Time of Flight Mass Cytometry (Cytof): Flying way beyond Fluorescent flow

flow cytometryFlow cytometry has been around since the 1950s when Wallace Coulter developed the first flow cytometry device and fluorescence-based flow cytometry was introduced in 1968 by Wolfgang Göhde.  Since then, fluorescence-based flow cytometry and fluorescence-activated cell sorting (FACS) have blown up to become a mainstay of analytical scientific approaches in every field of cell biology, especially immunology.  However, the dominance of fluorescence-based flow cytometry for analytical cellular biology may change with the recent introduction of a new technology: Time of Flight Mass Cytometry (CyTOF).

In fluorescence-based flow cytometry, cells or particles labeled with fluorescent dye-conjugated antibodies or other fluorescent proteins flow in a single file stream past a series of lasers that emit light at specific wavelengths, causing the fluorescent dyes to become excited and emit light caught by detectors.  Thus, a quantitative measure of intensity for each fluorescent parameter, pertaining to the expression level of the antibody-targeted antigen of interest, is obtained for every cell.  The BD Biosciences Influx cell sorter is currently a top of the line fluorescence-based flow cytometer, and supports up to 10 lasers and detection of up to 24 parameters.  However, even with a thorough understanding of flow cytometry, the actual number of utilizable parameters will be typically be far less due to limitations including spectral overlap of fluorescent dyes.

CyTOF utilizes an entirely different technique to quantify protein expression levels on a single cell level: the use of transition element isotopes to label antibodies.  The quantities of isotopes bound to each cell are then analyzed by a time-of-flight mass spectrometer.  While compensation issues due to spectral overlap between fluorophores limits the effective number of parameters assessable by fluorescence-based flow cytometry to far below the theoretical maximums, CyTOF does not suffer from these limitations as there is no requirement for compensation.  In addition, as the metal isotopes used are rare, there is no autofluorescence of cells, another limitation of fluorescence-based flow cytometry. Proof of principle studies have been published by Gary Nolan and colleagues at Stanford University, and have demonstrated the simultaneous use of 34 cell surface and intracellular parameters.  The CyTOF instrument can theoretically detect up to 100 isotopes, thus far extending the ability of researchers to simultaneously assess the expression of many more proteins per cell.

The CyTOF instrument is commercially available from DVS Sciences.  DVS Sciences also offers an expanding list of pre-conjugated metal isotope-labeled antibody reagents and additionally a MAXPAR® labeling kit for conjugation of other antibodies to 33 different metals, allowing researchers to select many additional antigens of interest for analysis.

I have previously stressed the importance of studying cell biology on the single cell level in order to understand the relationships that occur between expression of proteins and signaling states in unique cell populations and on the single cell level.  The addition of CyTOF to the reseracher’s arsenal will allow these types of questions to be addressed on an even more complex level.


Additional Reading:

The history and future of the fluorescence activated cell sorter and flow cytometry: a view from StanfordHerzenberg LA, Parks D, Sahaf B, Perez O, Roederer M, Herzenberg LA. Clin Chem. 2002 Oct;48(10):1819-27.

Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.  Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Science. 2011 May 6;332(6030):687-96. doi: 10.1126/science.1198704.

Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry.  Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, Pavlov S, Vorobiev S, Dick JE, Tanner SD. Anal Chem. 2009 Aug 15;81(16):6813-22. doi: 10.1021/ac901049w.

Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity. 2012 Jan 27;36(1):142-52. doi: 10.1016/j.immuni.2012.01.002.

Tricks for analyzing PBMC populations by flow cytometry

photo credit: PNNL – Pacific Northwest National Laboratory via photopincc

Natural IgMs: A possible therapeutic role in autoimmunity?

Antibodies play a significant role in countering foreign threats and ensuring specificity of self/non-self recognition. However, in healthy individuals, a substantial proportion of circulating IgM antibodies, secreted constitutively by B1 cells has been observed to demonstrate self-reactivity in the absence of antigen activation. These antibodies, which are present from birth without external stimulation, are known as natural auto-antibodies (NAA). Interestingly, such antibodies were found in human cord blood as well as in mice raised in germ-free conditions. One important feature of these molecules is their broad spectrum of reactivity to antigens ranging from proteins, polysaccharides and nucleotides to phospholipids. Though there are numerous reports that describe the crucial functions of NAAs in protection against infection, here I would like to discuss more about the role of these polymeric IgMs in maintaining tissue homeostasis and autoimmunity, with a brief look at the future of using this class of antibodies for therapeutic purposes.                                        

Though the immune system has strict mechanisms of ensuring removal of self reactive B cells to prevent autoimmune diseases, growing evidence suggests that auto IgMs produced by B1 cells play a major role in clearance of apoptotic cells (AC) and maintaining immune homeostasis. The innate immune system recognizes markers on cells destined to undergo apoptosis and clears them by a process called efferocytosis. Any defect in this clearance mechanism could lead to release and accumulation of autoantigenic proteins from these dying cells, resulting in the development of autoimmune diseases in predisposed individuals. A large number of the NAAs bind to oxidation associated markers like phosphorylcholine (PC) and malondialdehyde (MDA) that become exposed on apoptotic cells, but are conformationally inaccessible in the healthy ones. Recognition of such cells by auto IgMs promotes their complement mediated clearance (Fig. 1, Silverman 2012).


describe the imageFigure 1: A simplified overview of the clearance of apoptotic cells by natural IgMs via recruitment of complement factors (Silverman 2012)

