Reporting imaging flow cytometry data for publication: Why mask the detail?

Imaging flow cytometry: a primer

Imaging flow cytometry combines the high throughput nature of flow cytometry with the advantages of single cell image acquisition associated with microscopy. The measurement of large numbers of features from the resulting images provides rich datasets which have resulted in a wide range of novel biomedical applications. In this primer we discuss the typical imaging flow instrumentation, the form of data acquired and the typical analysis tools that can be applied to this data. Using examples from the literature we discuss the progression of the analysis methods that have been applied to imaging flow cytometry data. These methods start from the use of simple single image features and multiple channel gating strategies, followed by the design and use of custom features for phenotype classification, through to powerful machine and deep learning methods. For each of these methods, we outline the processes involved in analyzing typical datasets and provide details of example applications. Finally we discuss the current limitations of imaging flow cytometry and the innovations which are addressing these challenges.

Combining imaging flow cytometry and machine learning for high-throughput schistocyte quantification: A SVM classifier development and external validation cohort

Background

Schistocyte counts are a cornerstone of the diagnosis of thrombotic microangiopathy syndrome (TMA). Their manual quantification is complex and alternative automated methods suffer from pitfalls that limit their use. We report a method combining imaging flow cytometry (IFC) and artificial intelligence for the direct label-free and operator-independent quantification of schistocytes in whole blood.

Methods

We used 135,045 IFC images from blood acquisition among 14 patients to extract 188 features with IDEAS® software and 128 features from a convolutional neural network (CNN) with Keras framework in order to train a support vector machine (SVM) blood elements’ classifier used for schistocytes quantification.

Finding

Keras features showed better accuracy (94.03%, CI: 93.75-94.31%) than ideas features (91.54%, CI: 91.21-91.87%) in recognising whole-blood elements, and together they showed the best accuracy (95.64%, CI: 95.39-95.88%). We obtained an excellent correlation (0.93, CI: 0.90-0.96) between three haematologists and our method on a cohort of 102 patient samples. All patients with schistocytosis (>1% schistocytes) were detected with excellent specificity (91.3%, CI: 82.0-96.7%) and sensitivity (100%, CI: 89.4-100.0%). We confirmed these results with a similar specificity (91.1%, CI: 78.8-97.5%) and sensitivity (100%, CI: 88.1-100.0%) on a validation cohort (n=74) analysed in an independent healthcare centre. Simultaneous analysis of 16 samples in both study centres showed a very good correlation between the 2 imaging flow cytometers (Y=1.001x).

Interpretation

We demonstrate that IFC can represent a reliable tool for operator-independent schistocyte quantification with no pre-analytical processing which is of most importance in emergency situations such as TMA.

Funding

None.

Exosomes Associated with Human Ovarian Tumors Harbor a Reversible Checkpoint of T-cell Responses

Nano-sized membrane-encapsulated extracellular vesicles isolated from the ascites fluids of ovarian cancer patients are identified as exosomes based on their biophysical and compositional characteristics. We report here that T cells pulsed with these tumor-associated exosomes during TCR-dependent activation inhibit various activation endpoints including translocation of NFκB and NFAT into the nucleus, upregulation of CD69 and CD107a, production of cytokines, and cell proliferation. In addition, the activation of virus-specific CD8⁺ T cells that are stimulated with the cognate viral peptides presented in the context of class I MHC is also suppressed by the exosomes. The inhibition occurs without loss of cell viability and coincidentally with the binding and internalization of these exosomes. This exosome-mediated inhibition of T cells was transient and reversible: T cells exposed to exosomes can be reactivated once exosomes are removed. We conclude that tumor-associated exosomes are immunosuppressive and represent a therapeutic target, blockade of which would enhance the antitumor response of quiescent tumor-associated T cells and prevent the functional arrest of adoptively transferred tumor-specific T cells or chimeric antigen receptor T cells. Cancer Immunol Res; 6(2); 236-47. ©2018 AACR.

