The physician scientist: balancing clinical and research duties.

Physician scientists bridge the gap between biomedical research and clinical practice. However, the continuing decrease in number of people who choose this career path poses a threat to the advancement of biomedical science and the translation of research findings to clinical practice.

Alternatively Spliced Variants of Murine CD247 Influence T Cell Development and Activation, Revealing the Importance of the CD3ζ C-Terminal Region.

CD247, also known as CD3ζ, is a crucial signaling molecule that transduces signals delivered by TCR through its three ITAMs. CD3ζ is required for successful thymocyte development. Three additional alternatively spliced variants of murine CD247 have been described, that is, CD3ι, CD3θ, and CD3η, that differ from CD3ζ in the C terminus such that the third ITAM is lost. Previous studies demonstrated defects in T cell development in mice expressing CD3η, but the TCR signaling pathways affected by CD3η and the impacts of the CD3ι and CD3θ on T cell development were not explored. In this study, we used a retrovirus-mediated gene transfer technique to express these three isoforms individually and examined the roles of them on T cell development and activation. Rag1-/- mice reconstituted with CD3θ-expressing bone marrow failed to develop mature T cells. CD3ι-expressing T cells exhibited similar development and activation as cells expressing CD3ζ. In contrast, thymic development was severely impaired in CD3η-reconstituted mice. Single-positive but not double-positive CD3η-expressing thymocytes had reduced TCR expression, and CD5 expression was decreased at the double-positive stage, suggesting a defect in positive selection. Peripheral CD3η-expressing T cells had expanded CD44hi populations and upregulation of exhaustion markers seen by flow cytometry and RNA sequencing analysis. Analysis of early signaling events demonstrated significantly reduced activation of both the PLCγ1 and Akt/mTOR signaling pathways. There was also a reduction in the frequency of activation of CD3η-expressing T cells. These studies reveal the importance of the CD3ζ C-terminal region in T cell development and activation.

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes.

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.

TCR Signal Strength Regulates Akt Substrate Specificity To Induce Alternate Murine Th and T Regulatory Cell Differentiation Programs.

The Akt/mTOR pathway is a key driver of murine CD4+ T cell differentiation, and induction of regulatory T (Treg) cells results from low TCR signal strength and low Akt/mTOR signaling. However, strong TCR signals induce high Akt activity that promotes Th cell induction. Yet, it is unclear how Akt controls alternate T cell fate decisions. We find that the strength of the TCR signal results in differential Akt enzymatic activity. Surprisingly, the Akt substrate networks associated with T cell fate decisions are qualitatively different. Proteomic profiling of Akt signaling networks during Treg versus Th induction demonstrates that Akt differentially regulates RNA processing and splicing factors to drive T cell differentiation. Interestingly, heterogeneous nuclear ribonucleoprotein (hnRNP) L or hnRNP A1 are Akt substrates during Treg induction and have known roles in regulating the stability and splicing of key mRNAs that code for proteins in the canonical TCR signaling pathway, including CD3ζ and CD45. Functionally, inhibition of Akt enzymatic activity results in the dysregulation of splicing during T cell differentiation, and knockdown of hnRNP L or hnRNP A1 results in the lower induction of Treg cells. Together, this work suggests that a switch in substrate specificity coupled to the phosphorylation status of Akt may lead to alternative cell fates and demonstrates that proteins involved with alternative splicing are important factors in T cell fate decisions.

Differential T-cell receptor signals for T helper cell programming.

Upon encounter with their cognate antigen, naive CD4 T cells become activated and are induced to differentiate into several possible T helper (Th) cell subsets. This differentiation depends on a number of factors including antigen-presenting cells, cytokines and co-stimulatory molecules. The strength of the T-cell receptor (TCR) signal, related to the affinity of TCR for antigen and antigen dose, has emerged as a dominant factor in determining Th cell fate. Recent studies have revealed that TCR signals of high or low strength do not simply induce quantitatively different signals in the T cells, but rather qualitatively distinct pathways can be induced based on TCR signal strength. This review examines the recent literature in this area and highlights important new developments in our understanding of Th cell differentiation and TCR signal strength.

