Stochastic cytokine expression induces mixed T helper cell States

Differentiation and Regulation of Bovine Th2 Cells In Vitro

Bovine Th2 cells have usually been characterized by IL4 mRNA expression, but it is unclear whether their IL4 protein expression corresponds to transcription. We found that grass-fed healthy beef cattle, which had been regularly exposed to parasites on the grass, had a low frequency of IL4+ Th2 cells during flow cytometry, similar to animals grown in feedlots. To assess the distribution of IL4+ CD4+ T cells across tissues, samples from the blood, spleen, abomasal (draining), and inguinal lymph nodes were examined, which revealed limited IL4 protein detection in the CD4+ T cells across the examined tissues. To determine if bovine CD4+ T cells may develop into Th2 cells, naïve cells were stimulated with anti-bovine CD3 under a Th2 differentiation kit in vitro. The cells produced primarily IFNγ proteins, with only a small fraction (<10%) co-expressing IL4 proteins. Quantitative PCR confirmed elevated IFNγ transcription but no significant change in IL4 transcription. Surprisingly, GATA3, the master regulator of IL4, was highest in naïve CD4+ T cells but was considerably reduced following differentiation. To determine if the differentiated cells were true Th2 cells, an unbiased proteomic assay was carried out. The assay identified 4212 proteins, 422 of which were differently expressed compared to those in naïve cells. Based on these differential proteins, Th2-related upstream components were predicted, including CD3, CD28, IL4, and IL33, demonstrating typical Th2 differentiation. To boost IL4 expression, T cell receptor (TCR) stimulation strength was reduced by lowering anti-CD3 concentrations. Consequently, weak TCR stimulation essentially abolished Th2 expansion and survival. In addition, extra recombinant bovine IL4 (rbIL4) was added during Th2 differentiation, but, despite enhanced expansion, the IL4 level remained unaltered. These findings suggest that, while bovine CD4+ T cells can respond to Th2 differentiation stimuli, the bovine IL4 pathway is not regulated in the same way as in mice and humans. Furthermore, Ostertagia ostertagi (OO) extract, a gastrointestinal nematode in cattle, inhibited signaling via CD3, CD28, IL4, and TLRs/MYD88, indicating that external pathogens can influence bovine Th2 differentiation. In conclusion, though bovine CD4+ T cells can respond to IL4-driven differentiation, IL4 expression is not a defining feature of differentiated bovine Th2 cells.

Probing T-cell activation in nanoliter tumor co-cultures using membrane displacement trap arrays

Immune responses against cancer are inherently stochastic, with small numbers of individual T cells within a larger ensemble of lymphocytes initiating the molecular cascades that lead to tumor cytotoxicity. A potential source of this intra-tumor variability is the differential ability of immune cells to respond to tumor cells. Classical microwell co-cultures of T cells and tumor cells are inadequate for reliably culturing and analyzing low cell numbers needed to probe this variability, and have failed in recapitulating the heterogeneous small domains observed in tumors. Here we leverage a membrane displacement trap array technology that overcomes limitations of conventional microwell plates for immunodynamic studies. The microfluidic platform supports on-demand formation of dense nanowell cultures under continuous perfusion reflecting the tumor microenvironment, with real-time monitoring of T cell proliferation and activation within each nanowell. The system enables selective ejection of cells for profiling by fluorescence activated cell sorting, allowing observed on-chip variability in immune response to be correlated with off-chip quantification of T cell activation. The technology offers new potential for probing the molecular origins of T cell heterogeneity and identifying specific cell phenotypes responsible for initiating and propagating immune cascades within tumors. Insight Box Variability in T cell activation plays a critical role in the immune response against cancer. New tools are needed to unravel the mechanisms that drive successful anti-tumor immune response, and to support the development of novel immunotherapies utilizing rare T cell phenotypes that promote effective immune surveillance. To this end, we present a microfluidic cell culture platform capable of probing differential T cell activation in an array of nanoliter-scale wells coupled with off-chip cell analysis, enabling a high resolution view of variable immune response within tumor / T cell co-cultures containing cell ensembles orders of magnitude smaller than conventional well plate studies.

Single-cell analysis reveals TLR-induced macrophage heterogeneity and quorum sensing dictate population wide anti-inflammatory feedback in response to LPS

The role of macrophages in controlling tissue inflammation is indispensable to ensure a context-appropriate response to pathogens whilst preventing excessive tissue damage. Their initial response is largely characterized by high production of tumor necrosis factor alpha (TNFα) which primes and attracts other immune cells, thereafter, followed by production of interleukin 10 (IL-10) which inhibits cell activation and steers towards resolving of inflammation. This delicate balance is understood at a population level but how it is initiated at a single-cell level remains elusive. Here, we utilize our previously developed droplet approach to probe single-cell macrophage activation in response to toll-like receptor 4 (TLR4) stimulation, and how single-cell heterogeneity and cellular communication affect macrophage-mediated inflammatory homeostasis. We show that only a fraction of macrophages can produce IL-10 in addition to TNFα upon LPS-induced activation, and that these cells are not phenotypically different from IL-10 non-producers nor exhibit a distinct transcriptional pathway. Finally, we demonstrate that the dynamics of TNFα and IL-10 are heavily controlled by macrophage density as evidenced by 3D hydrogel cultures suggesting a potential role for quorum sensing. These exploratory results emphasize the relevance of understanding the complex communication between macrophages and other immune cells and how these amount to population-wide responses.

