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New technologies for monitoring human antigen-specific T cells and regulatory T cells by flow-cytometry
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ScienceDirect New technologies for monitoring human antigenspecific T cells and regulatory T cells by flow-cytometry Petra Bacher1 and Alexander Scheffold1,2 T cells orchestrate and execute immune responses against certain antigens recognized by their antigen receptor. They can acquire a highly divers set of functional properties, which provide the basis for immune protection, but also for immunepathologies and thus represent highly specific diagnostic and therapeutic targets. New cytometric technologies now allow identification and precise characterization of human conventional and regulatory T cells against basically any antigen and even within naive donors. These provide the basis for thorough analyses of immune protection against infections and to tackle unmet challenges such as T cell responses involved in tolerance and/or directed against undefined or complex antigens, that is, in autoimmunity or allergy. Together with the parallel evolution of single cell multi-parameter approaches this has revolutionized the quantitative and qualitative characterization of human T cells, bearing important diagnostic, prognostic or therapeutic potential. Addresses 1 Department of Cellular Immunology, Clinic for Rheumatology and Clinical Immunology, Charite´ – University Medicine Berlin, 10117 Berlin, Germany 2 German Rheumatism Research Centre (DRFZ) Berlin, Leibniz Association, 10117 Berlin, Germany Corresponding author: Scheffold, Alexander ([email protected])
Current Opinion in Pharmacology 2015, 23:17–24 This review comes from a themed issue on Immunomodulation Edited by Stephen M Anderton and Simon Fillatreau
http://dx.doi.org/10.1016/j.coph.2015.04.005 1471-4892/# 2015 Elsevier Ltd. All rights reserved.
Introduction Adaptive immunity is based on small clonal populations of antigen-specific lymphocytes as the central operational units. T cells activated through their antigen receptor (T cell receptor, TCR) via antigenic peptides bound to MHC molecules are central players in adaptive immune responses. Following activation they contribute to protection against pathogens, as well as to immune-pathologies, for example, resulting from a breakdown of tolerance against harmless environmental or auto-antigens. The few T cells capable of reacting against a single antigen www.sciencedirect.com
have been difficult to track due to the highly variable nature of the MHC-peptide complex as well as their typically low abundance. Much of our knowledge about antigen-specific T cells in certain immune reactions is therefore based on animal models using defined antigens and TCR transgenes. However, mouse models mimic human diseases only imperfectly, indicated by the fact that except for vaccinations (which have mostly been developed before the identification of the molecular and cellular basis of immunity), only few antigen-specific therapeutic strategies developed in the mouse model have successfully been applied in the human system [1,2]. Therefore the analysis of antigen-specific T cells directly in human samples is an essential component of translational immunology, both for a better understanding of basic cellular processes underlying human immune-mediated diseases, as well as for the development of antigen-specific diagnostics or therapies. We will discuss here the challenges and the advances that have been made during the last years towards the comprehensive analysis of conventional as well as regulatory human T cells specific for the various types of clinically relevant antigens.
Direct versus indirect approaches to access antigen-specific T cells MHC-peptide multimers — you find what you are looking for
Peptide-MHC multimers are unique tools since they allow to directly identifying T cells according to TCR binding to its physiological target [3]. They are independent of the functional status of the T cells as well as the antigen-presenting cells (APC) and can thus be applied to any cellular sample. For pathogens with low antigen complexity, for example, viruses or protein/peptide vaccines, immune-dominant antigens and epitopes have been identified, enabling their direct detection via peptide-MHC multimers. Recent work also introduced strategies to generate and combine up to 100 different multimers in one multi-parameter cytometric analysis using multimer barcoding [4–6,7,8,9]. But still, the extremely high variability of potential T cell antigens, due to strong polymorphism of the MHC genes and the large number of peptides, which can potentially be generated from a certain pathogen, limits this approach to a few situations with exactly defined peptide-MHC combinations. Moreover only relatively few functional peptide-MHC class II tetramers exist covering only few CD4T cell specificities. By contrast, for the majority of clinically relevant situations, that is, infections with complex pathogens, autoimmunity or hypersensitivity Current Opinion in Pharmacology 2015, 23:17–24
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reactions against environmental antigens, the precise target specificities of T cells are still unknown and might also be variable between individual patients or different stages of the disease. In particular physiological target antigens of Foxp3+ regulatory T cells (Treg) are currently almost unknown. Therefore, studies using peptide-MHC labeling so far focused on detection of Treg specific for the epitopes previously defined for conventional memory T cells (Tmemory). This has led to the identification of Treg as part of the immune response against several pathogens [10–13,14,15], tumors [16,17] or allergens [18,19,20,21]. However, such analyses do not consider the possibility that Treg target additional epitopes not shared with conventional T cells (Tcon). This would actually be expected for their role in suppression of autoimmunity and inappropriate responses against harmless environmental antigens and their differential selection within the thymus. Indeed TCR profiling studies suggest that Treg possess a TCR repertoire with minimal overlap to Tcon [22,23,24]. In addition, Treg isolated from different tissues have non-overlapping TCR repertoires, suggesting indeed local selection by — so far not defined antigens [25,26,27,28]. To the best of our knowledge, a dominant population of Treg specific for classical Treg targets, that is, auto-antigens, intestinal commensals or food, as postulated by murine studies, has not been identified in the human system. Thus the peptide-MHC multimer approach seems to be an ideal tool for a limited set of defined antigens, but bears the intrinsic risk to miss relevant specificities, which play a role only in certain pathologic situations or are unique to a particular T cell subset (see Figure 1). Interrogating T cell function — find what you are not (necessarily) looking for