Demystifying the cytokine network: Mathematical models point the way.

Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed.

Cutting Edge: Differential Regulation of PTEN by TCR, Akt, and FoxO1 Controls CD4+ T Cell Fate Decisions.

Signaling via the Akt/mammalian target of rapamycin pathway influences CD4(+) T cell differentiation; low levels favor regulatory T cell induction and high levels favor Th induction. Although the lipid phosphatase phosphatase and tensin homolog (PTEN) suppresses Akt activity, the control of PTEN activity is poorly studied in T cells. In this study, we identify multiple mechanisms that regulate PTEN expression. During Th induction, PTEN function is suppressed via lower mRNA levels, lower protein levels, and an increase in C-terminal phosphorylation. Conversely, during regulatory T cell induction, PTEN function is maintained through the stabilization of PTEN mRNA transcription and sustained protein levels. We demonstrate that differential Akt/mammalian target of rapamycin signaling regulates PTEN transcription via the FoxO1 transcription factor. A mathematical model that includes multiple modes of PTEN regulation recapitulates our experimental findings and demonstrates how several feedback loops determine differentiation outcomes. Collectively, this work provides novel mechanistic insights into how differential regulation of PTEN controls alternate CD4(+) T cell fate outcomes.

Oxidative stress-induced inhibition of Sirt1 by caveolin-1 promotes p53-dependent premature senescence and stimulates the secretion of interleukin 6 (IL-6).

Oxidative stress can induce premature cellular senescence. Senescent cells secrete various growth factors and cytokines, such as IL-6, that can signal to the tumor microenvironment and promote cancer cell growth. Sirtuin 1 (Sirt1) is a class III histone deacetylase that regulates a variety of physiological processes, including senescence. We found that caveolin-1, a structural protein component of caveolar membranes, is a direct binding partner of Sirt1, as shown by the binding of the scaffolding domain of caveolin-1 (amino acids 82-101) to the caveolin-binding domain of Sirt1 (amino acids 310-317). Our data show that oxidative stress promotes the sequestration of Sirt1 into caveolar membranes and the interaction of Sirt1 with caveolin-1, which lead to inhibition of Sirt1 activity. Reactive oxygen species stimulation promotes acetylation of p53 and premature senescence in wild-type but not caveolin-1 null mouse embryonic fibroblasts (MEFs). Either down-regulation of Sirt1 expression or re-expression of caveolin-1 in caveolin-1 null MEFs restores reactive oxygen species-induced acetylation of p53 and premature senescence. In addition, overexpression of caveolin-1 induces stress induced premature senescence in p53 wild-type but not p53 knockout MEFs. Phosphorylation of caveolin-1 on tyrosine 14 promotes the sequestration of Sirt1 into caveolar membranes and activates p53/senescence signaling. We also identified IL-6 as a caveolin-1-specific cytokine that is secreted by senescent fibroblasts following the caveolin-1-mediated inhibition of Sirt1. The caveolin-1-mediated secretion of IL-6 by senescent fibroblasts stimulates the growth of cancer cells. Therefore, by inhibiting Sirt1, caveolin-1 links free radicals to the activation of the p53/senescence pathway and the protumorigenic properties of IL-6.

Low TCR signal strength induces combined expansion of Th2 and regulatory T cell populations that protect mice from the development of type 1 diabetes.