Recent reports have demonstrated that mice engineered to be deficient in IgMs are more susceptible to autoimmune diseases resulting from the defective clearance of ACs. In other murine studies, it has been observed that IgMs against PC and MDA may lead to direct suppression of pro-inflammatory responses. In certain murine models of arthritis, infusion of anti PC natural IgMs conferred protection against inflammation. Also, in healthy humans a major portion of the natural IgMs is found to be generated against oxidation-associated epitopes on apoptotic cells. Indeed, recent studies in patients with systemic lupus erythromatosus substantiate the fact that higher levels of natural IgMs are associated with protection against autoimmunity. Moreover, several recent reports indicate that low levels of natural IgMs are associated with higher chances of atherosclerotic plaques, increased occurrence of strokes and even Alzheimer’s disease

With growing evidence of the beneficial role of natural IgMs in autoimmunity and other diseases, efforts are on to develop effective therapeutic strategies based on the properties of these unique antibodies. In recent reports, different strategies such as injection of anti-idiotypic antibodies, administration of IL-18 and immunization with PC containing antigens have been described to increase natural IgM response. Moreover, pooled human IgM from healthy donors have been used with favorable effects in experimental autoimmune disease models. In fact, a preparation of IgG containing pooled 12% IgM is currently used for treatment of sepsis. In the future, further understanding of the role of these natural antibodies and their progenitor B cells could lead the way for the development of effective IgM based therapies against autoimmunity. 



arijit bhowmickArijit Bhowmick is currently a postdoctoral researcher at the Immunology institute of the Mount Sinai Medical Center, NY. He received his PhD in structural immunology from the National Institute of Immunology, New Delhi. His current research interests encompass autoimmunity, Th17 cells and structure based inhibitor designing. 



Cool recent studies utilizing human PBMC

CD4_t_cellThe availability of human peripheral blood mononuclear cells (PBMC) from healthy individuals and from patients with various diseases allows for many studies on normal and abnormal functions of human immune cells.  Because human and murine immune biology differs in many ways, it is important that various methodologies for studying human immunology are established.  The two reports highlighted below demonstrate the usage of human PBMCs for mechanistic and pre-clinical human immune cell studies.

A recent report in The Journal of Immunology by Edwards et. al, demonstrated the usage of healthy human PBMC to elucidate the mechanisms involved in modulation of TH2 T cell responses by Toll-Like Receptor-7 (TLR7) agonists.  Because TLR7 stimulation perturbs TH2 responses, the potential use of rapidly metabolized 8-oxoadenine TLR7 antedrugs for treatment of allergic diseases was explored in this study in collaboration between AstraZeneca and Dainippon Sumitomo.  The TLR7 agonistic antedrug AZ12441970 was found to inhibit TH2 responses via at least two different mechanisms: TLR7-induced production of type I interferons (IFN) and induction of Notch-ligand expression on TLR7-responsive antigen presenting cells.  These led to inhibition of IL-5 production by T cells via the IFN and Notch signaling pathways, respectively.  TLR7-induction of IFNα was found to be intact in PBMCs from asthmatic patients when compared with healthy volunteers, and thus the authors proposed that this therapeutic strategy may be effective in allergic disease patients.

This study provides a demonstration of the usage of human PBMCs for elucidating signaling and immune-cell crosstalk mechanisms as well as determining the potential for the effectiveness of candidate drugs in patients with different disease states.

TLR7 Stimulation of APCs Results in Inhibition of IL-5 through Type I IFN and Notch Signaling Pathways in Human Peripheral Blood Mononuclear Cells. Edwards S, Jones C, Leishman AJ, Young BW, Matsui H, Tomizawa H, Murray CM, Biffen M. J Immunol. 2013 Mar 15;190(6):2585-92. doi: 10.4049/jimmunol.1200780.

The role of the cytokine IL-17 in cancer immunity continues to be controversial.  IL-17 and the IL-17-producing TH17 T cell subsets have been shown to have both pro-tumor as well as anti-tumor immune modulating functions in different cancer contexts.  Monocytes isolated from human PBMC can be differentiated into various myeloid cell types including dendritic cells (DC), providing a tool for studies on these human immune cell types.  In a recent Plos One article, Olsson Åkefeldt et. al, explore the role of IL-17 in survival of human monocyte-derived DCs in vitro, and the relevance of this during chemotherapy.

IL-17 was found to significantly prolong DC survival in vitro, however the cells took on expression of macrophage markers (CD14/CD68) and exhibited a pre-M2 macrophage phenotype.  The prolonged survival was associated with upregulated expression of pro-survival gene BCL-2A1.  Interestingly, IL-17 plus IFNγ treatment in vitro rendered these M2 macrophage-like DCs resistant to cell death induced by 11 of 17 tested chemotherapeutic agents.  Thus, to determine if IL-17 treatment would benefit patients by allowing DC survival during therapy, future studies should address whether this chemoresistance of IL-17 treated DCs occurs in patients undergoing chemotherapy, and to determine how IL-17 affects the anti- versus pro-tumor function of these DCs in various types of cancer.

Chemoresistance of Human Monocyte-Derived Dendritic Cells Is Regulated by IL-17A. Olsson Åkefeldt S, Maisse C, Belot A, Mazzorana M, Salvatore G, Bissay N, Jurdic P, Aricò M, Rabourdin-Combe C, Henter JI, Delprat C. PLoS One. 2013;8(2):e56865. doi: 10.1371/journal.pone.0056865. Epub 2013 Feb 18.

Studies like these are examples of the utility of using human PBMCs to elucidate mechanisms of human immune cell biology under normal and diseased conditions.

