Name: a dna/ki67-based flow cytometry assay for cell cycle analysis of antigen-specific cd8 t cells in vaccinated mice
Uploaded: 2021-01-05T13:00:00.000+00:00
Duration: 9 min 17 s
Description: Watch this Scientific Journal Video about A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice at JoVE.com

This work was supported by Reithera, by MIUR project 2017K55HLC_006, and by 5&#160;&#215; 1000 grant from Associazione Italiana Ricerca sul Cancro (AIRC).&#160;The following tetramer was obtained through the NIH Tetramer Facility: APC-conjugated H-2K (d) HIV gag 197-205 AMQMLKETI.

<ol>
	<li>Castellino, 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=Chemokines+enhance+immunity+by+guiding+naive+CD8++T+cells+to+sites+of+CD4++T+cell-dendritic+cell+interaction.">Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T cell-dendritic cell interaction.</a> Nature. 440 (7086), 890-895 (2006).</li><li>Zhang, N., Bevan, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CD8(+)+T+cells:+foot+soldiers+of+the+immune+system.">CD8(+) T cells: foot soldiers of the immune system.</a> Immunity. 35 (2), 161-168 (2011).</li><li>Baj&#233;noff, 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=Highways,+byways+and+breadcrumbs:+directing+lymphocyte+traffic+in+the+lymph+node.">Highways, byways and breadcrumbs: directing lymphocyte traffic in the lymph node.</a> Trends Immunology. 28 (8), 346-352 (2007).</li><li>Bevan, M. J., Fink, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+CD8+response+on+autopilot.">The CD8 response on autopilot.</a> Nature Immunology. 2 (5), 381-382 (2001).</li><li>Van Stipdonk, M. J., Lemmens, E. E., Schoenberger, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Na&#239;ve+CTLs+require+a+single+brief+period+of+antigenic+stimulation+for+clonal+expansion+and+differentiation.">Na&#239;ve CTLs require a single brief period of antigenic stimulation for clonal expansion and differentiation.</a> Nature Immunology. 2 (5), 423-429 (2001).</li><li>Kaech, S. M., Wherry, E. J., Ahmed, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effector+and+memory+T-cell+differentiation:+implications+for+vaccine+development.">Effector and memory T-cell differentiation: implications for vaccine development.</a> Nature Review Immunology. 2 (4), 251-262 (2002).</li><li>Beverley, P. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Primer:+making+sense+of+T-cell+memory.">Primer: making sense of T-cell memory.</a> Nature Clinical Practice Rheumatology. 4 (1), 43-49 (2008).</li><li>Parretta, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CD8+cell+division+maintaining+cytotoxic+memory+occurs+predominantly+in+the+bone+marrow.">CD8 cell division maintaining cytotoxic memory occurs predominantly in the bone marrow.</a> Journal of Immunology. 174 (12), 7654-7664 (2005).</li><li>Di Rosa, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Maintenance+of+memory+T+cells+in+the+bone+marrow:+survival+or+homeostatic+proliferation.">Maintenance of memory T cells in the bone marrow: survival or homeostatic proliferation.</a> Nature Review Immunology. 16 (4), 271 (2016).</li><li>Di Rosa, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two+niches+in+the+bone+marrow:+a+hypothesis+on+life-long+T+cell+memory.">Two niches in the bone marrow: a hypothesis on life-long T cell memory.</a> Trends in Immunology. 37 (8), 503-512 (2016).</li><li>Di Rosa, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Commentary:+Memory+CD8(+)+T+cells+colocalize+with+IL-7(+)+stromal+cells+in+bone+marrow+and+rest+in+terms+of+proliferation+and+transcription.">Commentary: Memory CD8(+) T cells colocalize with IL-7(+) stromal cells in bone marrow and rest in terms of proliferation and transcription.</a> Frontiers in Immunology. 7, 102 (2016).</li><li>Simonetti, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antigen-specific+CD8+T+cells+in+cell+cycle+circulate+in+the+blood+after+vaccination.">Antigen-specific CD8 T cells in cell cycle circulate in the blood after vaccination.</a> Scandinavian Journal of Immunology. 89 (2), 12735 (2019).</li><li>Wilson, 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=c-Myc+controls+the+balance+between+hematopoietic+stem+cell+self-renewal+and+differentiation.">c-Myc controls the balance between hematopoietic stem cell self-renewal and differentiation.</a> Genes &amp; Development. 18 (22), 2747-2763 (2004).</li><li>Hirche, 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=Systemic+virus+infections+differentially+modulate+cell+cycle+state+and+functionality+of+long-term+hematopoietic+stem+cells+in+vivo.">Systemic virus infections differentially modulate cell cycle state and functionality of long-term hematopoietic stem cells in vivo.</a> Cell Report. 19 (11), 2345-2356 (2017).</li><li>Colloca, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vaccine+vectors+derived+from+a+large+collection+of+simian+adenoviruses+induce+potent+cellular+immunity+across+multiple+species.">Vaccine vectors derived from a large collection of simian adenoviruses induce potent cellular immunity across multiple species.</a> Science Translational Medicine. 4 (115), (2012).</li><li>Di Lullo, 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=Marker+gene+swapping+facilitates+recombinant+Modified+Vaccinia+Virus+Ankara+production+by+host-range+selection.">Marker gene swapping facilitates recombinant Modified Vaccinia Virus Ankara production by host-range selection.</a> Journal of Virological Methods. 156 (1-2), 37-43 (2009).</li><li>Di Lullo, 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=The+combination+of+marker+gene+swapping+and+fluorescence-activated+cell+sorting+improves+the+efficiency+of+recombinant+modified+vaccinia+virus+Ankara+vaccine+production+for+human+use.">The combination of marker gene swapping and fluorescence-activated cell sorting improves the efficiency of recombinant modified vaccinia virus Ankara vaccine production for human use.</a> Journal of Virological Methods. 163 (2), 195-204 (2010).</li><li>. Mouse phenotype Available from: <a target="_blank" href="https://www.mousephenotype.org/data/secondaryproject/3i">https://www.mousephenotype.org/data/secondaryproject/3i</a> (2020)</li><li>Yoon, H., Kim, T. S., Braciale, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cell+cycle+time+of+CD8++T+cells+responding+in+vivo+is+controlled+by+the+type+of+antigenic+stimulus.">The cell cycle time of CD8+ T cells responding in vivo is controlled by the type of antigenic stimulus.</a> PLoS One. 5 (11), 15423 (2010).</li><li>Pauklin, S., Vallier, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cell-cycle+state+of+stem+cells+determines+cell+fate+propensity.">The cell-cycle state of stem cells determines cell fate propensity.</a> Cell. 155 (1), 135-147 (2013).</li><li>Vignon, 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=Flow+cytometric+quantification+of+all+phases+of+the+cell+cycle+and+apoptosis+in+a+two-color+fluorescence+plot.">Flow cytometric quantification of all phases of the cell cycle and apoptosis in a two-color fluorescence plot.</a> PLoS One. 8 (7), 68425 (2013).</li></ol>

A. Folgori and S. Capone are employees of Reithera Srl. A. Nicosia is named inventor on patent application WO 2005071093 (A3) &#34;Chimpanzee adenovirus vaccine carriers.&#34; The other authors have nothing to disclose.