AIMS/HYPOTHESIS: Weak stimulation of CD4(+) T cells induces expansion of CD4(+) forkhead box P3(+) regulatory T cells (Tregs) and can also promote T helper (Th) 2 responses, which have demonstrable beneficial effects on autoimmune diabetes. This study explored the feasibility of combined Treg/Th2 expansion for immunotherapy of type 1 diabetes in NOD mice. METHODS: We compared Treg and Th responses to dendritic cells (DC) presenting scaled antigen doses to islet-specific NOD CD4(+) T cells. Flow cytometric and Luminex analyses were performed to determine the phenotype and cytokine profile of expanded T cells. The ability of expanded T cells to prevent type 1 diabetes was tested in an adoptive transfer model. RESULTS: In vitro studies revealed a hierarchical, selective expansion of Treg and T effector (Teff) populations at different antigen doses. Thus, a single low dose produced a mixture of Tregs Th2 and type 1 regulatory (Tr1) cells, which prevented diabetes in NOD-SCID mice and increased the ratio of Treg/Teff cells infiltrating the pancreatic islets. Subcutaneous injection of DC, previously shown to prevent diabetes in NOD mice, induced expansion of the same mixture of Tregs Tr1 and Th2 cells. Low-dose expansion of Treg required MHC-T cell receptor interaction and was partly dependent on T cell derived TGF-ß and IL-2. Autocrine IFN-γ was required for the promotion of diabetogenic Th1 cells at high antigen doses. CONCLUSIONS/INTERPRETATION: Weak stimulation of CD4(+) T cells with DC and low-dose antigen expands a combination of antigen-specific Tregs Th2 and Tr1 cells that prevent autoimmunity, without the need to target or purify specific Treg populations.

An immunology primer for computational modelers.

The immune system is designed to protect an organism from infection and damage caused by a pathogen. A successful immune response requires the coordinated function of multiple cell types and molecules in the innate and adaptive immune systems. Given the complexity of the immune system, it would be advantageous to build computational models to better understand immune responses and develop models to better guide the design of immunotherapies. Often, researchers with strong quantitative backgrounds do not have formal training in immunology. Therefore, the goal of this review article is to provide a brief primer on cellular immunology that is geared for computational modelers.

Modeling the T cell immune response: a fascinating challenge.

The immune system is designed to protect the organism from infection and to repair damaged tissue. An effective response requires recognition of the threat, the appropriate effector mechanism to clear the pathogen and a return to homeostasis with minimal damage to self-tissues. T cells play a central role in orchestrating the immune response at all stages of the response and have been the subject of intense study by both experimental immunologists and modelers. This review examines some of the more critical questions in T cell biology and describes the latest attempts to address those questions using approaches that combine mathematical modeling and experiments.

Phosphorylation of hnRNP A1-Serine 199 Is Not Required for T Cell Differentiation and Function.

hnRNP A1 is an important RNA-binding protein that influences many stages of RNA processing, including transcription, alternative splicing, mRNA nuclear export, and RNA stability. However, the role of hnRNP A1 in immune cells, specifically CD4+ T cells, remains unclear. We previously showed that Akt phosphorylation of hnRNP A1 was dependent on TCR signal strength and was associated with Treg differentiation. To explore the impact of hnRNP A1 phosphorylation by Akt on CD4+ T cell differentiation, our laboratory generated a mutant mouse model, hnRNP A1-S199A (A1-MUT) in which the major Akt phosphorylation site on hnRNP A1 was mutated to alanine using CRISPR Cas9 technology. Immune profiling of A1-MUT mice revealed changes in the numbers of Tregs in the mesenteric lymph node. We found no significant differences in naive CD4+ T cell differentiation into Th1, Th2, Th17, or T regulatory cells (Tregs) in vitro. In vivo, Treg differentiation assays using OTII-A1-Mut CD4+ T cells exposed to OVA food revealed migration and homing defects in the A1-MUT but no change in Treg induction. A1-MUT mice were immunized with NP- keyhole limpet hemocyanin, and normal germinal center development, normal numbers of NP-specific B cells, and no change in Tfh numbers were observed. In conclusion, Akt phosphorylation of hnRNP A1 S199 does not play a role in CD4+ T cell fate or function in the models tested. This hnRNP A1-S199A mouse model should be a valuable tool to study the role of Akt phosphorylation of hnRNP A1-S199 in different cell types or other mouse models of human disease.

Recent insights into the role of Akt in CD4 T-cell activation and differentiation: alternative splicing and beyond.