Markers and functions of human CD4+ follicular helper T cells

human white blood cellCXCR5 is a chemokine receptor expressed by and used to identity human CD4+ follicular helper T cells (TFH).  TFH cells, as their name implies, promote the differentiation and survival of memory and plasma B cells in the B cell follicular and germinal center regions of secondary lymphoid organs. CXCR5+ TFH-like central memory CD4+ T cells (CD4+ TCM) also circulate in peripheral blood and can be detected among human peripheral blood mononuclear cells (PBMC).  CXCR5+ cells comprise 20-25% of CD4+ TCM cells in human PBMC.  However, what are the identifying markers and functional differences of CXCR5+ vs. CXCR5 CD4+ T cells from human PBMC and the prototypical CXCR5+ TFH cells in secondary lymphoid organs?

I have previously discussed markers that can be used for identification of human CD4+ TH1, TH2, and TH17 T cell helper subsets as well as CD4+ FoxP3+ regulatory T cells.  CXCR5 can be upregulated transiently on activated T cells, however a subset of PBMC T cells constitutively express CXCR5, indicating this is a uniquely functioning subset identifiable by this marker using flow cytometry or other methods.  PBMC CXCR5+ CD4+ TCM cells exhibit many but not all features of TFH cells present in secondary lymphoid organs, and thus may be the circulating memory counterpart of TFH cells.

CXCL13, the chemokine ligand for CXCR5, is highly expressed in B cell follicles and likely plays an important role in recruitment of CXCR5+ TFH cells to B cell zones.  Expression of ICOS by TFH cells has been demonstrated to be essential for their function in B cell help.  Additionally, TFH cells are higher expressers of CXCL13, as well as IL-21, IL-10, Bcl-6, and PD-1 than other helper T cell subsets.

Studies by Chevalier et al, and Morita et. al. compared the functional properties of CXCR5 and CXCR5+ CD4+ TCM cells from human PBMC.  PBMC CXCR5+ CD4+ cells are resting central memory cells in phenotype, being CD45RA, CCR7+ and CD62L+, but not expressing activated TFH markers such as ICOS and CD69.  Upon stimulation, CXCR5+ CD4+ TCM promote significantly higher B cell plasmablast differentiation and Ig secretion than CXCR5 CD4+ TCM cells, attributable to enhanced expression of ICOS and IL-10.  However, Bcl-6 expression was not found to be different between these PBMC subsets, and conclusions for expression levels and role of IL-21 were contradictory between these studies.

The question of whether PBMC CXCR5+ CD4+ TCM are distinct from TH1, TH2, and TH17 T cells was addressed by these studies as well. While Chevalier et al. found that CXCR5+ TCM cells were more non-polarized and secreted comparatively lower levels of cytokines associated with TH1, TH2, and TH17 T cells, Morita et. al, identified TH1, TH2, and TH17 T cells within CXCR5+ compartment, albeit at somewhat different frequencies than CXCR5 cells. Thus PBMC CXCR5+ CD4+ TCM are a heterogenous subset with features of both TFH cells and the various TH1, TH2, and TH17 subsets.  Further interrogation of the functions of these populations are needed.

PBMC CXCR5+ CD4+ cells have been identified as a highly relevant population to study in the context of vaccination and human disease.  Patients with systemic lupus erythematosus (SLE) have higher percentages of circulating CD4+CXCR5+ ICOS+ cells.  Patients with autoimmune juvenile dermatomyositis (JDM) were found to have an altered CXCR5+ compartment where the overall frequency of CXCR5+ cells was not different, but the ratio of TH2 and TH17 to TH1 cells within the CXCR5+ population was enhanced and associated with disease activity.

In the vaccine setting, emergence of a population of circulating ICOS+CXCR3+CXCR5+CD4+ T cells was found in individuals 7 days after influenza vaccination, and correlated with increased antibody titers and B cell plasmablasts. These cells could also induce plasma cell differentiation in vitro and  thus are important in the development of vaccine elicited protective antibody responses.

In conclusion, PBMC CXCR5+ CD4+ T cells are an important cellular subset to study in the context of human disease.  These cells are likely the circulating memory component of TFH cells, and alterations in frequencies and functions are associated with various human diseases and protective antibody responses following vaccination.


Further Reading:

Human blood CXCR5(+)CD4(+) T cells are counterparts of T follicular cells and contain specific subsets that differentially support antibody secretion.  Morita R, Schmitt N, Bentebibel SE, Ranganathan R, Bourdery L, Zurawski G, Foucat E, Dullaers M, Oh S, Sabzghabaei N, Lavecchio EM, Punaro M, Pascual V, Banchereau J, Ueno H. Immunity. 2011 Jan 28;34(1):108-21.

CXCR5 expressing human central memory CD4 T cells and their relevance for humoral immune responses.  Chevalier N, Jarrossay D, Ho E, Avery DT, Ma CS, Yu D, Sallusto F, Tangye SG, Mackay CR. J Immunol. 2011 May 15;186(10):5556-68.

Expansion of circulating T cells resembling follicular helper T cells is a fixed phenotype that identifies a subset of severe systemic lupus erythematosus. N. Simpson, P.A. Gatenby, A. Wilson, S. Malik, D.A. Fulcher, S.G. Tangye, H. Manku, T.J. Vyse, G. Roncador, G.A. Huttley et al.  Arthritis Rheum., 62 (2010), pp. 234–244.

Induction of ICOS+CXCR3+CXCR5+ TH Cells Correlates with Antibody Responses to Influenza Vaccination.  Bentebibel S. E. et al.  Sci Transl Med. 13 March 2013: Vol. 5, Issue 176, p. 176ra32.

