Probabilistic regulation of IL-4 production in Th2 cells: accessibility at the Il4 locus

STAT6 tunes maximum T cell IL-4 production from stochastically regulated Il4 alleles

T helper 2 (Th2) cells stochastically express from the Il4 locus but it has not been determined whether allelic expression is linked or independent. Here, we provide evidence that alleles are independently activated and inactivated. We compared Il4 locus expression in T cells from hemizygous IL-4 reporter mice in culture and in vivo following exposure to type 2 immunogens. In culture, Il4 alleles had independent, heritable expression probabilities. Modeling showed that in co-expressors, dual allele transcription occurs for only short periods, limiting per-cell mRNA variation in individual cells within a population of Th2 cells. In vivo profiles suggested that early in the immune response, IL-4 output was derived predominantly from single alleles, but co-expression became more frequent over time and were tuned by STAT6, supporting the probabilistic regulation of Il4 alleles in vivo among committed IL-4 producers. We suggest an imprinted probability of expression from individual alleles with a short transcriptional shutoff time controls the magnitude of T cell IL-4 output, but the amount produced per allele is amplified by STAT6 signaling. This form of regulation may be a relevant general mechanism governing cytokine expression.

Effects of adult Ascaris suum and their antigens (total and trans-cuticular excretory-secretory antigen, cuticular somatic antigen) on intestinal nutrient transport in vivo

Ascaris suum constitutes a major problem in commercial pig farming worldwide. Lower weight gains in infected pigs probably result from impaired nutrient absorption. This study investigated intestinal nutrient transport in 4 groups of 6 pigs each, which were inoculated with 30 living adult A. suum , or antigen fractions consisting of (1) total excretory–secretory (ES) antigens of adult worms, (2) ES antigens secreted exclusively from the parasites' body surface (trans-cuticular ES) and (3) cuticular somatic antigens of A. suum , compared to placebo-treated controls. Three days after inoculation into the gastrointestinal tract, glucose, alanine and glycyl-l -glutamine transport was measured in the duodenum, jejunum and ileum using Ussing chambers. Transcription of relevant genes [sodium glucose cotransporter 1 (SGLT1), glucose transporter 1 (GLUT1), GLUT2, hypoxia-inducible factor 1-alpha (Hif1α ), interleukin-4 (IL-4), IL-13, signal transducer and activator of transcription 6 (STAT6), peptide transporter 1 (PepT1)] and expression of transport proteins [SGLT1, phosphorylated SGLT1, GLUT2, Na+/K+-ATPase, amino acid transporter A (ASCT1), PepT1] were studied. Although no significant functional changes were noted after exposure to adult A. suum , a significant downregulation of jejunal GLUT1, STAT6, Hif1α and PepT1 transcription as well as ileal GLUT2 and PepT1 expression indicates a negative impact of infection on transport physiology. Therefore, the exposure period of 3 days may have been insufficient for functional alterations to become apparent. In contrast, A. suum antigens mainly induced an upregulation of transport processes and an increase in transcription of relevant genes in the duodenum and jejunum, possibly as a compensatory reaction after a transient downregulation. In the ileum, a consistent pattern of downregulation was observed in all inoculated groups, in line with the hypothesis of impaired nutrient transport.

Decoding the dynamics of multilayered stochastic antiviral IFN-I responses

Type I Interferon (IFN-I) responses were first recognized for their role in antiviral immunity, but it is now widely appreciated that IFN-Is have many immunomodulatory functions, influencing antitumor responses, autoimmune manifestations, and antimicrobial defenses. Given these pivotal roles, it may be surprising that multilayered stochastic events create highly heterogeneous, but tightly regulated, all-or-nothing cellular decisions. Recently, mathematical models have provided crucial insights into the stochastic nature of antiviral IFN-I responses, which we critically evaluate in this review. In this context, we emphasize the need for innovative single-cell technologies combined with mathematical models to further reveal, understand, and predict the complexity of the IFN-I system in physiological and pathological conditions that may be relevant to a plethora of diseases.

Antiviral interferon response at single-cell resolution

Experimental studies of the innate immune response of mammalian cells to viruses reveal pervasive heterogeneity at the level of single cells. Interferons are induced only in a fraction of virus-infected cells; subsequently a fraction of cells exposed to interferons upregulate interferon-stimulated genes. Nevertheless, quantitative experiments and linked mathematical models show that the interferon response can be effective in curbing viral spread through two distinct mechanisms. First, paracrine interferon signals from scattered source cells can protect many uninfected cells, and the self-amplification of interferon production might serve to calibrate response amplitude to strength of viral infection. Second, models of the tug-of-war between viral replication and the innate interferon response imply a pivotal role of interferon action on already infected cells in curbing viral spread, through effectively lowering virus replication rate. This finding is in line with the observation that several pathogenic viruses selectively abrogate interferon action on infected cells. Thus, interferons may delay viral spread in acute infections by acting as sentinels, warning uninfected cells of imminent danger, or as negative feedback regulators of virus replication in infected cells. The timing of the interferon response relative to the onset of viral replication is critical for its effectiveness in curbing viral spread.

Spatial distribution of IL4 controls iNKT cell-DC crosstalk in tumors

The spatiotemporal distribution of cytokines orchestrates immune responses in vivo, yet the underlying mechanisms remain to be explored. We showed here that the spatial distribution of interleukin-4 (IL4) in invariant natural killer T (iNKT) cells regulated crosstalk between iNKT cells and dendritic cells (DCs) and controlled iNKT cell-mediated T-helper type 1 (Th1) responses. The persistent polarization of IL4 induced by strong lipid antigens, that is, α-galactosylceramide (αGC), caused IL4 accumulation at the immunological synapse (IS), which promoted the activation of the IL4R-STAT6 (signal transducer and activator of transcription 6) pathway and production of IL12 in DCs, which enhanced interferon-γ (IFNγ) production in iNKT cells. Conversely, the nonpolarized secretion of IL4 induced by Th2 lipid antigens with a short or unsaturated chain was incapable of enhancing this iNKT cell-DC crosstalk and thus shifted the immune response to a Th2-type response. The nonpolarized secretion of IL4 in response to Th2 lipid antigens was caused by the degradation of Cdc42 in iNKT cells. Moreover, reduced Cdc42 expression was observed in tumor-infiltrating iNKT cells, which impaired IL4 polarization and disturbed iNKT cell-DC crosstalk in tumors.

Single-cell RNA-Seq analysis identifies a noncoding interleukin 4 (IL-4) RNA that post-transcriptionally up-regulates IL-4 production in T helper cells

High-throughput sequencing has revealed a tremendous complexity of cellular transcriptomes, which is partly due to the generation of multiple alternative transcripts from a single gene locus. Because alternative transcripts often have low abundance in bulk cells, the functions of most of these transcripts and their relationship with their canonical counterparts remain unclear. Here we applied single-cell RNA-Seq to analyze the transcriptome complexity of in vitro-differentiated, murine type 2 T helper (Th2) cells. We found that cytokine gene transcripts contribute most of the intercellular heterogeneity, with a group of universal cytokines, including interleukins 1a, 2, 3, and 16, being bimodally expressed. At the single-cell level, use of alternative promoters prevalently generated alternative transcripts. For instance, although undetectable in bulk cells, a noncoding RNA isoform of IL-4 (IL4nc), which was driven by an intronic promoter in the IL-4 locus, was predominantly expressed in a subset of Th2 cells. IL4nc displayed distinct temporal expression patterns compared with the canonical IL-4 mRNA and post-transcriptionally promoted the production of IL-4 protein in Th2 cells. In conclusion, our findings reveal a mechanism whereby minor noncanonical transcripts post-transcriptionally regulate expression of their cognate canonical genes.

