquisition software to set a threshold of 5,000 units on the FSC parameter to exclude very small debris.</li>
	<li>Use a stopping gate to acquire 10,000 cTfh cells (CD4+ CD45RA- CXCR5+). 
	NOTE: The individual user can collect more than 10,000 cells. This number was a compromise between collecting enough cells to provide meaningful results and the time taken for collection.</li>
	<li>Using an FSC-Area / SSC-Area dot plot, draw an ellipse or polygon gate to select the population of lymphocytes whilst excluding debris and overtly dead cells (events with a high SSC-Area and low FSC-Area).</li>
	<li>Using an FSC-Area / FSC-Width dot plot, draw a polygon gate to select single cells while excluding doublets (doublets have an increased area but similar width to single cells).</li>
	<li>Using an FSC-Area / CD45RA and viability marker dot plot, draw a rectangular gate to select live, CD45RA- cells (cells with a low fluorescence for this marker).</li>
	<li>Using an FSC-Area / CD4 dot plot, draw a rectangular gate to select CD4+ cells (cells with a high fluorescence for this marker).</li>
	<li>Using a CD4 / CXCR5 dot plot, draw a rectangular gate to select CXCR5+ (i.e., cTfh) cells (cells with a high fluorescence for this marker).</li>
	<li>Using a CXCR3 / CCR6 dot plot, place a quad gate to subdivide cTfh cells into cTfh1,2 and 17 cells (cells that are high and low for each marker). 
	NOTE: Cells with the phenotype CD4+ CXCR5+ CXCR3+ CCR6+ are poorly characterized. We refer to these cells as cTfh1/1718 because conventional helper T-cells (CD4+ CXCR5-) that are transitioning between Th17 and Th1 show expression of CXCR3 and CCR6 and have been described as cTfh1/1719.</li>
	<li>Using a PD-1 histogram, use the range tool to subdivide cTfh cells (or if preferred, the individual cTfh1,2,17 or 1/17 subsets) into PD-1-/+ or hi populations. 
	NOTE: The distinction between PD-1+ and PD-1hi is not well defined in the literature. The threshold was set as the same PD-1 intensity required to detect bona-fide Tfh in human tonsil lymphocyte suspensions using flow cytometry with the same antibody panel. Alternatively, a marker for ICOS can be added to the antibody panel, as only PD1hi cells are ICOS+.</li>
</ol>