Although T cell clonal expansion has been intensively studied, some aspects remain unknown, mostly because the tools available to investigate it are few and have their own drawbacks. From this perspective, we set up a highly sensitive flow cytometric method to analyze cell cycle of antigen-specific CD8 T cells at early times after vaccination in a mouse model. The protocol is based on a combination of Ki67 and DNA staining, which was previously used to analyze the cell cycle of BM hematopoietic cells in mice13,14. To adapt the protocol to antigen-specific CD8 T cells, we had to consider a few critical issues, including the choice of the DNA dye, the appropriate conditions to obtain comparable DNA staining across different samples, and the gating strategy for data analysis.
Many dyes are available for DNA staining, including propidium Iodide and 7-aminoactinomycin D; we chose Hoechst because it was compatible with membrane staining and the mild fixation / permeabilization protocol required for Ki67 staining. At the same time, staining with Hoechst allowed us to obtain a DNA histogram of excellent quality, i.e., the G0/G1 and G2/M DNA peaks had a much lower coefficient of variation (CV) than DNA peaks usually obtained with other DNA dyes, e.g., DRAQ519. Indeed, Hoechst can stain DNA even in live cells20.
Some strategies were used to avoid the fluctuation in Hoechst intensity in different samples of the same experiment. Hoechst staining was performed just before sample acquisition at the flow cytometer to minimize the decline of dye intensity during time. For those interested in reproducing the protocol in big experiments with numerous samples, we recommend performing Hoechst staining on a few samples at a time. One other drawback is that Hoechst intensity can be heavily influenced by cell number during incubation with the dye. For this reason, we strongly recommend always using the same number of cells and the same volume per sample for DNA staining. If a high number of cells is required for acquisition at the flow cytometer, we recommend preparing two or more identical samples and then merging them just before the Hoechst staining step.
A key point of the protocol is the gating strategy for data analysis. We recently published a novel strategy for T cell analysis at early times of the immune response, which allowed us to increase the sensitivity of detection of antigen-specific T cells12. We applied this strategy to the data shown here as follows. First, we excluded cell aggregates in the DNA-A/W plot. Second, after gating out dead cells, we used a fairly large lymphocyte gate in the FSC/SSC plot (&#34;relaxed gate&#34;). By this strategy, we were able to include highly activated antigen-specific CD8 T cells in S-G2/M that are usually missed by current gating strategies, as these cells have high FSC-A and SSC-A. In summary, the data analysis represents a critical part of the method, which is essential to obtain a sensitive detection of activated /proliferating antigen-specific T cells.
The method prevents the possibility of missing critical T cell data at early phases of immune response and opens new perspectives for T cell immuno-monitoring. A future improvement might be to include staining for phospho-histone 3 that would allow differentiation between G2 and M21. A current limitation is that cells have to be fixed and permeabilized to stain for the nuclear marker, Ki67. Thus, cells cannot be used for other types of analysis such as sorting and subsequent functional analysis. Moreover, DNA dyes, including Hoechst, usually interfere with the genomic DNA analysis and are not suitable for this type of evaluation. Identification of membrane markers that correlate with different cell cycle phases and that can be stained on live cells could overcome this limitation. In conclusion, the method has great potential for the evaluation of activated/proliferating T cells in several contexts such as vaccination, infection, immuno-mediated diseases, and immuno-therapy.

An erratum was issued for:&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/t/61867">A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice</a>. The Authors section and a figure were&#160;updated.
The authors section was updated from:
Sonia Simonetti*1,2, Ambra Natalini*1,2, Giovanna Peruzzi3, Alfredo Nicosia4, Antonella Folgori5, Stefania Capone5, Angela Santoni2, Francesca Di Rosa1 
1Institute of Molecular Biology and Pathology, National Research Council of Italy (CNR), 
2Department of Molecular Medicine, University of Rome &#8220;Sapienza&#8221;, 
3Center for Life Nano Science, Istituto Italiano di Tecnologia, 
4Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 
5Reithera Srl 
* These authors contributed equally
To:
Sonia Simonetti*1,2, Ambra Natalini*1,2, Giovanna Peruzzi3, Alfredo Nicosia4, Antonella Folgori5, Stefania Capone5, Angela Santoni2,6, Francesca Di Rosa1 
1Institute of Molecular Biology and Pathology, National Research Council of Italy (CNR), 
2Department of Molecular Medicine, University of Rome &#8220;Sapienza&#8221;, 
3Center for Life Nano Science, Istituto Italiano di Tecnologia, 
4Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 
5Reithera Srl 
6IRCCS, Neuromed 
* These authors contributed equally
Figure 1 was updated from:
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61867/61867fig1v2.jpg" /> 
Figure 1: Scheme of the protocol for cell cycle analysis of antigen-specific CD8 T cells.&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To:
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61867/61867fig1v4.jpg" /> 
Figure 1: Scheme of the protocol for cell cycle analysis of antigen-specific CD8 T cells.&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig1v4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

An erratum was issued for:&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/t/61867">A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice</a>. The Authors section and a figure were&#160;updated.