Analysis of Erythropoiesis Using Imaging Flow Cytometry

Erythroid maturation has been classically defined based on the remarkable changes visualized through microscopy. These involve the decrease in cell size, nuclear condensation and organelle loss, and include the final unique asymmetric division creating the short-lived nucleated pyrenocyte and the enucleate reticulocyte that matures into the red blood cell. Understanding the regulation of these processes has been challenging due to the difficulty in obtaining sufficient numbers of cells, particularly of rare intermediates, to study by microscopy. While flow cytometry can provide quantitative analysis of high cell numbers as well as critical tools for assaying processes like cell cycle, apoptosis and cell signaling, it cannot analyze or categorize cells based on morphology. Imaging flow cytometry (IFC) combines microscopy and flow cytometry by capturing brightfield and fluorescent images of large numbers of cells, which can be quantitated for both morphometric and fluorescent characteristics. Over the past 10 years, this approach has been increasingly used to study aspects of erythropoiesis. This chapter describes how to utilize IFC to enumerate multiple specific stages of erythropoiesis from primary tissue, as well as how to culture primary progenitors to enrich for the rare late stage enucleating cells in order to examine intracellular proteins involved in enucleation. These methods demonstrate the approaches and strength of IFC as a tool to bridge the power of microscopy and flow cytometry to more fully interrogate erythropoiesis.

Caveolin-1 Influences LFA-1 Redistribution upon TCR Stimulation in CD8 T Cells

TCR stimulation by peptide-MHC complexes on APCs requires precise reorganization of molecules into the area of cellular contact to form an immunological synapse from where T cell signaling is initiated. Caveolin (Cav)1, a widely expressed transmembrane protein, is involved in the regulation of membrane composition, cellular polarity and trafficking, and the organization of signal transduction pathways. The presence of Cav1 protein in T cells was identified only recently, and its function in this context is not well understood. We show that Cav1-knockout CD8 T cells have a reduction in membrane cholesterol and sphingomyelin, and upon TCR triggering they exhibit altered morphology and polarity, with reduced effector function compared with Cav1 wild-type CD8 T cells. In particular, redistribution of the β₂ integrin LFA-1 to the immunological synapse is compromised in Cav1-knockout T cells, as is the ability of LFA-1 to form high-avidity interactions with ICAM-1. Our results identify a role for Cav1 in membrane organization and β₂ integrin function in primary CD8 T cells.

High Throughput Analysis of Golgi Structure by Imaging Flow Cytometry

The Golgi apparatus is a dynamic organelle, which regulates the vesicular trafficking. While cellular trafficking requires active changes of the Golgi membranes, these are not accompanied by changes in the general Golgi’s structure. However, cellular processes such as mitosis, apoptosis and migration require fragmentation of the Golgi complex. Currently, these changes are most commonly studied by basic immunofluorescence and quantified by manual and subjective classification of the Golgi structure in 100–500 stained cells. Several other high-throughput methods exist as well, but those are either complicated or do not provide enough morphological information. Therefore, a simple and informative high content methodology should be beneficial for the study of Golgi architecture. Here we describe the use of high-throughput imaging flow cytometry for quantification of Golgi fragmentation, which provides a simple way to analyze the changes in an automated, quantitative and non-biased manner. Furthermore, it provides a rapid and accurate way to analyze more than 50,000 cells per sample. Our results demonstrate that this method is robust and statistically powerful, thus, providing a much-needed analytical tool for future studies on Golgi dynamics, and can be adapted to other experimental systems.

An open-source solution for advanced imaging flow cytometry data analysis using machine learning

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performed in a highly manual and subjective manner using very limited image analysis techniques in combination with conventional flow cytometry gating strategies. This approach is not scalable to the hundreds of available image-based features per cell and thus makes use of only a fraction of the spatial and morphometric information. As a result, the quality, reproducibility and rigour of results are limited by the skill, experience and ingenuity of the data analyst. Here, we describe a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms. Compensated and corrected raw image files (.rif) data files from an imaging flow cytometer (the proprietary .cif file format) are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analysed using cutting-edge machine learning and clustering approaches using "user-friendly" platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data sets. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye that include subtle measured differences in label free detection channels such as bright-field and dark-field imagery.

Masks in imaging flow cytometry

Data analysis in imaging flow cytometry incorporates elements of flow cytometry together with other aspects of morphological analysis of images. A crucial early step in this analysis is the creation of a mask to distinguish the portion of the image upon which further examination of specified features can be performed. Default masks are provided by the manufacturer of the imaging flow cytometer but additional custom masks can be created by the individual user for specific applications. Flawed or inaccurate masks can have a substantial negative impact on the overall analysis of a sample, thus great care must be taken to ensure the accuracy of masks. Here we discuss various types of masks and cite examples of their use. Furthermore we provide our insight for how to approach selecting and assessing the optimal mask for a specific analysis.