For less defined antigen-MHC combinations and in particular for complex pathogens or environmental antigens, less biased, indirect analysis tools have been developed, based on T cell activation parameters, following in vitro confrontation with antigen (reviewed in [29]). This features the unique possibility to study reactive T cells against basically any antigen, from peptides to rather undefined cell lysates, and in any donor HLA type. Ideally these indirect approaches should allow sensitive analysis of all T cell subsets, including naive, memory and Treg cells and should minimally affect the overall phenotype of the reactive T cells. This limits the usefulness of cytokines restricted to certain T cell subsets or late activation markers and proliferation (>72 hours) requiring extended stimulation times [30–34]. By contrast, in our experience CD154 (CD40L), which is already expressed after 5–7 hours of TCR stimulation by all naive and memory CD4T cells fully meets these criteria [35,36,37]. We used CD154 for defining naive and memory CD4T cell responses against complex pathogens such as fungi or commensal bacteria, but also autoantigens and even neo-antigens in healthy donors or Current Opinion in Pharmacology 2015, 23:17–24
relevant patient groups irrespective of the HLA type [35,38,39] (Bacher and Scheffold, unpublished data). This integrative feature of CD154 greatly facilitates normalization of functional or phenotypic subpopulations to the total antigen-specific repertoire. Treg lack most effector functions typically used as readout in conventional T cells. However, recently, several markers for activated Treg have been described [40–43]. CD137 seems to be the most promising, since it is selectively expressed by 5–7 hours stimulated Treg [40] and can be combined with CD154 for simultaneous analysis of Tcon and Treg. This marker combination has been used to directly sort allo-reactive Treg from peripheral blood [40] and helped to reveal an unexpected, strongly expanded Treg population specific for crude protein lysate or single proteins of ubiquitous fungal antigens in healthy donors [38,44]. Currently we use the same approach for systematic screening of ‘tolerogenic’ candidate antigens (auto-antigens, allergens, commensals, food) to unravel the specificities of the human Treg repertoire. However, the major limitation of all indirect approaches is that different antigen specificities cannot be resolved simultaneously in one sample. Therefore multimer and indirect approaches are highly complementary and indirect methods may also be ideal to rapidly identify single protein or peptide specificities. For example, we have used CD154 sorted T cells against whole pathogen lysates to rapidly expand specific T cell lines facilitating subsequent screening of single protein or peptide specificities [38].
Pre-enrichment technologies for increased sensitivity of detection and high resolution subset analysis One of the major roadblocks for antigen-specific cytometry in physiological TCR repertoires is the low frequency of T cells with certain specificity within a large number of irrelevant T cells. For naive T cells frequencies of about 1 in 106 have been estimated in mice and human [35,45–48,49,50,51]. But also antigen-specific memory T cells are typically in the range of 1–100 cells per 105 T cells in human blood at least in the absence of an acute infection [29]. These data from cytometric approaches correspond well with TCR sequencing data, which also revealed a high heterogeneity and only little clonal expansion in circulating human memory TCR repertoires [52,53,54]. Furthermore, antigen-experienced T cells are composed of a multitude of functionally diverse subsets, which may also subject to dynamic alterations, for example, depending on the environment or the actual host–pathogen interaction status (see also below). To cope with this high diversity the collection of a sufficient number of T cells allowing identifying even small subpopulations with high statistical power is a mandatory first www.sciencedirect.com
Antigen-specific T cell cytometry Bacher and Scheffold 19
Figure 1
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Different T cell subsets directed against a complex antigen can have overlapping or separate target specificities. (a) Peptide-MHC multimers can directly identify antigen-specific T cells in the naive memory and Treg compartment but require exactly defined MHC-peptide combinations. Most T cell epitopes defined to date were identified as targets of conventional memory T cells (Tmemory) and thus represent only a small part of all potential target proteins and/or peptide-MHC combinations contained within a complex pathogen, allergen or autoimmune target organ. Thus multimer approaches systematically may miss relevant specificities found in, Tnaive (b) or Treg (c) or subdominant Tmemory cells (d). By contrast, all antigen-specific T cells reactive to a certain antigen preparation (peptides, proteins or crude protein extracts) can be identified via specific activation markers, such as CD154 for Tcon and CD137 for Treg, that are expressed on all antigen-activated T cells following short in vitro activation.