Erratum: A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice

An erratum was issued for:&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/t/61867">A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice</a>. The Protocol, Representative Results, and Discussion sections have been&#160;updated.
Step 9.5 of the Protocol was updated from:
Double click on the fully stained sample in the group to open the graph window.
to:
Double click on the fully stained sample in the group to open the graph window and display the ungated events in a dot plot. Note that the x-and y-axis are labelled as in the fcs files, according to the Flow Cytometer settings (Table 2).
Step 9.6 of the Protocol was updated from:
Display the total events acquired for this sample in a dot plot with DNA-A on the x axis and DNA-W on the y-axis.
to:
Check that a sufficient number of ungated events is displayed for appropriate visualization. If necessary, open Preferences by clicking on the &#8220;heart&#8221; icon in the Workspace ribbon, select Graphs, then Dot Plot as graph type, and indicate the number of dots drawn in the corresponding box. Display ungated events in the graph window as a dot plot with DNA-A on the x-axis and DNA-W on the y-axis. Use linear scale for both axes. If necessary, change scale from logarithmic to linear by clicking on the box indicated with a &#8220;T&#8221; (Transform Data Display) close to each axis in the graph window.
Step 9.12 of the Protocol was updated from:
Double click in the center of the &#34;relaxed&#34; gate to display the cells in a dot plot with CD3 on the x-axis and CD8 on the y-axis.
to:
Double click in the center of the &#34;relaxed&#34; gate to display the cells in a dot plot with CD3 on the x-axis and CD8 on the y-axis. Use appropriate axis scale for visualization in the graph window. If necessary, modify x- and/or y-scale by clicking on the box indicated with a &#8220;T&#8221; (Transform Data Display) close to each axis, choose Customize axis function, and modify Extra Neg. decades, Width basis and Positive decades, as necessary.
Step 9.19 of the Protocol was updated from:
Repeat step 9.5 to 9.18 for the &#34;b-LN group.
to:
Copy the entire gating strategy from the &#8220;a-LN&#8221; to the &#34;b-spleen&#8221; group. Copy the first 3 gates of the gating strategy from the &#8220;a-LN&#8221; to the &#8220;c-BM&#8221; group (Figure 2A).
The fourth paragraph of the Representative Results was&#160;updated from:
Notably, the protocol allowed us to have an extremely low background in the antigen-specific CD8 T cell gate of LNs and spleen&#160;of untreated mice (usually 0.00% and at maximum 0.02%). The overlay of gag-specific CD8 T cells onto total CD8 T cells in the FSC-A / SSC-A plot showed that the gag-specific cells had high SSC-A and FSC-A (Figure 3D), confirming the need to use a &#34;relaxed&#34; FSC-A/ SSC-A gating to capture these cells. We then evaluated the percentages of gag-specific CD8 T cells in different cell cycle phases (Figure 4A). We found that gag-specific CD8 T cells in the spleen and even more in the draining LNs contained a high proportion of cells in S-G2/M phases at day 3 post-boost (18.60% and 33.52%, respectively)
to:
Notably, the protocol allowed us to have an extremely low background in the antigen-specific CD8 T cell gate of LNs and spleen&#160;of untreated mice (usually 0.00% and at maximum 0.02%). The&#160;comparison of gag-specific and not gag-specific FSC-A / SSC-A plots&#160;showed that the gag-specific cells had high SSC-A and FSC-A (Figure 3D), confirming the need to use a &#34;relaxed&#34; FSC-A/ SSC-A gate&#160;to capture these cells. We then evaluated the percentages of gag-specific CD8 T cells in different cell cycle phases (Figure 4A). We found that gag-specific CD8 T cells in the spleen and even more in the draining LNs contained a high proportion of cells in S-G2/M phases at day 3 post-boost (18.60% and 33.52%, respectively)
The fourth paragraph of the Discussion was&#160;updated from:
A key point of the protocol is the gating strategy for data analysis. We recently published a novel strategy for T cell analysis at early times of the immune response, which allowed us to increase the sensitivity of detection of antigen-specific T cells12. We applied this strategy to the data shown here as follows. First, we excluded cell aggregates in the DNA-A/W plot. Second, after gating out dead cells, we used a fairly large lymphocyte gate in the FSC/SSC plot (&#34;relaxed gate&#34;). By this strategy, we were able to include highly activated antigen-specific CD8 T cells in S-G2/M that are usually missed by current gating strategies, as these cells have high FSC-A and SSC-A. In summary, the data analysis represents a critical part of the method, which is essential to obtain a sensitive detection of activated /proliferating antigen-specific T cells.
to:
A key point of the protocol is the gating strategy for data analysis. We recently published a novel strategy for T cell analysis at early times of the immune response, which allowed us to increase the sensitivity of detection of antigen-specific T cells12. We applied this strategy to the data shown here as follows. First, we excluded cell aggregates in the DNA-A/W plot. Second, after gating out dead cells, we used a fairly large lymphocyte gate in the FSC/SSC plot (&#34;relaxed gate&#34;). Then, we gated on CD8 T cells, and on antigen-specific cells among them. We analyzed cell cycle by evaluating the DNA/ Ki67 staining profile of the antigen-specific CD8 T cells. By this strategy, we were able to include highly activated antigen-specific CD8 T cells in S-G2/M that are usually missed by current gating strategies, as these cells have high FSC-A and SSC-A. In summary, the data analysis represents a critical part of the method, which is essential to obtain a sensitive detection of activated /proliferating antigen-specific T cells.

An erratum was issued for:&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/t/61867">A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice</a>. The Protocol,&#160;Representative Results, and Discussion&#160;sections have been&#160;updated.

Na&#239;ve T cells undergo clonal expansion and differentiation upon antigen-priming. Differentiated T cells display effector functions that are essential for antigen clearance and for the maintenance of antigen-specific memory, which is key for long-lasting protection. During the first steps of the primary response, na&#239;ve T cell interaction with antigen-presenting cells (APCs) within specialized niches in lymphoid organs is critical to induce the huge T cell proliferation that characterizes the clonal expansion phase1,2,3. T cell-APC interaction is finely regulated by concentration and persistence of antigen, co-stimulatory signals, and soluble factors (cytokines and chemokines) that influence the quantity and quality of the T cell clonal progeny4,5,6,7.
Despite intensive studies of T cell clonal expansion, it is still not known whether antigen-primed T cells complete their entire cell cycle at the site of antigen recognition, or whether they migrate to other organs during cell cycle progression. This lack of knowledge is due to the properties of available tools&#160;for cell cycle analysis. These include monoclonal antibodies (mAbs) specific for the nuclear marker, Ki67, and cell dyes that either identify cells that have undergone the S-phase of the cell cycle (e.g.,&#160;Bromodeoxyuridine&#160;&#160;(BrdU)) or discriminate among daughter cells and their ancestors (e.g., carboxyfluorescein succinimidyl ester (CFSE)).
However, cell-labeling dyes, such as CFSE and BrdU, do not allow the determination as to whether cells found in a particular organ proliferated locally or rather migrated to this site after division8,9. Moreover, the intranuclear protein, Ki67, is only able to distinguish cells in G0 (Ki67-negative cells) from those in any other cell cycle phase (Ki67-positive cells). Thus, Ki67 analysis does not distinguish cells in active proliferation (i.e., in S, G2, or M) from those in G1, which may either quickly progress to division or stay for long periods in G1 or revert to quiescence10,11.
Here, we describe a new flow cytometric method for cell cycle analysis of antigen-specific CD8 T cells12 from the spleen and lymph nodes (LNs) of vaccinated mice (Figure 1). The method exploits a combination of Ki67 and DNA staining that was previously used to analyze the cell cycle of mouse bone marrow (BM) hematopoietic cells13,14. Here, we successfully applied Ki67 plus DNA staining, together with the recently published innovative gating strategy12, to the analysis of CD8 T cell clonal expansion. We were able to clearly discriminate between antigen-specific CD8 T cells in G0, in G1, and in S-G2/M phases in the spleen&#160;and draining LNs of vaccinated mice.