Modifying clonal selection theory with a probabilistic cell

Problem-solving strategies in immunology currently utilize a series of ad hoc, qualitative variations on a foundation of Burnet's formulation of clonal selection theory. These modifications, including versions of two-signal theory, describe how signals regulate lymphocytes to make important decisions governing self-tolerance and changes to their effector and memory states. These theories are useful but are proving inadequate to explain the observable genesis and control of heterogeneity in cell types, the nonlinear passage of cell fate trajectories and how the input from multiple environmental signals can be integrated at different times and strengths. Here, I argue for a paradigm change to place immune theory on a firmer philosophical and quantitative foundation to resolve these difficulties. This change rejects the notion of identical cell subsets and substitutes the concept of a cell as comprised of autonomous functional mechanical components subject to stochastic variations in construction and operation. The theory aims to explain immunity in terms of cell population dynamics, dictated by the operation of cell machinery, such as randomizing elements, division counters, and fate timers. The effect of communicating signals alone and in combination within this system is determined with a cellular calculus. A series of models developed with these principles can resolve logical cell fate and signaling paradoxes and offer a reinterpretation for how self-non-self discrimination and immune response class are controlled.

Downregulation of NFAT3 Due to Lack of T-Box Transcription Factor TBX5 Is Crucial for Cytokine Expression in T Cells

The NFAT family transcription factors play crucial roles in immunological and other biological activities. NFAT3 is rarely expressed in T cells, and the mechanisms and significance of the specific NFAT3 downregulation in T cells have been unknown. In human CD4⁺ T cells, overexpression of NFAT1 and NFAT3 enhanced and suppressed IL-2 expression, respectively. NFAT3 downregulation in Jurkat cells using RNA interference technology augmented IL-2 expression, whereas a knockdown of NFAT1, NFAT2, and NFAT4 suppressed it. The promoter/enhancer activity of the NFAT-binding site in the IL-2 gene was upregulated and downregulated by NFAT1 and NFAT3, respectively. A study employing NFAT1/NFAT3 chimeric molecules revealed that the region in NFAT3 responsible for NFAT promoter activity inhibition was located within its N-terminal transactivation domain, Ca²⁺-regulatory domain, and DNA-binding domain. Downregulation of NFAT3 expression in T cells is mediated by lower chromatin accessibility and enhancer activity in its promoter in comparison with aortic smooth muscle cells expressing endogenous NFAT3. The binding sites of T-box transcription factor TBX5 and NK-2 transcription factor-related locus 5 Nkx2.5, which were expressed at higher levels in aortic smooth muscle cells than in T cells, were located within the -387 to +97 NFAT3 promoter region, exhibiting the maximum enhancer activity. Mutating the binding site of TBX5 but not Nkx2.5 diminished the NFAT3 promoter activity, whereas the overexpression of TBX5 enhanced it. Introduction of TBX5 into CD4⁺ T cells enhanced the expression of NFAT3 and suppressed that of IL-2. TBX5 deficiency-mediated downregulation of NFAT3 is crucial for the high cytokine-producing activity of T cells.

Instructed subsets or agile swarms: how T-helper cells may adaptively counter uncertainty with variability and plasticity

Over recent years, extensive phenotypic variability and plasticity have been revealed among the T-helper cells of the mammalian adaptive immune system, even within clonal lineages of identical antigen specificity. This challenges the conventional view that T-helper cells assort into functionally distinct subsets following differential instruction by the innate immune system. We argue that the adaptive value of coping with uncertainty can reconcile the 'instructed subset' framework with T-helper variability and plasticity. However, we also suggest that T-helper cells might better be understood as agile swarms engaged in collective decision-making to promote host fitness. With rigorous testing, the 'agile swarms' framework may illuminate how variable and plastic individual T-helper cells interact to create coherent immunity.

Regulation of IL-4 Expression in Immunity and Diseases

IL-4 was first identified as a T cell-derived growth factor for B cells. Studies over the past several decades have markedly expanded our understanding of its cellular sources and function. In addition to T cells, IL-4 is produced by innate lymphocytes, such as NTK cells, and myeloid cells, such as basophils and mast cells. It is a signature cytokine of type 2 immune response but also has a nonimmune function. Its expression is tightly regulated at several levels, including signaling pathways, transcription factors, epigenetic modifications, microRNA, and long noncoding RNA. This chapter will review in detail the molecular mechanism regulating the cell type-specific expression of IL-4 in physiological and pathological type 2 immune responses.

T helper 2 (Th2) cell differentiation, type 2 innate lymphoid cell (ILC2) development and regulation of interleukin-4 (IL-4) and IL-13 production

Interleukin-4 (IL-4), IL-5 and IL-13, the signature cytokines that are produced during type 2 immune responses, are critical for protective immunity against infections of extracellular parasites and are responsible for asthma and many other allergic inflammatory diseases. Although many immune cell types within the myeloid lineage compartment including basophils, eosinophils and mast cells are capable of producing at least one of these cytokines, the production of these "type 2 immune response-related" cytokines by lymphoid lineages, CD4 T helper 2 (Th2) cells and type 2 innate lymphoid cells (ILC2s) in particular, are the central events during type 2 immune responses. In this review, I will focus on the signaling pathways and key molecules that determine the differentiation of naïve CD4 T cells into Th2 cells, and how the expression of Th2 cytokines, especially IL-4 and IL-13, is regulated in Th2 cells. The similarities and differences in the differentiation of Th2 cells, IL-4-producing T follicular helper (Tfh) cells and ILC2s as well as their relationships will also be discussed.

An animated landscape representation of CD4+ T-cell differentiation, variability, and plasticity: insights into the behavior of populations versus cells

Recent advances in understanding CD4(+) T-cell differentiation suggest that previous models of a few distinct, stable effector phenotypes were too simplistic. Although several well-characterized phenotypes are still recognized, some states display plasticity, and intermediate phenotypes exist. As a framework for reexamining these concepts, we use Waddington's landscape paradigm, augmented with explicit consideration of stochastic variations. Our animation program "LAVA" visualizes T-cell differentiation as cells moving across a landscape of hills and valleys, leading to attractor basins representing stable or semistable differentiation states. The model illustrates several principles, including: (i) cell populations may behave more predictably than individual cells; (ii) analogous to reticulate evolution, differentiation may proceed through a network of interconnected states, rather than a single well-defined pathway; (iii) relatively minor changes in the barriers between attractor basins can change the stability or plasticity of a population; (iv) intrapopulation variability of gene expression may be an important regulator of differentiation, rather than inconsequential noise; (v) the behavior of some populations may be defined mainly by the behavior of outlier cells. While not a quantitative representation of actual differentiation, our model is intended to provoke discussion of T-cell differentiation pathways, particularly highlighting a probabilistic view of transitions between states.

Computational modeling of heterogeneity and function of CD4+ T cells

The immune system is composed of many different cell types and hundreds of intersecting molecular pathways and signals. This large biological complexity requires coordination between distinct pro-inflammatory and regulatory cell subsets to respond to infection while maintaining tissue homeostasis. CD4+ T cells play a central role in orchestrating immune responses and in maintaining a balance between pro- and anti- inflammatory responses. This tight balance between regulatory and effector reactions depends on the ability of CD4+ T cells to modulate distinct pathways within large molecular networks, since dysregulated CD4+ T cell responses may result in chronic inflammatory and autoimmune diseases. The CD4+ T cell differentiation process comprises an intricate interplay between cytokines, their receptors, adaptor molecules, signaling cascades and transcription factors that help delineate cell fate and function. Computational modeling can help to describe, simulate, analyze, and predict some of the behaviors in this complicated differentiation network. This review provides a comprehensive overview of existing computational immunology methods as well as novel strategies used to model immune responses with a particular focus on CD4+ T cell differentiation.