step. Thus, the challenge of antigen-specific cytometry is not only to reliably distinguish the rare positive signals from background but also to collect sufficient cells in a reasonable time for characterization of subset composition at high resolution. To solve both problems magnetic pre-enrichment of rare cells has been combined with direct and indirect detection methods [6,35,45,50,51,55]. In this way up to 108–109 cells (compared to 105–106 cells of a www.sciencedirect.com
typical flow-cytometry experiment) can rapidly be processed to collect a high number of target cells for downstream analysis. This approach does also improve the signal-to-noise ratio and thus increases the level of sensitivity [35]. The gain of sensitivity does even allow detecting antigen-specific T cells within the naive [35,45,50,51] and also within the Treg repertoire [11,44], although total Treg being 10–20 times less abundant than Tcon, at least in peripheral blood. Current Opinion in Pharmacology 2015, 23:17–24
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It should be emphasized that this is not just a technical gadget for high-end cytometry, but rather the correct assessment of an individual’s immune status against a certain antigen requires the integration of all relevant T cell subsets. Early studies were focused on typical ‘memory’ features, such as production of effector cytokines, which excludes naive, as well as Treg from the analysis. However, the impact of a particular subpopulation on the immune response depends on the context, that is, its size relative to the total pool of antigen-specific T cells (see Figure 2). For example, recent data show that memory T cells specific for virus-antigens, auto-antigens or neo-antigens can readily be found even in unexposed
healthy donors [35,51,56]. However, in these examples naive T cells occurred in similar frequencies and actually the Tmemory/Tnaive ratio reflects mostly the ratio in the unselected total T cell population (own unpublished observation). This suggests that these memory cells were probably not generated by clonal expansion towards one defined cross-reactive antigen (which would expand Tmemory and simultaneously deplete the same specificity in the naive pool, i.e. Tmemory/Tnaive >> 1), but rather results from cross-recognition of neo-antigens by the broad polyclonal memory repertoire typically found in adult human donors. Actually this type of cross-recognition of neo-antigens or auto-antigens by
Figure 2
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Current Opinion in Pharmacology
The T cell immune status integrates the contribution by the Tnaive, Tmemory and Treg cells directed against the relevant antigen. The total CD4+ T cell pool consists of three main populations, Tnaive, Tmemory and Treg cells, with subset size variation mainly depending on age of the donor. Antigen-specific conventional T cell immunity comprises expansion of Tmemory and contraction of the Tnaive pool and optional expansion/ induction of Treg (a). Tolerance can be achieved by either conversion/expansion of Tnaive into Treg or selective expansion of thymic Treg without Tnaive contraction. Alternatively all specific T cells are deleted or anergized (b). Finally, antigens not encountered before, that is, neo-antigens or segregated auto-antigens, do not alter the T cell composition. However a variable amount of memory T cells (approximately at the same memory/ naive T cell ratio as in the total T cell population) may exist due to accidental cross-reactivity of TCRs within a broad polyclonal memory repertoire (c). Differentiation between these divergent immune status is only possible by determining the relative size (and clonal composition) of all contributing subsets. Current Opinion in Pharmacology 2015, 23:17–24
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Antigen-specific T cell cytometry Bacher and Scheffold 21
memory cells is probably a common phenomenon in humans (but not in 6 wk old spf mice) with major but so far insufficiently understood impact on human immunity.
combination with high-dimensional experimental strategies opens up completely new possibilities for experiments with human materials.
For example, by parallel analysis of naive, memory Tcon and Treg against Aspergillus fumigatus in the blood of healthy donors, we identified Treg as the dominantly expanded population [44] whereas Tcon still contained many naive T cells. To the best of our knowledge this is the first example for the selective expansion of Treg against a specific antigen in the absence of a strong memory response. These examples illustrate that naive and regulatory T cells must be integrated into antigenspecific T cell analyses to correctly resolve the individual immune status against a certain antigen (see Figure 2).
Conclusions
Accessing the naive repertoire using pre-enrichment technologies may also have the potential to predict the individual risk of immune-pathologies, like autoimmunity or allergy or the success of specific immune-modulations, that is, vaccination or tolerization, as has recently been demonstrated for the response to Bacillus anthracis vaccination [49]. Taken together pre-enrichment strategies in combination with technologies allowing broad and unbiased detection of all relevant antigen-specificities and functional subpopulations are a valuable tool to identify antigen specific T cells with high sensitivity and make them accessible for downstream multi-parameter characterization.