<table><tbody><tr><td>1-200 &amp;mu;L universal fit bulk packed pipet tips</td><td>Corning&amp;nbsp;</td><td>CLS4866-1000EA</td><td></td></tr><tr><td>2.4G2 anti-Fc&amp;gamma;R mAb&amp;nbsp;</td><td>BD</td><td>553141</td><td>10 &amp;mu;g/ml final concentration</td></tr><tr><td>5 ml syringe plunger</td><td>BD Emerald&amp;nbsp;</td><td>307733</td><td></td></tr><tr><td>15 ml conical tubes</td><td>MercK Millipore&amp;nbsp;</td><td>SBHA025SB</td><td></td></tr><tr><td>60 mm TC-treated Cell Culture Dish</td><td>Falcon</td><td>353002</td><td></td></tr><tr><td>70 &amp;mu;m cell strainer&amp;nbsp;</td><td>Falcon</td><td>352097</td><td></td></tr><tr><td>96-well Clear Round Bottom TC-treated Culture Microplate</td><td>Falcon&amp;nbsp;</td><td>353077</td><td></td></tr><tr><td>Anti-Rat/Hamster Ig,k/Negative Control Compensation Particles</td><td>BD- Bioscience</td><td>552845</td><td></td></tr><tr><td>Beta-mercaptoethanol&amp;nbsp;&amp;nbsp;</td><td>Sigma</td><td>M3148</td><td></td></tr><tr><td>Bovine Serum Albumin</td><td>Sigma</td><td>A07030</td><td></td></tr><tr><td>BUV805 Rat Anti-Mouse CD8a&amp;nbsp;</td><td>BD- Bioscience</td><td>564920</td><td>4 &amp;mu;g/ml final concentration</td></tr><tr><td>Dulbecco&#039;s Phosphate Buffer Saline w/o Calcium w/o Magnesium&amp;nbsp;</td><td>Euroclone</td><td>ECB4004L&amp;nbsp;</td><td></td></tr><tr><td>Eppendorf Safe-Lock Tubes, 1.5 mL</td><td>Eppendorf</td><td>30120159</td><td></td></tr><tr><td>Ethanol</td><td>Sigma</td><td>34852-1L-M</td><td></td></tr><tr><td>Ethylenediaminetetraacetic Acid Disodium Salt solution (EDTA)&amp;nbsp;</td><td>Sigma&amp;nbsp;</td><td>E7889</td><td></td></tr><tr><td>Fetal Bovine Serum</td><td>Corning</td><td>35-079-CV</td><td></td></tr><tr><td>Filcon, Sterile, Syringe-Type 70 &amp;mu;m</td><td>Falcon&amp;nbsp;</td><td>352350</td><td></td></tr><tr><td>Fixable Viability Dye eFluor 780</td><td>eBioscience</td><td>65-0865-14</td><td>1:1000 final concentration</td></tr><tr><td>Foxp3 / Transcription Factor Staining Buffer Set</td><td>eBioscience</td><td>00-5523-00</td><td>This Set contains fixation/permeabilization concentrate and diluent, and permeabilization buffer 10x</td></tr><tr><td>H-2k(d) AMQMLKETI allophycocyanin (APC)-labelled tetramer</td><td>provided by NIH Tetramer Core Facility</td><td></td><td>6 &amp;mu;g/ml final concentration</td></tr><tr><td>H-2k(d) AMQMLKETI phycoerythrine (PE) labelled pentamer</td><td>Proimmune&amp;nbsp;</td><td>F176-2A-E - 176</td><td>10 &amp;mu;L / sample&amp;nbsp;</td></tr><tr><td>Hoechst 33342, Trihydrochloride, Trihydrate - 10 mg/mL Solution in Water</td><td>ThermoFisher</td><td>H3570</td><td></td></tr><tr><td>Ki-67 Monoclonal Antibody (SolA15), FITC</td><td>eBioscience</td><td>11-5698-82</td><td>5 &amp;mu;g/ml final concentration</td></tr><tr><td>L-Glutamine 100X (200 mM)</td><td>Euroclone</td><td>ECB3000D&amp;nbsp;</td><td></td></tr><tr><td>Millex-HA Filters 0,45 &amp;micro;m</td><td>BD</td><td>340606</td><td></td></tr><tr><td>Penicillin/Streptomycin 100X</td><td>Euroclone</td><td>ECB3001D&amp;nbsp;</td><td></td></tr><tr><td>PE/Cyanine7 anti-mouse CD62L Antibody</td><td>Biolegend&amp;nbsp;</td><td>104418</td><td>0.2 &amp;mu;g/ml final concentration</td></tr><tr><td>PerCP-Cy&amp;trade;5.5 Hamster Anti-Mouse CD3e&amp;nbsp;</td><td>BD- Bioscience</td><td>551163</td><td>4.4 &amp;mu;g/ml final concentration</td></tr><tr><td>Red Blood Cell Lysis Buffer</td><td>Sigma</td><td>R7757</td><td></td></tr><tr><td>Round-Bottom Polystyrene Tubes, 5 mL</td><td>Falcon&amp;nbsp;</td><td>352058</td><td></td></tr><tr><td>RPMI 1640 Medium without L-Glutamine with Phenol Red</td><td>Euroclone</td><td>ECB9006L&amp;nbsp;</td><td></td></tr><tr><td>Software package for analyzing flow cytometry data</td><td>FlowJo</td><td>v.10</td><td></td></tr><tr><td>Software for acquisition of samples at flowcytometer</td><td>BD FACSDiva&amp;nbsp;</td><td>v 6.2</td><td></td></tr><tr><td>Trypan Blue Solution</td><td>Euroclone</td><td>ECM0990D</td><td></td></tr></tbody></table>

a dna/ki67-based flow cytometry assay for cell cycle analysis of antigen-specific cd8 t cells in vaccinated mice