Nuclear factor of activated T cells regulates the expression of interleukin-4 in Th2 cells in an all-or-none fashion

Th2 memory lymphocytes have imprinted their Il4 genes epigenetically for expression in dependence of T cell receptor restimulation. However, in a given restimulation, not all Th cells with a memory for IL-4 expression express IL-4. Here, we show that in reactivated Th2 cells, the transcription factors NFATc2, NF-kB p65, c-Maf, p300, Brg1, STAT6, and GATA-3 assemble at the Il4 promoter in Th2 cells expressing IL-4 but not in Th2 cells not expressing it. NFATc2 is critical for assembly of this transcription factor complex. Because NFATc2 translocation into the nucleus occurs in an all-or-none fashion, dependent on complete dephosphorylation by calcineurin, NFATc2 controls the frequencies of cells reexpressing Il4, translates analog differences in T cell receptor stimulation into a digital decision for Il4 reexpression, and instructs all reexpressing cells to express the same amount of IL-4. This analog-to-digital conversion may be critical for the immune system to respond to low concentrations of antigens.

Epigenetic control of immunity

Immunity relies on the heterogeneity of immune cells and their ability to respond to pathogen challenges. In the adaptive immune system, lymphocytes display a highly diverse antigen receptor repertoire that matches the vast diversity of pathogens. In the innate immune system, the cell's heterogeneity and phenotypic plasticity enable flexible responses to changes in tissue homeostasis caused by infection or damage. The immune responses are calibrated by the graded activity of immune cells that can vary from yeast-like proliferation to lifetime dormancy. This article describes key epigenetic processes that contribute to the function of immune cells during health and disease.

Cytokine diversity in the Th1-dominated human anti-influenza response caused by variable cytokine expression by Th1 cells, and a minor population of uncommitted IL-2+IFNγ- Thpp cells

Within overall Th1-like human memory T cell responses, individual T cells may express only some of the characteristic Th1 cytokines when reactivated. In the Th1-oriented memory response to influenza, we have tested the contributions of two potential mechanisms for this diversity: variable expression of cytokines by a uniform population during activation, or different stable subsets that consistently expressed subsets of the Th1 cytokine pattern. To test for short-term variability, in vitro-stimulated influenza-specific human memory CD4+ T cells were sorted according to IL-2 and IFNγ expression, cultured briefly in vitro, and cytokine patterns measured after restimulation. Cells that were initially IFNγ+ and either IL-2+ or IL-2- converged rapidly, containing similar proportions of IL-2-IFNγ+ and IL-2+IFNγ+ cells after culture and restimulation. Both phenotypes expressed Tbet, and similar patterns of mRNA. Thus variability of IL-2 expression in IFNγ+ cells appeared to be regulated more by short-term variability than by stable differentiated subsets. In contrast, heterogeneous expression of IFNγ in IL-2+ influenza-specific T cells appeared to be due partly to stable T cell subsets. After sorting, culture and restimulation, influenza-specific IL-2+IFNγ- and IL-2+IFNγ+ cells maintained significantly biased ratios of IFNγ+ and IFNγ- cells. IL-2+IFNγ- cells included both Tbet^lo and Tbet^hi cells, and showed more mRNA expression differences with either of the IFNγ+ populations. To test whether IL-2+IFNγ-Tbet^lo cells were Thpp cells (primed but uncommitted memory cells, predominant in responses to protein vaccines), influenza-specific IL-2+IFNγ- and IL-2+IFNγ+ T cells were sorted and cultured in Th1- or Th2-generating conditions. Both cell types yielded IFNγ-secreting cells in Th1 conditions, but only IL-2+IFNγ- cells were able to differentiate into IL-4-producing cells. Thus expression of IL-2 in the anti-influenza response may be regulated mainly by short term variability, whereas different T cell subsets, Th1 and Thpp, may contribute to variability in IFNγ expression.

Heterogeneity in immune responses: from populations to single cells

The mammalian immune system is tasked with protecting the host against a broad range of threats. Understanding how immune populations leverage cellular diversity to achieve this breadth and flexibility, particularly during dynamic processes such as differentiation and antigenic response, is a core challenge that is well suited for single cell analysis. Recent years have witnessed transformative and intersecting advances in nanofabrication and genomics that enable deep profiling of individual cells, affording exciting opportunities to study heterogeneity in the immune response at an unprecedented scope. In light of these advances, here we review recent work exploring how immune populations generate and leverage cellular heterogeneity at multiple molecular and phenotypic levels. Additionally, we highlight opportunities for single cell technologies to shed light on the causes and consequences of heterogeneity in the immune system.

CXCL11-dependent induction of FOXP3-negative regulatory T cells suppresses autoimmune encephalomyelitis

A single G protein-coupled receptor (GPCR) can activate multiple signaling cascades based on the binding of different ligands. The biological relevance of this feature in immune regulation has not been evaluated. The chemokine-binding GPCR CXCR3 is preferentially expressed on CD4+ T cells, and canonically binds 3 structurally related chemokines: CXCL9, CXCL10, and CXCL11. Here we have shown that CXCL10/CXCR3 interactions drive effector Th1 polarization via STAT1, STAT4, and STAT5 phosphorylation, while CXCL11/CXCR3 binding induces an immunotolerizing state that is characterized by IL-10(hi) (Tr1) and IL-4(hi) (Th2) cells, mediated via p70 kinase/mTOR in STAT3- and STAT6-dependent pathways. CXCL11 binds CXCR3 with a higher affinity than CXCL10, suggesting that CXCL11 has the potential to restrain inflammatory autoimmunity. We generated a CXCL11-Ig fusion molecule and evaluated its use in the EAE model of inflammatory autoimmune disease. Administration of CXCL11-Ig during the first episode of relapsing EAE in SJL/J mice not only led to rapid remission, but also prevented subsequent relapse. Using GFP-expressing effector CD4+ T cells, we observed that successful therapy was associated with reduced accumulation of these cells at the autoimmune site. Finally, we showed that very low doses of CXCL11 rapidly suppress signs of EAE in C57BL/6 mice lacking functional CXCL11.

Mapping differentiation under mixed culture conditions reveals a tunable continuum of T cell fates

An experimental and theoretical study of T cell differentiation in response to mixed-input conditions reveals that cells can tune between Th1 and Th2 states through a continuum of mixed phenotypes.

Cell differentiation is typically directed by external signals that drive opposing regulatory pathways. Studying differentiation under polarizing conditions, with only one input signal provided, is limited in its ability to resolve the logic of interactions between opposing pathways. Dissection of this logic can be facilitated by mapping the system's response to mixtures of input signals, which are expected to occur in vivo, where cells are simultaneously exposed to various signals with potentially opposing effects. Here, we systematically map the response of naïve T cells to mixtures of signals driving differentiation into the Th1 and Th2 lineages. We characterize cell state at the single cell level by measuring levels of the two lineage-specific transcription factors (T-bet and GATA3) and two lineage characteristic cytokines (IFN-γ and IL-4) that are driven by these transcription regulators. We find a continuum of mixed phenotypes in which individual cells co-express the two lineage-specific master regulators at levels that gradually depend on levels of the two input signals. Using mathematical modeling we show that such tunable mixed phenotype arises if autoregulatory positive feedback loops in the gene network regulating this process are gradual and dominant over cross-pathway inhibition. We also find that expression of the lineage-specific cytokines follows two independent stochastic processes that are biased by expression levels of the master regulators. Thus, cytokine expression is highly heterogeneous under mixed conditions, with subpopulations of cells expressing only IFN-γ, only IL-4, both cytokines, or neither. The fraction of cells in each of these subpopulations changes gradually with input conditions, reproducing the continuous internal state at the cell population level. These results suggest a differentiation scheme in which cells reflect uncertainty through a continuously tuneable mixed phenotype combined with a biased stochastic decision rather than a binary phenotype with a deterministic decision.