Photo credit: wellcome images / Foter.com / CC BY-NC-ND

The Fascinating System of Eye-induced Immune Regulation

The immune privilege of the eye is a widely recognized but frequently oversimplified concept. The notion that the eye possessed unusual immunological characteristics was recognized in the 19th century by van Dooremaal, who observed prolonged survival of murine skin grafts transplanted into the anterior chamber (AC) of the dog eye. The term ocular ‘immune privilege’ was articulated by Medawar, who recognized that the extended survival of foreign grafts in the AC was a remarkable departure from the fate of similar grafts transplanted to sites outside of the eye. Almost 30 years later, the seminal studies of Kaplan et al. demonstrated that alloantigenic cells introduced into the AC in fact did escape from the eye and induced a deviant immune response in which serum alloantibodies were generated, while systemic cell-mediated immune responses were suppressed in an antigen-specific manner. Subsequent studies in mice confirmed this AC-associated immune deviation (ACAID) and demonstrated that it is an important contributor to the immune privilege of the eye.


Figure 1. Organ systems involved in the induction of ACAID.
A brief description of the complex cellular-interplay, that causes ACAID (From Jerry Niederkorn’s review in Nature Immunology 7, 354 – 359;2006). Removal of the thymus, eye or spleen within 72 h of injection of antigen into the anterior chamber prevents the induction of ACAID. Chemical sympathectomy before anterior chamber injection of antigen also prevents the induction of ACAID. IL-, interleukin; BCR, B cell receptor. 


Several labs have since confirmed that antigens introduced into the AC elicit a deviant immune response, which is characterized by the antigen-specific suppression of classical Th1 immune responses, such as delayed-type hypersensitivity (DTH) and complement-fixing antibodies, while preserving the generation of noncomplement-fixing antibodies of the IgG1 isotype in the mouse. This complex phenomenon called ACAID involves multiple cell types that interact to create unique, antigen-specific immune suppression. Briefly, the injection of antigen into the ocular AC results in the antigen being taken up by circulating F4/80+ cells (a type of dendritic cell) that migrate to the spleen and thymus. Within 3 days of entering the thymus,  the F4/80+ cells induce the generation of CD4-CD8-NK1.1+ thymocytes that are believed to enter the circulation as recent thymic emigrants and home to the spleen, where they contribute to the generation of splenic regulatory cells. The spleen is the terminal organ in ACAID, where there is a complex interaction between the F4/80+ cells, natural killer T (NKT) cells, NK1.1 cell, gamma delta T cells and B cells, which in turn elicit the generation of CD4+ and CD8+ regulatory T cells (T regs) specific for the antigen that was introduced in the AC. These T regs are the key players in causing the antigen specific immune-suppression. That ACAID may occur in humans is suggested by the demonstration that individuals with acute retinal necrosis develop antibodies but not cell-mediated immunity to Varicella zoster.

Because the injection of antigen into the AC induces different phenotypes of Tregs and classically Tregs have been known to suppress autoimmunity, Bhowmick et al in 2011 investigated the ability of splenic regulatory T cells induced by an intracameral injection of MOG35-55 peptide to regulate MOG35-55-induced EAE (Experimental Autoimmune Encephalomyelitis), the animal model of human Multiple Sclerosis. In this animal model, MOG35-55 immunization results in an immune response against MOG35-55 peptide which is a component of the Myelin protein, hence causing an inflammatory auto-reaction against myelin and neurodegeneration, similar to the human disease – Multiple Sclerosis. Bhowmick et al found that the injection of MOG35-55 peptide into the ocular AC could suppress MOG35-55 peptide induced EAE, both as a cure (when injected after disease initiation) and as a prophylactic measure (when injected prior to disease induction). The suppression was antigen specific because when they injected an unrelated antigen e.g ovalbumin into the AC, it did not affect EAE in the recipient animal.

They next went on to isolate the AC-injection-induced splenic regulatory T cells and via elegant adoptive transfer experiments showed that AC-induced CD4+ regulatory T cells could suppress the diseases ONLY at the early stage (also known as the priming phase of the disease). While AC-induced CD8+ regulatory T cells could only suppress the progression of an already initiated diseases (known as the chronic phase of EAE). The CD8s were ineffective at the effector phase and vice versa. This was probably the first report which differentiated between the priming and chronic phase of EAE and showed that effective suppression of autoimmune response in EAE can be achieved by different regulatory T cell populations. This work also revealed that while the suppression of EAE by AC-induced CD8+ regulatory T cells is TGF-β dependent, the AC-induced CD4 T regs, do not use TGF-β.

Characteristically, previous studies have shown that ACAID-CD4 Treg cells do not express FoxP3. And the induction of and the activity of regulatory T cells in ACAID is independent of CD4+FoxP3+ regulatory T cells. AC-induced CD8+ regulatory cells suppress IFN-γ production in vitro and in vivo suppress T cells that effect a DTH reaction in immunized mice. Further, AC-induced CD8+ regulatory cells are restricted by Qa-1 antigens expressed by effector T cells. Since the non-classical MHC class I molecule Qa-1 is known to be expressed only on activated cells, AC-induced CD8+ regulatory T cells specifically suppress activated T cells and hence the effector or chronic phase of an autoimmune disease like EAE. Thus it can be concluded that ACAID suppresses the induction of effector T cells and also the activity of effector T cells by distinct populations of regulatory T cells. Recently it was shown that Type II collagen (CII), a key antigen involved in auto-immune responses during Rheumatoid Arthritis, could induce a similar CII-specific immune suppression via ACAID (Farooq et al 2012). A finding that has opened up possibilities of using this system in an Arthritis model to test its efficacy.

