Name: single-cell analysis of immunophenotype and cytokine production in peripheral whole blood via mass cytometry
Uploaded: 2018-06-26T13:30:00
Description: Watch this Scientific Journal Video about Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry at JoVE.com

We would like to thank Aimee Pugh-Bernard for her intellectual input and helpful comments. This work was supported by the Boettcher Foundation Webb-Waring Biomedical Research Award and award number K23-1K23AR070897 from the NIH to Elena W.Y. Hsieh. She was also supported by award number K12-HD000850 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Lucile Packard Foundation for Children&#39;s Health, Stanford CTSA UL1 TR001085, and Child Health Research Institute of Stanford University.

All methods described here have been approved by the Colorado Multiple Institutional Review Board (COMIRB) of the University of Colorado. All described procedures below should be performed in a sterile tissue culture hood unless stated otherwise, with filtered pipette tips, and all reagents filtered.
1. Preparation of Reagents for Peripheral Whole Blood Processing
<ol>
	<li>Prepare ruxolitinib stock aliquots (10&#8211;15 &#956;L/vial for single use) at 10 mM by diluting the lyophilized reage...

<ol>
	<li>Walsh, S. J., Rau, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autoimmune+diseases:+a+leading+cause+of+death+among+young+and+middle-aged+women+in+the+United+States.">Autoimmune diseases: a leading cause of death among young and middle-aged women in the United States.</a> American journal of public health. 90 (9), 1463-1466 (2000).</li><li>Mak, A., Cheung, M. W. -. L., Chiew, H. J., Liu, Y., Ho, R. C. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+trend+of+survival+and+damage+of+systemic+lupus+erythematosus:+meta-analysis+and+meta-regression+of+observational+studies+from+the+1950s+to+2000s.">Global trend of survival and damage of systemic lupus erythematosus: meta-analysis and meta-regression of observational studies from the 1950s to 2000s.</a> Seminars in arthritis and rheumatism. 41 (6), 830-839 (2012).</li><li>Kaul, A., Gordon, 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+lupus+erythematosus.">Systemic lupus erythematosus.</a> Nature reviews. Disease primers. 2, 16039 (2016).</li><li>Annunziato, F., Romagnani, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heterogeneity+of+human+effector+CD4++T+cells.">Heterogeneity of human effector CD4+ T cells.</a> Arthritis Research &amp; Therapy. 11 (6), 257 (2009).</li><li>Peck, A., Mellins, E. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plasticity+of+T-cell+phenotype+and+function:+the+T+helper+type+17+example.">Plasticity of T-cell phenotype and function: the T helper type 17 example.</a> Immunology. 129 (2), 147-153 (2010).</li><li>Basso, A. S., Cheroutre, H., Mucida, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=More+stories+on+Th17+cells.">More stories on Th17 cells.</a> Cell research. 19 (4), 399-411 (2009).</li><li>Ornatsky, O., Bandura, D., Baranov, V., Nitz, M., Winnik, M. A., Tanner, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Highly+multiparametric+analysis+by+mass+cytometry.">Highly multiparametric analysis by mass cytometry.</a> Journal of Immunological Methods. 361 (1-2), 1-20 (2010).</li><li>Ornatsky, O., Baranov, V. I., Bandura, D. R., Tanner, S. D., Dick, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+cellular+antigen+detection+by+ICP-MS.">Multiple cellular antigen detection by ICP-MS.</a> Journal of Immunological Methods. 308 (1-2), 68-76 (2006).</li><li>Bendall, S. C., Simonds, E. 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=Single-Cell+Mass+Cytometry+of+Differential+Immune+and+Drug+Responses+Across+a+Human+Hematopoietic+Continuum.">Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum.</a> Science. 332 (6030), 687-696 (2011).</li><li>Bandura, D. R., Baranov, V. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+Cytometry:+Technique+for+Real+Time+Single+Cell+Multitarget+Immunoassay+Based+on+Inductively+Coupled+Plasma+Time-of-Flight+Mass+Spectrometry.">Mass Cytometry: Technique for Real Time Single Cell Multitarget Immunoassay Based on Inductively Coupled Plasma Time-of-Flight Mass Spectrometry.</a> Analytical Chemistry. 81 (16), 6813-6822 (2009).</li><li>Leipold, M. D., Maecker, H. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+cytometry:+protocol+for+daily+tuning+and+running+cell+samples+on+a+CyTOF+mass+cytometer.">Mass cytometry: protocol for daily tuning and running cell samples on a CyTOF mass cytometer.</a> Journal of visualized experiments : JoVE. (69), e4398 (2012).</li><li>McCarthy, R. L., Duncan, A. D., Barton, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sample+Preparation+for+Mass+Cytometry+Analysis.">Sample Preparation for Mass Cytometry Analysis.</a> Journal of visualized experiments : JoVE. (122), (2017).</li><li>Rahman, A., Isenberg, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systemic+lupus+erythematosus.">Systemic lupus erythematosus.</a> The New England journal of medicine. 358 (9), 929-939 (2008).</li><li>O'Gorman, W. E., Hsieh, E. W. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+systems-level+analysis+of+human+Toll-like+receptor+activation+defines+a+chemokine+signature+in+patients+with+systemic+lupus+erythematosus.">Single-cell systems-level analysis of human Toll-like receptor activation defines a chemokine signature in patients with systemic lupus erythematosus.</a> The Journal of allergy and clinical immunology. 136 (5), 1326-1336 (2015).</li><li>O'Gorman, W. E., Kong, D. 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=Mass+cytometry+identifies+a+distinct+monocyte+cytokine+signature+shared+by+clinically+heterogeneous+pediatric+SLE+patients.">Mass cytometry identifies a distinct monocyte cytokine signature shared by clinically heterogeneous pediatric SLE patients.</a> Journal of Autoimmunity. 81, 74-89 (2017).</li><li>Simonds, E. F., Bendall, S. 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=Extracting+a+cellular+hierarchy+from+high-dimensional+cytometry+data+with+SPADE.">Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE.</a> Nature Biotechnology. , 1-8 (2011).</li><li>Amir, E. -. A. D., Davis, K. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=viSNE+enables+visualization+of+high+dimensional+single-cell+data+and+reveals+phenotypic+heterogeneity+of+leukemia.">viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.</a> Nature Biotechnology. 31 (6), 545-552 (2013).</li><li>Bruggner, R. V., Bodenmiller, B., Dill, D. L., Tibshirani, R. J., Nolan, G. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+identification+of+stratifying+signatures+in+cellular+subpopulations.">Automated identification of stratifying signatures in cellular subpopulations.</a> Proceedings of the National Academy of Sciences of the United States of America. 111 (26), E2770-E2777 (2014).</li><li>Levine, J. H., Simonds, E. 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=Data-Driven+Phenotypic+Dissection+of+AML+Reveals+Progenitor-like+Cells+that+Correlate+with+Prognosis.">Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis.</a> Cell. 162 (1), 184-197 (2015).</li><li>Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L., Nolan, G. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+mapping+of+phenotype+space+with+single-cell+data.">Automated mapping of phenotype space with single-cell data.</a> Nature Publishing Group. 13 (6), 493-496 (2016).</li><li>Spitzer, M. H., Gherardini, P. 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=IMMUNOLOGY.+An+interactive+reference+framework+for+modeling+a+dynamic+immune+system.">IMMUNOLOGY. An interactive reference framework for modeling a dynamic immune system.</a> Science. 349 (6244), 1259425 (2015).</li><li>Fienberg, H. G., Simonds, E. F., Fantl, W. J., Nolan, G. P., Bodenmiller, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+platinum-based+covalent+viability+reagent+for+single-cell+mass+cytometry.">A platinum-based covalent viability reagent for single-cell mass cytometry.</a> Cytometry Part A. 81 (6), 467-475 (2012).</li><li>Jansen, K., Blimkie, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polychromatic+flow+cytometric+high-throughput+assay+to+analyze+the+innate+immune+response+to+Toll-like+receptor+stimulation.">Polychromatic flow cytometric high-throughput assay to analyze the innate immune response to Toll-like receptor stimulation.</a> Journal of Immunological Methods. 336 (2), 183-192 (2008).</li><li>Zunder, E. R., Finck, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Palladium-based+mass+tag+cell+barcoding+with+a+doublet-filtering+scheme+and+single-cell+deconvolution+algorithm.">Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm.</a> Nature Protocols. 10 (2), 316-333 (2015).</li><li>Lai, L., Ong, R., Li, J., Albani, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+CD45-based+barcoding+approach+to+multiplex+mass-cytometry+(CyTOF).">A CD45-based barcoding approach to multiplex mass-cytometry (CyTOF).</a> Cytometry Part A. , (2015).</li><li>Mei, H. E., Leipold, M. D., Schulz, A. R., Chester, C., Maecker, H. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Barcoding+of+live+human+peripheral+blood+mononuclear+cells+for+multiplexed+mass+cytometry.">Barcoding of live human peripheral blood mononuclear cells for multiplexed mass cytometry.</a> The Journal of Immunology. 194 (4), 2022-2031 (2015).</li><li>Finck, R., Simonds, E. 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=Normalization+of+mass+cytometry+data+with+bead+standards.">Normalization of mass cytometry data with bead standards.</a> Cytometry Part A. 83 (5), 483-494 (2013).</li><li>Takahashi, C., Au-Yeung, 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=Mass+cytometry+panel+optimization+through+the+designed+distribution+of+signal+interference.">Mass cytometry panel optimization through the designed distribution of signal interference.</a> Cytometry. Part A : the journal of the International Society for Analytical Cytology. 91 (1), 39-47 (2017).</li></ol>