During cell differentiation, progenitor cells respond to external signals that drive the expression of genes that are characteristic of the differentiated cell states. This process is controlled by gene regulatory networks that typically involve positive autoregulation and cross-inhibition between master regulators of the two differentiated states. Mapping the system's response to mixtures of external signals can help us to understand the operational logic of these binary cell fate decisions. Here, we study differentiation of CD4⁺ T cells into Th1 and Th2 lineages under mixed-input conditions, at the single cell level. We reveal that cell state is not restricted to a small number of well-defined phenotypes, but rather tunes through a continuum of mixed-phenotype states in which levels of lineage-specifying transcription factors gradually change with the levels of the two inputs. Using mathematical modeling we establish the conditions under which the system has one stable steady state that continuously tunes in response to changes in levels of the inputs. Results of this model qualitatively explain our experimental observations. We further characterize expression patterns of downstream lineage-specific genes—cytokines that are driven by the two master regulators upon cell re-stimulation. We find a highly heterogeneous population with cells expressing either one of the cytokines, both cytokines, or neither. Of note, the fraction of cells in these subpopulations continuously tunes with input levels, thus reproducing a tunable state at the cell population level. Our results can be explained by a two-stage scheme in which the gene regulatory network is responsible for a continuously tunable cell state, which is translated into a heterogeneous cytokine expression pattern through uncorrelated and biased stochastic processes.

Logic of the inflammation-associated transcriptional response

Immune response to pathogens depends on coordinated regulation of numerous genes that contribute collectively to pathogen elimination and restoration of the integrity of the affected tissue. The pathogen-induced gene expression is governed largely by the signal-induced posttranslational histone modifications that facilitate assembly of the functionally distinct chromatin complexes. In this review, we describe the principles of chromatin-based gene regulation during innate immune responses. We discuss the ability of pathogens to hijack the host response by interfering with various arms of transcriptional machinery involved in the responses. In particular, we discuss the phenomenon of the histone mimicry where interaction between histones and transcriptional regulators is targeted by pathogens that carry the histone-like sequences (histone mimics). We show how the principle of isotone mimicry as an efficient way to control host gene expression has been sued for the development of novel anti-inflammatory pharmacological approaches.

The dynamic lives of T cells: new approaches and themes

Activated T cells have classically been thought to progress unidirectionally through discrete phenotypic states and differentiate into static lineages. It is increasingly evident, however, that T cells exhibit much more complex and flexible dynamic behaviors than initially appreciated, and that these behaviors influence the efficacy of T cell responses to immunological challenges. In this review, we discuss how new technologies for monitoring the dynamics of T cells are enhancing the resolution of the fine phenotypic and functional heterogeneity within populations of T cells and revealing how individual T cells transition among a continuum of states. Such insights into the dynamic properties of T cells should improve immune monitoring and inform strategies for therapeutic interventions.

Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response

The cellular recognition of viruses evokes the secretion of type-I interferons (IFNs) that induce an antiviral protective state. By live-cell imaging, we show that key steps of virus-induced signal transduction, IFN-β expression, and induction of IFN-stimulated genes (ISGs) are stochastic events in individual cells. The heterogeneity in IFN production is of cellular-and not viral-origin, and temporal unpredictability of IFN-β expression is largely due to cell-intrinsic noise generated both upstream and downstream of the activation of nuclear factor-κB and IFN regulatory factor transcription factors. Subsequent ISG induction occurs as a stochastic all-or-nothing switch, where the responding cells are protected against virus replication. Mathematical modelling and experimental validation show that reliable antiviral protection in the face of multi-layered cellular stochasticity is achieved by paracrine response amplification. Achieving coherent responses through intercellular communication is likely to be a more widely used strategy by mammalian cells to cope with pervasive stochasticity in signalling and gene expression.

Duel of the fates: the role of transcriptional circuits and noise in CD4+ cells

CD4+ T cells play key roles in orchestrating adaptive immune responses, and are a popular model for mammalian cell differentiation. While immune regulation would seem to require exactly adjusted mRNA and protein expression levels of key factors, there is little evidence that this is strictly the case. Stochastic gene expression and plasticity of cell types contrast the apparent need for precision. Recent work has provided insight into the magnitude of molecular noise, as well as the relationship between noise, transcriptional circuits and epigenetic modifications in a variety of cell types. These processes and their interplay will also govern gene expression patterns in the different CD4+ cell types, and the determination of their cellular fates.

Stochastic expression of the interferon-β gene

The analysis of stochastic interferon-beta gene expression in virus-infected mammalian cells reveals that the levels of components required for virtually every step in the virus induction pathway are limiting.

Virus infection of mammalian cells induces the production of high levels of type I interferons (IFNα and β), cytokines that orchestrate antiviral innate and adaptive immunity. Previous studies have shown that only a fraction of the infected cells produce IFN. However, the mechanisms responsible for this stochastic expression are poorly understood. Here we report an in depth analysis of IFN-expressing and non-expressing mouse cells infected with Sendai virus. Mouse embryonic fibroblasts in which an internal ribosome entry site/yellow fluorescent protein gene was inserted downstream from the endogenous IFNβ gene were used to distinguish between the two cell types, and they were isolated from each other using fluorescence-activated cell sorting methods. Analysis of the separated cells revealed that stochastic IFNβ expression is a consequence of cell-to-cell variability in the levels and/or activities of limiting components at every level of the virus induction process, ranging from viral replication and expression, to the sensing of viral RNA by host factors, to activation of the signaling pathway, to the levels of activated transcription factors. We propose that this highly complex stochastic IFNβ gene expression evolved to optimize both the level and distribution of type I IFNs in response to virus infection.

Eukaryotic cells can respond to extracellular signals by triggering the activation of specific genes. Viral infection of mammalian cells, for example, induces a high level of expression of type I interferons (IFNα and β), proteins required for antiviral immunity that protects cells from the infection. Previous studies have shown that the expression of the IFNβ gene is stochastic, and under optimal conditions only a fraction of the infected cells express the IFNβ gene. At present neither the mechanisms nor functions of this interesting phenomenon are well understood. We have addressed this question by analyzing IFN-expressing and non-expressing mouse cells that were infected with the highly transmissible Sendai virus. We show that stochastic IFNβ gene expression is a consequence of cell-to-cell differences in limiting levels and/or activities of virus components at every level of the virus induction process, from viral replication to expression. These differences include the sensing of viral RNA by host factors, the activation of the signaling pathway, and the levels of activated transcription factors. Our findings reveal the complexity of the regulatory mechanisms controlling stochastic IFNβ gene expression. We propose that the stochastic expression of IFN allows for an even distribution of IFN, thus avoiding over-expression of IFN in infected cells.

Enhanced chromatin accessibility and recruitment of JUNB mediate the sustained IL-4 expression in NFAT1 deficient T helper 2 cells

Nuclear factor of activated T cells (NFAT) is a family of transcription factors composed of five proteins. Among them, NFAT1 is a predominant NFAT protein in CD4(+) T cells. NFAT1 positively regulates transcription of a large number of inducible cytokine genes including IL-2, IL-4, IL-5 and other cytokines. However, disruption of NFAT1 results in an unexpected increase of IL-4. In this study, we have investigated the role of NFAT1 in regulation of IL-4 gene expression in T helper 2 cells (Th2) from an epigenetic viewpoint. NFAT1 deficient Th2 cells showed a sustained IL-4 expression while wild type (WT) cells reduced its expression. We tested whether epigenetic maintenance and changes in the chromatin architecture of IL-4 promoter locus play a role in differential IL-4 transcription between in WT and NFAT1 deficient Th2 cells. Compared with WT, NFAT1 deficient CD4(+) Th2 cells exhibited enhanced chromatin accessibility with permissive histone modification and DNA demethylation in the IL-4 promoter region. Transcription factors bound to IL-4 promoter region in the absence of NFAT1 were identified by Micro-LC/LC-MS/MS analysis. Among the candidates, preferential recruitment of JUNB to the IL-4 promoter was confirmed by chromatin immunoprecipitation analysis. Overexpression of JUNB together with SATB1 synergistically upregulated IL-4 promoter activity, while knockdown JUNB significantly reduced IL-4 expression. Our results suggest that the prolonged IL-4 expression in NFAT1 deficient Th2 cells is mediated by preferential binding of JUNB/SATB1 to the IL-4 promoter with permissive chromatin architecture.