Dissecting the dynamic transcriptional landscape of early T helper cell differentiation into Th1, Th2, and Th1/2 hybrid cells

Selective differentiation of CD4+ T helper (Th) cells into specialized subsets such as Th1 and Th2 cells is a key element of the adaptive immune system driving appropriate immune responses. Besides those canonical Th-cell lineages, hybrid phenotypes such as Th1/2 cells arise in vivo, and their generation could be reproduced in vitro. While master-regulator transcription factors like T-bet for Th1 and GATA-3 for Th2 cells drive and maintain differentiation into the canonical lineages, the transcriptional architecture of hybrid phenotypes is less well understood. In particular, it has remained unclear whether a hybrid phenotype implies a mixture of the effects of several canonical lineages for each gene, or rather a bimodal behavior across genes. Th-cell differentiation is a dynamic process in which the regulatory factors are modulated over time, but longitudinal studies of Th-cell differentiation are sparse. Here, we present a dynamic transcriptome analysis following Th-cell differentiation into Th1, Th2, and Th1/2 hybrid cells at 3-h time intervals in the first hours after stimulation. We identified an early bifurcation point in gene expression programs, and we found that only a minority of ~20% of Th cell-specific genes showed mixed effects from both Th1 and Th2 cells on Th1/2 hybrid cells. While most genes followed either Th1- or Th2-cell gene expression, another fraction of ~20% of genes followed a Th1 and Th2 cell-independent transcriptional program associated with the transcription factors STAT1 and STAT4. Overall, our results emphasize the key role of high-resolution longitudinal data for the characterization of cellular phenotypes.

The evolution of powerful yet perilous immune systems

The mammalian immune system packs serious punch against infection but can also cause harm: for example, coronavirus disease 2019 (COVID-19) made headline news of the simultaneous power and peril of human immune responses. In principle, natural selection leads to exquisite adaptation and therefore cytokine responsiveness that optimally balances the benefits of defense against its costs (e.g., immunopathology suffered and resources expended). Here, we illustrate how evolutionary biology can predict such optima and also help to explain when/why individuals exhibit apparently maladaptive immunopathological responses. Ultimately, we argue that the evolutionary legacies of multicellularity and life-history strategy, in addition to our coevolution with symbionts and our demographic history, together explain human susceptibility to overzealous, pathology-inducing cytokine responses. Evolutionary insight thereby complements molecular/cellular mechanistic insights into immunopathology.

Differential expression profile of gluten-specific T cells identified by single-cell RNA-seq

Gluten-specific CD4⁺ T cells drive the pathogenesis of celiac disease and circulating gluten-specific T cells can be identified by staining with HLA-DQ:gluten tetramers. In this first single-cell RNA-seq study of tetramer-sorted T cells from untreated celiac disease patients blood, we found that gluten-specific T cells showed distinct transcriptomic profiles consistent with activated effector memory T cells that shared features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in T-cell receptor signaling, translational processes, apoptosis, fatty acid transport, and redox potentials. Many of the gluten-specific T cells studied shared T-cell receptor with each other, indicating that circulating gluten-specific T cells belong to a limited number of clones. Moreover, the transcriptional profiles of cells that shared the same clonal origin were transcriptionally more similar compared with between clonally unrelated gluten-specific cells.

RNA transport from transcription to localized translation: a single molecule perspective

Transport of mRNAs is an important step of gene expression, which brings the genetic message from the DNA in the nucleus to a precise cytoplasmic location in a regulated fashion. Perturbation of this process can lead to pathologies such as developmental and neurological disorders. In this review, we discuss recent advances in the field of mRNA transport made using single molecule fluorescent imaging approaches. We present an overview of these approaches in fixed and live cells and their input in understanding the key steps of mRNA journey: transport across the nucleoplasm, export through the nuclear pores and delivery to its final cytoplasmic location. This review puts a particular emphasis on the coupling of mRNA transport with translation, such as localization-dependent translational regulation and translation-dependent mRNA localization. We also highlight the recently discovered translation factories, and how cellular and viral RNAs can hijack membrane transport systems to travel in the cytoplasm.

The Causes and Consequences of Spatial Organization of the Genome in Regulation of Gene Expression

Regulation of gene expression in time, space and quantity is orchestrated by the functional interplay of cis-acting elements and trans-acting factors. Our current view postulates that transcription factors recognize enhancer DNA and read the transcriptional regulatory code by cooperative DNA binding to specific DNA motifs, thus instructing the recruitment of transcriptional regulatory complexes forming a plethora of higher-ordered multi-protein-DNA and protein-protein complexes. Here, we reviewed the formation of multi-dimensional chromatin assemblies implicated in gene expression with emphasis on the regulatory role of enhancer hubs as coordinators of stochastic gene expression. Enhancer hubs contain many interacting regulatory elements and represent a remarkably dynamic and heterogeneous network of multivalent interactions. A functional consequence of such complex interaction networks could be that individual enhancers function synergistically to ensure coordination, tight control and robustness in regulation of expression of spatially connected genes. In this review, we discuss fundamental paradigms of such inter- and intra- chromosomal associations both in the context of immune-related genes and beyond.

Potential Landscapes, Bifurcations, and Robustness of Tristable Networks

Bistable switches that produce all-or-none responses have been found to regulate a number of natural cellular decision making processes, and subsequently synthetic switches were designed to exploit their potential. However, an increasing number of studies, particularly in the context of cellular differentiation, highlight the existence of a mixed state that can be explained by tristable switches. The criterion for designing robust tristable switches still remains to be understood from the perspective of network topology. To address such a question, we calculated the robustness of several 2- and 3-component network motifs, connected via only two positive feedback loops, in generating tristable signal response curves. By calculating the effective potential landscape and following its modifications with the bifurcation parameter, we constructed one-parameter bifurcation diagrams of these models in a high-throughput manner for a large combinations of parameters. We report here that introduction of a self-activatory positive feedback loop, directly or indirectly, into a mutual inhibition loop leads to generating the most robust tristable response. The high-throughput approach of our method further allowed us to determine the robustness of four types of tristable responses that originate from the relative locations of four bifurcation points. Using the method, we also analyzed the role of additional mutual inhibition loops in stabilizing the mixed state.