Overall these data indicate that the suppression of an ongoing autoimmune disease by the adoptive transfer of regulatory T cells might only be feasible when the regulatory T cells are specific for the pathogenic antigen. Alternatively, transfer of polyclonal regulatory T cells may cure ongoing disease only in lymphopenic hosts, in which the massive expansion of regulatory T cells may lead to the generation of a sufficient number of antigen-specific regulatory T cells. If this is also the case also in humans, it may represent a significant limitation for the clinical application of regulatory T cells in autoimmune diseases, as, to date, human self-antigen specific regulatory T cells have not been successfully expanded ex vivo. In this regard, the use of Anterior Chamber Associated Immune Deviation (ACAID), can be highly effective as ACAID can generate antigen-specific CD8+ and also CD4+ regulatory T cells.



Arijit BhowmickArijit Bhowmick is currently a postdoctoral researcher at the Immunology institute of the Mount Sinai Medical Center, NY. He received his PhD in structural immunology from the National Institute of Immunology, New Delhi. His current research interests encompass autoimmunity, Th17 cells and structure based inhibitor designing. 


Understanding MFI in the context of FACS data

Understanding MFI in the context of FACS data

The speed, sensitivity and versatility of flow cytometry are things of beauty, but with great power comes great responsibility. The fact is that with potentially millions of data points accrued over the run of a single sample, finding the best way to compare those data can be daunting. One of the more commonly misunderstood and often misleading tools in FACS analysis is a pesky little statistic — MFI.


What is MFI?

mean mode median MFIThe first point of confusion is born from the name itself. MFI is often used without explanation, to abbreviate either arithmetic mean, geometric mean, or median fluorescence intensity. In a perfect world, our data would be normally distributed and in that case means, median and mode are all equal. In reality, flow data is rarely normal and never perfect. The more that the data skews, the further the mean drifts in the direction of skew and becomes less representative of the data being analyze as seen on the graphical representation.

Because fluorescent intensity increases logarithmically, arithmetic mean quickly becomes useless to generalize a population of events, as a right-hand skew causes even more exaggeration of the mean. To combat this, geometric mean (gMFI) is often used to account for the log-normal behavior of flow data, however, even gMFI is susceptible to significant shifts. This leaves us with the median or the mid-point of the population. Median is considered a much more robust statistic in that it is less influenced by skew or outliers. Is there a “right” MFI to use to analyze flow data? No. But generally speaking, median is the safest choice and usually most representative of a “typical” cell.


Three common mistakes when using MFI

            Characterizing a bi-modal population: Any average only holds true for normal distributions, and a bi-modal population is by definition not normal. Statistics aside, gating each population and presenting percentages will yield data that is both more easily interpretable as well as more statistically significant.

            Comparing data from disparate experiments: Because fluorescent intensity is sensitive to experimental condition (e.g. antibody dilution, tandem dye degradation, laser fluctuations, etc.), it is dangerous to compare intensity of any kind across multiple experiments.

            Blindly using MFI as a quantification of expression: While FACS is more than sensitive enough to provide estimates of ligand abundance, such calculations require normalization and calibration using a standard curve. Additionally, it is tempting to say that a population with a higher MFI has higher expression than one with a lower MFI, however, care must be taken to ensure other factors are not responsible. For example, a large cell with more membrane and consequently more surface protein, can appear brighter than a smaller cell of the same type. Thus, it is important to control carefully for things such as size or compensation that may confound results.


So, when should I use MFI?

Not until asked by a reviewer.


MFI has many important uses, but can sometimes be as much a distraction from the data as it is a clarification. Ultimately, like any piece of data, MFI should only be applied if you are absolutely certain that it is the best comparison to make, otherwise it is simply clutter on an otherwise clean histogram.


For further reading:

Flowjo’s excellent explanation of the differences between mean, median and mode. http://flowjo.typepad.com/the_daily_dongle/2007/10/mean-median-mod.html

An amazing article explaining when and why to use bi-exponential axes. Importantly, the affect scaling can have on actually visualizing the median value of a population.



adam bestAdam Best is currently a post-doctoral fellow at the University of California, San Diego where he also received his Ph.D. in Biomedical Sciences. His research focuses on understanding the transcriptional events that govern the formation of memory T cells



Natural Killer Cell subtypes and markers in human PBMC

Natural killer cellsNatural Killer (NK) cells are a cytotoxic innate immune lymphocyte cell type.  In humans, NK cells comprise up to 15% of peripheral blood mononuclear cells (PBMC), and 5-20% of the PBMC lymphocyte population.  Several subtypes of NK cells exist in humans.  In this post, I will discuss phenotypic properties and markers of NK subtypes present in human PBMC.

Three subtypes of NK cells are recognized: CD56dim CD16+, CD56brightCD16+/- and CD56 CD16+ NK cells. The CD56dim CD16+ and CD56brightCD16+/- subsets are best studied and are phenotypically classified as a more cytotoxic and a more cytokine producing subset of NK cells, respectively.  NK cell activation is mediated by the balance between engagement of activating receptors including NKp46, NKp30, NKp44, NKG2D, CD16, 2B4, NKp80, and DNAM-1, and HLA-I binding inhibitory receptors including killer immunoglobulin-like receptors (KIRs), LIR1/ILT2 and NKG2A/CD94.  NK cells can also be activated in response to cytokines such as IL-2, IL-12, IL-15, and IL-18.