Peripheral CD4+ T-cell differentiation regulated by networks of cytokines and transcription factors

CD4(+) T cells, also known as T-helper (Th) cells, play an important role in orchestrating adaptive immune responses to various infectious agents. They are also involved in the induction of autoimmune and allergic diseases. Upon T-cell receptor (TCR)-mediated cell activation, naive CD4(+) T cells can differentiate into at least four major lineages, Th1, Th2, Th17, and iTreg cells, that participate in different types of immune responses. Networks of cytokines and transcription factors are critical for determining CD4(+) T-cell fates and effector cytokine production. Here, we review collaboration and cross-regulation between various essential cytokines in the activation/induction of key transcription factors during the process of Th cell differentiation towards these distinct lineages. We also discuss the interactions of key transcription factors at both genetic and protein levels and the function of the resulting network(s) in regulating the expression of effector cytokines.

Induction and maintenance of IL-4 expression are regulated differently by the 3' enhancer in CD4 T cells

IL-4 expression is known to be activated in CD4 T cells when they are differentiated to Th2 but not Th1 cells. However, CD4 T cells selected by MH class II-expressing thymocytes, named thymocyte-selected CD4 T cells (T-CD4 T cells), express IL-4 under both Th1 and Th2 conditions. In this study, we investigated molecular mechanisms by which IL-4 gene expression is regulated in T-CD4 T cells. We found that T-CD4 T cells express IL-4 soon after selection in the thymus. Deficiency of DNase I hypersensitive (HS) sites HS5a and HS5 at the 3'-enhancer region in the IL-4 gene decreased IL-4 production, but T-CD4 T cells were able to make IL-4 under the Th1-inducing condition. Consistent with this, IL-4 was expressed in Th1 differentiated T-CD4 T cells in the absence of recombination signal binding protein-J that interacts with HS5. When HS5 was examined separately from other endogenous regulatory elements using a reporter system, CD4 T cells that are selected by thymic epithelial cells cannot transcribe the IL-4 reporter gene with HS5 alone. However, HS5 was able to induce the expression of the IL-4 reporter gene in T-CD4 T cells. Interestingly, the Th1 differentiating signal led to deacetylation at HS5 of the IL-4 endogenous gene, whereas the Th2-inducing environment had no effect. Therefore, in T-CD4 T cells, HS5 plays an essential role during the induction phase of IL-4 expression, but the maintenance of IL-4 expression in Th1 cells requires additional regulatory elements.

Short-term memory in gene induction reveals the regulatory principle behind stochastic IL-4 expression

Combining experiments on primary T cells and mathematical modeling, we characterized the stochastic expression of the interleukin-4 cytokine gene in its physiologic context, showing that a two-step model of transcriptional regulation acting on chromatin rearrangement and RNA polymerase recruitment accounts for the level, kinetics, and population variability of expression.

A rate-limiting step upstream of transcription initiation, but occurring at the level of an individual allele, controls whether the interleukin-4 gene is expressed during antigenic stimulation, suggesting that the observed stochasticity of expression is linked to the dynamics of chromatin rearrangement.

The computational analysis predicts that the probability to re-express an interleukin-4 gene that has been expressed once is transiently increased. In support, we experimentally demonstrate a short-term memory for interleukin-4 expression at the predicted time scale of several days.

The model provides a unifying framework that accounts for both graded and binary modes of gene regulation. Graded changes in expression level can be achieved by controlling transcription initiation, whereas binary regulation acts at the level of chromatin rearrangement and is targeted during the differentiation of T cells that specialize in interleukin-4 production.

Cell populations are typically heterogeneous with respect to protein expression even when clonally derived from a single progenitor. In bacteria and yeast, such heterogeneity has been shown to be due to intrinsically stochastic dynamics of gene expression (Raj and van Oudenaarden, 2008). Thus, cross-population heterogeneity may be an unavoidable by-product of random fluctuations in molecular interactions (Raser and O'Shea, 2004; Pedraza and van Oudenaarden, 2005). The phenotypic variability deriving from it may also be beneficial for cell function, differentiation, or adaptation to changing environments (Chang et al, 2008; Feinerman et al, 2008; Losick and Desplan, 2008). However, little is known about how gene-expression variability is caused in mammalian cells.

Two principal modes of gene regulation have been identified: graded and binary. In the graded mode, transcriptional regulators can tune the level of a gene product in a continuous manner (Hazzalin and Mahadevan, 2002). In the binary mode, the gene is expressed at an invariant level, whereas its probability of being expressed in a given cell is regulated, so that the gene has discrete ‘on' and ‘off' states (Walters et al, 1995; Hume, 2000; Biggar and Crabtree, 2001). In humans and mice, cytokine genes are expressed in a binary manner (Bix and Locksley, 1998; Riviere et al, 1998; Hu-Li et al, 2001; Apostolou and Thanos, 2008). A particularly well-studied case is the interleukin-4 (il4) gene that is critical for antibody-based immune responses. This gene is expressed by antigen-stimulated T cells initially with low probability, so that in most IL-4-positive cells only one allele is active (Bix and Locksley, 1998; Riviere et al, 1998). The expressed allele is not imprinted but chosen stochastically during each cell stimulation (Hu-Li et al, 2001).

Here, we have studied the dynamics of IL-4 expression quantitatively. Primary murine CD4⁺ T cells have been differentiated uniformly into type-2 T-helper (Th2) cells that express the lineage-specifying transcription factor (TF) Gata-3 and are competent to activate the il4 gene upon challenge with antigen. Using T cells heterozygous for an il4 wild-type allele and an il4 allele with GFP knock-in after the promoter, the alleles are found to be expressed stochastically and in an uncorrelated manner (Figure 2A; Hu-Li et al, 2001). To account for the observed stochastic dynamics of IL-4 expression, we considered a basic model of gene transcription, mRNA translation, turnover, and protein secretion (Figure 2B). However, our experimental estimates of the intracellular life times of IL-4 mRNA and protein (∼1 h) and their absolute numbers (mRNA∼10³, protein∼10⁵) rule out random fluctuations in transcription, translation as well as mRNA and protein turnover as an explanation for the observed stochastic properties of IL-4 expression (Thattai and van Oudenaarden, 2001; Paulsson, 2004).

As il4 is known to be strongly regulated at the chromatin level (Ansel et al, 2006), we included in the model a reversible step of chromatin opening that is permissive for transcription (Figure 2C and D). Both chromatin opening and transcription initiation are driven by TFs that are transiently activated during the antigen stimulus, with NFAT1 playing a prominent role (Agarwal et al, 2000; Avni et al, 2002; Guo et al, 2004). The model accounts for the kinetics of NFAT1 TF activity (Figure 2E) (Loh et al, 1996). Using a best-fit procedure for estimating the kinetics of the chromatin transition and TF activity from experimental data, we found that the model accurately reproduces the distribution of IL-4 expression within the cell population over the entire time course of a stimulation (Figure 3A). At the same time, it accounts for the measured kinetics of IL-4 mRNA, intracellular and secreted protein (Figure 3B). Additional data show that the model can also explain IL-4 expression at different stages of Th2 differentiation and upon pharmacological inhibition of NFAT1 activity. In each case, the model predicts a slow and stochastic chromatin opening (Step 1 in Figure 2C) that is the limiting step for the activation of the gene.