Single-Cell Transcriptome Profiling of Immune Cell Repertoire of the Atlantic Cod Which Naturally Lacks the Major Histocompatibility Class II System

The Atlantic cod’s unusual immune system, entirely lacking the Major Histocompatibility class II pathway, has prompted intriguing questions about what mechanisms are used to combat bacterial infections and how immunological memory is generated. By single-cell RNA sequencing we here report an in-depth characterisation of cell types found in immune tissues, the spleen and peripheral blood leukocytes of Atlantic cod. Unbiased transcriptional clustering revealed eleven distinct immune cell signatures. Resolution at the single cell level enabled characterisation of the major cell subsets including the cytotoxic T cells, B cells, erythrocytes, thrombocytes, neutrophils, and macrophages. Additionally, to our knowledge we are the first to uncover cell subsets in Atlantic cod which may represent dendritic cells, natural killer-like cells, and a population of cytotoxic cells expressing GATA-3, a master transcription factor of T helper 2 cells. We further identify putative gene markers for each cluster and describe the relative proportions of each cell type in the spleen and peripheral blood leukocytes. Of the major haematopoietic cell populations, the lymphocytes make up 55 and 68% of the spleen and peripheral blood leukocytes respectively, while the myeloid cells make up 45 and 32%. By single-cell analysis, this study provides the most detailed molecular and cellular characterisation of the immune system of the Atlantic cod so far.

Multi-stability in cellular differentiation enabled by a network of three mutually repressing master regulators

Identifying the design principles of complex regulatory networks driving cellular decision-making remains essential to decode embryonic development as well as enhance cellular reprogramming. A well-studied network motif involved in cellular decision-making is a toggle switch-a set of two opposing transcription factors A and B, each of which is a master regulator of a specific cell fate and can inhibit the activity of the other. A toggle switch can lead to two possible states-(high A, low B) and (low A, high B)-and drives the 'either-or' choice between these two cell fates for a common progenitor cell. However, the principles of coupled toggle switches remain unclear. Here, we investigate the dynamics of three master regulators A, B and C inhibiting each other, thus forming three-coupled toggle switches to form a toggle triad. Our simulations show that this toggle triad can lead to co-existence of cells into three differentiated 'single positive' phenotypes-(high A, low B, low C), (low A, high B, low C) and (low A, low B, high C). Moreover, the hybrid or 'double positive' phenotypes-(high A, high B, low C), (low A, high B, high C) and (high A, low B, high C)-can coexist together with 'single positive' phenotypes. Including self-activation loops on A, B and C can increase the frequency of 'double positive' states. Finally, we apply our results to understand cellular decision-making in terms of differentiation of naive CD4⁺ T cells into Th1, Th2 and Th17 states, where hybrid Th1/Th2 and hybrid Th1/Th17 cells have been reported in addition to the Th1, Th2 and Th17 ones. Our results offer novel insights into the design principles of a multi-stable network topology and provide a framework for synthetic biology to design tristable systems.

Quorum sensing via dynamic cytokine signaling comprehensively explains divergent patterns of effector choice among helper T cells

In the animal kingdom, various forms of swarming enable groups of autonomous individuals to transform uncertain information into unified decisions which are probabilistically beneficial. Crossing scales from individual to group decisions requires dynamically accumulating signals among individuals. In striking parallel, the mammalian immune system is also a group of decentralized autonomous units (i.e. cells) which collectively navigate uncertainty with the help of dynamically accumulating signals (i.e. cytokines). Therefore, we apply techniques of understanding swarm behavior to a decision-making problem in the mammalian immune system, namely effector choice among CD4+ T helper (Th) cells. We find that incorporating dynamic cytokine signaling into a simple model of Th differentiation comprehensively explains divergent observations of this process. The plasticity and heterogeneity of individual Th cells, the tunable mixtures of effector types that can be generated in vitro, and the polarized yet updateable group effector commitment often observed in vivo are all explained by the same set of underlying molecular rules. These rules reveal that Th cells harness dynamic cytokine signaling to implement a system of quorum sensing. Quorum sensing, in turn, may confer adaptive advantages on the mammalian immune system, especially during coinfection and during coevolution with manipulative parasites. This highlights a new way of understanding the mammalian immune system as a cellular swarm, and it underscores the power of collectives throughout nature.

A Darwinian and Physical Look at Stem Cell Biology Helps Understanding the Role of Stochasticity in Development

Single-cell analysis allows biologists to gain huge insight into cell differentiation and tissue structuration. Randomness of differentiation, both in vitro and in vivo, of pluripotent (multipotent) stem cells is now demonstrated to be mainly based on stochastic gene expression. Nevertheless, it remains necessary to incorporate this inherent stochasticity of developmental processes within a coherent scheme. We argue here that the theory called ontophylogenesis is more relevant and better fits with experimental data than alternative theories which have been suggested based on the notions of self-organization and attractor states. The ontophylogenesis theory considers the generation of a differentiated state as a constrained random process: randomness is provided by the stochastic dynamics of biochemical reactions while the environmental constraints, including cell inner structures and cell-cell interactions, drive the system toward a stabilized state of equilibrium. In this conception, biological organization during development can be seen as the result of multiscale constraints produced by the dynamical organization of the biological system which retroacts on the stochastic dynamics at lower scales. This scheme makes it possible to really understand how the generation of reproducible structures at higher organization levels can be fully compatible with probabilistic behavior at the lower levels. It is compatible with the second law of thermodynamics but allows the overtaking of the limitations exhibited by models only based on entropy exchanges which cannot cope with the description nor the dynamics of the mesoscopic and macroscopic organization of biological systems.