CD56dim CD16+ NK cells:  This subtype comprises the majority, up to 90%, of PBMC NK cells and is considered the most cytotoxic subset.  CD16 is the FCγ receptor III, and can thus bind the FC portion of IgG antibodies and mediate antibody dependant cell-mediated cytotoxicity (ADCC) of antibody-bound target cells.  Expression of inhibitory receptors differs among NK subsets, and this subset exhibits lower expression of KIRs and ILT2 but higher expression of NKG2A/CD94 compared with CD56bright NK cells. Expression of granzyme B and perforin is also high in this subset compared with CD56bright NK cells.  A recent report by De Maria et. al, demonstrated that this subset does in fact robustly produce cytokines including IFNγ early after activation.

CD56brightCD16+/- NK cells: This subtype comprises up to 10% of NK cells in PBMC, but is the major NK subtype in tissues and secondary lymphoid organs.  This subset is conventionally known as the cytokine producing subset of NK cells, and rapidly produces cytokines and chemokines including IFNγ, TNFα, GM-CSF, and RANTES after activation.

Interestingly, in HIV-viremic individuals, a third CD56 CD16+ NK population is significantly expanded in PBMC comprising between 20-55% of NK cells.  This population in healthy individuals and aviremic HIV-infected individuals is rare, under 10% of total NK cells.  Compared with CD56+ NK cells, the CD56 CD16+ NK cells from HIV-viremic patients exhibited lower expression of activating receptors NKp46, NKp30, and NKp44, lower cytotoxic activity, higher expression levels of inhibitory receptors, and lower expression levels of cytokines including IFNγ, TNFα, and GM-CSF.  This subset is also expanded in individuals with chronic HCV infection.  Thus, the expansion of this poorly functional NK subset is likely clinically relevant in chronic viral disease.

In summary, these NK populations can be differentiated by expression of CD16 and CD56.  Of note, NKT (natural killer-like T) cells can also express these markers along with CD3.  Thus, to differentiate these cells from NKT cells, the inclusion of CD3 as a cell identification marker is critical in analysis of these cells by flow cytometry or other methods.


Further Reading:

CD56 negative NK cells: origin, function, and role in chronic viral disease.  Björkström NK, Ljunggren HG, Sandberg JK. Trends Immunol. 2010 Nov;31(11):401-6.

The biology of human natural killer-cell subsets. Cooper MA, Fehniger TA, Caligiuri MA. (2001) Trends Immunol 22: 633–640.

Natural killer cell distribution and trafficking in human tissues.  Carrega P, Ferlazzo G. Front Immunol. 2012;3:347.

Revisiting human natural killer cell subset function revealed cytolytic CD56(dim)CD16+ NK cells as rapid producers of abundant IFN-gamma on activation.  De Maria A, Bozzano F, Cantoni C, Moretta L. Proc Natl Acad Sci U S A. 2011 Jan 11;108(2):728-32.

Natural killer cells in HIV-1 infection: dichotomous effects of viremia on inhibitory and activating receptors and their functional correlates.  Mavilio D, Benjamin J, Daucher M, Lombardo G, Kottilil S, Planta MA, Marcenaro E, Bottino C, Moretta L, Moretta A, Fauci AS. Proc Natl Acad Sci U S A. 2003 Dec 9;100(25):15011-6.

Characterization of CD56−/CD16+ natural killer (NK) cells: a highly dysfunctional NK subset expanded in HIV-infected viremic individuals. Mavilio D, Lombardo G, Benjamin J, Kim D, Follman D, et al.. (2005) Proc Natl Acad Sci U S A. 102: 2886–2891.

Generation of CD4+ Th1 cells from human PBMC

CD4+ T helper type 1 (TH1) cells are the effector T cell population that governs cell mediated immune responses against intracellular pathogens including viruses and intracellular bacteria.  TH1 cells mediate their effect by secreting cytokines such as interferon-gamma (IFNγ) and IL-2, and express cell surface markers including CXCR3 and CCR5 and the characteristic TH1 master transcription factor T-bet (TBX21) which can also be used for detection of TH1cells by flow cytometry, as discussed in a previous blog post.

Differentiation of naïve human CD4+ T cells down the TH1 pathway involves cytokines such as IL-12 which activates STAT4, and induces expression of IFNγ and T-bet.  As such, in vitro protocols differentiating peripheral blood mononuclear cells (PBMC)-derived naïve CD4+ T cells into TH1 cells involves incubation with IL-12 in the context of T cell activation through the T cell receptor (TCR) complex.

In my experience, TH1 cells are by far the easiest CD4+ helper T cell population to generate in vitro.  In order to generate TH1 cells from human PBMC, naïve CD4+ T cells must first be isolated.  Multiple methods of naïve CD4+ T cell isolation can be utilized, and magnetic bead- based methods are common and easy methods.  Companies such as Miltenyi Biotech and Stem Cell Technologies offer kits for isolation of untouched naïve CD4+ T cells from PBMC by negative isolation methodologies.

Following isolation, naïve CD4+ T cells are activated through the TCR complex.  Tissue culture plates can be coated with anti-CD3 (OKT1) and anti-CD28 antibodies in PBS prior to culture.  Alternatively, naïve CD4+ T cells can be cultured with Dynal CD3/CD28 T Cell Expander Dynabeads (Life Technologies) at a 1 bead per cell ratio.  A third alternative involves coating tissue culture plates with anti-CD3 alone and obtaining CD28 co-stimulation by the addition of autologous monocytes isolated from PBMCs into the culture.

To generate TH1 cells, recombinant human IL-12 is added alone, or at a lower dose in combination with anti-IL-4 blocking antibodies to inhibit the counteractive effects of IL-4 and TH2 pathways on TH1 cell polarization.  Finally recombinant human IL-2 is added to promote T cell proliferation.  Media and cytokines/blocking antibodies are refreshed every two to three days depending on the cell density, and as the cells expand the time to refresh the media shortens.