Here we describe a novel, single-cell, proteomic approach to simultaneously assess multiple immune cell types and detect their various cytokine perturbations in the milieu of patient specific &#34;pathogenic&#34; peripheral blood plasma circulating factors. This method employs peripheral whole blood as the analytical vehicle, and mass cytometry as the tool for the evaluation of immune cellular phenotypic and functional abnormalities. The method is readily applicable to human and mice studies21, an...

Autoimmune diseases are a major cause of morbidity and mortality affecting 3-8% of the population. In the United States, autoimmune disorders are among the leading causes of death among young and middle-aged women (ages &#60;65 years)1,2. Autoimmune disorders are characterized by heterogeneous clinical presentation and diverse underlying immunological processes. The spectrum of heterogeneity is well represented across different disorders, such as joint involvement in rheumatoid arthritis (RA) and neurological disease in multiple sclerosis (MS). However, this level of heterogeneity is also exemplified within a single disorder, such as systemic lupus erythematosus (SLE): some patients may present with renal pathology, while others suffer from hematologic or joint involvement3.
The underlying immunopathogenesis in autoimmune disorders mirrors the clinical heterogeneity, involving auto- and hyper-activation of multiple innate and adaptive immune cell subsets, and concomitant dysregulated cytokine production. While cytokines play a pivotal role in the pathogenesis of autoimmune disease, understanding their specific role in the mechanism of disease has proven to be challenging. Cytokines are characterized by pleiotropy (one cytokine can have multiple effects on different cell types), redundancy (multiple cytokines can have the same effect), duality (one cytokine can have pro- or anti-inflammatory effects under different conditions), and plasticity (cytokines can be molded into a role different from its &#34;original&#34; one, depending on the environment)4,5,6. Consequently, population-level methods cannot distinguish heterogeneous cellular responses to the same &#34;cytokine milieu&#34;. Similarly, study designs that focus on one specific aspect of the immune system (a single cell type or cytokine), do not offer a global assessment of all the elements involved in complex autoimmune disease. While patient sera-based studies have afforded important insights into autoimmunity, they do not provide the specific cellular source of the dysregulated cytokines detected.
Recently, we developed a single-cell proteomic approach to simultaneously assess multiple immune cell types, and detect their various cytokine perturbations in the milieu of patient specific &#34;pathogenic&#34; peripheral blood plasma circulating factors. The workflow described here is characterized by the use of intact peripheral whole blood samples, as opposed to isolated peripheral blood mononuclear cells (PBMCs). Peripheral whole blood represents the most physiologically relevant vehicle to study systemic immune-mediated disease, including 1) non-mononuclear blood cells often involved in autoimmune disease (i.e., neutrophils, platelets), and 2) plasma circulating factors, such as nucleic acids, immune complexes, and cytokines, which have immune activating roles. To capture the &#34;intrinsic pathogenic&#34; dysregulated cytokine production, peripheral blood samples are processed immediately after the blood draw (T0, Time zero), and after 6 h of incubation at 37 &#176;C (physiological body temperature) with a protein transport inhibitor in the absence of any exogenous stimulating condition (T6, Time 6 h), to detect cytokine production (accumulation, T6-T0) that would reflect the &#34;intrinsic&#34; disease state (Figure 1). To study dysregulated processes that reflect over or under-activation of signaling pathways involved in immune responses relevant to the disease, peripheral blood samples are treated (6 h incubation at 37 &#176;C with a protein transport inhibitor) with an exogenous stimulating condition that reflects disease pathogenesis, such as Toll-Like-Receptor (TLR) agonists in the case of SLE (T6 + R848, Time 6 h with 1 &#181;g/mL R848), to detect cytokine production that would reflect a response to nucleic acids (comparing T0 vs. T6 vs. T6 + R848, Figure 1). To study immunomodulatory effects of available therapeutics ex vivo, as they pertain to the precise immune dysregulated processes for specific patients, peripheral blood samples are treated with a JAK inhibitor at the relevant therapeutic concentration (here, 5 uM ruxolitinib; T6 + 5R, Time 6 h with 5 uM ruxolitinib), to detect changes in &#34;intrinsic&#34; disease state in response to the drug (T0 vs. T6 vs. T6 + 5R, Figure 1). A JAK inhibitor was chosen for this study because JAK inhibitors have been shown to be successful in the treatment of autoimmune disorders such as RA.
To simultaneously evaluate the dysregulated processes described above in multiple immune cell subsets, peripheral blood samples from SLE patients and healthy controls were processed as described above and analyzed by mass cytometry. Mass cytometry, also known as Cytometry-Time-Of-Flight, offers single-cell analysis of over 40 parameters without issues of spectral overlap7,8,9. This technique utilizes rare earth metal isotopes in the form of soluble metal ions as tags bound to antibodies, instead of fluorophores10. Additional details regarding the mass cytometry technological platform (i.e., tuning and calibration, sample acquisition) can be found in Leipold et al. and McCarthy et al.11,12 The high-dimensionality of mass cytometry enables simultaneous measurement of multiple cytokines throughout innate and adaptive immune cell subsets with single-cell granularity (Table of Materials).
Current conventional clinical and laboratory parameters are often not sensitive or specific enough for detecting ongoing disease activity or the response to specific immunomodulators13, reflecting the need to better delineate the underlying immune changes that drive flare-ups. Given the pervasiveness of cytokine dysregulation in autoimmune disease, a plethora of treatment approaches that use antibodies or small molecular inhibitors targeting cytokines or signaling proteins involved in the regulation of cytokine production have recently emerged. In its basic format, the peripheral blood analytical approach described here provides a platform to identify patient-specific dysregulated cell subsets and their abnormal cytokine production in autoimmune disease with systemic manifestations. This methodology allows for the personalization of therapeutic choices as specific dysregulated cytokines can be identified, and specific treatment options can be tested ex vivo to assess their ability to immunomodulate the patient specific disease process.