The slowness of chromatin opening inferred by the model implies an extended lifetime of the open chromatin state (several days), which lasts longer than TF activity during antigenic stimulation (several hours). This indicates that acute IL-4 expression is terminated by the cessation of TF activity (Step 2 in Figure 2C), rather than by the closing of the chromatin (Step 1). In support of this prediction, we observed an elevated fraction of IL-4-producing cells after secondary stimulations administered within a few days of the primary stimulus. Consistent with the model, this elevation disappeared with a half-life of ∼3 days (Figure 4B). To test whether this ‘short-term memory' for activation of the il4 gene is indeed due to the IL-4 producers in the primary stimulation, we sorted stimulated Th2 cells into viable IL-4-producing and non-producing fractions using the cytokine secretion assay (Ouyang et al, 2000) and cultured them separately for different resting periods. The probability of IL-4 re-expression in the positive-sorted cells was consistently larger than in negative-sorted cells and decreased progressively over several days (Figure 4C). By contrast, the sorted IL-4 negative cells exhibited a constant induction probability indistinguishable from the unsorted population. This behavior was not due to differential cell proliferation in the sorted populations or different success of Th2 differentiation. Moreover, using heterozygous il4-wild-type/il4-gfp cells, and sorting for expression of the wild-type allele, we observed that expression of the il4-gfp allele was similar in IL-4-positive and negative sorted fractions. Taken together, these findings imply that stochastic, slow chromatin changes at individual il4 genes govern the binary expression pattern of this cytokine.

In conclusion, we propose an experimentally based model of inducible gene expression where strong stochasticity arises from slow (hours to days) chromatin opening and closing transitions, rather than being due to small numbers of mRNA or protein molecules or transcriptional bursting (Raj et al, 2006). This rate-limiting step upstream of transcription initiation (which may entail several interacting epigenetic processes) naturally gives rise to a binary expression pattern of the gene. By contrast, regulation at the level of transcription initiation can have a graded effect on the expression level. We provide evidence that both binary and graded regulation can occur for the il4 gene. Physiological regulation of il4 seems to be mainly binary, thus enabling a dose–response within a population while producing an unequivocal all-or-none signal at the single-cell level.

Although cell-to-cell variability has been recognized as an unavoidable consequence of stochasticity in gene expression, it may also serve a functional role for tuning physiological responses within a cell population. In the immune system, remarkably large variability in the expression of cytokine genes has been observed in homogeneous populations of lymphocytes, but the underlying molecular mechanisms are incompletely understood. Here, we study the interleukin-4 gene (il4) in T-helper lymphocytes, combining mathematical modeling with the experimental quantification of expression variability and critical parameters. We show that a stochastic rate-limiting step upstream of transcription initiation, but acting at the level of an individual allele, controls il4 expression. Only a fraction of cells reaches an active, transcription-competent state in the transient time window determined by antigen stimulation. We support this finding by experimental evidence of a previously unknown short-term memory that was predicted by the model to arise from the long lifetime of the active state. Our analysis shows how a stochastic mechanism acting at the chromatin level can be integrated with transcriptional regulation to quantitatively control cell-to-cell variability.

Transcriptional regulation of Th2 cell differentiation

CD4 T helper 2 (Th2) cells have critical functions in immune responses against extracellular parasites and are involved in asthma and other allergic diseases. The differentiation of naïve CD4 T cells into Th2 cells is initiated from T-cell receptor and cytokine-mediated signaling followed by upregulation of GATA3 and activation of signal transducer and activator of transcription 5 (STAT5), two indispensable events for this differentiation process. In this review, regulation of GATA3 expression and STAT5 activation and functions of these two transcription factors in inducing the expression of Th2 cytokines, cytokine receptors as well as epigenetic modification at Th2 cytokine locus are summarized. Furthermore, I present positive and negative regulatory networks important for Th2 cell commitment, selective growth of committed Th2 cells and suppression of alternative lineage fates. Finally, the difference between in vitro and in vivo Th2 differentiation is discussed.

T-box 21 transcription factor is responsible for distorted T(H)2 differentiation in human peripheral CD4+ T cells

BACKGROUND

Regardless of T(H)1/T(H)2 theory, CD4(+) T cells of patients with allergic asthma, a typical T(H)2 disease, and those of healthy subjects expressed equivalent levels of IFN-gamma, even though T(H)2 cytokines were significantly upregulated in asthmatic patients.

OBJECTIVE

The mechanisms underlying distorted T(H)2 cell polarization in human T cells were elucidated.

METHODS

Cytokine-producing activity and the expression of T(H)1/T(H)2-specific transcription factors in naïve, T(H)1/T(H)2, or both CD4(+) T cells derived from human peripheral and cord blood were comparatively analyzed. The mechanisms of the differential expression of T-box 21 transcription factor (T-bet) in the cells were assessed by determining the chromatin accessibility at the TBX21 gene. The functional roles of T-bet and other transcription factors in human T(H)1/T(H)2 differentiation were further investigated.

RESULTS

T(H)2 cells derived from naive CD4(+) T cells in peripheral blood but not in cord blood produced IFN-gamma. T-bet was expressed in peripheral, but not cord blood, resting naive T cells. Consistently, the accessibility at the proximal TBX21 gene promoter in peripheral naive T cells was higher than that in cord blood naive T cells. IFN-gamma-producing activity was induced in T(H)2-differentiated cord blood T cells by means of ectopic expression of T-bet. In addition, a reduction of T-bet in peripheral T cells suppressed IFN-gamma production. T-bet not only upregulated IFN-gamma but also downregulated IL-4 and IL-13 gene transcription, independently of the modification of T(H)1/T(H)2 balance.

CONCLUSION

The expression of T-bet at a naive stage is crucial for the development of IFN-gamma-producing T cells in human peripheral blood, even in T(H)2-related diseases.

Probabilistic regulation of IL-4 production

Among a population of uniformly differentiated TH(2) cells, only a portion express IL-4 upon stimulation and those that do often express the product of only a single allele. We review the evidence for the basis of IL-4 monoallelism and argue that it depends upon probabilistic expression of the Il4 gene. Further, we argue that probabilistic expression may provide a powerful mechanism through which certain key functions of IL-4, such as immunoglobulin class switching and determination of macrophage phenotype, may be efficiently regulated.

Ectopic expression of peripheral-tissue antigens in the thymic epithelium: probabilistic, monoallelic, misinitiated

Thymic medullary epithelial cells (MECs) express a broad repertoire of peripheral-tissue antigens (PTAs), many of which depend on the transcriptional regulatory factor Aire. Although Aire is known to be critically important for shaping a self-tolerant T cell repertoire, its role in MEC maturation and function remains poorly understood. Using a highly sensitive and reproducible single-cell PCR assay, we demonstrate that individual Aire-expressing MECs transcribe a subset of PTA genes in a probabilistic fashion, with no signs of preferential coexpression of genes characteristic of particular extrathymic epithelial cell lineages. In addition, Aire-dependent PTA genes in MECs are transcribed monoallelically or biallelically in a stochastic pattern, in contrast to the usually biallelic transcription of these same genes in the relevant peripheral cells or of Aire-independent genes in MECs. Expression of PTA genes in MECs depends on transcriptional regulators and uses transcriptional start sites different from those used in peripheral cells. These findings support the "terminal differentiation" model of Aire function: as MECs mature, they transcribe more and more PTA genes, culminating in a cell population that is both capable of presenting antigens (MHCII(hi), CD80(hi)) and can draw on a large repertoire of antigens to present.

Flexibility accompanies commitment of memory CD4 lymphocytes derived from IL-4 locus-activated precursors

Differentiation of T helper (Th) subset 2 effector lymphocytes is thought to foreclose on IFN-gamma gene expression. Using an IL-4 locus modified to detect transcriptional induction of this effector cytokine gene in developing Th2 cells, we show here that these cells contributed effectively to a long-term memory population. A memory CD4 subset formed efficiently from an activated population after transcriptional induction of the IL-4 locus and differentiation into an IL-4-producing subset with Th2 characteristics. Memory lymphocytes derived from Th2 cells with IL-4 locus activation remained committed to transcriptional competence of Th2 cytokine genes when reactivated and cultured under strong Th1-polarizing conditions. This commitment to transcriptional competence at Th2 cytokine gene loci upon recall activation indicates that linear differentiation is a substantial component of type 2 memory. Strikingly, however, descendants of the Th2 population could turn on IFN-gamma expression when reactivated after a quiescent period, revealing an unexpected flexibility allowing activation of the forbidden IFN-gamma gene after reactivation and growth.