Modes of Communication between T Cells and Relevance for Immune Responses

T cells are essential mediators of the adaptive immune system, which constantly patrol the body in search for invading pathogens. During an infection, T cells that recognise the pathogen are recruited, expand and differentiate into subtypes tailored to the infection. In addition, they differentiate into subsets required for short and long-term control of the pathogen, i.e., effector or memory. T cells have a remarkable degree of plasticity and heterogeneity in their response, however, their overall response to a given infection is consistent and robust. Much research has focused on how individual T cells are activated and programmed. However, in order to achieve a critical level of population-wide reproducibility and robustness, neighbouring cells and surrounding tissues have to provide or amplify relevant signals to tune the overall response accordingly. The characteristics of the immune response-stochastic on the individual cell level, robust on the global level-necessitate coordinated responses on a system-wide level, which facilitates the control of pathogens, while maintaining self-tolerance. This global coordination can only be achieved by constant cellular communication between responding cells, and faults in this intercellular crosstalk can potentially lead to immunopathology or autoimmunity. In this review, we will discuss how T cells mount a global, collective response, by describing the modes of T cell-T cell (T-T) communication they use and highlighting their physiological relevance in programming and controlling the T cell response.

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.

Challenges in measuring and understanding biological noise

Biochemical reactions are intrinsically stochastic, leading to variation in the production of mRNAs and proteins within cells. In the scientific literature, this source of variation is typically referred to as 'noise'. The observed variability in molecular phenotypes arises from a combination of processes that amplify and attenuate noise. Our ability to quantify cell-to-cell variability in numerous biological contexts has been revolutionized by recent advances in single-cell technology, from imaging approaches through to 'omics' strategies. However, defining, accurately measuring and disentangling the stochastic and deterministic components of cell-to-cell variability is challenging. In this Review, we discuss the sources, impact and function of molecular phenotypic variability and highlight future directions to understand its role.

Single-Cell RNA Sequencing of the T Helper Cell Response to House Dust Mites Defines a Distinct Gene Expression Signature in Airway Th2 Cells

Naive CD4⁺ T cells differentiate into functionally diverse T helper (Th) cell subsets. Th2 cells play a pathogenic role in asthma, yet a clear picture of their transcriptional profile is lacking. We performed single-cell RNA sequencing (scRNA-seq) of T helper cells from lymph node, lung, and airways in the house dust mite (HDM) model of allergic airway disease. scRNA-seq resolved transcriptional profiles of naive CD4⁺ T, Th1, Th2, regulatory T (Treg) cells, and a CD4⁺ T cell population responsive to type I interferons. Th2 cells in the airways were enriched for transcription of many genes, including Cd200r1, Il6, Plac8, and Igfbp7, and their mRNA profile was supported by analysis of chromatin accessibility and flow cytometry. Pathways associated with lipid metabolism were enriched in Th2 cells, and experiments with inhibitors of key metabolic pathways supported roles for glucose and lipid metabolism. These findings provide insight into the differentiation of pathogenic Th2 cells in the context of allergy.

Single-cell Analysis of CAR-T Cell Activation Reveals A Mixed TH1/TH2 Response Independent of Differentiation

The activation mechanism of chimeric antigen receptor (CAR)-engineered T cells may differ substantially from T cells carrying native T cell receptor, but this difference remains poorly understood. We present the first comprehensive portrait of single-cell level transcriptional and cytokine signatures of anti-CD19/4-1BB/CD28/CD3ζ CAR-T cells upon antigen-specific stimulation. Both CD4⁺ helper T (T_H) cells and CD8⁺ cytotoxic CAR-T cells are equally effective in directly killing target tumor cells and their cytotoxic activity is associated with the elevation of a range of T_H1 and T_H2 signature cytokines, e.g., interferon γ, tumor necrotic factor α, interleukin 5 (IL5), and IL13, as confirmed by the expression of master transcription factor genes TBX21 and GATA3. However, rather than conforming to stringent T_H1 or T_H2 subtypes, single-cell analysis reveals that the predominant response is a highly mixed T_H1/T_H2 function in the same cell. The regulatory T cell activity, although observed in a small fraction of activated cells, emerges from this hybrid T_H1/T_H2 population. Granulocyte-macrophage colony stimulating factor (GM-CSF) is produced from the majority of cells regardless of the polarization states, further contrasting CAR-T to classic T cells. Surprisingly, the cytokine response is minimally associated with differentiation status, although all major differentiation subsets such as naïve, central memory, effector memory, and effector are detected. All these suggest that the activation of CAR-engineered T cells is a canonical process that leads to a highly mixed response combining both type 1 and type 2 cytokines together with GM-CSF, supporting the notion that polyfunctional CAR-T cells correlate with objective response of patients in clinical trials. This work provides new insights into the mechanism of CAR activation and implies the necessity for cellular function assays to characterize the quality of CAR-T infusion products and monitor therapeutic responses in patients.

Cis-activation in the Notch signaling pathway

The Notch signaling pathway consists of transmembrane ligands and receptors that can interact both within the same cell (cis) and across cell boundaries (trans). Previous work has shown that cis-interactions act to inhibit productive signaling. Here, by analyzing Notch activation in single cells while controlling cell density and ligand expression level, we show that cis-ligands can also activate Notch receptors. This cis-activation process resembles trans-activation in its ligand level dependence, susceptibility to cis-inhibition, and sensitivity to Fringe modification. Cis-activation occurred for multiple ligand-receptor pairs, in diverse cell types, and affected survival in neural stem cells. Finally, mathematical modeling shows how cis-activation could potentially expand the capabilities of Notch signaling, for example enabling ‘negative’ (repressive) signaling. These results establish cis-activation as an additional mode of signaling in the Notch pathway, and should contribute to a more complete understanding of how Notch signaling functions in developmental, physiological, and biomedical contexts.

Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology

Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long-term control of infection while also preventing an over-zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro- and anti-inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host-directed therapies.

Exploring intermediate cell states through the lens of single cells

As our catalog of cell states expands, appropriate characterization of these states and the transitions between them is crucial. Here we discuss the roles of intermediate cell states (ICSs) in this growing collection. We begin with definitions and discuss evidence for the existence of ICSs and their relevance in various tissues. We then provide a list of possible functions for ICSs with examples. Finally, we describe means by which ICSs and their functional roles can be identified from single-cell data or predicted from models.