Lymphocyte activationTH1 cells can be generated and assayed for functions including IFNγ expression in as few as three days.  If long term or clonal T cells assays are of interest, cells can be expanded in the presence of IL-2 for 2-3 weeks following single cell cloning.  As previously discussed, TH1 cells can be identified by IFNγ expression following a 4-6 hour incubation with TCR activation by plate bound anti-CD3 plus anti-CD28, CD3/CD28 Dynabeads, or PMA/ionomycin in the presence of brefeldin-A.  Cells are then fixed, permeabilized, and stained for cell surface markers and intracellular IFNγ.

Finally, as a comparison, tandem experiments can be run in which naïve CD4+ T cells are maintained under non-polarizing (TH0) conditions.  For this, often no cytokines aside from IL-2 are added.  However the addition of anti-IL-12 and anti-IL-4 may be necessary to inhibit any cells from differentiating down TH1 or TH2 pathways by production of these cytokines by the T cells themselves.

In conclusion, generation of CD4+ TH1cells from human PBMC is a relatively simple and straightforward protocol, and very high percentages of TH1cells can be obtained through optimized protocols.


Further Reading:

Differentiation of effector CD4 T cell populations (*).  Zhu J, Yamane H, Paul WE.  Annu Rev Immunol. 2010;28:445-89.

Memory and flexibility of cytokine gene expression as separable properties of human T(H)1 and T(H)2 lymphocytes.  Messi M, Giacchetto I, Nagata K, Lanzavecchia A, Natoli G, Sallusto F.  Nat Immunol. 2003 Jan;4(1):78-86.

A critical function for transforming growth factor-beta, interleukin 23 and proinflammatory cytokines in driving and modulating human T(H)-17 responses.  Volpe E, Servant N, Zollinger R, Bogiatzi SI, Hupé P, Barillot E, Soumelis V. Nat Immunol. 2008 Jun;9(6):650-7.

Identification of CD8+ TC1, TC2, and TC17 populations in human PBMC

Human peripheral blood mononuclear cells (PBMC) are composed of heterogeneous populations of various immune cell types.  CD4+ and CD8+ T cells are known to exist in various functional and differentiated states.  Following antigen experience, naïve T cells are thought to progressively differentiate along a path through central memory, effector memory, and terminally differentiated effector states. Markers for differentiating PBMC T cells into these subtypes using multiparametric flow cytometry include: CD3, CD4, CD8, CD45RA or CD45RO, and CCR7 or CD62L.

The cytokine milieu T cells are exposed to during antigen encounter directs differentiation into various subtypes that exhibit unique functional properties and gene expression programs including cytokines, transcription factors, and surface markers.  This is true for both CD4+ and CD8+ T cells. In a previous post, I discussed various markers that can be utilized by flow cytometry to identify CD4+ TH1, TH2, and TH17 populations in human PBMC.

CD8+ T cells can also differentiate into unique subsets similar to TH1, TH2, and TH17 CD4+ T cells.  The CD8+ versions of these subsets are referred to as TC1, TC2, and TC17 CD8+ T cells, respectively, and are defined by expression of the same characteristic cytokines as their CD4+ counterparts.

As previously discussed, expression of subset-specific surface markers is easily determined by flow cytometry. Identification of intracellular cytokine production in T cells can be assessed following 4-6 hours of TCR stimulation with anti-CD3 and anti-CD28 antibodies or the combination of Phorbol 12-Myristate 13-Acetate (PMA) and ionomycin in the presence of brefeldin A or monensin.  The cells are then fixed and permeabilized with buffers such as BD Biosciences’ Cytofix Cytoperm buffer set followed by antibody staining for cytokine expression and flow cytometry.

Like CD4+ TH1 cells, CD8+ TC1 cells characteristically produce IFNγ.  This population is by far the most common cytokine-producing CD8+ cell subset, and is very easy to identify using intracellular staining for IFNγ.

As with CD4+ TH2 cells, CD8+ TC2 cells can be identified by expression of IL-4, IL-5, and IL-13Cosmi et. al, found that the surface marker CRTH2 was a robust marker for identification of CD8+ and CD4+ cells producing IL-4, IL-5, and IL-13 expression but not IFNγ.  Expression of chemokine receptors CCR3 and CCR4 however, did not exclude IFNγ-producing cells.  Because expression of IL-4, IL-5, and IL-13 can be difficult to detect, CRTH2 may be the easiest of these markers for TC2 identification in human PBMC.

CD8+ TC17 cells are characterized by expression of the cytokine IL-17.  Expression of the chemokine receptors CCR5 and CCR6 were shown to enrich for IL-17 producing CD8+ cells.  However CCR5 and CCR6 expression are also associated with TC1 cells, and thus may not be useful to differentiate between these subsets.

CD8 Tc1 Tc2 Tc17 PMA resized 600

Figure: Expression of IFNγ, IL-17, and CRTH2 in CD8+ T cells from PBMC stimulated with for 4 hours with PMA/ionomycin.

In my own studies, I have utilized TCR or PMA/ionomycin stimulation of PBMCs to successfully identify IFNγ (TC1) and IL-17 (TC17) expressing cells, and CRTH2 expression to identify TC2 cells, as these may be the most robust markers for identification of these unique CD8+ T cell populations. Note also that these same markers reliably detect CD4+ TH1, TH17, and TH2 cells, respectively. Thus, these markers are useful to quantitate and study the function of both CD8+ and CD4+ subsets in human PBMC.