Identification and classification of the malaria parasite blood developmental stages, using imaging flow cytometry

Malaria is the most devastating parasitic disease of humans, caused by the unicellular protozoa of the Plasmodium genus, such as Plasmodium falciparum (Pf) and is responsible for up to a million deaths each year. Pf life cycle is complex, with transmission of the parasite between humans via mosquitos involving a remarkable series of morphological transformations. In the bloodstream, the parasites undergo asexual multiplications inside the red blood cell (RBC), where they mature through the ring (R), trophozoite (T) and schizont (S) stages, and sexual development, resulting in gametocytes (G). All symptoms of malaria pathology are caused by the asexual blood stage parasites. Flow cytometry methods were previously used to detect malaria infected (i) RBCs, in live or fixed cells, using DNA (Hoechst) and RNA (Thiazole Orange) stains. Here, by using imaging flow cytometry, we developed improved methods of identifying and quantifying each of the four parasite blood stages (R, T, S and G). This technique allows multi-channel, high resolution imaging of individual parasites, as well as detailed morphological quantification of Pf-iRBCs cultures. Moreover, by measuring iRBC morphological properties, we can eliminate corrupted and extracellular (dying) parasites from the analysis, providing accurate quantification and robust measurement of the parasitemia profile. This new method is a valuable tool in malaria molecular biology research and drug screen assays.

Quantifying MHC dextramer-induced NFAT activation in antigen-specific T cells as a functional response parameter

MHC-multimers are reagents used for the detection and enumeration of antigen-specific T cells (ASTs). These reagents exploit the mechanism by which T cell receptors (TCR) on cytotoxic CD8 T cells recognize specific antigens in the context of a major histocompatibility complex (MHC) molecule during antigen presentation. MHC-multimers are fluorescently-labeled dextran polymers that carry MHC Class I molecules and peptide sequences that can be modified to represent specific cognate sequences of the antigen of interest with dextramers having a 10-fold multiplicity of the MHC/peptide combination within a single multimer. Since the binding of antigen-specific dextramers mimics antigen presentation to the TCR, the present study sought to determine whether this TCR engagement on the AST was sufficient to elicit a functional T cell response. The effect of binding of CMV specific dextramers on the activation of the NFAT signal transduction cascade was assessed in peripheral blood from bone marrow transplant recipients previously determined to be positive for CMV-ASTs (CASTs). NFAT activation was quantified by measuring nuclear translocation of NFAT1 in CD8+ CASTs and CD8+ non-CASTs by imaging flow cytometry. Our results demonstrate that an increase in the nuclear localization of NFAT1 was detectable in the CASTs following the CMV-dextramer binding and could be observed as early as 10min post-exposure. The NFAT1 activation correlated with a downstream functional response in the form of interferon gamma production. Sample preparation, temperature, and duration of dextramer exposure were important parameters affecting the dextramer-induced NFAT activation with 2h exposure in whole blood at room temperature being the optimal of the conditions tested. Intra- and inter-individual heterogeneity was observed with regards to the NFAT activation in the CASTs. Importantly, no effect of the dextramers was observed in the CD8+ non-CASTs, and therefore dextramer negative cell populations. Exposure to PMA/ionomycin following dextramer exposure resulted in a homogeneous NFAT activation in both the dextramer-positive but NFAT1 nonresponsive CAST and non-CAST cells. Thus, the data demonstrate that binding of antigen-specific dextramers to ASTs specifically results in activation of NFAT, that the NFAT activation correlates with a downstream functional response and that the response can be heterogeneous. This functional parameter may provide insight to the issue whether enumeration alone of ASTs is a sufficient parameter to assess an individual's immune status against a specific antigen.

Nanoscale bio-platforms for living cell interrogation: current status and future perspectives

The living cell is a complex entity that dynamically responds to both intracellular and extracellular environments. Extensive efforts have been devoted to the understanding intracellular functions orchestrated with mRNAs and proteins in investigation of the fate of a single-cell, including proliferation, apoptosis, motility, differentiation and mutations. The rapid development of modern cellular analysis techniques (e.g. PCR, western blotting, immunochemistry, etc.) offers new opportunities in quantitative analysis of RNA/protein expression up to a single cell level. The recent entries of nanoscale platforms that include kinds of methodologies with high spatial and temporal resolution have been widely employed to probe the living cells. In this tutorial review paper, we give insight into background introduction and technical innovation of currently reported nanoscale platforms for living cell interrogation. These highlighted technologies are documented in details within four categories, including nano-biosensors for label-free detection of living cells, nanodevices for living cell probing by intracellular marker delivery, high-throughput platforms towards clinical current, and the progress of microscopic imaging platforms for cell/tissue tracking in vitro and in vivo. Perspectives for system improvement were also discussed to solve the limitations remains in current techniques, for the purpose of clinical use in future.