A cellular and molecular view of T helper 17 cell plasticity in autoimmunity

Since the original identification of the T helper 17 (Th17) subset in 2005, it has become evident that these cells do not only contribute to host defence against pathogens, such as bacteria and fungi, but that they are also critically involved in the pathogenesis of many autoimmune diseases. In contrast to the classic Th1 and Th2 cells, which represent rather stably polarized subsets, Th17 cells display remarkable heterogeneity and plasticity. This has been attributed to the characteristics of the key transcription factor that guides Th17 differentiation, retinoic acid receptor-related orphan nuclear receptor gamma (RORγ). Unlike the 'master regulators' T-bet and GATA3 that orchestrate Th1 and Th2 differentiation, respectively, RORγ controls transcription at relatively few loci in Th17 cells. Moreover, its expression is not stabilized by positive feedback loops but rather influenced by environmental cues, allowing for substantial functional plasticity. Importantly, a subset of IL-17/IFNγ double-producing Th17 cells was identified in both human and mouse models. Evidence is accumulating that these IL-17/IFNγ double-producing cells are pathogenic drivers in autoimmune diseases, including rheumatoid arthritis, multiple sclerosis and inflammatory bowel disease. In addition, IL-17/IFNγ double-producing cells have been identified in disorders in which the role of autoimmunity remains unclear, such as sarcoidosis. The observed plasticity of Th17 cells towards the Th1 phenotype can be explained by extensive epigenetic priming of the IFNG locus in Th17 cells. In fact, Th17 cells display an IFNG chromatin landscape that is remarkably similar to that of Th1 cells. On the other hand, pathogenic capabilities of Th17 cells can be restrained by stimulating IL-10 production and transdifferentiation into IL-10 producing T regulatory type 1 (Tr1) cells. In this review, we discuss recent advances in our knowledge on the cellular and molecular mechanisms involved in Th17 differentiation, heterogeneity and plasticity. We focus on transcriptional regulation of the Th17 expression program, the epigenetic dynamics involved, and how genetic variants associated with autoimmunity may affect immune responses through distal gene regulatory elements. Finally, the implications of Th17 cell plasticity for the pathogenesis and treatment of human autoimmune diseases will be discussed.

T-cell immunology in sarcoidosis: Disruption of a delicate balance between helper and regulatory T-cells

PURPOSE OF REVIEW

Although the aetiology of sarcoidosis is not yet completely understood, immunological changes within the T-cell compartment are characteristic for an exaggerated antigen-driven immune response. In this review, we describe the most recent findings on T-cell subset responses and regulation in sarcoidosis. We discuss how future immunological research can advance the field to unravel pathobiological mechanisms of this intriguingly complex disease.

RECENT FINDINGS

Research into the field of T-cell plasticity has recently challenged the long-held T helper type 1 (Th1) paradigm in sarcoidosis and striking parallels with autoimmune disorders and common variable immunodeficiency were recognized. For instance, it was demonstrated that Th17.1-cells rather than Th1-cells are responsible for the exaggerated IFN-γ production in pulmonary sarcoidosis. Furthermore, impaired regulatory T-cell function and alterations within the expression of co-inhibitory receptors that control T-cell responses, such as PD-1, CTLA-4 and BTNL2, raise new questions regarding T-cell regulation in pulmonary sarcoidosis.

SUMMARY

It becomes increasingly clear that Th17(.1)-cells and regulatory T-cells are key players in sarcoidosis T-cell immunology. New findings on plasticity and co-inhibitory receptor expression by these subsets help build a more comprehensive model for T-cell regulation in sarcoidosis and will finally shed light on the potential of new treatment modalities.

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.

SINCERITIES: inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles

Motivation

Single cell transcriptional profiling opens up a new avenue in studying the functional role of cell-to-cell variability in physiological processes. The analysis of single cell expression profiles creates new challenges due to the distributive nature of the data and the stochastic dynamics of gene transcription process. The reconstruction of gene regulatory networks (GRNs) using single cell transcriptional profiles is particularly challenging, especially when directed gene-gene relationships are desired.

Results

We developed SINCERITIES (SINgle CEll Regularized Inference using TIme-stamped Expression profileS) for the inference of GRNs from single cell transcriptional profiles. We focused on time-stamped cross-sectional expression data, commonly generated from transcriptional profiling of single cells collected at multiple time points after cell stimulation. SINCERITIES recovers directed regulatory relationships among genes by employing regularized linear regression (ridge regression), using temporal changes in the distributions of gene expressions. Meanwhile, the modes of the gene regulations (activation and repression) come from partial correlation analyses between pairs of genes. We demonstrated the efficacy of SINCERITIES in inferring GRNs using in silico time-stamped single cell expression data and single cell transcriptional profiles of THP-1 monocytic human leukemia cells. The case studies showed that SINCERITIES could provide accurate GRN predictions, significantly better than other GRN inference algorithms such as TSNI, GENIE3 and JUMP3. Moreover, SINCERITIES has a low computational complexity and is amenable to problems of extremely large dimensionality. Finally, an application of SINCERITIES to single cell expression data of T2EC chicken erythrocytes pointed to BATF as a candidate novel regulator of erythroid development.

Availability and implementation

MATLAB and R version of SINCERITIES are freely available from the following websites: http://www.cabsel.ethz.ch/tools/sincerities.html and https://github.com/CABSEL/SINCERITIES. The single cell THP-1 and T2EC transcriptional profiles are available from the original publications (Kouno et al., 2013; Richard et al., 2016). The in silico single cell data are available on SINCERITIES websites.

Supplementary information

Supplementary data are available at Bioinformatics online.