The activation and differentiation of CD4+ T cells is a complex process that is controlled by many factors. A critical component of the signaling pathway triggered following T-cell receptor (TCR) engagement is the serine threonine kinase Akt. Akt is involved in the control of many cellular processes including proliferation, metabolism, and differentiation of specific TH-cell subsets. Recent work has shown that, depending on the nature or strength of the TCR activation, Akt may activate different sets of substrates which then lead to differential cellular outcomes. Akt plays an important role in controlling the strength of the TCR signal and several recent studies have identified novel mechanisms including control of the expression of negative regulators of TCR signaling, and the influence on regulatory T cells (Treg) and TH17 differentiation. Many of these functions are mediated via control of the FoxO family of transcription factors, that play an important role in metabolism and Th cell differentiation. A theme that is emerging is that Akt does not function in the same way in all T-cell types. We highlight differences between CD4 and CD8 T cells as well as between Treg, TH17, and TFH cells. While Akt activity has been implicated in the control of alternative splicing in tumor cells, recent studies are emerging that indicate that similar functions may exist in CD4 T cells. In this mini review, we highlight some of the recent advances in these areas of Akt function that demonstrate the varied role that Akt plays in the function of CD4 T cells.

Synergism Between IL21 and Anti-PD-1 Combination Therapy is Underpinned by the Coordinated Reprogramming of the Immune Cellular Network in the Tumor Microenvironment.

T cell-stimulating cytokines and immune checkpoint inhibitors (ICI) are an ideal combination for increasing response rates of cancer immunotherapy. However, the results of clinical trials have not been satisfying. It is important to understand the mechanism of synergy between these two therapeutic modalities. Here, through integrated analysis of multiple single-cell RNA sequencing (scRNA-seq) datasets of human tumor-infiltrating immune cells, we demonstrate that IL21 is produced by tumor-associated T follicular helper cells and hyperactivated/exhausted CXCL13+CD4+ T cells in the human tumor microenvironment (TME). In the mouse model, the hyperactivated/exhausted CD4+ T cell-derived IL21 enhances the helper function of CD4+ T cells that boost CD8+ T cell-mediated immune responses during PD-1 blockade immunotherapy. In addition, we demonstrated that IL21's antitumor activity did not require T-cell trafficking. Using scRNA-seq analysis of the whole tumor-infiltrating immune cells, we demonstrated that IL21 treatment in combination with anti-PD-1 blockade synergistically drives tumor antigen-specific CD8+ T cells to undergo clonal expansion and differentiate toward the hyperactive/exhausted functional state in the TME. In addition, IL21 treatment and anti-PD-1 blockade synergistically promote dendritic cell (DC) activation and maturation to mature DC as well as monocyte to type 1 macrophage (M1) differentiation in the TME. Furthermore, the combined treatment reprograms the immune cellular network by reshaping cell-cell communication in the TME. Our study establishes unique mechanisms of synergy between IL21 and PD-1-based ICI in the TME through the coordinated promotion of type 1 immune responses. Significance: This study reveals how cytokine and checkpoint inhibitor therapy can be combined to increase the efficacy of cancer immunotherapy.

GATA-3 up-regulation in CD8+ T cells as a biomarker of immune dysfunction in systemic sclerosis, resulting in excessive interleukin-13 production.

OBJECTIVE: Despite the importance of interleukin-13 (IL-13) in systemic sclerosis (SSc) and other fibrotic diseases, its mechanisms of action are not understood. We have reported that excessive amounts of IL-13 are produced by peripheral blood effector CD8+ T cells from patients with diffuse cutaneous SSc (dcSSc). The aim of the present study was to establish the molecular basis of IL-13 dysregulation in the pathogenesis of SSc. METHODS: Quantitative polymerase chain reaction analysis and intracellular staining were used to study the transcription factors that control naive peripheral blood CD8+ T cell differentiation into type 1 and type 2 cytokine-secreting cells. Intracellular staining revealed that GATA-3 levels in freshly isolated naive CD8+ T cells correlated with specific clinical manifestations. We therefore assessed the effects of GATA-3 inhibition on IL-13 production in CD8+ T cells from the SSc patients. RESULTS: Freshly isolated naive peripheral blood CD8+ T cells expressed high levels of GATA-3 and failed to down-regulate IL-13 production when cultured under type 1-skewing conditions, but maintained adequate levels of interferon-γ production. Cellular GATA-3 levels were significantly higher in patients with dcSSc and early inflammatory disease. Silencing of GATA-3 with small interfering RNA significantly reduced IL-13 production by CD8+ T cells, demonstrating a causal relationship between GATA-3 and IL-13. CONCLUSION: These results provide important new insights into SSc pathogenesis and suggest that increased GATA-3 expression in CD8+ T cells could be a highly relevant biomarker of immune dysfunction in patients with dcSSc. GATA-3 could be a novel therapeutic target for this currently incurable disease.