The Analysis of Cell Cycle, Proliferation, and Asymmetric Cell Division by Imaging Flow Cytometry

Measuring cellular DNA content by conventional flow cytometry (CFC) and fluorescent DNA-binding dyes is a highly robust method for analysing cell cycle distributions within heterogeneous populations. However, any conclusions drawn from single-parameter DNA analysis alone can often be confounded by the asynchronous nature of cell proliferation. We have shown that by combining fluorescent DNA stains with proliferation tracking dyes and antigenic staining for mitotic cells one can elucidate the division history and cell cycle position of any cell within an asynchronously dividing population. Furthermore if one applies this panel to an imaging flow cytometry (IFC) system then the spatial information allows resolution of the four main mitotic phases and the ability to study molecular distributions within these populations. We have employed such an approach to study the prevalence of asymmetric cell division (ACD) within activated immune cells by measuring the distribution of key fate determining molecules across the plane of cytokinesis in a high-throughput, objective, and internally controlled manner. Moreover the ability to perform high-resolution, temporal dissection of the cell division process lends itself perfectly to investigating the influence chemotherapeutic agents exert on the proliferative capacity of transformed cell lines. Here we describe the method in detail and its application to both ACD and general cell cycle analysis.

Imaging Flow Cytometric Analysis of Primary Bone Marrow Megakaryocytes

In light of the indispensible role of platelets in the maintenance of hemostasis, understanding the biology of platelet production from bone marrow megakaryocytes (MKs) may uncover new therapeutic strategies for thrombocytopenia. While there has been much recent interest in optimizing culture systems to facilitate the study of the morphologically unique MK lineage, these systems lack the intricacy of in vivo megakaryopoiesis. Given the limitations of many common techniques for the in vivo study of MKs, in this chapter we describe a method to quantify and analyze primary murine bone marrow megakaryocytes utilizing imaging flow cytometry.

An imaging flow cytometry-based approach to measuring the spatiotemporal calcium mobilisation in activated T cells

Calcium ions (Ca(2+)) are a ubiquitous transducer of cellular signals controlling key processes such as proliferation, differentiation, secretion and metabolism. In the context of T cells, stimulation through the T cell receptor has been shown to induce the release of Ca(2+) from intracellular stores. This sudden elevation within the cytoplasm triggers the opening of ion channels in the plasma membrane allowing an influx of extracellular Ca(2+) that in turn activates key molecules such as calcineurin. This cascade ultimately results in gene transcription and changes in the cellular state. Traditional methods for measuring Ca(2+) include spectrophotometry, conventional flow cytometry (CFC) and live cell imaging techniques. While each method has strengths and weaknesses, none can offer a detailed picture of Ca(2+) mobilisation in response to various agonists. Here we report an Imaging Flow Cytometry (IFC)-based method that combines the throughput and statistical rigour of CFC with the spatial information of a microscope. By co-staining cells with Ca(2+) indicators and organelle-specific dyes we can address the spatiotemporal patterns of Ca(2+) flux in Jurkat cells after stimulation with anti-CD3. The multispectral, high-throughput nature of IFC means that the organelle co-staining functions to direct the measurement of Ca(2+) indicator fluorescence to either the endoplasmic reticulum (ER) or the mitochondrial compartments without the need to treat cells with detergents such as digitonin to eliminate cytoplasmic background. We have used this system to look at the cellular localisation of Ca(2+) after stimulating cells with CD3, thapsigargin or ionomycin in the presence or absence of extracellular Ca(2+). Our data suggest that there is a dynamic interplay between the ER and mitochondrial compartments and that mitochondria act as a sink for both intracellular and extracellular derived Ca(2+). Moreover, by generating an NFAT-GFP expressing Jurkat line, we were able to combine mitochondrial Ca(2+) measurements with nuclear translocation. In conclusion, this method enables the high throughput study of spatiotemporal patterns of Ca2(+) signals in T cells responding to different stimuli.