Multi-parameter analysis tools to resolve T cell diversity and to maximize information output from limited sample materials Recent developments have revolutionized multi-parameter analysis of single cells and have been instrumental to highlight that human memory T cells against a single antigen or pathogen and even on the clonal level are functionally and phenotypically highly heterogeneous [8,35,38,52,57]. This composition is highly dynamic, depending on the local environment or the immune status, for example, acute versus chronic or past infections, therefore providing an ideal diagnostic target (reviewed in [58,59]). Thus the ultimate goal for diagnostic or prognostic use of antigen-specific T cell analysis is to resolve subset composition at the highest possible resolution. In the recent years a number of single cell analysis tools have been developed which can be combined with antigenspecific T cell detection and allow simultaneous measurement of up to several hundred parameters (reviewed in [58,60]). The high number of available parameters also allows integration of sample barcoding, for example, to combine more than 100 different peptide-MHC specificities [8] or 20 single blood samples into one measurement [61]. This maximizes the information obtained from a single experiment to which is especially relevant in case of unique and often limited (often 100 ml of blood) patient samples. Therefore antigen-specific cytometry in www.sciencedirect.com
Antigen-specific T cell can be analyzed within all relevant T cell subsets and basically against any antigen and from any human donor. Together with new multidimensional single cell analysis tools this provides unique means to characterize T cell immunity at high resolution and allows to review basic mechanisms of immunity and tolerance originally identified in animal models now directly in humans. In particular, the role of defined antigens and the antigen-specific T cells in many human immunepathologies, that is, autoimmunity, allergy or inflammatory bowel disease is far from being understood. The technologies reviewed here, allow addressing these demanding questions of human immunology, which will provide a solid basis for antigen-specific diagnostics and therapies.
Conflict of interest statement AS is an consultant to Miltenyi Biotec. MB holds several patents on the use of CD154 and CD137 for antigenspecific T cell analysis.
Acknowledgement This work was supported by grants from the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 633 and Sonderforschungsbereich 650.
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46. Chu HH, Moon JJ, Kruse AC, Pepper M, Jenkins MK: Negative selection and peptide chemistry determine the size of naive foreign peptide-MHC class II-specific CD4+ T cell populations. J Immunol 2010, 185:4705-4713. 47. Chu HH, Moon JJ, Takada K, Pepper M, Molitor JA, Schacker TW, Hogquist KA, Jameson SC, Jenkins MK: Positive selection optimizes the number and function of MHCII-restricted CD4+ T cell clones in the naive polyclonal repertoire. Proc Natl Acad Sci U S A 2009, 106:11241-11245. 48. Geiger R, Duhen T, Lanzavecchia A, Sallusto F: Human naive and memory CD4+ T cell repertoires specific for naturally processed antigens analyzed using libraries of amplified T cells. J Exp Med 2009, 206:1525-1534. 49. Kwok WW, Tan V, Gillette L, Littell CT, Soltis MA, LaFond RB, Yang J, James EA, DeLong JH: Frequency of epitope-specific naive CD4(+) T cells correlates with immunodominance in the human memory repertoire. J Immunol 2012, 188:2537-2544. This paper demonstrates that the size of the antigen-specific naive repertoire may predict the subsequent memory T cell response. 50. Moon JJ, Chu HH, Pepper M, McSorley SJ, Jameson SC, Kedl RM, Jenkins MK: Naive CD4(+) T cell frequency varies for different epitopes and predicts repertoire diversity and response magnitude. Immunity 2007, 27:203-213. 51. Su LF, Kidd BA, Han A, Kotzin JJ, Davis MM: Virus-specific CD4(+) memory-phenotype T cells are abundant in unexposed adults. Immunity 2013, 38:373-383. This paper demonstrates by use of tetramer enrichment that crossreactivity against neo-epitopes is a fundamental part of human T cell memory. 52. Becattini S, Latorre D, Mele F, Foglierini M, De Gregorio C, Cassotta A, Fernandez B, Kelderman S, Schumacher TN, Corti D et al.: T cell immunity. Functional heterogeneity of human memory CD4(+) T cell clones primed by pathogens or vaccines. Science 2015, 347:400-406. This paper demonstrates that single TCR clones directed against a certain pathogen can differentiate into a diverse range of T helper cell subsets in human individuals. 53. Klarenbeek PL, Tak PP, van Schaik BD, Zwinderman AH, Jakobs ME, Zhang Z, van Kampen AH, van Lier RA, Baas F, de Vries N: Human T-cell memory consists mainly of unexpanded clones. Immunol Lett 2010, 133:42-48. 54. Qi Q, Liu Y, Cheng Y, Glanville J, Zhang D, Lee JY, Olshen RA, Weyand CM, Boyd SD, Goronzy JJ: Diversity and clonal selection in the human T-cell repertoire. Proc Natl Acad Sci U S A 2014, 111:13139-13144. This paper used TCR deep sequencing to demonstrate a broad polyclonal repertoire and a limited age-related clonal outgrowth in human memory T cells in comparison to naive T cells. 55. Brosterhus H, Brings S, Leyendeckers H, Manz RA, Miltenyi S, Radbruch A, Assenmacher M, Schmitz J: Enrichment and detection of live antigen-specific CD4(+) and CD8(+) T cells based on cytokine secretion. Eur J Immunol 1999, 29:4053-4059. 56. Campion SL, Brodie TM, Fischer W, Korber BT, Rossetti A, Goonetilleke N, McMichael AJ, Sallusto F: Proteome-wide analysis of HIV-specific naive and memory CD4(+) T cells in unexposed blood donors. J Exp Med 2014, 211:1273-1280. This paper uses T cell libraries to identify cross-reactive T cells against HIV epitopes present in healthy human T cell memory. 57. Newell EW, Sigal N, Bendall SC, Nolan GP, Davis MM: Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity 2012, 36:142-152.
