Nathan D. Pennock

T cell responses: naïve to memory and everything in between

THE MAMMALIAN IMMUNE SYSTEM can be broadly divided into two main arms: innate and adaptive immunity. As its name implies, the cells and receptors of the innate immune system are critical for the rapid recognition of the infectious agent and initiating a proinflammatory response. While the inflammation generated by innate immune cells [neutrophils, macrophages, monocytes, natural killer (NK) cells, dendritic cells (DCs), etc.] is important in the initial containment of the infection, it also informs and directs the expansion and differentiation of adaptive immune cells. Responding to the inflammatory environment created by the innate response, cells of the adaptive arm of the immune response (B cells, T cells, and T cells) are stimulated to expand in number (proliferate) and to differentiate into cells with a range of functions appropriate for the immunological challenge. Upon elimination of the invading pathogen, the majority of adaptive cells die and leave behind an (evergrowing) array of memory cell subsets. These memory cells offer a diversity of migratory properties and functions, collectively mediating a rapid and protective immune response upon reinfection. Thus, the major advantages of an adaptive response to the host are twofold. First, it allows the host to form an immune response that is specifically tailored to the invading pathogen. Second, it forms a pool of memory cells from these specific effectors that can last for many years, capable of protecting the host against reinfection by their rapid response. This combination of specificity and memory are the mechanistic underpinnings for the clinical success of vaccination. Critical to almost all functions of the adaptive immune response is the activation and programming of T cells from their naive/resting state. Although there is much more to be learned, we now have a good basic understanding of the signals and cell types involved in the various stages of the T cell response initiated within the secondary lymphoid organs (SLOs). To provide a comprehensive overview, this review will summarize the T cell response broken down into three major stages: activation, differentiation, and memory formation. We will then assemble these components into a description of the anatomy of an immune response and its relationship to productive immune protection.

Disruption of the homeostatic balance between autoaggressive (CD4+CD40+) and regulatory (CD4+CD25+FoxP3+) T cells promotes diabetes

Although regulatory T cells (Tregs) are well described, identifying autoaggressive effector T cells has proven more difficult. However, we identified CD4loCD40+ (Th40) cells as being necessary and sufficient for diabetes in the NOD mouse model. Importantly, these cells are present in pancreata of prediabetic and diabetic NOD mice, and Th40 cells but not CD4+CD40– T cells transfer progressive insulitis and diabetes to NOD.scid recipients. Nonobese‐resistant (NOR) mice have the identical T cell developmental background as NOD mice, yet they are diabetes‐resistant. The seminal issue is how NOR mice remain tolerant to diabetogenic self‐antigens. We show here that autoaggressive T cells develop in NOR mice and are confined to the Th40 subset. However, NOR mice maintain Treg numbers equivalent to their Th40 numbers. NOD mice have statistically equal numbers of CD4+CD25+forkhead box P3+intrinsic Tregs compared with NOR or nonautoimmune BALB/c mice, and NOD Tregs are equally as suppressive as NOR Tregs. A critical difference is that NOD mice develop expanded numbers of Th40 cells. We suggest that a determinant factor for autoimmunity includes the Th40:Treg ratio. Mechanistically, NOD Th40 cells have low susceptibility to Fas‐induced cell death and unlike cells from NOR and BALB/c mice, have predominantly low Fas expression. CD40 engagement of Th40 cells induces Fas expression but further confers resistance to Fas‐mediated cell death in NOD mice. A second fundamental difference is that NOD Th40 cells undergo much more rapid homeostatic expansion than Th40 cells from NOR mice.

IL-27 is required for shaping the magnitude, affinity distribution, and memory of T cells responding to subunit immunization.

Significance Traditional immunizations involve the controlled introduction of attenuated bacteria or viruses, allowing for generation of immunity prior to exposure to the dangerous native pathogen. In contrast, subunit immunization utilizes only pieces of the pathogen combined with a separate immune stimulatory agent (adjuvant). Although subunit immunizations do generate effective neutralizing antibodies, they do not generate robust T-cell responses. T cells provide therapeutic benefit by directly inducing cell lysis and shaping the immune response through soluble proteins (cytokines) critical for intervening in cancer and viral infection. Here, we demonstrate that subunit vaccines are uniquely and unexpectedly dependent on the cytokine IL-27 for making strong T-cell responses. An elusive goal of cellular immune vaccines is the generation of large numbers of antigen-specific T cells in response to subunit immunization. A broad spectrum of cytokines and cell-surface costimulatory molecules are known to shape the programming, magnitude, and repertoire of T cells responding to vaccination. We show here that the majority of innate immune receptor agonist-based vaccine adjuvants unexpectedly depend on IL-27 for eliciting CD4+ and CD8+ T-cell responses. This is in sharp contrast to infectious challenge, which generates T-cell responses that are IL-27–independent. Mixed bone marrow chimera experiments demonstrate that IL-27 dependency is T cell-intrinsic, requiring T-cell expression of IL-27Rα. Further, we show that IL-27 dependency not only dictates the magnitude of vaccine-elicited T-cell responses but also is critical for the programming and persistence of high-affinity T cells to subunit immunization. Collectively, our data highlight the unexpected central importance of IL-27 in the generation of robust, high-affinity cellular immune responses to subunit immunization.