Epigenetic regulation of Th2 cytokine expression in atopic diseases

The immune response to allergens starts with stimulation of a naïve T helper (Th) cell and its differentiation into a Th2 cell, expressing the cytokines interleukin (IL)-4, IL-5 and IL-13 responsible for the allergic response. The initial pattern of cytokine expression is retained during restimulation and division of the Th2 cell to create a population of specific allergen-responsive memory Th2 cells. Both, the coordinate cytokine expression and the inherited cytokine memory are specified by epigenetic mechanisms. Th2-specific changes in chromatin configuration at the Th2 locus act locally to open DNA, allowing recruitment of transcriptional machinery and rapid induction of cytokine expression. Induction of the transcription factor GATA3 is critical to this process. Loss of DNA methylation at the Th2 locus during differentiation from a naïve Th cell correlates to increased histone acetylation, consistent with the expression of IL-4, IL-5 and IL-13. The silencing of the Th2 locus in Th1 cells was associated with repressive histone methylation. These data indicate the formation of a 'poised' chromatin configuration at the Th2 locus that in combination with specific transcription factors specifies the cytokine repertoire in daughter cells and allows the immediate, rapid induction of cytokines by those cells in response to allergen.

Pathogen-imposed skewing of mouse chemokine and cytokine expression at the infected tissue site

Compartmentalization of immunity ensures tight regulation of T cell activation in the LN and precise effector T cell delivery to inflamed sites. Herein we show that the tissue-specific accumulation of effector T cells can be subverted by a pathogen at the infection site. Using the Leishmania major mouse model of dermal infection, we observed a restricted chemokine profile at the infection site, i.e., the expression of Th2 cell-attracting CCL7 but not of Th1 cell-attracting chemokines. Consistent with these chemokine expression data, recruitment of cytokine-producing T cells to the infection site was also selective. Both IL-4- and IFN-gamma-producing effector T cells homed to inflamed OVA/CFA-immunized dermis, but only IL-4-producing cells homed to L. major-infected dermis. The narrowing of the cytokine repertoire at the site of infection with L. major was driven, in part, by pathogen-induced CCL7. Inflammatory signals failed to disrupt the early restrictive L. major infection site, which suggests that L. major dominantly modifies the local milieu. We have highlighted an emerging principle in pathogen-host interactions: that the cytokine repertoire at the infection site and the LN draining the infection site can be different because of the ability of the pathogen to modify the chemokine profile at the infection site. Thus, pathogens may edit the LN cytokine repertoire through differential recruitment of cytokine-producing cells.

Unconventional association of the polycomb group proteins with cytokine genes in differentiated T helper cells

The cytokine transcription profiles of developing T helper 1 and T helper 2 cells are imprinted and induced appropriately following stimulation of differentiated cells. Epigenetic regulation combines several mechanisms to ensure the inheritance of transcriptional programs. We found that the expression of the polycomb group proteins, whose role in maintaining gene silencing is well documented, was induced during development in both T helper lineages. Nevertheless, the polycomb proteins, YY1, Mel-18, Ring1A, Ezh2, and Eed, bound to the Il4 and Ifng loci in a differential pattern. In contrast to the prevailing dogma, the binding activity of the polycomb proteins in differentiated T helper cells was associated with cytokine transcription. The polycomb proteins bound to the cytokine genes under resting conditions, and their binding was induced dynamically following stimulation. The recruitment of the polycomb proteins Mel-18 and Ezh2 to the cytokine promoters was inhibited in the presence of cyclosporine A, suggesting the involvement of NFAT. Considering their binding pattern at the cytokine genes and their known function in higher order folding of regulatory elements, we propose a model whereby the polycomb proteins, in some contexts, positively regulate gene expression by mediating long-distance chromosomal interactions.

Sex specifically associated promoter polymorphism in multiple sclerosis affects interleukin 4 expression levels

The interleukin 4 promoter polymorphism -589 C/T (rs2243250) was genotyped in 869 multiple sclerosis (MS) patients and 595 healthy blood donors. Sex-specific MS association was evident whereas two flanking polymorphisms showed insignificant P values. In dual luciferase assays of cultured Jurkat cells the cloned promoter comprising the -589 T allele leads to higher expression as compared to the respective construct with the C allele. Together these findings may be discussed functionally as contributing to the genetic predisposition and to the pathogenesis in MS.

Quantitative insights into stochastic monoallelic expression of cytokine genes

Gene expression from both parental alleles is beneficial by masking the effects of deleterious recessive mutations and by reducing the noise in gene expression in diploid organisms. However, a class of genes are expressed preferentially or strictly from a single allele. The selective advantage of avoiding biallelic expression is clear for allelic-excluded antigen receptor and odorant receptor genes, genes undergoing X-chromosome inactivation in females and parental genomic imprinted genes. In contrast, there is no clear biological rationale for the predominant and stochastic monoallelic expression of cytokine genes in the immune system, and the underlying mechanism is elusive and controversial. A clarification of the mechanism of predominant monoallelic expression would be instrumental in better understanding its eventual biological functional. This prompted the development of a quantitative framework that could describe the dynamics of the pattern of allele expression of the IL-10 gene, from which general quantitative insights could be gained. We report that the experimental observations on these patterns of allelic expression cannot be easily reconciled with a simple model of stochastic transcriptional activation, in which the two alleles are, at any time, equally competent for transcription. Instead, these observations call into action a general model of eukaryotic transcriptional regulation according to which the locus competence for transcription is dynamic, involving multiple, cooperative and stochastic modification steps. In this model, the probability that an allele becomes transcriptionally active is a function of the number of chromatin modifications that it accumulated. On the basis of the properties of this model, we argue that predominant monoallelic expression might have had no adaptive role, and may have evolved under indirect selection for low frequency of expressing cells.

Expression of IL-10 in Th memory lymphocytes is conditional on IL-12 or IL-4, unless the IL-10 gene is imprinted by GATA-3

In Th1 and Th2 memory lymphocytes, the genes for the cytokines interleukin (IL)-4 and interferon-gamma (IFN-gamma) are imprinted for expression upon restimulation. This cytokine memory is based on expression of the transcription factors T-bet for IFN-gamma, and GATA-3 for IL-4, and epigenetic modification of the cytokine genes. In Th2 cells, expression of the cytokine IL-10 is also induced by GATA-3. Here, we show that this induction is initially not accompanied by epigenetic modification of the IL-10 gene. Only after repeated restimulation of a memory Th2 cell in the presence of IL-4, extensive histone acetylation of the IL-10 gene is detectable. This epigenetic imprinting correlates with the development of a memory for IL-10 in repeatedly restimulated Th2 cells. In Th1 cells, IL-10 expression is induced by IL-12, but the IL-10 gene lacks detectable histone acetylation. Accordingly, IL-10 expression in restimulated memory Th1 cells remains conditional on the presence of IL-12. This finding defines a potential anti-inflammatory role for IL-12 in Th1 recall responses. While in primary Th1 responses IL-12 is required to induce expression of the pro-inflammatory cytokine IFN-gamma, in secondary Th1 responses IFN-gamma re-expression is independent of IL-12, which still is able to induce expression of the anti-inflammatory cytokine IL-10.