44. Bacher P, Kniemeyer O, Schonbrunn A, Sawitzki B, Assenmacher M, Rietschel E, Steinbach A, Cornely OA, Brakhage AA, Thiel A et al.: Antigen-specific expansion of human regulatory T cells as a major tolerance mechanism against mucosal fungi. Mucosal Immunol 2014, 7:916-928. This paper is the first demonstration of a selectively expanded Treg population against a specific antigen in human blood providing a potential tolerance mechanism against allergies.
58. Newell EW, Davis MM: Beyond model antigens: high dimensional methods for the analysis of antigen-specific T cells. Nat Biotechnol 2014, 32:149-157. A comprehensive review about the state-of-the-art of identification and multiparameter analyses of antigen-specific T cells.
45. Alanio C, Lemaitre F, Law HK, Hasan M, Albert ML: Enumeration of human antigen-specific naive CD8+ T cells reveals conserved precursor frequencies. Blood 2010, 115:3718-3725.
59. Seder RA, Darrah PA, Roederer M: T-cell quality in memory and protection: implications for vaccine design. Nat Rev Immunol 2008, 8:247-258.
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60. Chattopadhyay PK, Gierahn TM, Roederer M, Love JC: Single-cell technologies for monitoring immune systems. Nat Immunol 2014, 15:128-135. A comprehensive review about the state-of-the-art single cell technologies available for downstream analysis of antigen-specific T cells.
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61. Mei HE, Leipold MD, Schulz AR, Chester C, Maecker HT: Barcoding of live human peripheral blood mononuclear cells for multiplexed mass cytometry. J Immunol 2015, 194:2022-2031. This paper describes the application of multiparameter cytometry for barcoding allowing to integrate multiple samples into one measurement.
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ScienceDirect New technologies for monitoring human antigenspecific T cells and regulatory T cells by flow-cytometry Petra Bacher1 and Alexander Scheffold1,2 T cells orchestrate and execute immune responses against certain antigens recognized by their antigen receptor. They can acquire a highly divers set of functional properties, which provide the basis for immune protection, but also for immunepathologies and thus represent highly specific diagnostic and therapeutic targets. New cytometric technologies now allow identification and precise characterization of human conventional and regulatory T cells against basically any antigen and even within naive donors. These provide the basis for thorough analyses of immune protection against infections and to tackle unmet challenges such as T cell responses involved in tolerance and/or directed against undefined or complex antigens, that is, in autoimmunity or allergy. Together with the parallel evolution of single cell multi-parameter approaches this has revolutionized the quantitative and qualitative characterization of human T cells, bearing important diagnostic, prognostic or therapeutic potential. Addresses 1 Department of Cellular Immunology, Clinic for Rheumatology and Clinical Immunology, Charite´ – University Medicine Berlin, 10117 Berlin, Germany 2 German Rheumatism Research Centre (DRFZ) Berlin, Leibniz Association, 10117 Berlin, Germany Corresponding author: Scheffold, Alexander ([email protected])
Current Opinion in Pharmacology 2015, 23:17–24 This review comes from a themed issue on Immunomodulation Edited by Stephen M Anderton and Simon Fillatreau
http://dx.doi.org/10.1016/j.coph.2015.04.005 1471-4892/# 2015 Elsevier Ltd. All rights reserved.