The cell cycle of antigen-specific T cells in vivo has been examined by using a few methods, all of which possess some limitations. Bromodeoxyuridine (BrdU) marks cells that are in or recently completed S-phase, and carboxyfluorescein succinimidyl ester (CFSE) detects daughter cells after division. However, these dyes do not allow identification of the cell cycle phase at the time of analysis. An alternative approach is to exploit Ki67, a marker that is highly expressed by cells in all phases of the cell cycle except the quiescent phase G0. Unfortunately, Ki67 does not allow further differentiation as it does not separate cells in S-phase that are committed to mitosis from those in G1 that can remain in this phase, proceed into cycling, or move into G0.
Here, we describe a flow cytometric method for capturing a &#34;snapshot&#34; of T cells in different cell cycle phases in mouse secondary lymphoid organs. The method combines Ki67 and DNA staining with major histocompatibility complex (MHC)-peptide-multimer staining and an innovative gating strategy, allowing us to successfully differentiate between antigen-specific CD8 T cells in G0, in G1 and in S-G2/M phases of the cell cycle in the spleen&#160;and draining lymph nodes of mice after vaccination with viral vectors carrying the model antigen gag of human immunodeficiency virus (HIV)-1.
Critical steps of the method were the choice of the DNA dye and the gating strategy to increase the assay sensitivity and to include highly activated/proliferating antigen-specific T cells that would have been missed by current criteria of analysis. The DNA dye, Hoechst 33342, enabled us to obtain a high-quality discrimination&#160;of the G0/G1 and G2/M DNA peaks, while preserving membrane and intracellular staining. The method has great potential to increase knowledge about T cell response in vivo and to improve immuno-monitoring analysis.

The cell cycle phases of cells from spleen, LNs, and BM of Balb/c mice were analyzed using the fluorescent DNA dye, Hoechst, and an anti-Ki67 mAb, according to the protocol summarized in Figure 1. This staining allowed the differentiation of cells in the following phases of cell cycle: G0 (Ki67neg, with 2N of DNA defined as DNAlow), G1 (Ki67pos, DNAlow), and S-G2/M (Ki67pos, with a DNA content comprised between 2N and 4N, or equal to 4N of DNA defined as DNAintermediate/high).
We first performed cell cycle analysis of BM cells to reproduce previously published results13,14 and then analyzed the cells of interest, i.e., CD8 T cells. Figure 2 shows a typical example of cell cycle analysis of BM cells (Figure 2A). The protocol yielded a low coefficient of variation (CV) of G0/G1 and G2/M DNA peaks, indicating the excellent quality of the DNA staining (Figure 2B, showing an example with CV &lt; 2.5; CV was always &lt; 5 in all the experiments).
We then applied the same protocol to antigen-specific CD8 T cells from vaccinated mice. BALB/c mice were vaccinated against the antigen gag of HIV-1 by using Chad3-gag for priming and MVA-gag for boosting, both engineered to carry HIV-1 gag. At day (d) 3 post-boost, we analyzed the frequency of gag-specific CD8 T cells from the spleen and draining LNs. We took advantage of the newly defined gating strategy for T cells in the early phase of immune response, which in contrast to the conventional strategy, is appropriate for detecting highly activated antigen-responding CD8 T cells12. We executed the novel strategy in five subsequent steps. In step 1, we excluded doublets or aggregates by DNA-A/ -W gate, and in step 2, we identified live cells by dead cell marker exclusion. In step 3, we identified the population of interest using a non-conventional "relaxed" FSC-A/ SSC-A gate (Figure 3A) instead of the canonical narrow lymphocyte gate12. After gating on CD3+CD8+ cells (step 4 of Figure 3A), we identified gag-specific CD8 T cells by using two different MHC multimers, i.e., Pent-gag and Tetr-gag (step 5 of Figure 3A). We used two multimers instead of one to improve the sensitivity of gag-specific CD8 T cell detection in vaccinated mice, without increasing the staining background in untreated mice (Figure 3B and C, step 5). Thus, we successfully distinguished untreated mice (0.00% and 0.00% antigen-specific CD8 T cells in LNs and spleen, respectively) from vaccinated mice (0.46% and 0.29% antigen-specific CD8 T cells in LNs and spleen, respectively, Figure 3B and C).
Notably, the protocol allowed us to have an extremely low background in the antigen-specific CD8 T cell gate of LNs and spleen of untreated mice (usually 0.00% and at maximum 0.02%). The comparison of gag-specific and not gag-specific FSC-A / SSC-A plots showed that the gag-specific cells had high SSC-A and FSC-A (Figure 3D), confirming the need to use a "relaxed" FSC-A/ SSC-A gate to capture these cells. We then evaluated the percentages of gag-specific CD8 T cells in different cell cycle phases (Figure 4A). We found that gag-specific CD8 T cells in the spleen and even more in the draining LNs contained a high proportion of cells in S-G2/M phases at day 3 post-boost (18.60% and 33.52%, respectively).
Furthermore, we found that gag-specific CD8 T cells in S-G2/M phases had high FSC-A and SSC-A, when overlaid onto the total CD8 T cells from the same organ (Figure 4B). CD62L expression by gag-specific CD8 T cells was low, as expected for activated T cells, except for a few cells in G0 in the LNs (Figure 4C). Altogether, these results confirmed that the "relaxed" gate (step 3 of Figure 3A, B, and C) was required to include all of the proliferating antigen-specific CD8 T cells12. The protocol was extremely valuable for a "snapshot" evaluation of cell cycle phases of antigen-specific CD8 T cells at the time of analysis and of CD62L expression by cells in different cell cycle phases.
<img alt="Flowchart: Lymphoid cell staining process over two days; includes staining, analysis steps." class="xfigimg" src="/files/ftp_upload/61867/61867fig1v4.jpg" data-altupdatedat="1747736610000" data-alt="Figure 1"> 
Figure 1: Scheme of the protocol for cell cycle analysis of antigen-specific CD8 T cells. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig1v4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Flow cytometry diagrams; cell cycle analysis; DNA-A, FSC-A, SSC-A; gating strategy, Ki67 marker." class="xfigimg" src="/files/ftp_upload/61867/61867fig2v2.jpg" data-altupdatedat="1747736610000" data-alt="Figure 2"> 
Figure 2: Cell cycle analysis of BM cells. BM cells from untreated Balb/c mice were stained and analyzed by flow cytometry. (A) Example of gating strategy. We gated on single cells in the DNA-A/-W plot (left) and subsequently on live cells by dead cell dye exclusion (middle). Then, a "relaxed" FSC-A/SSC-A gate was used for all BM cells (right). (B) Example of cell cycle analysis of BM cells (left). We used a combination of Ki67 and DNA staining to identify cells in the following phases of cell cycle: G0 (bottom left quadrant, Ki67neg-DNAlow cells), G1 (top left quadrant, Ki67pos-DNAlow), S-G2/M (top right quadrant, Ki67pos-DNAintermediate/high). Fluorescence Minus One (FMO) control of Ki67 mAb (middle) and DNA histogram (right) are shown. In the DNA histogram plot, the left and right gates correspond to the G0/G1 and the G2/M DNA peak, respectively, and the numbers represent the coefficients of variation (CV) of each peak. In all the other plots, the numbers represent cell percentages in the indicated gates. The figure shows 1 representative experiment out of 5. In each experiment, we analyzed pooled BM cells from 3 mice. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig2v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Flow cytometry analysis of lymphocyte activation; includes CD8 T cell identification and gag-specificity." class="xfigimg" src="/files/ftp_upload/61867/61867fig3v2.jpg" data-altupdatedat="1747736610000" data-alt="Figure 3"> 
Figure 3: Analysis of antigen-specific CD8 T cells from LNs and spleen. Balb/c mice were primed intramuscularly (i.m.) with Chad3-gag and boosted i.m. with MVA-gag. At day 3 post-boost, draining LN and spleen cells from vaccinated and untreated control mice were stained and analyzed by flow cytometry. (A) Scheme of the gating strategy in five steps to identify single cells (Step 1); live cells (Step 2); lymphocytes (Step 3); CD8 T cells (Step 4); and gag-specific cells (Step 5). (B-C) Example of plots: analysis of cells from (B) LNs and (C) spleen of untreated (top) and vaccinated (bottom) mice. We identified single cells on the DNA-A/ -W plot in Step 1. Then, in Step 2, we selected live cells by dead cell dye exclusion. In Step 3, we used a non-canonical "relaxed" gate for lymphocytes. In Step 4, we identified CD8 T cells by their double expression of CD3 and CD8. We then identified gag-specific cells and not gag-specific in Step 5, based on their capacity to bind fluorochrome-labelled H-2kd-gag-Pentamer (Pent-gag) and H-2kd-gag-Tetramer (Tetr-gag), or not, respectively. (D) FSC-A/SSC-A profiles of gag-specific (blue) and not gag-specific (grey) cells after gating as described above. Numbers represent cell percentages in the indicated gates. The figure shows 1 representative experiment out of 5. In each experiment, we analyzed pooled spleen and pooled LN cells from 3 vaccinated mice and 3 untreated mice. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig3v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Flow cytometry analysis showing Ki67 expression and CD8 cell proliferation in lymph nodes and spleen." class="xfigimg" src="/files/ftp_upload/61867/61867fig4v2.jpg" data-altupdatedat="1747736610000" data-alt="Figure 4"> 
Figure 4: Cell cycle analysis of antigen-specific CD8 T cells. Mice were vaccinated as in Figure 3 and cell cycle analysis of gag-specific cells was performed at day 3 post-boost, after gating in 5 steps as in Figure 3. (A) Example of cell cycle analysis of gag-specific CD8 T cells from LNs (top) and spleen (bottom) of vaccinated mice. Cell cycle phases were identified as in Figure 2B. The panels represent cells in G0, in G1, and in S-G2/M (left) and Fluorescence Minus One (FMO) control of Ki67 mAb (right). Numbers represent cell percentages in the indicated gates. (B) FSC-A/SSC-A dot plots showing gag-specific CD8 T cells in S-G2/M phases (in red) overlaid onto total CD3+CD8+ T cells (in grey) from LNs (top) and spleen (bottom) of vaccinated mice. (C) Offset histograms showing CD62L expression by gag-specific CD8 T cells in G0 (green), in G1 (blue), and in S-G2/M (red) from LNs (top) and spleen (bottom) of vaccinated mice. The y-axes indicate normalized number of events. The figure shows 1 representative example out of 5 independent experiments with a total of 15 mice. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/61867fig4v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Material: Flow cytometer settings. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61867/JoVE-DiRosa-FlowCytometer-Configuration_.xlsx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice at JoVE.com