Appraising the suitability of succinimidyl and lipophilic fluorescent dyes to track proliferation in non-quiescent cells by dye dilution

Successful completion of the cell cycle usually results in two identical daughter progeny. This process of generational doubling is termed proliferation and when it occurs in a regulated fashion the benefits range from driving embryonic development to mounting a successful immune response. However when it occurs in a dis-regulated fashion, it is one of the hallmarks of cancer and autoimmunity. These very reasons make proliferation a highly informative parameter in many different biological systems. Conventional flow cytometry (CFC) is a high-throughput, fluorescence-based method for measuring the phenotype and function of cells. The application of CFC to measuring proliferation requires a fluorescent dye able to mark live cells so that when they divide, the daughter progeny receives approximately half the fluorescence of the parent. In measurement space, this translates into peaks of fluorescence decreasing by approximately half, each corresponding to a round of division. It is essential that these peaks can be resolved from one another otherwise it is nearly impossible to obtain accurate quantitative proliferation data. Peak resolution is affected by many things, including instrument performance, the choice of fluorescent dye and the inherent properties of the cells under investigation. There are now many fluorescent dyes available for tracking proliferation by dye dilution differing in their chemistry and spectral properties. Here we provide a method for assessing the performance of various candidate dyes with particular emphasis on situations where the cell type is non-quiescent. We have shown previously that even under optimised instrument and labelling conditions, the heterogeneity of non-quiescent cells makes it impossible to obtain an input width below the threshold for peak resolution without reducing the fluorescence distribution using a cell sorter. Moreover, our method also measures how the dye performs post-labelling in terms of loss/transfer to other cells and how the dye is inherited across the cytokinetic plane. All of these factors will affect peak resolution both in non-quiescent and primary cell types.

Utilization of imaging flow cytometry to define intermediates of megakaryopoiesis in vivo and in vitro

Imaging flow cytometry is a particularly powerful analytical approach for the study of megakaryopoiesis. It can utilize well-defined immunophenotypic markers as well as assess maturation of megakaryocytes by their increasing ploidy as they endoreplicate. Imaging flow cytometry can also assess morphometric cell characteristics of size and nuclear to cytoplasmic ratio, which are informative indications of maturation. However, megakaryopoiesis is challenging for flow cytometric analysis, particularly in vivo, because megakaryocytes are very rare in the bone marrow and their odd shape, high DNA content and cell size are similar to clumps of cells. Additionally, both megakaryocytes and immunophenotypically similar platelets are frequently found associated with other cells. Due to these challenges, imaging flow cytometry of megakaryopoiesis exemplifies several strengths of this approach in utilizing fluorescent signal's shape, texture and overlap with other fluorescent signals to distinguish megakaryocytes from a variety of contaminants and to restrict analysis to megakaryocytes, even when associated with other cells. Presented here is a strategy for imaging flow cytometric analysis of rare murine megakaryocytes directly from the bone marrow as well those grown in vitro and analyzed as live cells, or after fixation and permeabilization.

An image cytometer based on angular spatial frequency processing and its validation for rapid detection and quantification of waterborne microorganisms

Image cytometer based on angular spatial frequency processing for the early detection of waterborne bacteria.

Improved quantitative analysis of primary bone marrow megakaryocytes utilizing imaging flow cytometry

Life-threatening thrombocytopenia can develop following bone marrow injury due to decreased platelet production from megakaryocytes (MKs). However, the study of primary MKs has been complicated by their low frequency in the bone marrow and by technical challenges presented by their unique maturation properties. More accurate and efficient methods for the analysis of in vivo MKs are needed to enhance our understanding of megakaryopoiesis and ultimately develop new therapeutic strategies for thrombocytopenia. Imaging flow cytometry (IFC) combines the morphometric capabilities of microscopy with the high-throughput analyses of flow cytometry (FC). Here, we investigate the application of IFC on the ImageStream(X) platform to the analysis of primary MKs isolated from murine bone marrow. Our data highlight and address technical challenges for conventional FC posed by the wide range of cellular size within the MK lineage as well as the shared surface phenotype with abundant platelet progeny. We further demonstrate that IFC can be used to reproducibly and efficiently quantify the frequency of primary murine MKs in the marrow, both at steady-state and in the setting of radiation-induced bone marrow injury, as well as assess their ploidy distribution. The ability to accurately analyze the full spectrum of maturing MKs in the bone marrow now allows for many possible applications of IFC to enhance our understanding of megakaryopoiesis and platelet production.