Introduction Adaptive immunity is based on small clonal populations of antigen-specific lymphocytes as the central operational units. T cells activated through their antigen receptor (T cell receptor, TCR) via antigenic peptides bound to MHC molecules are central players in adaptive immune responses. Following activation they contribute to protection against pathogens, as well as to immune-pathologies, for example, resulting from a breakdown of tolerance against harmless environmental or auto-antigens. The few T cells capable of reacting against a single antigen www.sciencedirect.com
have been difficult to track due to the highly variable nature of the MHC-peptide complex as well as their typically low abundance. Much of our knowledge about antigen-specific T cells in certain immune reactions is therefore based on animal models using defined antigens and TCR transgenes. However, mouse models mimic human diseases only imperfectly, indicated by the fact that except for vaccinations (which have mostly been developed before the identification of the molecular and cellular basis of immunity), only few antigen-specific therapeutic strategies developed in the mouse model have successfully been applied in the human system [1,2]. Therefore the analysis of antigen-specific T cells directly in human samples is an essential component of translational immunology, both for a better understanding of basic cellular processes underlying human immune-mediated diseases, as well as for the development of antigen-specific diagnostics or therapies. We will discuss here the challenges and the advances that have been made during the last years towards the comprehensive analysis of conventional as well as regulatory human T cells specific for the various types of clinically relevant antigens.
Direct versus indirect approaches to access antigen-specific T cells MHC-peptide multimers — you find what you are looking for
Peptide-MHC multimers are unique tools since they allow to directly identifying T cells according to TCR binding to its physiological target [3]. They are independent of the functional status of the T cells as well as the antigen-presenting cells (APC) and can thus be applied to any cellular sample. For pathogens with low antigen complexity, for example, viruses or protein/peptide vaccines, immune-dominant antigens and epitopes have been identified, enabling their direct detection via peptide-MHC multimers. Recent work also introduced strategies to generate and combine up to 100 different multimers in one multi-parameter cytometric analysis using multimer barcoding [4–6,7,8,9]. But still, the extremely high variability of potential T cell antigens, due to strong polymorphism of the MHC genes and the large number of peptides, which can potentially be generated from a certain pathogen, limits this approach to a few situations with exactly defined peptide-MHC combinations. Moreover only relatively few functional peptide-MHC class II tetramers exist covering only few CD4T cell specificities. By contrast, for the majority of clinically relevant situations, that is, infections with complex pathogens, autoimmunity or hypersensitivity Current Opinion in Pharmacology 2015, 23:17–24
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reactions against environmental antigens, the precise target specificities of T cells are still unknown and might also be variable between individual patients or different stages of the disease. In particular physiological target antigens of Foxp3+ regulatory T cells (Treg) are currently almost unknown. Therefore, studies using peptide-MHC labeling so far focused on detection of Treg specific for the epitopes previously defined for conventional memory T cells (Tmemory). This has led to the identification of Treg as part of the immune response against several pathogens [10–13,14,15], tumors [16,17] or allergens [18,19,20,21]. However, such analyses do not consider the possibility that Treg target additional epitopes not shared with conventional T cells (Tcon). This would actually be expected for their role in suppression of autoimmunity and inappropriate responses against harmless environmental antigens and their differential selection within the thymus. Indeed TCR profiling studies suggest that Treg possess a TCR repertoire with minimal overlap to Tcon [22,23,24]. In addition, Treg isolated from different tissues have non-overlapping TCR repertoires, suggesting indeed local selection by — so far not defined antigens [25,26,27,28]. To the best of our knowledge, a dominant population of Treg specific for classical Treg targets, that is, auto-antigens, intestinal commensals or food, as postulated by murine studies, has not been identified in the human system. Thus the peptide-MHC multimer approach seems to be an ideal tool for a limited set of defined antigens, but bears the intrinsic risk to miss relevant specificities, which play a role only in certain pathologic situations or are unique to a particular T cell subset (see Figure 1). Interrogating T cell function — find what you are not (necessarily) looking for
For less defined antigen-MHC combinations and in particular for complex pathogens or environmental antigens, less biased, indirect analysis tools have been developed, based on T cell activation parameters, following in vitro confrontation with antigen (reviewed in [29]). This features the unique possibility to study reactive T cells against basically any antigen, from peptides to rather undefined cell lysates, and in any donor HLA type. Ideally these indirect approaches should allow sensitive analysis of all T cell subsets, including naive, memory and Treg cells and should minimally affect the overall phenotype of the reactive T cells. This limits the usefulness of cytokines restricted to certain T cell subsets or late activation markers and proliferation (>72 hours) requiring extended stimulation times [30–34]. By contrast, in our experience CD154 (CD40L), which is already expressed after 5–7 hours of TCR stimulation by all naive and memory CD4T cells fully meets these criteria [35,36,37]. We used CD154 for defining naive and memory CD4T cell responses against complex pathogens such as fungi or commensal bacteria, but also autoantigens and even neo-antigens in healthy donors or Current Opinion in Pharmacology 2015, 23:17–24
relevant patient groups irrespective of the HLA type [35,38,39] (Bacher and Scheffold, unpublished data). This integrative feature of CD154 greatly facilitates normalization of functional or phenotypic subpopulations to the total antigen-specific repertoire. Treg lack most effector functions typically used as readout in conventional T cells. However, recently, several markers for activated Treg have been described [40–43]. CD137 seems to be the most promising, since it is selectively expressed by 5–7 hours stimulated Treg [40] and can be combined with CD154 for simultaneous analysis of Tcon and Treg. This marker combination has been used to directly sort allo-reactive Treg from peripheral blood [40] and helped to reveal an unexpected, strongly expanded Treg population specific for crude protein lysate or single proteins of ubiquitous fungal antigens in healthy donors [38,44]. Currently we use the same approach for systematic screening of ‘tolerogenic’ candidate antigens (auto-antigens, allergens, commensals, food) to unravel the specificities of the human Treg repertoire. However, the major limitation of all indirect approaches is that different antigen specificities cannot be resolved simultaneously in one sample. Therefore multimer and indirect approaches are highly complementary and indirect methods may also be ideal to rapidly identify single protein or peptide specificities. For example, we have used CD154 sorted T cells against whole pathogen lysates to rapidly expand specific T cell lines facilitating subsequent screening of single protein or peptide specificities [38].