<table>
	<tbody>
		<tr>
			<td>Ruxolitinib</td>
			<td>Santa Cruz</td>
			<td>SC-364729A</td>
			<td>Stock Conc: 10 mM; Final Conc: 5 &#956;M</td>
		</tr>
		<tr>
			<td>R848</td>
			<td>Invivogen</td>
			<td>tlrl-r848-5</td>
			<td>Stock Conc: 1 &#956;g/&#956;L; Final Conc: 1 &#956;g/mL</td>
		</tr>
		<tr>
			<td>LPS-EK</td>
			<td>Invivogen</td>
			<td>tlrl-eklps</td>
			<td>Stock Conc: 1 &#956;g/&#956;L; Final Conc: 0.1 &#956;g/mL</td>
		</tr>
		<tr>
			<td>Sterile PBS</td>
			<td>Lonza</td>
			<td>17-516F</td>
			<td></td>
		</tr>
		<tr>
			<td>Lyse/Fix Buffer</td>
			<td>BD biosciences</td>
			<td>558049</td>
			<td>Stock Conc: 5X; Final Conc: 1X (dilute in ddH2O)</td>
		</tr>
		<tr>
			<td>&#160;BD Phosflow perm/wash buffer I</td>
			<td>BD biosciences</td>
			<td>557885</td>
			<td>Stock Conc: 10X; Final Conc: 1:10 (dilute in ddH2O)</td>
		</tr>
		<tr>
			<td>RPMI</td>
			<td>Gibco</td>
			<td>21870-076</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Azide (NaN3)</td>
			<td>Sigma-Aldrich</td>
			<td>S-8032</td>
			<td>Stock Conc: &#62;99.9%; Final Conc: 0.0002</td>
		</tr>
		<tr>
			<td>Protein Transport Inhibitor (PTI)</td>
			<td>eBiosciences</td>
			<td>00-4980-93</td>
			<td>Stock Conc: 500X; Final Conc: 1X</td>
		</tr>
		<tr>
			<td>DNA Intercalator</td>
			<td>Fluidigm</td>
			<td>201192B</td>
			<td>Stock Conc: 500 &#956;M; Final Conc: 0.1 &#956;M</td>
		</tr>
		<tr>
			<td>Cell Staining Media (CSM)</td>
			<td></td>
			<td></td>
			<td>PBS + 0.5% BSA, 0.02% NaN3</td>
		</tr>
		<tr>
			<td>MaxPar Barcode Perm Buffer</td>
			<td>Fluidigm</td>
			<td>201057</td>
			<td>Stock Conc: 10X; Final Conc: 1X</td>
		</tr>
		<tr>
			<td>20-plex Pd Barcode Set</td>
			<td>Fluidigm</td>
			<td>S0014</td>
			<td>Stock Conc: n/a; Final Conc: n/a</td>
		</tr>
		<tr>
			<td>EQ TM Four Element Calibration Beads</td>
			<td>Fluidigm</td>
			<td>201078</td>
			<td>Stock Conc: 10X; Final Conc: 1X</td>
		</tr>
		<tr>
			<td>16% MeOH-free Formaldehyde Solution</td>
			<td>Thermo</td>
			<td>28908</td>
			<td>Stock Conc: 16% (w/v); Final Conc: 1.6% (w/v)</td>
		</tr>
		<tr>
			<td>Sterile round bottom polystyrene tubes</td>
			<td>VWR</td>
			<td>60818-496</td>
			<td>Stock Conc: n/a; Final Conc: n/a</td>
		</tr>
		<tr>
			<td>Polypropylene cluster tubes</td>
			<td>Light Labs</td>
			<td>A-9001</td>
			<td>Stock Conc: n/a; Final Conc: n/a</td>
		</tr>
		<tr>
			<td>Helios CyTOF instrument</td>
			<td>Fluidigm</td>
			<td>Helios</td>
			<td>All solutions to be used in CyTOF analysis need to be free of metal contamination. ddH2O is used in the preparation of any solutions should have a resistivity of at least 18.0 M&#937;.cm. ddH2O and any self-prepared solutions should be stored in new plastic or glass bottles that have never been autoclaved.</td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Antibodies used for Mass Cytometry</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Surface markers</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>CD1c</td>
			<td>Biolegend</td>
			<td>L161</td>
			<td>Mass: 161</td>
		</tr>
		<tr>
			<td>CD3</td>
			<td>BD</td>
			<td>UCHT1</td>
			<td>Mass: 144</td>
		</tr>
		<tr>
			<td>CD4</td>
			<td>Biolegend</td>
			<td>SK3</td>
			<td>Mass: 174</td>
		</tr>
		<tr>
			<td>CD7</td>
			<td>BD</td>
			<td>M-T701</td>
			<td>Mass: 149</td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>Biolegend</td>
			<td>SK1</td>
			<td>Mass: 142</td>
		</tr>
		<tr>
			<td>CD11b</td>
			<td>Fluidigm</td>
			<td>ICRF44</td>
			<td>Mass: 209</td>
		</tr>
		<tr>
			<td>CD11c</td>
			<td>BD</td>
			<td>B-ly6</td>
			<td>Mass: 152</td>
		</tr>
		<tr>
