Graft-versus-host disease, but not graft-versus-leukemia immunity, is mediated by GM-CSF–licensed myeloid cells

Allogeneic hematopoietic cell transplantation (allo-HCT) not only is an effective treatment for several hematologic malignancies but can also result in potentially life-threatening graft-versus-host disease (GvHD). GvHD is caused by T cells within the allograft attacking nonmalignant host tissues; however, these same T cells mediate the therapeutic graft-versus-leukemia (GvL) response. Thus, there is an urgent need to understand how to mechanistically uncouple GvL from GvHD. Using preclinical models of full and partial MHC-mismatched HCT, we here show that the granulocyte-macrophage colony-stimulating factor (GM-CSF) produced by allogeneic T cells distinguishes between the two processes. GM-CSF drives GvHD pathology by licensing donor-derived phagocytes to produce inflammatory mediators such as interleukin-1β and reactive oxygen species. In contrast, GM-CSF did not affect allogeneic T cells or their capacity to eliminate leukemic cells, retaining undiminished GvL responses. Last, tissue biopsies and peripheral blood mononuclear cells from patients with grade IV GvHD showed an elevation of GM-CSF–producing T cells, suggesting that GM-CSF neutralization has translational potential in allo-HCT

MicroRNA-31 Reduces the Motility of Proinflammatory T Helper 1 Lymphocytes

Proinflammatory type 1 T helper (Th1) cells are enriched in inflamed tissues and contribute to the maintenance of chronic inflammation in rheumatic diseases. Here we show that the microRNA- (miR-) 31 is upregulated in murine Th1 cells with a history of repeated reactivation and in memory Th cells isolated from the synovial fluid of patients with rheumatic joint disease. Knock-down of miR-31 resulted in the upregulation of genes associated with cytoskeletal rearrangement and motility and induced the expression of target genes involved in T cell activation, chemokine receptor– and integrin-signaling. Accordingly, inhibition of miR-31 resulted in increased migratory activity of repeatedly activated Th1 cells. The transcription factors T-bet and FOXO1 act as positive and negative regulators of T cell receptor (TCR)–mediated miR-31 expression, respectively. Taken together, our data show that a gene regulatory network involving miR-31, T-bet, and FOXO1 controls the migratory behavior of proinflammatory Th1 cells

Selective targeting of pro-inflammatory Th1 cells by microRNA-148a-specific antagomirs in vivo.

In T lymphocytes, expression of miR-148a is induced by T-bet and Twist1, and is specific for pro-inflammatory Th1 cells. In these cells, miR-148a inhibits the expression of the pro-apoptotic protein Bim and promotes their survival. Here we use sequence-specific cholesterol-modified oligonucleotides against miR-148a (antagomir-148a) for the selective elimination of pro-inflammatory Th1 cells in vivo. In the murine model of transfer colitis, antagomir-148a treatment reduced the number of pro-inflammatory Th1 cells in the colon of colitic mice by 50% and inhibited miR-148a expression by 71% in the remaining Th1 cells. Expression of Bim protein in colonic Th1 cells was increased. Antagomir-148a-mediated reduction of Th1 cells resulted in a significant amelioration of colitis. The effect of antagomir-148a was selective for chronic inflammation. Antigen-specific memory Th cells that were generated by an acute immune reaction to nitrophenylacetyl-coupled chicken gamma globulin (NP-CGG) were not affected by treatment with antagomir-148a, both during the effector and the memory phase. In addition, antibody titers to NP-CGG were not altered. Thus, antagomir-148a might qualify as an effective drug to selectively deplete pro-inflammatory Th1 cells of chronic inflammation without affecting the protective immunological memory

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer‐reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state‐of‐the‐art handbook for basic and clinical researchers.DFG, 389687267, Kompartimentalisierung, Aufrechterhaltung und Reaktivierung humaner Gedächtnis-T-Lymphozyten aus Knochenmark und peripherem BlutDFG, 80750187, SFB 841: Leberentzündungen: Infektion, Immunregulation und KonsequenzenEC/H2020/800924/EU/International Cancer Research Fellowships - 2/iCARE-2DFG, 252623821, Die Rolle von follikulären T-Helferzellen in T-Helferzell-Differenzierung, Funktion und PlastizitätDFG, 390873048, EXC 2151: ImmunoSensation2 - the immune sensory syste

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers

Development, application and computational analysis of high-dimensional fluorescent antibody panels for single-cell flow cytometry

The interrogation of single cells is revolutionizing biology, especially our understanding of the immune system. Flow cytometry is still one of the most versatile and high-throughput approaches for single-cell analysis, and its capability has been recently extended to detect up to 28 colors, thus approaching the utility of cytometry by time of flight (CyTOF). However, flow cytometry suffers from autofluorescence and spreading error (SE) generated by errors in the measurement of photons mainly at red and far-red wavelengths, which limit barcoding and the detection of dim markers. Consequently, development of 28-color fluorescent antibody panels for flow cytometry is laborious and time consuming. Here, we describe the steps that are required to successfully achieve 28-color measurement capability. To do this, we provide a reference map of the fluorescence spreading errors in the 28-color space to simplify panel design and predict the success of fluorescent antibody combinations. Finally, we provide detailed instructions for the computational analysis of such complex data by existing, popular algorithms (PhenoGraph and FlowSOM). We exemplify our approach by designing a high-dimensional panel to characterize the immune system, but we anticipate that our approach can be used to design any high-dimensional flow cytometry panel of choice. The full protocol takes a few days to complete, depending on the time spent on panel design and data analysis

The AP1 transcription factor Fosl2 promotes systemic autoimmunity and inflammation by repressing treg development

Regulatory T cells (Tregs) represent a major population in the control of immune homeostasis and autoimmunity. Here we show that Fos-like 2 (Fosl2), a TCR-induced AP1 transcription factor, represses Treg development and controls autoimmunity. Mice overexpressing Fosl2 (Fosl2$^{tg}$) indeed show a systemic inflammatory phenotype, with immune infiltrates in multiple organs. This phenotype is absent in Fosl2$^{tg}$ × Rag2$^{-/-}$ mice lacking T and B cells, and Fosl2 induces T cell-intrinsic reduction of Treg development that is responsible for the inflammatory phenotype. Fosl2$^{tg}$ T cells can transfer inflammation, which is suppressed by the co-delivery of Tregs, while Fosl2 deficiency in T cells reduces the severity of autoimmunity in the EAE model. We find that Fosl2 could affect expression of FoxP3 and other Treg development genes. Our data highlight the importance of AP1 transcription factors, in particular Fosl2, during T cell development to determine Treg differentiation and control autoimmunity