Pre-enrichment technologies for increased sensitivity of detection and high resolution subset analysis One of the major roadblocks for antigen-specific cytometry in physiological TCR repertoires is the low frequency of T cells with certain specificity within a large number of irrelevant T cells. For naive T cells frequencies of about 1 in 106 have been estimated in mice and human [35,45–48,49,50,51]. But also antigen-specific memory T cells are typically in the range of 1–100 cells per 105 T cells in human blood at least in the absence of an acute infection [29]. These data from cytometric approaches correspond well with TCR sequencing data, which also revealed a high heterogeneity and only little clonal expansion in circulating human memory TCR repertoires [52,53,54]. Furthermore, antigen-experienced T cells are composed of a multitude of functionally diverse subsets, which may also subject to dynamic alterations, for example, depending on the environment or the actual host–pathogen interaction status (see also below). To cope with this high diversity the collection of a sufficient number of T cells allowing identifying even small subpopulations with high statistical power is a mandatory first www.sciencedirect.com
Antigen-specific T cell cytometry Bacher and Scheffold 19
Figure 1
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Peptide-MHC multimer
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Different T cell subsets directed against a complex antigen can have overlapping or separate target specificities. (a) Peptide-MHC multimers can directly identify antigen-specific T cells in the naive memory and Treg compartment but require exactly defined MHC-peptide combinations. Most T cell epitopes defined to date were identified as targets of conventional memory T cells (Tmemory) and thus represent only a small part of all potential target proteins and/or peptide-MHC combinations contained within a complex pathogen, allergen or autoimmune target organ. Thus multimer approaches systematically may miss relevant specificities found in, Tnaive (b) or Treg (c) or subdominant Tmemory cells (d). By contrast, all antigen-specific T cells reactive to a certain antigen preparation (peptides, proteins or crude protein extracts) can be identified via specific activation markers, such as CD154 for Tcon and CD137 for Treg, that are expressed on all antigen-activated T cells following short in vitro activation.
step. Thus, the challenge of antigen-specific cytometry is not only to reliably distinguish the rare positive signals from background but also to collect sufficient cells in a reasonable time for characterization of subset composition at high resolution. To solve both problems magnetic pre-enrichment of rare cells has been combined with direct and indirect detection methods [6,35,45,50,51,55]. In this way up to 108–109 cells (compared to 105–106 cells of a www.sciencedirect.com
typical flow-cytometry experiment) can rapidly be processed to collect a high number of target cells for downstream analysis. This approach does also improve the signal-to-noise ratio and thus increases the level of sensitivity [35]. The gain of sensitivity does even allow detecting antigen-specific T cells within the naive [35,45,50,51] and also within the Treg repertoire [11,44], although total Treg being 10–20 times less abundant than Tcon, at least in peripheral blood. Current Opinion in Pharmacology 2015, 23:17–24
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It should be emphasized that this is not just a technical gadget for high-end cytometry, but rather the correct assessment of an individual’s immune status against a certain antigen requires the integration of all relevant T cell subsets. Early studies were focused on typical ‘memory’ features, such as production of effector cytokines, which excludes naive, as well as Treg from the analysis. However, the impact of a particular subpopulation on the immune response depends on the context, that is, its size relative to the total pool of antigen-specific T cells (see Figure 2). For example, recent data show that memory T cells specific for virus-antigens, auto-antigens or neo-antigens can readily be found even in unexposed
healthy donors [35,51,56]. However, in these examples naive T cells occurred in similar frequencies and actually the Tmemory/Tnaive ratio reflects mostly the ratio in the unselected total T cell population (own unpublished observation). This suggests that these memory cells were probably not generated by clonal expansion towards one defined cross-reactive antigen (which would expand Tmemory and simultaneously deplete the same specificity in the naive pool, i.e. Tmemory/Tnaive >> 1), but rather results from cross-recognition of neo-antigens by the broad polyclonal memory repertoire typically found in adult human donors. Actually this type of cross-recognition of neo-antigens or auto-antigens by
Figure 2
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Thymic Treg expansion Tmemory
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Current Opinion in Pharmacology