			<td>CD15</td>
			<td>BD</td>
			<td>HI98</td>
			<td>Mass: 115</td>
		</tr>
		<tr>
			<td>CD14</td>
			<td>Biolegend</td>
			<td>M5E2</td>
			<td>Mass: 154</td>
		</tr>
		<tr>
			<td>CD16</td>
			<td>eBioscience/Thermo</td>
			<td>B73.1</td>
			<td>Mass: 165</td>
		</tr>
		<tr>
			<td>CD19</td>
			<td>Santa Cruz</td>
			<td>SJ25C1</td>
			<td>Mass: 163</td>
		</tr>
		<tr>
			<td>CD21</td>
			<td>Biolegend</td>
			<td>Bu32</td>
			<td>Mass: 141</td>
		</tr>
		<tr>
			<td>CD27</td>
			<td>BD</td>
			<td>L128</td>
			<td>Mass: 155</td>
		</tr>
		<tr>
			<td>CD38</td>
			<td>Fluidigm</td>
			<td>HIT2</td>
			<td>Mass: 172</td>
		</tr>
		<tr>
			<td>CD45 total</td>
			<td>Biolegend</td>
			<td>HI30</td>
			<td>Mass: 89</td>
		</tr>
		<tr>
			<td>CD45RA</td>
			<td>Biolegend</td>
			<td>HI100</td>
			<td>Mass: 153</td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>Miltenyi</td>
			<td>REA196</td>
			<td>Mass: 168</td>
		</tr>
		<tr>
			<td>CD66</td>
			<td>BD</td>
			<td>B1.1/CD66</td>
			<td>Mass: 113</td>
		</tr>
		<tr>
			<td>CD86</td>
			<td>Fluidigm</td>
			<td>IT2.2</td>
			<td>Mass: 150</td>
		</tr>
		<tr>
			<td>CD123</td>
			<td>Fluidigm</td>
			<td>6H6</td>
			<td>Mass: 143</td>
		</tr>
		<tr>
			<td>CD278/ICOS</td>
			<td>Biolegend</td>
			<td>C398.4A</td>
			<td>Mass: 156</td>
		</tr>
		<tr>
			<td>CD179/PD1</td>
			<td>Biolegend</td>
			<td>EH12.2H7</td>
			<td>Mass: 162</td>
		</tr>
		<tr>
			<td>IgD</td>
			<td>Biolegend</td>
			<td>IA6-2</td>
			<td>Mass: 146</td>
		</tr>
		<tr>
			<td>IgM</td>
			<td>Biolegend</td>
			<td>MHM-88</td>
			<td>Mass: 151</td>
		</tr>
		<tr>
			<td>CXCR5</td>
			<td>BD</td>
			<td>RF8B2</td>
			<td>Mass: 173</td>
		</tr>
		<tr>
			<td>HLADR</td>
			<td>Biolegend</td>
			<td>L243</td>
			<td>Mass: 167</td>
		</tr>
		<tr>
			<td>Cytokines</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>IL-1&#945;</td>
			<td>Biolegend</td>
			<td>364-3B3-14</td>
			<td>Mass: 147</td>
		</tr>
		<tr>
			<td>IL-1&#946;</td>
			<td>Biolegend&#160;</td>
			<td>H1b-98</td>
			<td>Mass: 169</td>
		</tr>
		<tr>
			<td>IL-1RA</td>
			<td>Santa Cruz&#160;</td>
			<td>AS17</td>
			<td>Mass: 157</td>
		</tr>
		<tr>
			<td>IL-6</td>
			<td>Biolegend</td>
			<td>MQ2-13A5</td>
			<td>Mass: 164</td>
		</tr>
		<tr>
			<td>IL-8</td>
			<td>BD</td>
			<td>E8N1</td>
			<td>Mass: 160</td>
		</tr>
		<tr>
			<td>IL-12/IL-23p40</td>
			<td>Biolegend&#160;</td>
			<td>C8.6</td>
			<td>Mass: 171</td>
		</tr>
		<tr>
			<td>IL-17A</td>
			<td>Biolegend&#160;</td>
			<td>BL168</td>
			<td>Mass: 148</td>
		</tr>
		<tr>
			<td>IL23p19</td>
			<td>eBioscience/Thermo</td>
			<td>23dcdp</td>
			<td>Mass: 176</td>
		</tr>
		<tr>
			<td>MIP1&#946;</td>
			<td>BD</td>
			<td>D21-1351</td>
			<td>Mass: 158</td>
		</tr>
		<tr>
			<td>MCP1</td>
			<td>BD</td>
			<td>5D3-F7</td>
			<td>Mass: 170</td>
		</tr>
		<tr>
			<td>IFN&#945;</td>
			<td>Miltenyi&#160;</td>
			<td>LT27:295</td>
			<td>Mass: 175</td>
		</tr>
		<tr>
			<td>IFN&#947;</td>
			<td>Biolegend</td>
			<td>4S.B3</td>
			<td>Mass: 165</td>
		</tr>
		<tr>
			<td>PTEN</td>
			<td>BD</td>
			<td>A2B1</td>
			<td>Mass: 159</td>
		</tr>
		<tr>
			<td>TNF&#945;</td>
			<td>Biolegend</td>
			<td>Mab11</td>
			<td>Mass: 166</td>
		</tr>
		<tr>
			<td>Note: If the manufacturer is stated as Fluidigm, this antibody was purchased from Fluidigm with metal pre-conjugated. If the manufacturer is stated as other than Fluidigm, this antibody was self-conjugated using the MaxPar Multi-Metal Labeling&#160; Kit (Fluidigm Cat: 201300) according to manufacturer protocol.&#160;</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