<ol><li>Vinuesa, C. G., Linterman, M. A., Yu, D., MacLennan, I. C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Follicular+Helper+T+Cells%5BTitle%5D)+AND+%22Annual+Review+of+Immunology%22%5BJournal%5D)">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/pubmed?term=((Bcl6+Mediates+the+Development+of+T+Follicular+Helper+Cells%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Bcl6 Mediates the Development of T Follicular Helper Cells.</a> Science. 325 (5943), New York, N.Y. 1001-1005 (2009).</li>
<li>Breitfeld, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Follicular+B+Helper+T+Cells+Express+Cxc+Chemokine+Receptor+5%2C+Localize+to+B+Cell+Follicles%2C+and+Support+Immunoglobulin+Production%5BTitle%5D)+AND+%22The+Journal+of+Experimental+Medicine%22%5BJournal%5D)">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/pubmed?term=((Follicular+helper+T+cells+are+required+for+systemic+autoimmunity%5BTitle%5D)+AND+%22The+Journal+of+Experimental+Medicine%22%5BJournal%5D)">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/pubmed?term=((Spatiotemporal+Dynamics+of+Intratumoral+Immune+Cells+Reveal+the+Immune+Landscape+in+Human+Cancer%5BTitle%5D)+AND+%22Immunity%22%5BJournal%5D)">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/pubmed?term=((CD4%2B+follicular+helper+T+cell+infiltration+predicts+breast+cancer+survival%5BTitle%5D)+AND+%22The+Journal+of+Clinical+Investigation%22%5BJournal%5D)">CD4+ follicular helper T cell infiltration predicts breast cancer survival.</a> The Journal of Clinical Investigation. 123 (7), 2873-2892 (2013).</li>
<li>Amé-Thomas, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Characterization+of+intratumoral+follicular+helper+T+cells+in+follicular+lymphoma%3A+role+in+the+survival+of+malignant+B+cells%5BTitle%5D)+AND+%22Leukemia%22%5BJournal%5D)">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/pubmed?term=((ICOS+Deficiency+Is+Associated+with+a+Severe+Reduction+of+CXCR5%2BCD4+Germinal+Center+Th+Cells%5BTitle%5D)+AND+%22The+Journal+of+Immunology%22%5BJournal%5D)">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/pubmed?term=((Human+Blood+CXCR5%2BCD4%2B+T+Cells+Are+Counterparts+of+T+Follicular+Cells+and+Contain+Specific+Subsets+that+Differentially+Support+Antibody+Secretion%5BTitle%5D)+AND+%22Immunity%22%5BJournal%5D)">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/pubmed?term=((Human+circulating+PD-1%2BCXCR3-CXCR5%2B+memory+Tfh+cells+are+highly+functional+and+correlate+with+broadly+neutralizing+HIV+antibody+responses%5BTitle%5D)+AND+%22Immunity%22%5BJournal%5D)">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="https://www.ncbi.nlm.nih.gov/pubmed/24138884">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/pubmed?term=((Phenotype+and+functions+of+memory+Tfh+cells+in+human+blood%5BTitle%5D)+AND+%22Trends+in+Immunology%22%5BJournal%5D)">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/pubmed?term=((Expansion+of+circulating+T+cells+resembling+follicular+helper+T+cells+is+a+fixed+phenotype+that+identifies+a+subset+of+severe+systemic+lupus+erythematosus%5BTitle%5D)+AND+%22Arthritis+and+Rheumatism%22%5BJournal%5D)">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/pubmed?term=((High+frequencies+of+activated+B+cells+and+T+follicular+helper+cells+are+correlated+with+disease+activity+in+patients+with+new-onset+rheumatoid+arthritis%5BTitle%5D)+AND+%22Clinical+and+Experimental+Immunology%22%5BJournal%5D)">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/pubmed?term=((Human+Circulating+T+Follicular+Helper+Cell+Subsets+in+Health+and+Disease%5BTitle%5D)+AND+%22Journal+of+Clinical+Immunology%22%5BJournal%5D)">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/pubmed?term=((Flow+cytometry+controls%2C+instrument+setup%2C+and+the+determination+of+positivity%5BTitle%5D)+AND+%22Cytometry+Part+A%22%5BJournal%5D)">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/pubmed?term=((Impaired+Function+of+CD4%2B+T+Follicular+Helper+%28Tfh%29+Cells+Associated+with+Hepatocellular+Carcinoma+Progression%5BTitle%5D)+AND+%22PLOS+ONE%22%5BJournal%5D)">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/pubmed?term=((Circulating+Tfh1+%28cTfh1%29+cell+numbers+and+PD1+expression+are+elevated+in+low-grade+B-cell+non-Hodgkin%27s+lymphoma+and+cTfh+gene+expression+is+perturbed+in+marginal+zone+lymphoma%5BTitle%5D)+AND+%22PLOS+ONE%22%5BJournal%5D)">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/pubmed?term=((Phenotypic+and+functional+features+of+human+Th17+cells%5BTitle%5D)+AND+%22Journal+of+Experimental+Medicine%22%5BJournal%5D)">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/pubmed?term=((Phenotype+and+function+of+CXCR5%2BCD45RA-CD4%2B+T+cells+were+altered+in+HBV-related+hepatocellular+carcinoma+and+elevated+serum+CXCL13+predicted+better+prognosis%5BTitle%5D)+AND+%22Oncotarget%22%5BJournal%5D)">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/pubmed?term=((Circulating+CXCR5%2BCD4%2Bhelper+T+cells+in+systemic+lupus+erythematosus+patients+share+phenotypic+properties+with+germinal+center+follicular+helper+T+cells+and+promote+antibody+production%5BTitle%5D)+AND+%22Lupus%22%5BJournal%5D)">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/pubmed?term=((The+receptor+PD-1+controls+follicular+regulatory+T+cells+in+the+lymph+nodes+and+blood%5BTitle%5D)+AND+%22Nature+Immunology%22%5BJournal%5D)">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/pubmed?term=((Circulating+T+follicular+regulatory+and+helper+cells+have+memory-like+properties%5BTitle%5D)+AND+%22The+Journal+of+Clinical+Investigation%22%5BJournal%5D)">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/pubmed?term=((Defective+TFH+Cell+Function+and+Increased+TFR+Cells+Contribute+to+Defective+Antibody+Production+in+Aging%5BTitle%5D)+AND+%22Cell+Reports%22%5BJournal%5D)">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="https://www.ncbi.nlm.nih.gov/pubmed/22752562">CD4+CD25+CD127low/- T Cells: A More Specific Treg Population in Human Peripheral Blood.</a> Inflammation. 35 (6), 1773-1780 (2012).</li>
</ol>

The authors have nothing to disclose.