Additional Reading

Generation of polarized antigen-specific CD8 effector populations: reciprocal action of interleukin (IL)-4 and IL-12 in promoting type 2 versus type 1 cytokine profiles.  Croft M, Carter L, Swain SL, Dutton RW. J Exp Med. 1994 Nov 1;180(5):1715-28.

CRTH2 is the most reliable marker for the detection of circulating human type 2 Th and type 2 T cytotoxic cells in health and disease.  Cosmi L, Annunziato F, Galli MIG, Maggi RME, Nagata K, Romagnani S.  Eur J Immunol. 2000 Oct;30(10):2972-9.

Cutting edge: Phenotypic characterization and differentiation of human CD8+ T cells producing IL-17.  Kondo T, Takata H, Matsuki F, Takiguchi M. J Immunol. 2009 Feb 15;182(4):1794-8.

Functional expression of chemokine receptor CCR6 on human effector memory CD8+ T cells.  Kondo T, Takata H, Takiguchi M. Eur J Immunol. 2007 Jan;37(1):54-65.

Maturing and Assaying Monocyte-Derived Dendritic Cells

Generating dendritic cells (DCs) from PBMC CD14+ monocytes allows researchers to do a host of immunological assays. A common example of this is to examine the reactivity of a T cell mixture to a certain antigen of interest. However, prior to doing such antigen presentation assays, DCs must be properly matured in order to fully elicit a T cell response.

After generating your monocyte derived DCs (mDCs) from PBMCs, as I described in my previous post, you will have several choices on how to mature them. Two of the most common choices are to either use LPS or a monocyte maturation cocktail (MMC). LPS binds TLR4, which results in a host of downstream inflammatory genes being upregulated. Addition of IFNγ can polarize the DCs to a Th1 phenotype, while the addition of TNFα can polarize the DCs somewhat towards a Th2 phenotype. MMC, however, usually involves the addition of several molecules including TNFα, IL-6, IL-1β, and PGE2. The overall effect of this pool of molecules is to elicit a mixed Th1 and Th2 response by the DCs. Thus, the maturation method of choice is a critical choice for the researcher and may vary depending on the downstream functional assay.

Interrogating your DCs by flow cytometry is a good idea so you can be sure you have attained the cell phenotype you desire. mDCs will commonly express CD11c and CD1c and should be CD123-. Furthermore, upregulation of costimulatory molecules CD80 and CD86 and the immunoregulatory molecule CD83 and downregulation of CD14 are hallmarks of DC maturation. HLA molecules are also significantly upregulated. Remember, these molecules are not just cell markers, but have important functional relevance. The upregulation of costimulatory molecules is critical for the activation of T cells and the upregulation of surface HLA molecules is a reflection is the enhance antigen presentation capability of a mature DC.Dendritic Cells Dot Plot with CD1c and CD11c Expression

Running your DCs on the flow cytometer will require a few special tweaks on your normal cytometer settings. The first thing you will notice is that the DCs are rather massive and irregular shaped cells. You will therefore likely need to significantly decrease both your forward scatter and side scatter to locate them on your dot plot. Secondly you will want to significantly decrease the voltages for all the channels detecting fluorchromes on your DC activation markers. These activation markers are expressed at such a high level on the DCs, that they are incredibly bright. A third issue is the high level of auto-fluorescence on DCs. It is always a good idea to have some extra DCs you can run while setting up your voltages to make sure your CD marker fluorochromes are all on scale.  Be sure to use the activated sample of DCs for this! Once you have verified your settings will work, you can then proceed to normal compensation set up.

Once your cytometer settings are established your cells are ready to assay. It is a good idea to have a sample of DCs that you did not stimulate as a control to compare your matured DCs to. In my experience the best way to compare markers, such as CD83, CD86, HLA-ABC, and HLA-DR, is by using histogram overlays. Their upregulation can often be a slight shift in fluorescent intensity, which you can readout by graphing Median Fluorescent Intensity (MFI). Of course be sure that you have titered your antibodies appropriately and use isotype controls when you can. Also keep in mind that comparing MFI readouts between different assay days, different stains, and different experiments is virtually impossible. Try to group your assays whenever possible, but if not, fold change in MFI is a useful, though not ideal, calculation for comparing these sorts of data.


Differentiation of Peripheral Blood Monocytes into Dendritic Cells. David W. O’Neill, Nina Bhardwaj. Current Protocols in Immunology. July, 2005.

Improved methods for the generation of dendritic cells from nonproliferating progenitors in human blood. Bender A, Sapp M, Schuler G, Steinman RM, Bhardwaj N.  J Immunol Methods. 1996 Sep 27;196(2):121-35.

Monocyte-derived DC maturation strategies and related pathways: a transcriptional view. Luciano Castiello, Marianna Sabatino,   Ping Jin, Carol Clayberger, Francesco M. Marincola, Alan M. Krensky, David F. Stroncek. Cancer Immunol Immunother. 2011 April; 60(4): 457–466.

Taking dendritic cells into medicine. Steinman RM, Banchereau J. Nature. 2007;449:419–426.

Current approaches in dendritic cell generation and future implications for cancer immunotherapy.  Tuyaerts S, Aerts JL, Corthals J, et al. Cancer Immunol Immunother. 2007;56:1513–1537.

Comparative evaluation of techniques for the manufacturing of dendritic cell-based cancer vaccines.  Dohnal AM, Graffi S, Witt V, et al. J Cell Mol Med. 2009;13:125–135. 

describe the imageColt Egelston is currently a post-doctoral fellow at the Beckman Research Institute of the City of Hope, in Duarte, CA. He received his Ph.D. from Rush University in Chicago and is interested in all things immunology.