single-cell analysis of immunophenotype and cytokine production in peripheral whole blood via mass cytometry

Cytokines play a pivotal role in the pathogenesis of autoimmune diseases. Hence, the measurement of cytokine levels has been the focus of multiple studies in an attempt to understand the precise mechanisms that lead to the breakdown of self-tolerance and subsequent autoimmunity. Approaches thus far have been based on the study of one specific aspect of the immune system (a single or few cell types or cytokines), and do not offer a global assessment of complex autoimmune disease. While patient sera-based studies have afforded important insights into autoimmunity, they do not provide the specific cellular source of the dysregulated cytokines detected. A comprehensive single-cell approach to evaluate cytokine production in multiple immune cell subsets, within the context of &#34;intrinsic&#34; patient-specific plasma circulating factors, is described here. This approach enables monitoring of the patient-specific immune phenotype (surface markers) and function (cytokines), either in its native &#34;intrinsic pathogenic&#34; disease state, or in the presence of therapeutic agents (in vivo or ex vivo).

Figure 1 demonstrates the workflow for the stimulation and processing of the peripheral blood samples, including allocation of blood sample aliquots, timing of the addition of stimulation agents, protein transport inhibitor cocktail, and incubation times until the red blood cell (RBC) lysis and fixation. The choice of stimulating agents will depend on the signaling and cytokine pathways that are targeted for assessment. For example, in the protocol described ...

Watch this Scientific Journal Video about Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry at JoVE.com

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Here we describe a single-cell proteomic approach to evaluate immune phenotypic and functional (intracellular cytokine induction) alterations in peripheral whole blood samples, analyzed via mass cytometry.

Cytokines play a pivotal role in the pathogenesis of autoimmune diseases. Hence, the measurement of cytokine levels has been the focus of multiple studies ...

This method can help answer questions in the autoimmunity field such as identifying cell frequency abnormalities and function differences such as production of key cytokines in the setting of autoimmune disease. The main advantage of this method is that it can capture a broad repertoire or different cell types and function differences from a easily obtainable peripheral blood sample. Generally, individuals new to this process may struggle with getting the timing of the blood processing steps right, the antibody panel design, the barcoding process itself, and analysis of high dimensional single cell data.This systems immunology approach is particularly suitable for autoimmune diseases like SLE where immune dysregulation is pervasive and evident in peripheral blood. Visual demonstration of this method is important to clarify the timing of steps and also to show how multiple samples can be barcoded and pooled prior to mass cytometry analysis. To begin this procedure, place the labeled round bottom polystyrene tubes of five different conditions for whole blood processing on a rack.Next, add one milliliter of 37 degree Celsius RPMI to each tube. Then, add one milliliter of whole blood to each tube and pipette up and down several times to mix thoroughly with RPMI. Subsequently, add 10 microliters of pre-diluted ruxolitinib to the tube labeled T six plus five R and mix thoroughly.Place the rack of tubes in the incubator at 37 degrees Celsius and begin timing the incubation. To process the T zero sample, pipette the entire content of the T zero tube into a labeled conical tube containing 20 milliliters of 37 degree Celsius lyse/fix buffer at working concentration. To optimize cell recovery, rinse the tube with lyse/fix buffer and mix by inverting the conical tube.Incubate the cells at 37 degrees Celsius for 15 minutes to allow for lysis and fixation. Then, centrifuge the cells at 500 times G for five minutes at room temperature. Afterward, decant the supernatant and re-suspend the cells in one milliliter of ice cold PBS to break up the pellet.Then, fill the conical tube to a 15 milliliter volume with PBS. Subsequently, centrifuge the cells at 500 times G for five minutes at room temperature. Re-suspend the cells in one milliliter of CSM to break up the pellet.Then, transfer the sample to a labeled microcentrifuge tube for antibody staining. Using an automated cell counter, count the cells with a 10 microliter sample. Next, centrifuge the cells at 500 times G for five minutes at room temperature.Afterward, aspirate the supernatant, leaving the pellet in about 60 microliters of residual. Keep this pellet on ice until the samples from other conditions have completed processing. At T equals 30 minutes, transfer the tube rack to the tissue culture hood.Add 10 microliters of R848 at 0.1 grams per microliter to the T six plus R848 tube and mix thoroughly. Then, add 10 microliters of LPS at 0.01 micrograms per microliter to the T six plus LPS tube and mix thoroughly. Afterward, add four microliters of protein transport inhibitor to the tubes labeled T six, T six plus five R, and T six plus LPS and return the samples to the incubator until T equals six hours.Mix the samples thoroughly with a P1000 pipette every two hours. At T equals two hours, add four microliters of protein transport inhibitor cocktail to the T six plus R848 tube. Mix all samples and return the rack to the incubator until T equals six hours.At T equals four hours, mix the samples with a P1000 pipette one more time. At T equals six hours, process T six, T six plus LPS, T six plus R848, and T six plus five R blood sample tubes as described for the T zero sample. Then, store the pellets in residual CSM volume at minus 80 degrees Celsius to process later.To barcode the lysed, fixed cells, thaw the samples from the minus 80 degrees Celsius storage slowly on ice. Dilute the 10X barcoding perm buffer with PBS by one to 10 and make enough buffer for three milliliters per sample. Fill one non-sterile trough with CSM and one with the one X barcoding perm buffer.Then, add one milliliter of ice cold CSM to the freshly thawed samples, mix thoroughly, and transfer to the respective pre-labeled polypropylene cluster tubes. Now, take a 10 microliter sample and count the cells using an automated cell counter. Normalize the cell counts in each cluster tube by removing the volume of excess cells.Then, centrifuge the cells at 600 times G for five minutes at room temperature. Re-suspend the cells in one milliliter of one X barcoding perm buffer with a multichannel pipette and centrifuge at 600 times G for five minutes at room temperature. Afterward, aspirate off the supernatant.Line up the cluster tubes on a rack in the same order as indicated on the barcode key so the sample matches with its barcode. Add 800 microliters of one X barcoding perm buffer by multichannel pipette to all samples in the cluster tubes without touching the cell pellet to reduce cell loss. Then, set aside the rack with the cluster tubes.Remove the 20-plex palladium barcoding kit tube strips from minus 20 degrees Celsius and thaw at room temperature. Add 100 microliters of one X barcoding perm buffer, mix thoroughly, and transfer 120 microliters of the re-suspended barcode mix into the corresponding cell samples in the cluster tubes. Mix thoroughly by multichannel pipette so that there is no cross-contamination between individually barcoded samples.Incubate cluster tubes for 30 minutes at room temperature to allow the barcodes to label the cells. After 30 minutes, centrifuge the samples at 600 times G for five minutes at room temperature. Aspirate the supernatant, then re-suspend them in one milliliter of CSM.Subsequently, centrifuge and re-suspend in CSM again. Afterward, centrifuge at 600 times G for five minutes at room temperature and aspirate the supernatant. With a single pipette and using the same tip, transfer all cell pellets in about 70 to 80 microliters of residual volume to one polystyrene tube.Do not eject the pipette tip. Set aside the single pipette with this tip. With a multichannel pipette and new tips, add 100 microliters of CSM to each original cluster tube to maximize cell recovery.Using the single pipette with the tip that was set aside, transfer all cell pellets in 100 microliters of residual volume to the same polystyrene tube. Add CSM to top off the polystyrene tube to about three milliliters. Count and record the cell number of the pooled barcode set.Then, centrifuge at 600 times G for five minutes at room temperature and aspirate the supernatant. Proceed to staining the barcoded samples on the same day. This schematic demonstrates the workflow for the stimulation and processing of the peripheral blood samples, including allocation of blood sample aliquots, timing of the addition of stimulation agents, protein transport inhibitor cocktail, and incubation times until the red blood cell lysis and fixation.The choice of stimulating agents will depend on the signaling and cytokine pathways that are targeted for assessment. Following fixation and RBC lysis, the individual lysed, fixed cell samples from a healthy donor were barcoded, labeled with 26 antibodies against surface markers, permeabilized, and stained with 14 antibodies against cytokines. The limited gating strategy representing the identification of CD14 high monocytes is shown here.From left to right, each 2D plot represented is a population subset from the parent population that is gated from the 2D plot immediately to the left. Using CD14 high monocytes as representative in eight immune cell subsets, a mass cytometry analysis was performed on peripheral blood samples from a healthy donor at time zero unstimulated and following stimulation with TLR agonist LPS and R848 and the T-cell activator PMA ionomycin. An example of the cytokine induction in CD14 high monocytes is shown and selected cytokines with specificity to the stimulating agent used are depicted.R848 selectively induces IL-12p40 subunit and MCP1 in CD14 high monocytes while LPS does not. In contrast, PMA ionomycin does not induce cytokines in CD14 high monocytes. Once mastered, the blood stimulations can be done in about seven hours and the barcoding step can get done in just about an hour.When attempting this procedure, it's important to be mindful of the timing of the steps and to plan ahead accordingly. Once you have this procedure in place, you can consider altering the blood stimulation conditions in the mass cytometry panel in order to assess the immune cell responses that are specific to your own research aims. After watching this video, you should have a good understanding of how to elicit cytokine responses from whole blood samples and how to pool multiple samples into a barcoded set for mass cytometry analysis.