The T cell immune status integrates the contribution by the Tnaive, Tmemory and Treg cells directed against the relevant antigen. The total CD4+ T cell pool consists of three main populations, Tnaive, Tmemory and Treg cells, with subset size variation mainly depending on age of the donor. Antigen-specific conventional T cell immunity comprises expansion of Tmemory and contraction of the Tnaive pool and optional expansion/ induction of Treg (a). Tolerance can be achieved by either conversion/expansion of Tnaive into Treg or selective expansion of thymic Treg without Tnaive contraction. Alternatively all specific T cells are deleted or anergized (b). Finally, antigens not encountered before, that is, neo-antigens or segregated auto-antigens, do not alter the T cell composition. However a variable amount of memory T cells (approximately at the same memory/ naive T cell ratio as in the total T cell population) may exist due to accidental cross-reactivity of TCRs within a broad polyclonal memory repertoire (c). Differentiation between these divergent immune status is only possible by determining the relative size (and clonal composition) of all contributing subsets. Current Opinion in Pharmacology 2015, 23:17–24
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Antigen-specific T cell cytometry Bacher and Scheffold 21
memory cells is probably a common phenomenon in humans (but not in 6 wk old spf mice) with major but so far insufficiently understood impact on human immunity.
combination with high-dimensional experimental strategies opens up completely new possibilities for experiments with human materials.
For example, by parallel analysis of naive, memory Tcon and Treg against Aspergillus fumigatus in the blood of healthy donors, we identified Treg as the dominantly expanded population [44] whereas Tcon still contained many naive T cells. To the best of our knowledge this is the first example for the selective expansion of Treg against a specific antigen in the absence of a strong memory response. These examples illustrate that naive and regulatory T cells must be integrated into antigenspecific T cell analyses to correctly resolve the individual immune status against a certain antigen (see Figure 2).
Conclusions
Accessing the naive repertoire using pre-enrichment technologies may also have the potential to predict the individual risk of immune-pathologies, like autoimmunity or allergy or the success of specific immune-modulations, that is, vaccination or tolerization, as has recently been demonstrated for the response to Bacillus anthracis vaccination [49]. Taken together pre-enrichment strategies in combination with technologies allowing broad and unbiased detection of all relevant antigen-specificities and functional subpopulations are a valuable tool to identify antigen specific T cells with high sensitivity and make them accessible for downstream multi-parameter characterization.
Multi-parameter analysis tools to resolve T cell diversity and to maximize information output from limited sample materials Recent developments have revolutionized multi-parameter analysis of single cells and have been instrumental to highlight that human memory T cells against a single antigen or pathogen and even on the clonal level are functionally and phenotypically highly heterogeneous [8,35,38,52,57]. This composition is highly dynamic, depending on the local environment or the immune status, for example, acute versus chronic or past infections, therefore providing an ideal diagnostic target (reviewed in [58,59]). Thus the ultimate goal for diagnostic or prognostic use of antigen-specific T cell analysis is to resolve subset composition at the highest possible resolution. In the recent years a number of single cell analysis tools have been developed which can be combined with antigenspecific T cell detection and allow simultaneous measurement of up to several hundred parameters (reviewed in [58,60]). The high number of available parameters also allows integration of sample barcoding, for example, to combine more than 100 different peptide-MHC specificities [8] or 20 single blood samples into one measurement [61]. This maximizes the information obtained from a single experiment to which is especially relevant in case of unique and often limited (often 100 ml of blood) patient samples. Therefore antigen-specific cytometry in www.sciencedirect.com
Antigen-specific T cell can be analyzed within all relevant T cell subsets and basically against any antigen and from any human donor. Together with new multidimensional single cell analysis tools this provides unique means to characterize T cell immunity at high resolution and allows to review basic mechanisms of immunity and tolerance originally identified in animal models now directly in humans. In particular, the role of defined antigens and the antigen-specific T cells in many human immunepathologies, that is, autoimmunity, allergy or inflammatory bowel disease is far from being understood. The technologies reviewed here, allow addressing these demanding questions of human immunology, which will provide a solid basis for antigen-specific diagnostics and therapies.
Conflict of interest statement AS is an consultant to Miltenyi Biotec. MB holds several patents on the use of CD154 and CD137 for antigenspecific T cell analysis.
Acknowledgement This work was supported by grants from the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 633 and Sonderforschungsbereich 650.
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