An analytical workflow for investigating cytokine profiles

Understanding cytokine profiles of disease states has provided researchers with great insight into immunologic signaling associated with disease onset and progression, affording opportunities for advancement in diagnostics and therapeutic intervention. Multiparameter flow cytometric assays support identification of specific cytokine secreting subpopulations. Bead‐based assays provide simultaneous measurement for the production of ever‐growing numbers of cytokines. These technologies demand appropriate analytical techniques to extract relevant information efficiently. We illustrate the power of an analytical workflow to reveal significant alterations in T‐cell cytokine expression patterns in type 1 diabetes (T1D) and breast cancer. This workflow consists of population‐level analysis, followed by donor‐level analysis, data transformation such as stratification or normalization, and a return to population‐level analysis. In the T1D study, T‐cell cytokine production was measured with a cytokine bead array. In the breast cancer study, intracellular cytokine staining measured T cell responses to stimulation with a variety of antigens. Summary statistics from each study were loaded into a relational database, together with associated experimental metadata and clinical parameters. Visual and statistical results were generated with custom Java software. In the T1D study, donor‐level analysis led to the stratification of donors based on unstimulated cytokine expression. The resulting cohorts showed statistically significant differences in poststimulation production of IL‐10, IL‐1β, IL‐8, and TNFβ. In the breast cancer study, the differing magnitude of cytokine responses required data normalization to support statistical comparisons. Once normalized, data showed a statistically significant decrease in the expression of IFNγ on CD4+ and CD8+ T cells when stimulated with tumor‐associated antigens (TAAs) when compared with an infectious disease antigen stimulus, and a statistically significant increase in expression of IL‐2 on CD8+ T cells. In conclusion, the analytical workflow described herein yielded statistically supported and biologically relevant findings that were otherwise unapparent.

The Discovery of a Reciprocal Relationship between Tyrosine-Kinase Signaling and Cullin Neddylation

While neddylation is known to activate cullin (CUL)-RING ubiquitin ligases (CRLs), its role in regulating T cell signaling is poorly understood. Using the investigational NEDD8 activating enzyme (NAE) inhibitor, MLN4924, we found that neddylation negatively regulates T cell receptor (TCR) signaling, as its inhibition increases IL-2 production, T cell proliferation and Treg development in vitro. We also discovered that loss of CUL neddylation occurs upon TCR signaling, and CRLs negatively regulate IL-2 production. Additionally, we found that tyrosine kinase signaling leads to CUL deneddylation in multiple cell types. These studies indicate that CUL neddylation is a global regulatory mechanism for tyrosine kinase signaling.

Clonal expansion of vaccine-elicited T cells is independent of aerobic glycolysis

T cell responses to subunit vaccination require both IL-27 and IL-15 to support an aerobic glycolysis–independent metabolic program. Mitochondria fuel vaccine-induced T cells Effective T cell responses to subunit vaccines administered with an adjuvant depend on a different set of signals than natural T cell responses to infectious microbes. Klarquist et al. compared the cytokine and metabolic requirements for clonal expansion of mouse CD8+ T cells responding to adjuvanted subunit vaccination or infection. In contrast to T cells responding to infection, T cells responding to vaccination were compromised in the absence of either IL-27 or IL-15 signaling and used mitochondrial function rather than aerobic glycolysis to support proliferation. These results demonstrate the existence of fundamental metabolic differences in CD8+ T cell responses to vaccines versus infection that need to be considered as part of the process of designing new vaccines. In contrast to responses against infectious challenge, T cell responses induced via adjuvanted subunit vaccination are dependent on interleukin-27 (IL-27). We show that subunit vaccine–elicited cellular responses are also dependent on IL-15, again in contrast to the infectious response. Early expression of interferon regulatory factor 4 (IRF4) was compromised in either IL-27– or IL-15–deficient environments after vaccination but not infection. Because IRF4 facilitates metabolic support of proliferating cells via aerobic glycolysis, we expected this form of metabolic activity to be reduced in the absence of IL-27 or IL-15 signaling after vaccination. Instead, metabolic flux analysis indicated that vaccine-elicited T cells used only mitochondrial function to support their clonal expansion. Loss of IL-27 or IL-15 signaling during vaccination resulted in a reduction in mitochondrial function, with no corresponding increase in aerobic glycolysis. Consistent with these observations, the T cell response to vaccination was unaffected by in vivo treatment with the glycolytic inhibitor 2-deoxyglucose, whereas the response to viral challenge was markedly lowered. Collectively, our data identify IL-27 and IL-15 as critical to vaccine-elicited T cell responses because of their capacity to fuel clonal expansion through a mitochondrial metabolic program previously thought only capable of supporting quiescent naïve and memory T cells.