Diverse continuum of CD4+ T-cell states is determined by hierarchical additive integration of cytokine signals

During cell differentiation, progenitor cells integrate signals from their environment that guide their development into specialized phenotypes. The ways by which cells respond to complex signal combinations remain difficult to analyze and model. To gain additional insight into signal integration, we systematically mapped the response of CD4⁺ T cells to a large number of input cytokine combinations that drive their differentiation. We find that, in response to varied input combinations, cells differentiate into a continuum of cell fates as opposed to a limited number of discrete phenotypes. Input cytokines hierarchically influence the cell population, with TGFβ being most dominant followed by IL-6 and IL-4. Mathematical modeling explains these results using additive signal integration within hierarchical groups of input cytokine combinations and correctly predicts cell population response to new input conditions. These findings suggest that complex cellular responses can be effectively described using a segmented linear approach, providing a framework for prediction of cellular responses to new cytokine combinations and doses, with implications to fine-tuned immunotherapies.

Human amnion favours tissue repair by inducing the M1-to-M2 switch and enhancing M2 macrophage features

Human amniotic mesenchymal cells (hAMTCs) possess interesting immunomodulatory properties, making them attractive candidates for regenerative medicine applications. Recent in vivo reports argue in favour of an important role for macrophages as targets of hAMTC‐mediated suppression of inflammation and the enhancement of tissue repair. However, a comprehensive study of the effects of hAMTCs and their conditioned medium (CM) on human macrophage differentiation and function is unavailable. In the present study we found that hAMTCs and CM induce the differentiation of myeloid cells (U937 and monocytes) towards macrophages. We then investigated their effects on monocytes differentiated toward pro‐inflammatory M1 and anti‐inflammatory M2 macrophages. Monocytes treated under M1 conditions in the presence of hAMTCs or CMs shifted towards M2‐like macrophages, which expressed CD14, CD209, CD23, CD163 and PM‐2 K, possessed higher phagocytic activity and produced higher IL‐10 and lower pro‐inflammatory cytokines. They were also poor T cell stimulators and Th1 inducers, while they were able to increase activated and naïve suppressive Treg subsets. We show that prostaglandins, and not IL‐6, play a role in determining the M2 activation status. Instead, monocytes treated under M2 conditions in the presence of hAMTCs or CM retained M2‐like features, but with an enhanced anti‐inflammatory profile, having a reduced expression of the co‐stimulatory molecule CD80, reduced phagocytosis activity and decreased the secretion of inflammatory chemokines. Importantly, we provide evidence that macrophages re‐educated by CM improve tissue regeneration/repair in wound‐healing models. In conclusion, we identified new cell targets of hAMTCs and their bioactive factors and here provide insight into the beneficial effects observed when these cells are used in therapeutic approaches in vivo. © 2016 The Authors Journal of Tissue Engineering and Regenerative Medicine Published by John Wiley & Sons Ltd.

Single Cell Analysis Reveals Concomitant Transcription of Pluripotent and Lineage Markers During the Early Steps of Differentiation of Embryonic Stem Cells

The differentiation of embryonic stem cells is associated with extensive changes in gene expression. It is not yet clear whether these changes are the result of binary switch-like mechanisms or that of continuous and progressive variation. Here, I have used immunostaining and single molecule RNA fluorescence in situ hybridization (FISH) to assess changes in the expression of the well-known pluripotency-associated gene Pou5f1 (also known as Oct4) and early differentiation markers Sox1 and T-brachyury in single cells during the early steps of differentiation of mouse embryonic stem cells. I found extensive overlap between the expression of Pou5f1/Sox1 or Pou5f1/T-brachyury shortly after the initiation of differentiation towards either the neuronal or the mesendodermal lineage, but no evidence of correlation between their respective expression levels. Quantitative analysis of transcriptional output at the sites of nascent transcription revealed that Pou5f1 and Sox1 were transcribed in pulses and that embryonic stem cell differentiation was accompanied by changes in pulsing frequencies. The progressive induction of Sox1 was further associated with an increase in the average size of individual transcriptional bursts. Surprisingly, single cells that actively and simultaneously transcribe both the pluripotency- and the lineage-associated genes could easily be found in the differentiating population. The results presented here show for the first time that lineage priming can occur in cells that are actively transcribing a pluripotent marker. Furthermore, they suggest that this process is associated with changes in transcriptional dynamics.

Signaling in T cells - is anything the m(a)TOR with the picture(s)?

The excitement surrounding checkpoint inhibitors in the treatment of patients with cancer exemplifies a triumph of the long-term value of investing in basic science and fundamental questions of T-cell signaling. The pharmaceutical future actively embraces ways of making more patients’ cancers responsive to these inhibitors. Such a process will be aided by elucidation of signaling and regulation. With thousands of articles spread across almost 30 years, this commentary can touch only on portions of the canonical picture of T-cell signaling and provide a few parables from work on mammalian (or mechanistic) target of rapamycin (mTOR) pathways as they link to early and later phases of lymphocyte activation. The piece will turn a critical eye to some issues with models about these pathways in T cells. Many of the best insights lie in the future despite all that is uncovered already, but a contention is that further therapeutic successes will be fostered by dealing with disparities among findings and attention to the temporal, spatial, and stochastic aspects of T-cell responses. Finally, thoughts on some (though not all) items urgently needed for future progress will be mooted.

Single-cell technologies to study the immune system

The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single‐cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single‐cell technologies, their limitations and future applications to study the immune system.

Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function

There is a growing appreciation of the extent of transcriptome variation across individual cells of the same cell type. While expression variation may be a byproduct of, for example, dynamic or homeostatic processes, here we consider whether single-cell molecular variation per se might be crucial for population-level function. Under this hypothesis, molecular variation indicates a diversity of hidden functional capacities within an ensemble of identical cells, and this functional diversity facilitates collective behavior that would be inaccessible to a homogenous population. In reviewing this topic, we explore possible functions that might be carried by a heterogeneous ensemble of cells; however, this question has proven difficult to test, both because methods to manipulate molecular variation are limited and because it is complicated to define, and measure, population-level function. We consider several possible methods to further pursue the hypothesis that variation is function through the use of comparative analysis and novel experimental techniques.