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 where Tfh dysregulation is implicated in pathogenesis such as autoimmunity and certain types of solid and haematological cancer. In addition, the changes in cTfh function in disease could be investigated by sorting cTfh cells using flow cytometry as only cell surface markers are used in this protocol. Sorting cTfh cells in MZL patients enabled us to find differences in gene expression profiles when compared to normal subjects21.
We found that efficient CD4+ T-cell isolation improved the data analysis. We describe the steps involved in detail because minor issues such as centrifuge braking and speed were critical to the isolation procedure. Another important step, as for all flow cytometry analysis, is to set the compensation and FMO controls.
PD-1 expression varies on cTfh cells and those cells with the highest PD-1 might be the most functional and therefore relevant, especially for the study of autoimmune disease11,12. One important issue was to decide the gate for the identification of PD-1hi cells, the activated cTfh subset, as there is no standard limit defined in the literature. This important but minor subset probably reflects active Tfh differentiation in lymphoid tissue11. To overcome this challenge, the threshold was set such that it was the same as that required to detect bona-fide Tfh cells from human tonsil with the same antibody panel. We recognize that obtaining tonsils might be problematic for some users. An alternative, would be to expand the antibody panel used in this protocol by the addition of anti-ICOS, as only PD-1hi cells are ICOS+ 12.
Here, we present an antibody panel to detect surface markers characteristic of circulating CD4+ T-cells. Circulating T-follicular regulatory cells (cTfr) are the blood memory compartment of T-follicular regulatory cells (Tfr) that are resident in lymphoid tissue and have important roles in regulating the germinal center reaction22,23. cTfr are blood CD4+ CXCR5+ cells that co-express T-regulatory cell markers including the transcription factor FoxP3. Measuring cTfr alongside cTfh may provide a more complete picture of activity in the germinal center, and could present a biomarker in disease in its own right24. Although cTfr numbers are inherently low (mean: 1.82%, SD: 1.40, n = 24 of total CD4+ cells in our own experiments), separating cTfr from cTfh would also increase the specificity of cTfh analysis. Adding a combination of specific T-regulatory cell-surface markers to our panel such as CD25 and CD12725 would enable the detection of cTfr in addition to all cTfh subsets in the same experiment using a very similar protocol. Alternatively, the more classical intracellular regulatory marker FoxP3 could be used, though this requires fixation and permeabilization preventing downstream functional assays. In concentrating on cTfh analysis, however, there are also advantages to defining a minimum panel that can be employed in conjunction with a standard laboratory flow cytometer to obtain clinically or experimentally useful results.

