Although the role of the T(H)1 and T(H)17 subsets of helper T cells as disease mediators in autoimmune neuroinflammation remains a subject of some debate, none of their signature cytokines are essential for disease development. Here we report that interleukin 23 (IL-23) and the transcription factor RORγt drove expression of the cytokine GM-CSF in helper T cells, whereas IL-12, interferon-γ (IFN-γ) and IL-27 acted as negative regulators. Autoreactive helper T cells specifically lacking GM-CSF failed to initiate neuroinflammation despite expression of IL-17A or IFN-γ, whereas GM-CSF secretion by Ifng(-/-)Il17a(-/-) helper T cells was sufficient to induce experimental autoimmune encephalomyelitis (EAE). During the disease effector phase, GM-CSF sustained neuroinflammation via myeloid cells that infiltrated the central nervous system. Thus, in contrast to all other known helper T cell-derived cytokines, GM-CSF serves a nonredundant function in the initiation of autoimmune inflammation regardless of helper T cell polarization.

Ever since its invention half a century ago, flow cytometry has been a major tool for single-cell analysis, fueling advances in our understanding of a variety of complex cellular systems, in particular the immune system. The last decade has witnessed significant technical improvements in available cytometry platforms, such that more than 20 parameters can be analyzed on a single-cell level by fluorescence-based flow cytometry. The advent of mass cytometry has pushed this limit up to, currently, 50 parameters. However, traditional analysis approaches for the resulting high-dimensional datasets, such as gating on bivariate dot plots, have proven to be inefficient. Although a variety of novel computational analysis approaches to interpret these datasets are already available, they have not yet made it into the mainstream and remain largely unknown to many immunologists. Therefore, this review aims at providing a practical overview of novel analysis techniques for high-dimensional cytometry data including SPADE, t-SNE, Wanderlust, Citrus, and PhenoGraph, and how these applications can be used advantageously not only for the most complex datasets, but also for standard 14-parameter cytometry datasets. Keywords: Citrus CyTOF Data analysis Flow cytometry Mass cytometry PSM PhenoGraph SPADE t-SNE WanderlustYear 2015 marked the 50-year anniversary of the publication of the first cell sorter, a device that was able to separate cells in suspension based on their difference in volume [1], as well as the first cytometry-based cell analyzer [2]. Shortly after that, the first sorter that could discriminate cells based on fluorescence was developed [3,4], and this seminal work marked the advent of flow cytometry as a widely used, single-cell analysis technique driving the identification of all major immune cell subsets known today [3,5] (for an overview, see Fig. 1, top). These days, many laboratories are equipped with flow cytometers capable of detecting 10-20 parameters [6], revealing an ever-increasing diversity within established cellular subsets, such as CD4 + T-helper cells or professional APCs. Quite recently, an alternative cytometry-based technique has been developed that relies on antibodies labeled with heavyCorrespondence: Prof. Burkhard Becher e-mail: becher@immunology.uzh.ch metal isotopes instead of fluorophores, detecting the resulting signals using a time-of-flight detector as is done in atomic mass spectrometers [7][8][9]. This method has been termed "mass cytometry" and became commercially known as the "CyTOF" (cytometry by time-of-flight), allowing the theoretical detection of more than 100 parameters per cell.While both fluorescence-based flow cytometry as well as mass cytometry provide a technological platform to interrogate the immune system at a previously unprecedented level (for a comparison of the two techniques see [10]), scientific progress depends on our ability to analyze and comprehend the resulting data in a meaningful way. Historically, flow cytometric data were-and still is-analyzed using a se...

Expansion and differentiation of antigen-experienced PD-1+TCF-1+ stem-like CD8+ T cells into effector cells is critical for the success of immunotherapies based on PD-1 blockade1–4. Hashimoto et al. have shown that, in chronic infections, administration of the cytokine interleukin (IL)-2 triggers an alternative differentiation path of stem-like T cells towards a distinct population of ‘better effector’ CD8+ T cells similar to those generated in an acute infection5. IL-2 binding to the IL-2 receptor α-chain (CD25) was essential in triggering this alternative differentiation path and expanding better effectors with distinct transcriptional and epigenetic profiles. However, constitutive expression of CD25 on regulatory T cells and some endothelial cells also contributes to unwanted systemic effects from IL-2 therapy. Therefore, engineered IL-2 receptor β- and γ-chain (IL-2Rβγ)-biased agonists are currently being developed6–10. Here we show that IL-2Rβγ-biased agonists are unable to preferentially expand better effector T cells in cancer models and describe PD1-IL2v, a new immunocytokine that overcomes the need for CD25 binding by docking in cis to PD-1. Cis binding of PD1-IL2v to PD-1 and IL-2Rβγ on the same cell recovers the ability to differentiate stem-like CD8+ T cells into better effectors in the absence of CD25 binding in both chronic infection and cancer models and provides superior efficacy. By contrast, PD-1- or PD-L1-blocking antibodies alone, or their combination with clinically relevant doses of non-PD-1-targeted IL2v, cannot expand this unique subset of better effector T cells and instead lead to the accumulation of terminally differentiated, exhausted T cells. These findings provide the basis for the development of a new generation of PD-1 cis-targeted IL-2R agonists with enhanced therapeutic potential for the treatment of cancer and chronic infections.

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Experimental cerebral malaria (ECM) is a gamma interferon (IFN-γ)-dependent syndrome. However, whether IFN-γ promotes ECM through direct and synergistic targeting of multiple cell populations or by acting primarily on a specific responsive cell type is currently unknown. Here, using a panel of cell- and compartment-specific IFN-γ receptor 2 (IFN-γR2)-deficient mice, we show that IFN-γ causes ECM by signaling within both the hematopoietic and nonhematopoietic compartments. Mechanistically, hematopoietic and nonhematopoietic compartment-specific IFN-γR signaling exerts additive effects in orchestrating intracerebral inflammation, leading to the development of ECM. Surprisingly, mice with specific deletion of IFN-γR2 expression on myeloid cells, T cells, or neurons were completely susceptible to terminal ECM. Utilizing a reductionist in vitro system, we show that synergistic IFN-γ and tumor necrosis factor (TNF) stimulation promotes strong activation of brain blood vessel endothelial cells. Combined, our data show that within the hematopoietic compartment, IFN-γ causes ECM by acting redundantly or by targeting non-T cell or non-myeloid cell populations. Within the nonhematopoietic compartment, brain endothelial cells, but not neurons, may be the major target of IFN-γ leading to ECM development. Collectively, our data provide information on how IFN-γ mediates the development of cerebral pathology during malaria infection.