Avidity of human T cell receptor engineered CD4(+) T cells drives T-helper differentiation fate

The role of the T cell receptor (TCR) in antigen recognition and activation of T lymphocytes is well established. However, how the TCR affects T-helper differentiation/skewing is less well understood, particularly for human CD4(+) (CD4) T cell subsets. Here we investigate the role of TCR specific antigen avidity in differentiation and maintenance of human Th1, Th2 and Th17 subsets. Two human TCRs, both specific for the same peptide antigen but with different avidities, were cloned and expressed in human CD4 T cells. These TCR engineered cells were then stimulated with specific antigen in unskewed and T-helper skewed conditions. We show that TCR avidity can control the percentage of IL-4 and IFN-γ co-expression in unskewed TCR engineered cells, that effector function can be maintained in a TCR avidity-dependent manner in skewed TCR engineered cells, and that increased TCR avidity can accelerate Th1 skewing of TCR engineered cells.

[Randomness and cell fate]

Thermal fluctuations at the molecular scale cause random fluctuations of gene expression, which, in association with differentiation circuits, can lead to phenotypic diversification in cell populations. In this synthesis article, we detail the mechanisms that generate this diversification and illustrate their consequences in various organisms. In bacteria, random phenotypic diversification allows to anticipate environmental changes that are otherwise unpredictable, in particular during metabolic transitions and stress responses, for example inducing a transient form of antibiotic resistance. In multi-cellular organisms, similar mechanisms allow the maintenance of healthy tissues, such as intestinal crypts, epidermis and retina, but also seem to play a role in establishment and renewal of tumoral heterogeneity.

A Mathematical Framework for Understanding Four-Dimensional Heterogeneous Differentiation of CD4+ T Cells

At least four distinct lineages of CD4+ T cells play diverse roles in the immune system. Both in vivo and in vitro, naïve CD4+ T cells often differentiate into a variety of cellular phenotypes. Previously, we developed a mathematical framework to study heterogeneous differentiation of two lineages governed by a mutual-inhibition motif. To understand heterogeneous differentiation of CD4+ T cells involving more than two lineages, we present here a mathematical framework for the analysis of multiple stable steady states in dynamical systems with multiple state variables interacting through multiple mutual-inhibition loops. A mathematical model for CD4+ T cells based on this framework can reproduce known properties of heterogeneous differentiation involving multiple lineages of this cell differentiation system, such as heterogeneous differentiation of TH1-TH2, TH1-TH17 and iTReg-TH17 under single or mixed types of differentiation stimuli. The model shows that high concentrations of differentiation stimuli favor the formation of phenotypes with co-expression of lineage-specific master regulators.

GATA-3 function in innate and adaptive immunity

The zinc-finger transcription factor GATA-3 has received much attention as a master regulator of T helper 2 (Th2) cell differentiation, during which it controls interleukin-4 (IL-4), IL-5, and IL-13 expression. More recently, GATA-3 was shown to contribute to type 2 immunity through regulation of group 2 innate lymphoid cell (ILC2) development and function. Furthermore, during thymopoiesis, GATA-3 represses B cell potential in early T cell precursors, activates TCR signaling in pre-T cells, and promotes the CD4(+) T cell lineage after positive selection. GATA-3 also functions outside the thymus in hematopoietic stem cells, regulatory T cells, CD8(+) T cells, thymic natural killer cells, and ILC precursors. Here we discuss the varied functions of GATA-3 in innate and adaptive immune cells, with emphasis on its activity in T cells and ILCs, and examine the mechanistic basis for the dose-dependent, developmental-stage- and cell-lineage-specific activity of this transcription factor.

Insufficient interleukin-12 signalling favours differentiation of human CD4(+) and CD8(+) T cells into GATA-3(+) and GATA-3(+) T-bet(+) subsets in humanized mice

Differentiation of CD4(+) T cells into type 1 or type 2 subsets is mediated by the expression of the opposing lineage defining transcription factors T-bet and GATA-3. However, the existence of GATA-3(+) T-bet(+) CD4(+) T cells in mice suggests functional plasticity of these subsets. Little is known about type 1 and type 2 plasticity of human T-cell subsets in vivo. Here, we show that in the xenogeneic environment of humanized mice, which lacks a functional immune-regulatory network, human CD4(+) and, notably, CD8(+) T cells preferentially differentiate into interleukin (IL)-4(+) GATA-3(+) and IL-4(+) interferon-γ(+) GATA-3(+) T-bet(+) subsets. Treatment with recombinant human IL-12 or expansion of IL-12-producing human dendritic cells in vivo reverted this phenotype and led to the down-regulation of GATA-3 expression. These changes also correlated with improved antiviral immune responses in humanized mice. In conclusion, our study shows the capacity of human CD4(+) and CD8(+) T cells for stable co-expression of GATA-3 and T-bet in humanized mice and reveals a critical role for IL-12 in regulating this phenotype.

Stochastic variations of migration speed between cells in clonal populations

We combined microfluidic tools and molecular probes to monitor the migration speed of successive generations of cancer cells. We found that the migratory speed of individual cells changes stochastically from parent cells to their descendants, while the average speed of successive generations of cells remains constant. Further studies of the interrelations between cell migration and division processes may help identify the molecular determinants of cell speed and lead to new therapies to slow the invasion of cancer cells and delay metastases.

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.

Noise in multiple sclerosis: unwanted and necessary

As our knowledge about the etiology of multiple sclerosis (MS) increases, deterministic paradigms appear insufficient to describe the pathogenesis of the disease, and the impression is that stochastic phenomena (i.e. random events not necessarily resulting in disease in all individuals) may contribute to the development of MS. However, sources and mechanisms of stochastic behavior have not been investigated and there is no proposed framework to incorporate nondeterministic processes into disease biology. In this report, we will first describe analogies between physics of nonlinear systems and cell biology, showing how small-scale random perturbations can impact on large-scale phenomena, including cell function. We will then review growing and solid evidence showing that stochastic gene expression (or gene expression “noise”) can be a driver of phenotypic variation. Moreover, we will describe new methods that open unprecedented opportunities for the study of such phenomena in patients and the impact of this information on our understanding of MS course and therapy.