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><tbody><tr><td>RosetteSep Human CD4+ T Cell Enrichment Cocktail</td><td>STEMCELL TECHNOLOGIES</td><td>15062</td><td></td></tr><tr><td>Ficoll-Paque PLUS</td><td>GE Healthcare Life Sciences</td><td>17144003</td><td></td></tr><tr><td>BUV395 Mouse Anti-Human CD183&amp;nbsp;Clone 1C6/CXCR3</td><td>BD Horizon</td><td>565223</td><td></td></tr><tr><td>BV711 Mouse Anti-Human CD196 (CCR6)&amp;nbsp;Clone 11A9</td><td>BD Horizon</td><td>563923</td><td></td></tr><tr><td>BV421 Rat Anti-Human CXCR5 (CD185)&amp;nbsp;Clone&amp;nbsp;RF8B2</td><td>BD Horizon</td><td>562747</td><td></td></tr><tr><td>BB515 Mouse Anti-Human CD4&amp;nbsp;Clone &amp;nbsp;RPA-T4</td><td>BD Horizon</td><td>564419</td><td></td></tr><tr><td>PE Mouse Anti-Human CD279&amp;nbsp;Clone MIH4</td><td>BD Pharmingen</td><td>557946</td><td></td></tr><tr><td>APC-H7 Mouse Anti-Human CD45RA Clone&amp;nbsp; HI100</td><td>BD Pharmingen</td><td>560674</td><td></td></tr><tr><td>LIVE/DEAD Fixable Far Red Dead Cell Stain Kit, for 633 or 635 nm excitation</td><td>ThermoFisher Scientific</td><td>L34973</td><td></td></tr><tr><td>Brilliant Stain Buffer</td><td>BD Horizon</td><td>563794</td><td></td></tr><tr><td>Anti-Mouse Ig, &amp;kappa;/Negative Control Compensation Particles Set</td><td>BD CompBead</td><td>552843</td><td></td></tr><tr><td>FACS Aria II Flow Cytometer</td><td>BD Biosciences</td><td>644832</td><td></td></tr><tr><td>FACSDiva 6.1.3</td><td>BD Biosciences</td><td>643629</td><td>Flow Cytometer Acquisition Software</td></tr><tr><td>FlowJo 10.2</td><td>Treestar Inc.</td><td></td><td>Flow Cytometry Data Analysis Software</td></tr><tr><td>Anti-CXCR3 antibody</td><td>BD Horizon&amp;nbsp;</td><td>565223</td><td></td></tr><tr><td>Anti-CCR6 antibody</td><td>BD Horizon&amp;nbsp;</td><td>563923</td><td></td></tr><tr><td>Anti-CXCR5 antibody</td><td>BD Horizon&amp;nbsp;</td><td>562747</td><td></td></tr><tr><td>Anti-CD4 antibody</td><td>BD Horizon&amp;nbsp;</td><td>564419</td><td></td></tr><tr><td>Anti-PD-1 antibody</td><td>BD Pharmingen&amp;nbsp;</td><td>557946</td><td></td></tr><tr><td>Anti-CD45RA antibody</td><td>BD Pharmingen&amp;nbsp;</td><td>560674</td><td></td></tr><tr><td>Viability Marker</td><td>ThermoFisher Scientific&amp;nbsp;</td><td>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 CD4+ cells had a median value of 29.4% (inter-quartile range (IQR) = 10.8) across 12 normal subjects. Multiple studies across several different diseases including hepatocellular carcinoma17,20, systemic lupus erythematous11,21, and rheumatoid arthritis11,14 have been conflicting in the ability to detect a difference in overall cTfh between heathy controls and patients. No significant differences were found in overall cTfh between normal subjects and MZL or BNHL patients (Figure 4B)21.
Identification of PD-1 expression within cTfh cells from a representative normal subject and BNHL patient for comparison is shown in Figure 5A. PD-1 expression was significantly higher in MZL and BNHL patients than normal subjects (Figure 5B)21. Similar increases in PD-1 expression have been demonstrated in multiple autoimmune disorders11,12,13,14.
Identification of cTfh1,2,17 and 1/17 within the population of cTfh cells using CXCR3 and CCR6 expression from a representative normal subject is shown in Figure 6A. The proportion of cTfh1 cells was significantly higher in MZL and BNHL patients than normal subjects (Figure 6B)21.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58431/58431fig1.jpg" /> 
Figure 1: Illustration of overall gating strategy used to identify cTfh cells and their subsets. From top left, a population of lymphocytes are distinguished, and the doublets are excluded. Live CD45RA- cells are selected using a &#34;dump channel&#34;. CD4+ cells are gated and CXCR5+ cells are identified as cTfh. cTfh are divided into cTfh1, 2 or 17-like using CXCR3 and CCR6 expression. PD-1 expression within these subsets is then distinguished. Figures taken from a representative normal subject blood sample. FSC-A, FSC Area; SSC-A SSC Area; FSC-W, FSC Width. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58431/58431fig2.jpg" /> 
Figure 2: Illustration of FMO controls. Each biaxial flow cytometry plot shows CD4+ cells stained with all fluorophores except the one of interest to demonstrate the minimum at which gates for fluorescence positivity can be set. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58431/58431fig3.jpg" /> 
Figure 3: Biaxial flow cytometry plot showing the identification of CD4+ cells after gating to live lymphocytes. Taken from a representative normal subject blood sample. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58431/58431fig4.jpg" /> 
Figure 4: Identification of cTfh cells. (A) Biaxial flow cytometry plot showing CXCR5+ expression on cells gated for CD4+ CD45RA-. Taken from a representative normal subject. (B) Relative percentages of cTfh within total CD4+ cells in normal subjects (n = 12), MZL (n = 7), BNHL (n = 9). Horizontal lines represent the median, and error bars represent inter-quartile range. No significant differences were found between groups using the Mann-Whitney U test. This figure has been modified from Byford et al.21. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/58431/58431fig5.jpg" /> 
Figure 5: PD-1 expression and relationship to cTfh cells. (A) Flow cytometry histogram used to determine PD-1 expression within total cTfh cells. Taken from a representative normal subject and BNHL patient. (B) PD-1+ cells as a proportion of total cTfh cells. Horizontal lines represent the median, and error bars represent inter-quartile range. Medians are significantly (Mann-Whitney U-test) different between normal subjects (21.5%, IQR = 10.8, n = 12) and lymphoma patients (MZL 54.1%, IQR = 21.2, n = 7, p = 0.0008 and BNHL 45.2%, IQR =11.4, n = 9, p = 0.0003). This figure has been modified from Byford et al.21. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/58431/58431fig6.jpg" /> 
Figure 6: CXCR3 and CCR6 expression and their relationship to cTfh1 numbers. (A) Biaxial flow cytometry plot showing the expression of CXCR3 and CCR6 on CD4+ CD45RA- CXCR5+ cells. Taken from a representative normal subject and BNHL patient. (B) cTfh1 cells as a percentage of total cTfh cells. Horizontal lines represent the median, and error bars represent inter-quartile range. Medians are significantly (Mann-Whitney U-test) different between normal subjects (20.8%, IQR = 6.7, n = 12) and lymphoma patients (MZL 32.1%, IQR = 6.8, n = 7, p = 0.013, and BNHL 35.4%, IQR = 7.6%, n = 9, p = 0.0056). This figure has been modified from Byford et al.21. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58431/58431fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/58431/58431table1.jpg" /> 
Table 1: Flow cytometry antibody panel.