A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice

Clonal expansion is a key feature of antigen-specific T cell response. However, the cell cycle of antigen-responding T cells has been poorly investigated, partly because of technical limitations. We describe a flow cytometric method to analyze clonally expanding antigen-specific CD8 T cells in spleen and lymph nodes of vaccinated mice.

The cell cycle of antigen-specific T cells in vivo has been examined by using a few methods, all of which possess some limitations. Bromodeoxyuridine ...

a-dnaki67-based-flow-cytometry-assay-for-cell-cycle-analysis-antigen

Nanyang Technological University

Research

JoVE Journal

Immunology and Infection

7.1K Views.  National Research Council of Italy (CNR). Ons protocol biedt een praktische benadering waarmee de milt en lymfeklieren van muizen kunnen worden gebruikt om de dynamiek van T-celrespons groter weer te geven dan het verstrekken van een steady-state fenotypische momentopname. Onze techniek detecteert gevoelig antigeenspecifieke CD8 T-cellen die bezig zijn met een voortdurende respons. Prolifererende CD8 T-cellen worden gemeten zonder de mogelijk verstorende effecten van in vivo medicamenteuze behandeling of celoverdracht.Onze tec...

Video: A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice

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 ...

Isolation and Staining of Mouse Skin Keratinocytes for Cell Cycle Specific Analysis of Cellular Protein Expression by Mass Cytometry

The goal of this protocol is to detect and quantify protein expression changes in a cell cycle-dependent manner using single cells isolated from the epidermis of mouse skin. There are seven important steps: separation of the epidermis from the dermis, digestion of the epidermis, staining of the epidermal cell populations with cisplatin, sample barcoding, staining with metal tagged antibodies for cell cycle markers and proteins of interest, detection of metal-tagged antibodies by mass cytometry, and the analysis of expression in the various cell cycle phases. The advantage of this approach over histological methods is the potential to assay the expression pattern of &#62;40 different markers in a single cell at different phases of the cell cycle. This approach also allows for the multivariate correlation analysis of protein expression that is more quantifiable than histological/imaging methods. The disadvantage of this protocol is that a suspension of single cells is needed, which results in the loss of location information provided by the staining of tissue sections. This approach may also require the inclusion of additional markers to identify different cell types in crude cell suspensions. The application of this protocol is evident in the analysis of hyperplastic skin disease models. Moreover, this protocol can be adapted for the analysis of specific sub-type of cells (e.g., stem cells) by the addition of lineage-specific antibodies. This protocol can also be adapted for the analysis of skin cells in other experimental species.