Single-cell RNA-seq reveals dynamic paracrine control of cellular variation

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript's level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a 'core' module of antiviral genes is expressed very early by a few 'precocious' cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced 'peaked' inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.

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.

Secreting and sensing the same molecule allows cells to achieve versatile social behaviors

Cells that secrete and sense the same signaling molecule are ubiquitous. To uncover the functional capabilities of the core "secrete-and-sense" circuit motif shared by these cells, we engineered yeast to secrete and sense the mating pheromone. Perturbing each circuit element revealed parameters that control the degree to which the cell communicated with itself versus with its neighbors. This tunable interplay of self-communication and neighbor communication enables cells to span a diverse repertoire of cellular behaviors. These include a cell being asocial by responding only to itself and social through quorum sensing, and an isogenic population of cells splitting into social and asocial subpopulations. A mathematical model explained these behaviors. The versatility of the secrete-and-sense circuit motif may explain its recurrence across species.

Stable T-bet(+)GATA-3(+) Th1/Th2 hybrid cells arise in vivo, can develop directly from naive precursors, and limit immunopathologic inflammation

The stable lineage commitment of naïve T helper cells to a hybrid Th1/2 phenotype reveals the cell-intrinsic reconciliation of two opposing T cell differentiation programs and provides a self-limiting mechanism to dampen immunopathology.

Differentiated T helper (Th) cell lineages are thought to emerge from alternative cell fate decisions. However, recent studies indicated that differentiated Th cells can adopt mixed phenotypes during secondary immunological challenges. Here we show that natural primary immune responses against parasites generate bifunctional Th1 and Th2 hybrid cells that co-express the lineage-specifying transcription factors T-bet and GATA-3 and co-produce Th1 and Th2 cytokines. The integration of Th1-promoting interferon (IFN)-γ and interleukin (IL)-12 signals together with Th2-favoring IL-4 signals commits naive Th cells directly and homogeneously to the hybrid Th1/2 phenotype. Specifically, IFN-γ signals are essential for T-bet⁺GATA-3⁺ cells to develop in vitro and in vivo by breaking the dominance of IL-4 over IL-12 signals. The hybrid Th1/2 phenotype is stably maintained in memory cells in vivo for months. It resists reprogramming into classic Th1 or Th2 cells by Th1- or Th2-promoting stimuli, which rather induce quantitative modulations of the combined Th1 and Th2 programs without abolishing either. The hybrid phenotype is associated with intermediate manifestations of both Th1 and Th2 cell properties. Consistently, hybrid Th1/2 cells support inflammatory type-1 and type-2 immune responses but cause less immunopathology than Th1 and Th2 cells, respectively. Thus, we propose the self-limitation of effector T cells based on the stable cell-intrinsic balance of two opposing differentiation programs as a novel concept of how the immune system can prevent excessive inflammation.

T helper (Th) cells, a subgroup of white blood cells important in the immune system, can differentiate into diverse lineages, for example Th1 and Th2, whose effector mechanisms target different types of pathogens but cause problems if not properly regulated. Lineage commitment is driven by cytokine signals that control the expression of distinct lineage-specifying “master regulator” transcription factor molecules. Lineage commitment is thought to reflect alternative cell-fate decisions because the initiated differentiation programs have self-amplifying and mutually repressive features. Here we show that the Th1 and Th2 differentiation programs are more compatible with each other than previously thought. Individual naive T cells can simultaneously integrate Th1- and Th2-polarizing signals and develop into hybrid Th1/2 cells that stably co-express both the Th1 master regulator T-bet and the Th2 master regulator GATA-3. We find that hybrid Th1/2 cells arise naturally during parasite infections and that the two opposing differentiation programs can stably co-exist in resting memory Th1/2 cells for periods of months. Th1- or Th2-polarizing stimuli induced quantitative modulations in the hybrid state but did not extinguish either program. The cell-intrinsic antagonism gives the hybrid Th1/2 cells properties that are quantitatively intermediate between those of Th1 and Th2 cells. Thus, in typical Th1 and Th2 immune responses, hybrid Th1/2 cells cause less immunopathology than their classic Th1 or Th2 counterparts, demonstrating a cell-intrinsic self-limiting mechanism that can prevent excessive inflammation.

Hybrid T-helper cells: stabilizing the moderate center in a polarized system

Polarization of cell phenotypes, a common strategy to achieve cell type diversity in metazoa, results from binary cell-fate decisions in the branching pedigree of development. Such "either-or" fate decisions are controlled by two opposing cell fate-determining transcription factors. Each of the two distinct "master regulators" promotes differentiation of its respective sister lineage. But they also suppress one other, leading to their mutually exclusive expression in the two ensuing lineages. Thus, promiscuous coexistence of the antagonist regulators in the same cell, the hallmark of the common "undecided" progenitor of two sister lineages, is considered unstable. This antagonism ensures robust polarization into two discretely distinct cell types. But now the immune system's T-helper (Th) cells and their two canonical subtypes, Th1 and Th2 cells, tell a different story, as revealed in three papers recently published in PLOS Biology. The intermediate state that co-expresses the two opposing master regulators of the Th1 and Th2 subtypes, T-bet and Gata3, is highly stable and is not necessarily an undecided precursor. Instead, the Th1/Th2 hybrid cell is a robust new type with properties of both Th1 and Th2 cells. These hybrid cells are functionally active and possess the benefit of moderation: self-limitation of effector T cell function to prevent excessive inflammation, a permanent risk in host defense that can cause tissue damage or autoimmunity. Gene regulatory network analysis suggests that stabilization of the intermediate center in a polarizing system can be achieved by minor tweaking of the architecture of the mutual suppression gene circuit, and thus is a design option readily available to evolution.

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.