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 ...

isolation-cd4-t-cells-analysis-circulating-t-follicular-helper-ctfh

Nanyang Technological University

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JoVE Journal

Biology

12.2K Views.  University of Leicester. Deze methode kan helpen om de verschillen tussen circulerende T-folliculaire helper celsets in gezonde en zieke toestanden aan te tonen. De belangrijkste voordelen van deze techniek zijn dat het snel is, dat de monsters batch-verwerkt kunnen worden, en dat de cellen in leven blijven voor downstream functionele analyse. Deze techniek vergemakkelijkt de evaluatie van circulerende T-folliculaire helper subsets als biomarkers voor progressie van de ziekte als ze correleren met markers van klinisc...

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

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 Th17 Differentiation of Na&iuml;ve CD4 T Lymphocytes

Th17 cells are a distinct subset of T cells that have been found to produce interleukin 17 (IL-17), and differ in function from the other T cell subsets including Th1, Th2, and regulatory T cells. Th17 cells have emerged as a central culprit in overzealous inflammatory immune responses associated with many autoimmune disorders. In this method we purify T lymphocytes from the spleen and lymph nodes of C57BL/6 mice, and stimulate purified CD4+ T cells under control and Th17-inducing environments. The Th17-inducing environment includes stimulation in the presence of anti-CD3 and anti-CD28 antibodies, IL-6, and TGF-&#946;. After incubation for at least 72 hours and for up to five days at 37 &#176;C, cells are subsequently analyzed for the capability to produce IL-17 through flow cytometry, qPCR, and ELISAs. Th17 differentiated CD4+CD25- T cells can be utilized to further elucidate the role that Th17 cells play in the onset and progression of autoimmunity and host defense. Moreover, Th17 differentiation of CD4+CD25- lymphocytes from distinct murine knockout/disease models can contribute to our understanding of cell fate plasticity.

Isolation and Th17 Differentiation of Na&#239;ve CD4 T Lymphocytes

With effector functions distinct from other T cell subsets, Th17 cells have been centrally implicated in inflammatory autoimmunity. This in vitro Th17 differentiation protocol provides a means to determine whether na&#239;ve CD4+ T lymphocytes can differentiate into Th17 cells, and to further examine their role in autoimmunity and host response.

Th17 cells are a distinct subset of T cells that have been found to produce interleukin 17 (IL-17), and differ in function from the other T cell subsets ...