single-cell-analysis-immunophenotype-cytokine-production-peripheral

Research

JoVE Journal

Immunology and Infection

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly constituted by proteins and exopolysaccharides, among other factors 7-10. The microbial community encased within the biofilm often shows the differentiation of distinct subpopulation of specialized cells 11-17. These subpopulations coexist and often show spatial and temporal organization within the biofilm 18-21.
Biofilm formation in the model organism Bacillus subtilis requires the differentiation of distinct subpopulations of specialized cells. Among them, the subpopulation of matrix producers, responsible to produce and secrete the extracellular matrix of the biofilm is essential for biofilm formation 11,19. Hence, differentiation of matrix producers is a hallmark of biofilm formation in B. subtilis.
We have used fluorescent reporters to visualize and quantify the subpopulation of matrix producers in biofilms of B. subtilis 15,19,22-24. Concretely, we have observed that the subpopulation of matrix producers differentiates in response to the presence of self-produced extracellular signal surfactin 25. Interestingly, surfactin is produced by a subpopulation of specialized cells different from the subpopulation of matrix producers 15.
We have detailed in this report the technical approach necessary to visualize and quantify the subpopulation of matrix producers and surfactin producers within the biofilms of B. subtilis. To do this, fluorescent reporters of genes required for matrix production and surfactin production are inserted into the chromosome of B. subtilis. Reporters are expressed only in a subpopulation of specialized cells. Then, the subpopulations can be monitored using fluorescence microscopy and flow cytometry (See Fig 1).
The fact that different subpopulations of specialized cells coexist within multicellular communities of bacteria gives us a different perspective about the regulation of gene expression in prokaryotes. This protocol addresses this phenomenon experimentally and it can be easily adapted to any other working model, to elucidate the molecular mechanisms underlying phenotypic heterogeneity within a microbial community.

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Microbial biofilms are generally constituted by distinct subpopulations of specialized cells. Single-cell analysis of these subpopulations requires the use of fluorescent reporters. Here we describe a protocol to visualize and monitor several subpopulationswithin B. subtilis biofilms using fluorescence microscopy and flow cytometry.

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly ...

Enumeration of Major Peripheral Blood Leukocyte Populations for Multicenter Clinical Trials Using a Whole Blood Phenotyping Assay

Cryopreservation of peripheral blood leukocytes is widely used to preserve cells for immune response evaluations in clinical trials and offers many advantages for ease and standardization of immunological assessments, but detrimental effects of this process have been observed on some cell subsets, such as granulocytes, B cells, and dendritic cells 1-3. Assaying fresh leukocytes gives a more accurate picture of the in vivo state of the cells, but is often difficult to perform in the context of large clinical trials. Fresh cell assays are dependent upon volunteer commitments and timeframes and, if time-consuming, their application can be impractical due to the working hours required of laboratory personnel. In addition, when trials are conducted at multiple centers, laboratories with the resources and training necessary to perform the assays may not be located in sufficient proximity to clinical sites. To address these issues, we have developed an 11-color antibody staining panel that can be used with Trucount tubes (Becton Dickinson; San Jose, CA) to phenotype and enumerate the major leukocyte populations within the peripheral blood, yielding more robust cell-type specific information than assays such as a complete blood count (CBC) or assays with commercially-available panels designed for Trucount tubes that stain for only a few cell types. The staining procedure is simple, requires only 100 &mu;l of fresh whole blood, and takes approximately 45 minutes, making it feasible for standard blood-processing labs to perform. It is adapted from the BD Trucount tube technical data sheet (<a href="http://www.bdbiosciences.com/external_files/is/doc/tds/Package_Inserts_CE/live/web_enabled/23-3483-06_PI_Trucount tubes_CE_EN.pdf" target="_blank">version 8/2010</a>). The staining antibody cocktail can be prepared in advance in bulk at a central assay laboratory and shipped to the site processing labs. Stained tubes can be fixed and frozen for shipment to the central assay laboratory for multicolor flow cytometry analysis. The data generated from this staining panel can be used to track changes in leukocyte concentrations over time in relation to intervention and could easily be further developed to assess activation states of specific cell types of interest. In this report, we demonstrate the procedure used by blood-processing lab technicians to perform staining on fresh whole blood and the steps to analyze these stained samples at a central assay laboratory supporting a multicenter clinical trial. The video details the procedure as it is performed in the context of a clinical trial blood draw in the HIV Vaccine Trials Network (HVTN).

In this report, we demonstrate the staining and analysis steps of a phenotyping assay performed on fresh whole blood to enumerate major innate and adaptive leukocyte populations. We emphasize considerations for performing these procedures in the context of a multicenter clinical trial.

Cryopreservation of peripheral blood leukocytes is widely used to preserve cells for immune response evaluations in clinical trials and offers many ...