This protocol describes how to isolate skin keratinocytes from mouse models, to stain with metal-tagged antibodies, and to analyze stained cells by mass cytometry in order to profile the expression pattern of proteins of interest in the different cell cycle phases.

The goal of this protocol is to detect and quantify protein expression changes in a cell cycle-dependent manner using single cells isolated from the ...

Developmental Biology

Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination

Traditional vaccine adjuvants, such as alum, elicit suboptimal CD8+ T cell responses. To address this major challenge in vaccine development, various nanoparticle systems have been engineered to mimic features of pathogens to improve antigen delivery to draining lymph nodes and increase antigen uptake by antigen-presenting cells, leading to new vaccine formulations optimized for induction of antigen-specific CD8+ T cell responses. In this article, we describe the synthesis of a &#8220;pathogen-mimicking&#8221; nanoparticle system, termed interbilayer-crosslinked multilamellar vesicles (ICMVs) that can serve as an effective vaccine carrier for co-delivery of subunit antigens and immunostimulatory agents and elicitation of potent cytotoxic CD8+ T lymphocyte (CTL) responses. We describe methods for characterizing hydrodynamic size and surface charge of vaccine nanoparticles with dynamic light scattering and zeta potential analyzer and present a confocal microscopy-based procedure to analyze nanoparticle-mediated antigen delivery to draining lymph nodes. Furthermore, we show a new bioluminescence whole-animal imaging technique utilizing adoptive transfer of luciferase-expressing, antigen-specific CD8+ T cells into recipient mice, followed by nanoparticle vaccination, which permits non-invasive interrogation of expansion and trafficking patterns of CTLs in real time. We also describe tetramer staining and flow cytometric analysis of peripheral blood mononuclear cells for longitudinal quantification of endogenous T cell responses in mice vaccinated with nanoparticles.

We describe whole-animal imaging and flow cytometry-based techniques for monitoring expansion of antigen-specific CD8+ T cells in response to immunization with nanoparticles in a murine model of vaccination.

Traditional vaccine adjuvants, such as alum, elicit suboptimal CD8+ T cell responses. To address this major challenge in vaccine development, various ...

Flow Cytometry-Based Monitoring of Cancer-Immunity Cycle 

Co-Culture In Vitro Systems to Reproduce the Cancer-Immunity Cycle

Fundamental cancer research and the development of effective counterattack therapies both rely on experimental studies detailing the interactions between cancer and immune cells, the so-called cancer-immunity cycle. In vitro co-culture systems combined with multiparametric flow cytometry (mFC) and tumor-on-a-chip microfluidic devices (ToCs) enable simple, fast, and reliable monitoring and characterization of each step of the cancer-immunity cycle and lead to the identification of the mechanisms responsible for tipping the balance between cancer immunosurveillance and immunoevasion. A thorough understanding of the dynamic interplays between cancer and immune cells provides critical insights to outsmart tumors and will accelerate the pace of therapeutic personalization and optimization in patients. Specifically, here we detail a straightforward mFC- and ToC-assisted protocol for unraveling the dynamic complexities of each step of the cancer-immunity cycle in murine cancer cell lines and mouse-derived immune cells and focus on immunosurveillance. Considering the time- and cost-related features of this protocol, it is certainly feasible on a large scale. Moreover, with minor variations, this protocol can be both adapted to human cancer cell lines and human peripheral-blood-derived immune cells and combined with genetic and/or pharmacologic inhibition of specific pathways in order to identify biomarkers of immune response.

Monitoring the Cancer-Immunity Cycle and Exploring Tumor Microenvironment Dynamics

Here, we detail a simple, fast, and reliable multiparametric flow cytometry- and tumor-on-a-chip-assisted protocol to monitor and characterize the steps constituting the cancer-immunity cycle. Indeed, a thorough understanding of the interplays between cancer and immune cells provides critical insights to outsmart tumors and guide clinical care.

Fundamental cancer research and the development of effective counterattack therapies both rely on experimental studies detailing the interactions between ...

Cancer Research

Simultaneous Quantification of Anti-vector and Anti-transgene-Specific CD8+ T Cells Via MHC I Tetramer Staining After Vaccination with a Viral Vector

Upon viral infection, antigen-specific CD8+ cytotoxic T cells (CTLs) arise and contribute to the elimination of infected cells to prevent the spread of pathogens. Therefore, the frequency of antigen-specific CTLs is indicative of the strength of the T cell response against a specific antigen. Such analysis is important in basic immunology, vaccine development, cancer immunobiology and the adaptive immunology. In the vaccine field, the CTL response directed against components of a viral vector co-determines how effective the generation of antigen-specific cells against the antigen of interest (i.e., transgene) is. Antigen-specific CTLs can either be detected by stimulation with specific peptides followed by intracellular cytokine staining or by the direct staining of antigen-specific T cell receptors (TCRs) and analysis by flow cytometry. The first method is rather time-consuming since it requires sacrificing of animals to isolate cells from organs. Also, it requires isolation of blood from small animals which is difficult to perform. The latter method is rather fast, can be easily done with small amounts of blood and is not dependent on specific effector functions, such as cytolytic activity. MHC tetramers are an ideal tool to detect antigen-specific TCRs.
Here, we describe a protocol to simultaneously detect antigen-specific CTLs for the immunodominant peptides of the viral vector VSV-GP (LCMV-GP, VSV-NP) and transgenes (OVA, HPV 16 E7, eGFP) by MHC I tetramer staining and flow cytometry. Staining is possible either directly from blood or from single cell suspensions of organs, such as spleen. Blood or single cell suspensions of organs are incubated with tetramers. After staining with antibodies against CD3 and CD8, antigen-specific CTLs are quantified by flow cytometry. Optionally, antibodies against CD43, CD44, CD62L or others can be included to determine the activation status of antigen-specific CD8+T cells and to discriminate between na&#239;ve and effector cells.

Simultaneous Quantification of Anti-vector and Anti-transgene-Specific CD8+ T Cells Via MHC I Tetramer Staining After Vaccination with a Viral Vector

Here, we present a protocol for the ex vivo qualitative detection of antigen-specific CD8+ T cells. Analysis is possible with single cell suspensions from organs or from small amounts of blood. A broad range of studies require the analysis of cytotoxic T cell responses (vaccination and cancer immunotherapy studies).