Immunology and Infection

Cell-based Flow Cytometry Assay to Measure Cytotoxic Activity

Cytolytic activity of CD8+ T cells is rarely evaluated. We describe here a new cell-based assay to measure the capacity of antigen-specific CD8+ T cells to kill CD4+ T cells loaded with their cognate peptide. Target CD4+ T cells are divided into two populations, labeled with two different concentrations of CFSE. One population is pulsed with the peptide of interest (CFSE-low) while the other remains un-pulsed (CFSE-high). Pulsed and un-pulsed CD4+ T cells are mixed at an equal ratio and incubated with an increasing number of purified CD8+ T cells. The specific killing of autologous target CD4+ T cells is analyzed by flow cytometry after coculture with CD8+ T cells containing the antigen-specific effector CD8+ T cells detected by peptide/MHCI tetramer staining. The specific lysis of target CD4+ T cells measured at different effector versus target ratios, allows for the calculation of lytic units, LU30/106 cells. This simple and straightforward assay allows for the accurate measurement of the intrinsic capacity of CD8+ T cells to kill target CD4+ T cells.

This protocol describes a sensitive, cell-based cytotoxicity assay. By enumerating the decrease in frequency of live target CD4+ T cells in the presence of an increasing number of effector CD8+ T cells, this assay allows for the direct assessment of cytolytic activity of antigen-specific CD8+ T cells.

Cytolytic activity of CD8+ T cells is rarely evaluated. We describe here a new cell-based assay to measure the capacity of antigen-specific CD8+ T cells ...

Retroviral Transduction of Helper T Cells as a Genetic Approach to Study Mechanisms Controlling their Differentiation and Function

Helper T cell development and function must be tightly regulated to induce an appropriate immune response that eliminates specific pathogens yet prevents autoimmunity. Many approaches involving different model organisms have been utilized to understand the mechanisms controlling helper T cell development and function. However, studies using mouse models have proven to be highly informative due to the availability of genetic, cellular, and biochemical systems. One genetic approach in mice used by many labs involves retroviral transduction of primary helper T cells. This is a powerful approach due to its relative ease, making it accessible to almost any laboratory with basic skills in molecular biology and immunology. Therefore, multiple genes in wild type or mutant forms can readily be tested for function in helper T cells to understand their importance and mechanisms of action. We have optimized this approach and describe here the protocols for production of high titer retroviruses, isolation of primary murine helper T cells, and their transduction by retroviruses and differentiation toward the different helper subsets. Finally, the use of this approach is described in uncovering mechanisms utilized by microRNAs (miRNAs) to regulate pathways controlling helper T cell development and function.

Many experimental systems have been utilized to understand the mechanisms regulating T cell development and function in an immune response. Here a genetic approach using retroviral transduction is described, which is economic, time efficient, and most importantly, highly informative in identifying regulatory pathways.

Helper T cell development and function must be tightly regulated to induce an appropriate immune response that eliminates specific pathogens yet prevents ...

Analysis of Human T Cell Activity in an Allogeneic Co-Culture Setting of Pre-Treated Tumor Cells

Cytotoxic T cells play a key role in the elimination of tumor cells and are, therefore, intensively studied in cancer immunology. The frequency and activity of cytotoxic T cells within tumors and their tumor microenvironment (TME) are now well-established prognostic and predictive biomarkers for numerous tumor types. However, it is well-known that various tumor treatment modalities, including radiotherapy, chemotherapy, immunotherapy, and targeted therapy, modulate not only the immunogenicity of the tumor but also the immune system itself. Consequently, the interaction between tumor cells and T cells requires more intensive study in different therapeutic contexts to fully understand the complex role of T cells during tumor therapy. To address this need, a protocol was developed to analyze the activity and proliferative capacity of human cytotoxic (CD8+) T cells in co-culture with pre-treated tumor cells. Specifically, CD8+ T cells from healthy donors are stained with the non-toxic proliferation marker carboxyfluorescein diacetate succinimidyl ester (CFSE) and stimulated using CD3/CD28-coated plates. Subsequently, T cells are co-cultured with pre-treated tumor cells. As a readout, T cell proliferation is quantified by measuring CFSE signal distribution and assessing the expression of surface activation markers via flow cytometry. This can be further complemented by quantifying cytokine release using enzyme-linked immunosorbent assay (ELISA). This method facilitates the evaluation of treatment-induced changes in the interaction between tumor cells and T cells, providing a foundation for more detailed analyses of tumor treatment modalities and their immunogenicity in a human ex vivo setting. Additionally, it contributes to the reduction of pre-clinical in vivo analyses.