Dissecting Innate Immune Signaling in Viral Evasion of Cytokine Production

In response to a viral infection, the host innate immune response is activated to up-regulate gene expression and production of antiviral cytokines. Conversely, viruses have evolved intricate strategies to evade and exploit host immune signaling for survival and propagation. Viral immune evasion, entailing host defense and viral evasion, provides one of the most fascinating and dynamic interfaces to discern the host-virus interaction. These studies advance our understanding in innate immune regulation and pave our way to develop novel antiviral therapies.
Murine &#947;HV68 is a natural pathogen of murine rodents. &#947;HV68 infection of mice provides a tractable small animal model to examine the antiviral response to human KSHV and EBV of which perturbation of in vivo virus-host interactions is not applicable. Here we describe a protocol to determine the antiviral cytokine production. This protocol can be adapted to other viruses and signaling pathways.
Recently, we have discovered that &#947;HV68 hijacks MAVS and IKK&#946;, key innate immune signaling components downstream of the cytosolic RIG-I and MDA5, to abrogate NF&#922;B activation and antiviral cytokine production. Specifically, &#947;HV68 infection activates IKK&#946; and that activated IKK&#946; phosphorylates RelA to accelerate RelA degradation. As such, &#947;HV68 efficiently uncouples NF&#922;B activation from its upstream activated IKK&#946;, negating antiviral cytokine gene expression. This study elucidates an intricate strategy whereby the upstream innate immune activation is intercepted by a viral pathogen to nullify the immediate downstream transcriptional activation and evade antiviral cytokine production.

We describe a protocol to measure the antiviral cytokine production in mice infected with a model herpesvirus, murine gamma herpesvirus 68 (&#947;HV68) that is closely-related to human Kaposi&#8217;s sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV). Utilizing genetically modified mouse strains and mouse embryonic fibroblasts (MEFs), we assessed the antiviral cytokine production both in vivo and ex vivo. &#8220;Reconstituting&#8221; the expression of innate immune components in knockout embryonic fibroblasts by lentiviral transduction, we further pinpoint specific innate immune molecules and dissect the key signaling events that differentially regulate the antiviral cytokine production.

In response to a viral infection, the host innate immune response is activated to up-regulate gene expression and production of antiviral cytokines. ...

A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood

Immunophenotyping of peripheral blood by flow cytometry determines changes in the frequency and activation status of peripheral leukocytes during disease and treatment. It has the potential to predict therapeutic efficacy and identify novel therapeutic targets. Whole blood staining utilizes unmanipulated blood, which minimizes artifacts that can occur during sample preparation. However, whole blood staining must also be done on freshly collected blood to ensure the integrity of the sample. Additionally, it is best to prepare antibody cocktails on the same day to avoid potential instability of tandem-dyes and prevent reagent interaction between brilliant violet dyes. Therefore, whole blood staining requires careful standardization to control for intra and inter-experimental variability.
Here, we report deployment of an automated liquid handler equipped with a two-dimensional (2D) barcode reader into a standard process of making antibody cocktails for flow cytometry. Antibodies were transferred into 2D barcoded tubes arranged in a 96 well format and their contents compiled in a database. The liquid handler could then locate the source antibody vials by referencing antibody names within the database. Our method eliminated tedious coordination for positioning of source antibody tubes. It provided versatility allowing the user to easily change any number of details in the antibody dispensing process such as specific antibody to use, volume, and destination by modifying the database without rewriting the scripting in the software method for each assay.
A proof of concept experiment achieved outstanding inter and intra- assay precision, demonstrated by replicate preparation of an 11-color, 17-antibody flow cytometry assay. These methodologies increased overall throughput for flow cytometry assays and facilitated daily preparation of the complex antibody cocktails required for the detailed phenotypic characterization of freshly collected anticoagulated peripheral blood.

Whole blood Immunophenotyping is indispensable for monitoring the human immune system. However, the number of reagents required and the instability of specific fluorochromes in premixed cocktails necessitates daily reagent preparation. Here we show that semi-automated preparation of staining antibody cocktail helps establish reliable immunophenotyping by minimizing variability in reagent dispensing.

Immunophenotyping of peripheral blood by flow cytometry determines changes in the frequency and activation status of peripheral leukocytes during disease ...

Isolation and Flow Cytometric Analysis of Glioma-infiltrating Peripheral Blood Mononuclear Cells

Our laboratory has recently demonstrated that natural killer (NK) cells are capable of eradicating orthotopically implanted mouse GL26 and rat CNS-1 malignant gliomas soon after intracranial engraftment if the cancer cells are rendered deficient in their expression of the &#946;-galactoside-binding lectin galectin-1 (gal-1). More recent work now shows that a population of Gr-1+/CD11b+ myeloid cells is critical to this effect. To better understand the mechanisms by which NK and myeloid cells cooperate to confer gal-1-deficient tumor rejection we have developed a comprehensive protocol for the isolation and analysis of glioma-infiltrating peripheral blood mononuclear cells (PBMC). The method is demonstrated here by comparing PBMC infiltration into the tumor microenvironment of gal-1-expressing GL26 gliomas with those rendered gal-1-deficient via shRNA knockdown. The protocol begins with a description of&#160;how to culture and prepare GL26 cells for inoculation into the syngeneic C57BL/6J mouse brain. It then explains the steps involved in the isolation and flow cytometric analysis of glioma-infiltrating PBMCs from the early brain tumor microenvironment. The method is adaptable to a number of in vivo experimental designs in which temporal data on immune infiltration into the brain is required. The method is sensitive and highly reproducible, as glioma-infiltrating PBMCs can be isolated from intracranial tumors as soon as 24 hr post-tumor engraftment with similar cell counts observed from time point matched tumors throughout independent experiments. A single experimentalist can perform the method from brain harvesting to flow cytometric analysis of glioma-infiltrating PBMCs in roughly 4-6 hr depending on the number of samples to be analyzed. Alternative glioma models and/or cell-specific detection antibodies may also be used at the experimentalists&#8217; discretion to assess the infiltration of several other immune cell types of interest without the need for alterations to the overall procedure.

Presented here is a straightforward method for the isolation and flow cytometric analysis of glioma-infiltrating peripheral blood mononuclear cells that yields time-dependent quantitative data on the number and activation status of immune cells entering the early brain tumor microenvironment.

Our laboratory has recently demonstrated that natural killer (NK) cells are capable of eradicating orthotopically implanted mouse GL26 and rat CNS-1 ...