GATA3 up-regulation associated with surface expression of CD294/CRTH2: a unique feature of human Th cells

GATA-3 and T-box expressed in T cells (T-bet) play central roles in Th-cell development and function. Consistently, studies in mice document their selective expression in Th1 and Th2 cells, respectively. In contrast, it is not clear whether these genes are regulated in human Th cells. Here we show that T-bet expression is polarized to a comparable degree in human and mouse Th-cell cultures, while only mouse GATA3 is subject to substantial regulation. This did not reflect differential skewing efficiency in human versus mouse cultures, as these contained similar frequencies of IFN-gamma- and IL-4-producing cells. However, GATA-3 was expressed at significantly higher levels in human IL-4-producing cells enriched via capture with monoclonal antibodies (mAbs) against the PGD(2) receptor, CRTH2, the best selective Th2-cell surface marker to date. Along with increased IL-4 and GATA-3, CRTH2(+) Th cells isolated from Th2-skewed cultures or the circulating memory pool exhibited markedly decreased IFN-gamma and T-bet expression. Thus, the human GATA-3 gene is not regulated in response to polarizing signals that are sufficient to direct Th2-specific expression in mouse cells. This postulates the involvement of an additional level of complexity in the regulation of human GATA-3 expression and stresses the existence of nontrivial differences in the regulation of human versus mouse T-cell function.

Regulation of class I major histocompatibility complex receptor expression in natural killer cells: one promoter is not enough!

The class I major histocompatibility complex (MHC) receptors expressed by natural killer (NK) cells play an important role in regulating their function. The number and type of inhibitory receptors expressed by NK cells must be tightly controlled in order to avoid the generation of dominantly inhibited NK cells. The selective stochastic expression of the class I MHC receptors generates a variegated NK cell population capable of discriminating subtle changes in MHC expression on potential target cells. The molecular mechanisms controlling the cell-specific and probabilistic expression of these receptors are without doubt very complex. The traditional approach of considering a core promoter modulated by upstream enhancer elements is likely too simplistic a paradigm to adequately explain the regulation of these genes, as well as other gene clusters that are not expressed in an 'all or none' fashion. Our studies on the regulation of the mouse Ly49 and human killer immunoglobulin-like receptor (KIR) clusters of class I MHC receptor genes have revealed the presence of multiple transcripts in both sense and antisense orientations. In both systems, an antisense promoter overlaps a promoter that produces sense transcripts, creating a bidirectional element. In the Ly49 genes, the competing promoters behave as probabilistic switches, and it is likely that the human bidirectional promoters will have a similar property. The antisense transcripts generated in the Ly49 genes are far removed from the promoter responsible for Ly49 expression in mature NK cells, whereas the antisense KIR transcripts detected are within the adult promoter region. This finding suggests that the mechanism of promoter regulation in the KIR genes may be quite different from that of the Ly49 genes. This review summarizes the current state of knowledge regarding class I MHC receptor gene regulation. The models proposed for the control of the probabilistic expression of the Ly49 and KIR genes are discussed in the context of current knowledge regarding the complex control of other well-studied gene clusters such as the beta-globin and cytokine clusters.

Adoptively transferred Th1 cell populations lose IFNgamma+ cells by cytokine down-regulation on single-cell level

Against the background of effector T cell heterogenity in terms of their in situ cytokine expression, IFNgamma production has been argued to define distinct Th1 lineages: whereas IFNgamma- Th1 cells survive and differentiate in vivo, IFNgamma+ Th1 cells eventually undergo apoptosis. Alternatively, lineage commitment might not be directly associated with the actual IFNgamma production. To address this issue, we adoptively transferred in vitro-polarized Th1 cell populations. Although absolute numbers of total Th1 cells after 3 days in vivo remained unchanged, numbers of IFNgamma+ within the Th1 cells declined by approximately 50%. This was not affected by the initial frequencies of IFNgamma+ cells within the transferred Th1 cell populations and by the presence of the antigen. Arguing against positive selection of IFNgamma non-producers in vivo, cell division rates of IFNgamma+ and IFNgamma- Th1 cells were comparable. Our data suggest that the 'loss' of IFNgamma+ cells within the transferred Th1 cell population might be rather caused by down-regulation of the cytokine expression on single-cell level than by deletion of individual IFNgamma+ cells. Thus, our findings are more in line with the hypothesis that actual cytokine expression does not define distinct differentiation states and polarization-specific genes remain accessible also in IFNgamma- Th1 effector cells.

The interleukin-4 enhancer CNS-2 is regulated by Notch signals and controls initial expression in NKT cells and memory-type CD4 T cells

Epigenetic changes in chromatin structure at the T helper (Th2) locus correlate with interukin-4 (IL-4) and IL-13 expression during Th2 differentiation. By using a transgenic green fluorescence protein (GFP) reporter system, we show that conserved noncoding sequence-2 (CNS-2), located downstream of the Il4 locus, is a constitutively active enhancer in NKT cells as well as in a subset of CD44(hi) memory phenotype CD4+ T cells. CNS-2 enhancer activity and initial IL-4 expression in CD44(hi) CD4+ T cells were abolished in mice with a CD4-specific deletion of the transcriptional mediator of Notch signaling, Rbp-j. Depletion of CNS-2 active CD4+ T cells markedly decreased Th2 differentiation from naive CD4 T cells and antigen-specific IgE production after in vivo priming. These findings indicate that Notch-regulated CNS-2 enhancer controls initial IL-4 expression in NKT and memory phenotype CD4+ T cells and that CNS-2 active CD44(hi) memory phenotype T cells are important in facilitating Th2 differentiation of naive CD4+ T cells in allergic responses.

Regulation of Th2 differentiation and Il4 locus accessibility

Helper T cells coordinate immune responses through the production of cytokines. Th2 cells express the closely linked Il4, Il13, and Il5 cytokine genes, whereas these same genes are silenced in the Th1 lineage. The Th1/Th2 lineage choice has become a textbook example for the regulation of cell differentiation, and recent discoveries have further refined and expanded our understanding of how Th2 differentiation is initiated and reinforced by signals from antigen-presenting cells and cytokine-driven feedback loops. Epigenetic changes that stabilize the active or silent state of the Il4 locus in differentiating helper T cells have been a major focus of recent research. Overall, the field is progressing toward an integrated model of the signaling and transcription factor networks, cis-regulatory elements, epigenetic modifications, and RNA interference mechanisms that converge to determine the lineage fate and gene expression patterns of differentiating helper T cells.

T helper cell differentiation: regulation by cis elements and epigenetics

Cytokine loci undergo changes in chromatin structure when naive CD4(+) T cells differentiate into Th1 or Th2 cells and have also been examined for regulatory sequences underlying such changes and their functional correlates. Studies have shown that distal regulatory elements control the Ifng and Th2 cytokine loci and are primary targets for tissue-specific transcription factors, serving as centers for epigenetic changes that mark heritable traits in effector cells. Reports of intra- and, remarkably, interchromosomal interactions between these regulatory elements shed light on the mechanisms by which they regulate gene expression, revealing an extraordinary new picture that conceptually extends our views on how genes are regulated from two to three dimensions. Here, we summarize these recent findings on the role of regulatory elements and their mechanisms of action, which are of broad significance for gene regulation, not only of the immune system but also of many, if not all, coregulated genes.

Cutting edge: Itk-dependent signals required for CD4+ T cells to exert, but not gain, Th2 effector function

The TCR signals for the release of CD4 effector function are poorly understood. Itk plays an essential role in Th2, but not Th1, responses. However, when Itk is required during Th2 development is unclear. We followed the fate of Itk-deficient T cells during Th2 development in vitro and in vivo using an IL-4/GFP reporter. Surprisingly, a similar frequency of itk(-/-) CD4(+) cells differentiated and committed to the Th2 lineage as wild-type cells. However, Itk-deficient Th2 cells failed to exert effector function upon TCR triggering. Loss of function was marked by defective transcriptional enhancement of Th2 cytokines and GATA3. IL-4 production in itk(-/-) Th2s could be rescued by the expression of kinase-active Itk. Thus, Itk is necessary for the release, but not gain, of Th2 function. We suggest that the liberation of effector function is tightly controlled through qualitative changes in TCR signals, facilitating postdifferentiation regulation of cytokine responses.