The present protocol describes an experimental workflow that allows for the ex vivo analysis of human T cell stimulation in an allogenic co-culture system with pre-treated tumor cells.

Cytotoxic T cells play a key role in the elimination of tumor cells and are, therefore, intensively studied in cancer immunology. The frequency and ...

Cancer Research

Multicolor Flow Cytometry-based Quantification of Mitochondria and Lysosomes in T Cells

T cells utilize different metabolic programs to match their functional needs during differentiation and proliferation. Mitochondria are crucial cellular components responsible for supplying cell energy; however, excess mitochondria also produce reactive oxygen species (ROS) that could cause cell death. Therefore, the number of mitochondria must constantly be adjusted to fit the needs of the cells. This dynamic regulation is achieved in part through the function of lysosomes that remove surplus/damaged organelles and macromolecules. Hence, cellular mitochondrial and lysosomal contents are key indicators to evaluate the metabolic adjustment of cells. With the development of probes for organelles, well-characterized lysosome or mitochondria-specific dyes have become available in various formats to label cellular lysosomes and mitochondria. Multicolor flow cytometry is a common tool to profile cell phenotypes, and has the capability to be integrated with other assays. Here, we present a detailed protocol of how to combine organelle-specific dyes with surface markers staining to measure the amount of lysosomes and mitochondria in different T cell populations on a flow cytometer.

This article illustrates a powerful method to quantify mitochondria or lysosomes in living cells. The combination of lysosome- or mitochondria-specific dyes with fluorescently conjugated antibodies against surface markers allows the quantification of these organelles in mixed cell populations, like primary cells harvested from tissue samples, by using multicolor flow cytometry.

T cells utilize different metabolic programs to match their functional needs during differentiation and proliferation. Mitochondria are crucial cellular ...

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, ...

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.

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. ...

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 ...

Cell Cycle Analysis: Assessing CD4 and CD8 T Cell Proliferation After Stimulation Using CFSE Staining and Flow Cytometry

Source: Perchet Thibaut1,2,3, Meunier Sylvain1,2,3, Sophie Novault4, Rachel Golub1,2,3 
1 Unit for Lymphpoiesis, 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 cell cycle is a universal process of life. During the cell cycle, a cell undergoes several modifications to divide into two daughter cells. This mechanism occurs throughout an organism&#39;s life in response to its needs. Cell divisions and embryonic development produce a full organism from a single-celled zygote. During adulthood, the cell cycle is central to many critical biological processes, such as tissue repairs.
Mechanisms of cell division are tightly controlled events where the cell undergoes stepwise modifications before final division. Cells that are not yet in the cycle are described as being in the Gap 0 (G0) phase. During this stage the cell is considered quiescent. When the cell starts to cycle, four distinct phases are recognized: Gap 1 (G1), Synthesis (S), Gap 2 (G2) and Mitosis (M). G1 phase is a checkpoint for resources needed by the cell for DNA synthesis. Then, S phase occurs, and DNA replication starts, followed by the G2 interphase, another checkpoint that controls all elements necessary to for the cell to divide. Finally, the cell enters mitosis and divides into two daughter cells.
Cell division is a highly informative parameter in many different biological systems. In the field of immunology, analysis of leukocyte proliferation can indicate the mechanism of the immune response. Other domains of investigation also rely on cell cycle analysis. For instance, analysis of the cell cycle during tumor development has improved our understanding of cancer.
Many fluorescent dyes are now available for tracking cell proliferation. These dyes differ in their chemical and spectral properties. Two different classes of dyes exist: protein dyes permanently combine with protein by forming a covalent bond, and membrane dyes stably intercalate within cell membranes via strong hydrophobic associations. In vitro and in vivo studies of immune cell proliferation by flow cytometry are among the most common applications of both classes of cell tracking dyes (1, 2).
CFSE (Carboxyfluorescein succinimidyl ester) is a fluorescent dye that marks dividing cells. Initially, all the cells receive the same amount of dye; dividing cells evenly split the dye they received between their two daughter cells. Consequently, the cell cycle can be followed by the progressive decrease of dye intensity in the cells. CFSE staining is followed by conventional multi-parametric flow cytometry, a high-throughput, fluorescence-based technology that allows phenotypic and functional characterization of cells based on their degree of CFSE staining (3).
In the following experiment, we assess the proliferation of CD4+ and CD8+ T cells in-vitro, following CD3 stimulation, using CFSE staining and flow cytometry.

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

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