In Science Journals.

Highlights from the Science family of journals.

Dominant role of antigen dose in CD4+Foxp3+ regulatory T cell induction and expansion.

The definitions of tolerogenic vs immunogenic dendritic cells (DC) remain controversial. Immature DC have been shown to induce T regulatory cells (Treg) specific for foreign and allogeneic Ags. However, we have previously reported that mature DC (mDC) prevented the onset of autoimmune diabetes, whereas immature DC (iDC) were therapeutically ineffective. In this study, islet-specific CD4(+) T cells from BDC2.5 TCR-transgenic mice were stimulated in the absence of exogenous cytokine with iDC or mDC pulsed with high- or low-affinity antigenic peptides and examined for Treg induction. Both iDC and mDC presenting low peptide doses induced weak TCR signaling via the Akt/mammalian target of rapamycin (mTOR) pathway, resulting in significant expansion of Foxp3(+) Treg. Furthermore, unpulsed mDC, but not iDC, also induced Treg. High peptide doses induced strong Akt/mTOR signaling and favored the expansion of Foxp3(neg) Th cells. The inverse correlation of Foxp3 and Akt/mTOR signaling was also observed in DO11.10 and OT-II TCR-transgenic T cells and was recapitulated with anti-CD3/CD28 stimulation in the absence of DC. IL-6 production in these cultures correlated positively with Ag dose and inversely with Treg expansion. Studies with T cells or DC from IL-6(-/-) mice revealed that IL-6 production by T cells was more important in the inhibition of Treg induction at low Ag doses. These studies indicate that the strength of Akt/mTOR signaling, a critical T cell-intrinsic determinant for Treg vs Th induction, can be controlled by adjusting the dose of antigenic peptide. Furthermore, this operates in a dominant fashion over DC phenotype and cytokine production.

Hematopoietic cell types: prototype for a revised cell ontology.

The Cell Ontology (CL) aims for the representation of in vivo and in vitro cell types from all of biology. The CL is a candidate reference ontology of the OBO Foundry and requires extensive revision to bring it up to current standards for biomedical ontologies, both in its structure and its coverage of various subfields of biology. We have now addressed the specific content of one area of the CL, the section of the ontology dealing with hematopoietic cells. This section has been extensively revised to improve its content and eliminate multiple inheritance in the asserted hierarchy, and the groundwork has been laid for structuring the hematopoietic cell type terms as cross-products incorporating logical definitions built from relationships to external ontologies, such as the Protein Ontology and the Gene Ontology. The methods and improvements to the CL in this area represent a paradigm for improvement of the entire ontology over time.

COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes.

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results indicate that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8 + T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation. AUTHOR SUMMARY: Understanding of how the immune system responds to SARS-CoV-2 infections is critical for improving diagnostic and treatment approaches. Identifying which immune mechanisms lead to divergent outcomes can be clinically difficult, and experimental models and longitudinal data are only beginning to emerge. In response, we developed a mechanistic, mathematical and computational model of the immunopathology of COVID-19 calibrated to and validated against a broad set of experimental and clinical immunological data. To study the drivers of severe COVID-19, we used our model to expand a cohort of virtual patients, each with realistic disease dynamics. Our results identify key processes that regulate the immune response to SARS-CoV-2 infection in virtual patients and suggest viable therapeutic targets, underlining the importance of a rational approach to studying novel pathogens using intra-host models.