Upon viral infection, antigen-specific CD8+ cytotoxic T cells (CTLs) arise and contribute to the elimination of infected cells to prevent the spread of ...

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

The assessment of modern sub-unit vaccines reveals that the generation of neutralizing antibodies is important but not sufficient for adjuvant selection. Therefore, adjuvants with both humoral and cellular immuno-stimulatory capabilities that are able to promote cytotoxic T lymphocytes (CTL) responses are urgently needed. Thus, faithful monitoring of adjuvant candidates that induce cross-priming and subsequently enhance CTL generation represents a crucial step in vaccine development. In here we present an application for a method that uses SIINFEKL-specific (OT-I) T cells to monitor the cross-presentation of the model antigen ovalbumin (OVA) in vivo in the presence of different adjuvant candidates. This method represents a rapid test to select adjuvants with the best cross-priming capabilities. The proliferation of CD8+ T cells is the most valuable indication of cross-priming and it is also regarded as a correlate of adjuvant-induced cross-presentation. This feature can be evaluated in different immune organs like lymph nodes and spleen. The extent of the CTL generation can also be monitored, thereby giving insights on the nature of a local (draining lymph node mainly) or a systemic response (distant lymph nodes and/or spleen). This technique further allows multiple modifications for testing drugs that can inhibit specific cross-presentation pathways and also offers the possibility to be used in different strains of conventional and genetically modified mice. In summary, the application that we present here will be useful for vaccine laboratories in industry or academia that develop or modify chemical adjuvants for vaccine research and development.

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development

We present here an application for a standard immunological technique (CFSE stained OT-I proliferation) intended to rapidly monitor adjuvant-mediated cytotoxic T lymphocyte (CTL) generation in vivo. This fast estimation of CTL capacities is useful for the development of prophylactic vaccines against intracellular pathogens as well as therapeutic cancer vaccines.

The assessment of modern sub-unit vaccines reveals that the generation of neutralizing antibodies is important but not sufficient for adjuvant selection. ...

Medicine

Isolation of Mouse Kidney-Resident CD8+ T cells for Flow Cytometry Analysis

Tissue-resident memory T cell (TRM) is a rapidly expanding field of immunology research. Isolating T cells from various non-lymphoid tissues is one of the key steps to investigate TRMs. There are slight variations in lymphocyte isolation protocols for different organs. Kidney is an essential non-lymphoid organ with numerous immune cell infiltration especially after pathogen exposure or autoimmune activation. In recent years, multiple labs including our own have started characterizing kidney resident CD8+ T cells in various physiological and pathological settings in both mouse and human. Due to the abundance of T lymphocytes, kidney represents an attractive model organ to study TRMs in non-mucosal or non-barrier tissues. Here, we will describe a protocol commonly used in TRM-focused labs to isolate CD8+ T cells from mouse kidneys following systemic viral infection. Briefly, using an acute lymphocytic choriomeningitis virus (LCMV) infection model in C57BL/6 mice, we demonstrate intravascular CD8+ T cell labeling, enzymatic digestion, and density gradient centrifugation to isolate and enrich lymphocytes from mouse kidneys to make samples ready for the subsequent flow cytometry analysis.

Isolation of Mouse Kidney-Resident CD8+ T cells for Flow Cytometry Analysis

Following viral infection, kidney harbors a relatively large number of CD8+ T cells and offers an opportunity to study non-mucosal TRM cells. Here, we describe a protocol to isolate mouse kidney lymphocytes for flow cytometry analysis.

Tissue-resident memory T cell (TRM) is a rapidly expanding field of immunology research. Isolating T cells from various non-lymphoid tissues is one of the ...

Elucidating T-Cell Kinetics: Methods for Real-Time Migration Analysis

Real-Time In Vitro Migration Assay for Primary Murine CD8+ T Cells

The adaptive immune response is reliant on a T cell&#39;s ability to migrate through blood, lymph, and tissue&#160;in response to pathogens and foreign bodies. T cell migration is a complex process that requires the coordination of many signal inputs from the environment and local immune cells, including chemokines, chemokine receptors, and adhesion molecules. Furthermore, T cell motility is influenced by dynamic surrounding environmental cues, which can alter activation state, transcriptional landscape, adhesion molecule expression, and more. In vivo, the complexity of these seemingly intertwined factors makes it difficult to distinguish individual signals that contribute to T cell migration. This protocol provides a string of methods from T cell isolation to computer-aided analysis to assess T cell migration in real-time&#160;under highly specific environmental conditions.&#160;These conditions&#160;may help&#160;elucidate mechanisms that regulate migration, improving our&#160;understanding of T cell kinetics and providing&#160;strong mechanistic evidence that is difficult&#160;to attain through animal experiments. A deeper understanding of the&#160;molecular interactions that impact cell&#160;migration is important to develop improved therapeutics.

Author Spotlight: Understanding Disease Mechanisms Through Real-Time Analysis of T-Cell Migration

This protocol providesa method of primary murine T cell isolation and time-lapse microscopy of T cell migration under specific environmental conditions with quantitative analysis.

The adaptive immune response is reliant on a T cell&#39;s ability to migrate through blood, lymph, and tissue&#160;in response to pathogens and foreign ...

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.

Cell Cycle Analysis: Assessing CD4 and CD8 T Cell Proliferation

Source: Perchet Thibaut1,2,3, Meunier Sylvain1,2,3, Sophie Novault4, Rachel Golub1,2,3
1 Unit for Lymphpoiesis, Department of Immunology, Pasteur ...

Education

JoVE Science Education

Advanced Biology

Immunology

An Assay for Cell Cycle Analysis of Antigen-Specific CD8+ T Cells

Source: Simonetti, S., et al. <a href="https://app-jove-com.remotexs.ntu.edu.sg/v/61867">A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice.</a> J. Vis. Exp. (2021)
This video demonstrates an assay to analyze antigen-specific CD8+ T cells in different cell cycle stages. Fluorescently-labeled viable cells are selected using flow cytometry, and the cells in the different cell cycle stages are identified by their DNA content using antibodies against cell proliferation-associated nuclear protein and a nucleic acid stain.

1. Preparation of medium and staining solution

	Prepare Complete Medium: Roswell Park Memorial Institute (RPMI) medium with 2 mM glutamine, 100 U/mL ...

A DNA/Ki67-Based Flow Cytometry Assay for Cell Cycle Analysis of Antigen-Specific CD8 T Cells in Vaccinated Mice

Samenvatting

Meer video's verkennen

Hoofdstukken in deze video