A method for evaluating the use of fluorescent dyes to track proliferation in cell lines by dye dilution

Labeling nonquiescent cells with carboxyfluorescein succinimidyl ester (CFSE)-like dyes gives rise to a population width exceeding the threshold for resolving division peaks by flow cytometry. Width is a function of biological heterogeneity plus extrinsic and intrinsic error sources associated with the measurement process. Optimal cytometer performance minimizes extrinsic error, but reducing intrinsic error to the point of facilitating peak resolution requires careful fluorochrome selection and fluorescent cell sorting. In this study, we labeled the Jurkat and A549 cell lines with CFSE, CellTraceViolet (CTV), and eFluor 670 proliferation dye (EPD) to test if we could resolve division peaks in culture after reducing the labeled input widths by cell sorting. Reanalysis of the sorted populations to ascertain the level of reduction achieved always led to widths exceeding the gated limits due to the contribution of errors. Measuring detector-specific extrinsic error by sorting uniform fluorescent particles with similar spectral properties to the tracking dyes allowed us to determine the intrinsic error for each dye and cell type using a simple mathematical approach. We found that cell intrinsic error ultimately dictated whether we could resolve division peaks, and that as this increased, the required sort gate width to resolve any division peaks decreased to the point whereby issues with yield made A549 unsuitable for this approach. Finally, attempts to improve yields by setting two concurrent sort gates on the fluorescence distribution enriched for cells in different stages of the cell cycle that had nonequivalent proliferative properties in culture and thus should be practiced with caution.

Genetic tracing via DNGR-1 expression history defines dendritic cells as a hematopoietic lineage

Mononuclear phagocytes are classified as macrophages or dendritic cells (DCs) based on cell morphology, phenotype, or select functional properties. However, these attributes are not absolute and often overlap, leading to difficulties in cell-type identification. To circumvent this issue, we describe a mouse model to define DCs based on their ontogenetic descendence from a committed precursor. We show that precursors of mouse conventional DCs, but not other leukocytes, are marked by expression of DNGR-1. Genetic tracing of DNGR-1 expression history specifically marks cells traditionally ascribed to the DC lineage, and this restriction is maintained after inflammation. Notably, in some tissues, cells previously thought to be monocytes/macrophages are in fact descendants from DC precursors. These studies provide an in vivo model for fate mapping of DCs, distinguishing them from other leukocyte lineages, and thus help to unravel the functional complexity of the mononuclear phagocyte system.

Differential polarization of C-terminal Src kinase between naive and antigen-experienced CD8+ T cells

In CD8(+) T cells, engagement of the TCR with agonist peptide:MHC molecules causes dynamic redistribution of surface molecules including the CD8 coreceptor to the immunological synapse. CD8 associates with the Src-family kinase (SFK) Lck, which, in turn, initiates the rapid tyrosine phosphorylation events that drive cellular activation. Compared with naive T cells, Ag-experienced CD8(+) T cells make shorter contacts with APC, are less dependent on costimulation, and are triggered by lower concentrations of Ag, yet the molecular basis of this more efficient response of memory T cells is not fully understood. In this article, we show differences between naive and Ag-experienced CD8(+) T cells in colocalization of the SFKs and their negative regulator, C-terminal Src kinase (Csk). In naive CD8(+) T cells, there was pronounced colocalization of SFKs and Csk at the site of TCR triggering, whereas in Ag-experienced cells, Csk displayed a bipolar distribution with a proportion of the molecules sequestered within a cytosolic area in the distal pole of the cell. The data show that there is differential redistribution of a key negative regulator away from the site of TCR engagement in Ag-experienced CD8(+) T cells, which might be associated with the more efficient responses of these cells on re-exposure to Ag.

Multi-parametric phospho-flow cytometry: a crucial tool for T lymphocyte signaling studies

Tools such as protein immunoblotting have proven benefits for investigating T lymphocyte signaling but have several drawbacks such as the number of cells required and the difficulty of distinguishing subset-specific differences without expensive and invasive cell sorting. Recent advances in immunology and the identification of T lymphocyte sub-populations making up only a very small fraction of the total population highlight the importance of studying signaling in those small subsets in a feasible, cost-effective, high-throughput manner. To this end, we have developed a simplified protocol to study both intracellular phosphorylation patterns of important signal transduction molecules concomitantly with T cell surface marker expression. A multi-parametric analysis may allow the quantification of the phosphorylation of up to five signaling molecules in CD4 and CD8 T lymphocytes and their naïve, central memory, effector memory, and TEMRA subsets. This enables precise identification of subset-specific signaling and alterations of signaling pathways in physiological and pathological situations. The importance of such detailed analysis is discussed.