Flow Cytometric Analysis of Natural Killer Cell Lytic Activity in Human Whole Blood

NK cell cytotoxicity is a widely used measure to determine the effect of outside intervention on NK cell function. However, the accuracy and reproducibility of this assay can be considered unstable, either because of user&#39;s errors or because of the sensitivity of NK cells to experimental manipulation. To eliminate these issues, a workflow that reduces them to a minimum was established and is presented here. To illustrate, we obtained blood samples, at various time points, from runners (n = 4) that were submitted to an intense bout of exercise. First, NK cells are simultaneously identified and isolated through CD56 tagging and magnetic-based sorting, directly from whole blood and from as little as one milliliter. The sorted NK cells are removed of any reagent or capping antibodies. They can be counted in order to establish an accurate NK cell count per milliliter of blood. Secondly, the sorted NK cells (effectors cells or E) can be mixed with 3,3&#39;-Diotadecyloxacarbocyanine Perchlorate (DiO) tagged K562 cells (target cells or T) at an assay-optimal 1:5 T:E ratio, and analyzed using an imaging flow-cytometer that allows for the visualization of each event and the elimination of any false positive or false negatives (such as doublets or effector cells). This workflow can be completed in about 4 h, and allows for very stable results even when working with human samples. When available, research teams can test several experimental interventions in human subjects, and compare measurements across several time points without compromising the data&#39;s integrity.

This work describes an advanced workflow for the accurate and fast determination of NK (Natural Killer) cell count and NK cell cytotoxicity in human blood samples.

NK cell cytotoxicity is a widely used measure to determine the effect of outside intervention on NK cell function. However, the accuracy and ...

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis

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

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

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

Preparation of Whole Bone Marrow for Mass Cytometry Analysis of Neutrophil-lineage Cells

In this article, we present a protocol that is optimized to preserve neutrophil-lineage cells in fresh BM for whole BM CyTOF analysis. We utilized a myeloid-biased 39-antibody CyTOF panel to evaluate the hematopoietic system with a focus on the neutrophil-lineage cells by using this protocol. The CyTOF result was analyzed with an open-resource dimensional reduction algorithm, viSNE, and the data was presented to demonstrate the outcome of this protocol. We have discovered new neutrophil-lineage cell populations based on this protocol. This protocol of fresh whole BM preparation may be used for 1), CyTOF analysis to discover unidentified cell populations from whole BM, 2), investigating whole BM defects for patients with blood disorders such as leukemia, 3), assisting optimization of fluorescence-activated flow cytometry protocols that utilize fresh whole BM.

Here, we present a protocol to process fresh bone marrow (BM) isolated from mouse or human for high-dimensional mass cytometry (Cytometry by Time-Of-Flight, CyTOF) analysis of neutrophil-lineage cells.

In this article, we present a protocol that is optimized to preserve neutrophil-lineage cells in fresh BM for whole BM CyTOF analysis. We utilized a ...

Separation of Immune Cell Subpopulations in Peripheral Blood Samples from Children with Infectious Mononucleosis

Infectious mononucleosis (IM) is an acute syndrome mostly associated with primary Epstein&#8211;Barr virus (EBV) infection. The main clinical symptoms include irregular fever, lymphadenopathy, and significantly increased lymphocytes in peripheral blood. The pathogenic mechanism of IM is still unclear; there is no effective treatment method for it, with mainly symptomatic therapies being available. The main question in EBV immunobiology is why only a small subset of infected individuals shows severe clinical symptoms and even develop EBV-associated malignancies, whilemost individuals are asymptomatic for life with the virus.
B cells are first involved in IM because EBV receptors are presented on their surface. Natural killer (NK) cells are cytotoxic innate lymphocytes that are important for killing EBV-infected cells. The proportion of CD4+ T cells decreases while that of CD8+ T cells expands dramatically during acute EBV infection, and the persistence of CD8+ T cells is important for lifelong control of IM. Those immune cells play important roles in IM, and their functions need to be identified separately. For this purpose, monocytes are separated first from peripheral blood mononuclear cells (PBMCs) of IM individuals using CD14 microbeads, a column, and a magnetic separator.
The remaining PBMCs are stained with peridinin-chlorophyll-protein (PerCP)/Cyanine 5.5 anti-CD3, allophycocyanin (APC)/Cyanine 7 anti-CD4, phycoerythrin (PE) anti-CD8, fluorescein isothiocyanate (FITC) anti-CD19, APC anti-CD56, and APC anti-CD16 antibodies to sort CD4+ T cells, CD8+ T cells, B cells, and NK cells using a flow cytometer. Furthermore, transcriptome sequencing of five subpopulations was performed to explore their functions and pathogenic mechanisms in IM.

We describe a method combining immunomagnetic beads and fluorescence-activated cell sorting to isolate and analyze defined immune cell subpopulations of peripheral blood mononuclear cells (monocytes, CD4+ T cells, CD8+ T cells, B cells, and natural killer cells). Using this method, magnetic and fluorescently labeled cells can be purified and analyzed.

Infectious mononucleosis (IM) is an acute syndrome mostly associated with primary Epstein&#8211;Barr virus (EBV) infection. The main clinical symptoms ...

Detection of Polyfunctional T Cells in Children Vaccinated with Japanese Encephalitis Vaccine via the Flow Cytometry Technique

T cell-mediated immunity plays an important role in controlling flavivirus infection, either after vaccination or after natural infection. The "quality" of a T cell needs to be assessed by function, and higher function is associated with more powerful immune protection. T cells that can simultaneously produce two or more cytokines or chemokines at the single-cell level are called polyfunctional T cells (TPFs), which mediate immune responses through a variety of molecular mechanisms to express degranulation markers (CD107a) and secrete interferon (IFN)-&#947;, tumor necrosis factor (TNF)-&#945;, interleukin (IL)-2, or macrophage inflammatory protein (MIP)-1&#945;. There is increasing evidence that TPFs are closely related to the maintenance of long-term immune memory and protection and that their increased proportion is an important marker of protective immunity and is important in the effective control of viral infection and reactivation. This evaluation applies not only to specific immune responses but also to the assessment of cross-reactive immune responses. Here, taking the Japanese encephalitis virus (JEV) as an example, the detection method and flow cytometry color scheme of JEV-specific TPFs produced by peripheral blood mononuclear cells of children vaccinated against Japanese encephalitis were tested to provide a reference for similar studies.

Detection of Polyfunctional T Cells in Children Vaccinated with Japanese Encephalitis Vaccine via the Flow Cytometry Technique

The present protocol combines ex vivo stimulation and flow cytometry to analyze polyfunctional T cell (TPF)&#160;profiles in peripheral blood mononuclear cells (PBMCs) within Japanese encephalitis virus (JEV)-vaccinated children. The detection method and flow cytometry color scheme of JEV-specific TPFs were tested to provide a reference for similar studies.

T cell-mediated immunity plays an important role in controlling flavivirus infection, either after vaccination or after natural infection. The "quality" ...