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Microglia have been identified as key players in Alzheimer's disease pathogenesis, and other neurodegenerative diseases. Iba1, and more specifically TMEM119 and P2RY12 are gaining ground as presumedly more specific microglia markers, but comprehensive characterization of the expression of these three markers individually as well as combined is currently missing. Here we used a multispectral immunofluorescence dataset, in which over seventy thousand microglia from both aged controls and Alzheimer patients have been analysed for expression of Iba1, TMEM119 and P2RY12 on a single-cell level. For all markers, we studied the overlap and differences in expression patterns and the effect of proximity to β-amyloid plaques. We found no difference in absolute microglia numbers between control and Alzheimer subjects, but the prevalence of specific combinations of markers (phenotypes) differed greatly. In controls, the majority of microglia expressed all three markers. In Alzheimer patients, a significant loss of TMEM119+-phenotypes was observed, independent of the presence of β-amyloid plaques in its proximity. Contrary, phenotypes showing loss of P2RY12, but consistent Iba1 expression were increasingly prevalent around β-amyloid plaques. No morphological features were conclusively associated with loss or gain of any of the markers or any of the identified phenotypes. All in all, none of the three markers were expressed by all microglia, nor can be wholly regarded as a pan- or homeostatic marker, and preferential phenotypes were observed depending on the surrounding pathological or homeostatic environment. This work could help select and interpret microglia markers in previous and future studies.

Chronic intestinal inflammation underlies inflammatory bowel disease (IBD). Previous studies indicated alterations in the cellular immune system; however, it has been challenging to interrogate the role of all immune cell subsets simultaneously. Therefore, we aimed to identify immune cell types associated with inflammation in IBD using high-dimensional mass cytometry. We analyzed 188 intestinal biopsies and paired blood samples of newly-diagnosed, treatment-naive patients (n=42) and controls (n=26) in two independent cohorts. We applied mass cytometry (36-antibody panel) to resolve single cells and analyzed the data with unbiased Hierarchical-SNE. In addition, imaging-mass cytometry (IMC) was performed to reveal the spatial distribution of the immune subsets in the tissue. We identified 44 distinct immune subsets. Correlation network analysis identified a network of inflammation-associated subsets, including HLA-DR+CD38+ EM CD4+ T cells, T regulatory-like cells, PD1+ EM CD8+ T cells, neutrophils, CD27+ TCRγδ cells and NK cells. All disease-associated subsets were validated in a second cohort. This network was abundant in a subset of patients, independent of IBD subtype, severity or intestinal location. Putative disease-associated CD4+ T cells were detectable in blood. Finally, imaging-mass cytometry revealed the spatial colocalization of neutrophils, memory CD4+ T cells and myeloid cells in the inflamed intestine. Our study indicates that a cellular network of both innate and adaptive immune cells colocalizes in inflamed biopsies from a subset of patients. These results contribute to dissecting disease heterogeneity and may guide the development of targeted therapeutics in IBD.

Abstract Brain iron accumulation has been found to accelerate disease progression in amyloid-β(Aβ) positive Alzheimer patients, though the mechanism is still unknown. Microglia have been identified as key players in the disease pathogenesis, and are highly reactive cells responding to aberrations such as increased iron levels. Therefore, using histological methods, multispectral immunofluorescence and an automated in-house developed microglia segmentation and analysis pipeline, we studied the occurrence of iron-accumulating microglia and the effect on its activation state in human Alzheimer brains. We identified a subset of microglia with increased expression of the iron storage protein ferritin light chain (FTL), together with increased Iba1 expression, decreased TMEM119 and P2RY12 expression. This activated microglia subset represented iron-accumulating microglia and appeared morphologically dystrophic. Multispectral immunofluorescence allowed for spatial analysis of FTL+Iba1+-microglia, which were found to be the predominant Aβ-plaque infiltrating microglia. Finally, an increase of FTL+Iba1+-microglia was seen in patients with high Aβ load and Tau load. These findings suggest iron to be taken up by microglia and to influence the functional phenotype of these cells, especially in conjunction with Aβ.

Background The composition of the tumor immune microenvironment (TIME) associated with good prognosis generally also predicts the success of immunotherapy, and both entail the presence of pre-existing tumor-specific T cells. Here, the blueprint of the TIME associated with such an ongoing tumor-specific T-cell response was dissected in a unique prospective oropharyngeal squamous cell carcinoma (OPSCC) cohort, in which tumor-specific tumor-infiltrating T cells were detected (immune responsiveness (IR+)) or not (lack of immune responsiveness (IR−)).Methods A comprehensive multimodal, high-dimensional strategy was applied to dissect the TIME of treatment-naive IR+ and IR− OPSCC tissue, including bulk RNA sequencing (NanoString), imaging mass cytometry (Hyperion) for phenotyping and spatial interaction analyses of immune cells, and combined single-cell gene expression profiling and T-cell receptor (TCR) sequencing (single-cell RNA sequencing (scRNAseq)) to characterize the transcriptional states of clonally expanded tumor-infiltrating T cells.Results IR+ patients had an excellent survival during >10 years follow-up. The tumors of IR+ patients expressed higher levels of genes strongly related to interferon gamma signaling, T-cell activation, TCR signaling, and mononuclear cell differentiation, as well as genes involved in several immune signaling pathways, than IR− patients. The top differently overexpressed genes included CXCL12 and LTB, involved in ectopic lymphoid structure development. Moreover, scRNAseq not only revealed that CD4+ T cells were the main producers of LTB but also identified a subset of clonally expanded CD8+ T cells, dominantly present in IR+ tumors, which secreted the T cell and dendritic cell (DC) attracting chemokine CCL4. Indeed, immune cell infiltration in IR+ tumors is stronger, highly coordinated, and has a distinct spatial phenotypical signature characterized by intratumoral microaggregates of CD8+CD103+ and CD4+ T cells with DCs. In contrast, the IR− TIME comprised spatial interactions between lymphocytes and various immunosuppressive myeloid cell populations. The impact of these chemokines on local immunity and clinical outcome was confirmed in an independent The Cancer Genome Atlas OPSCC cohort.Conclusion The production of lymphoid cell attracting and organizing chemokines by tumor-specific T cells in IR+ tumors constitutes a positive feedback loop to sustain the formation of the DC–T-cell microaggregates and identifies patients with excellent survival after standard therapy.

Abstract Background The clinical benefit of immunotherapeutic approaches against cancer has been well established although complete responses are only observed in a minority of patients. Combination immunotherapy offers an attractive avenue to develop more effective cancer therapies by improving the efficacy and duration of the tumor-specific T-cell response. Here, we aimed at deciphering the mechanisms governing the response to PD-1/PD-L1 checkpoint blockade to support the rational design of combination immunotherapy. Methods Mice bearing subcutaneous MC-38 tumors were treated with blocking PD-L1 antibodies. To establish high-dimensional immune signatures of immunotherapy-specific responses, the tumor microenvironment was analyzed by CyTOF mass cytometry using 38 cellular markers. Findings were further examined and validated by flow cytometry and by functional in vivo experiments. Immune profiling was extended to the tumor microenvironment of colorectal cancer patients. Results PD-L1 blockade induced selectively the expansion of tumor-infiltrating CD4+ and CD8+ T-cell subsets, co-expressing both activating (ICOS) and inhibitory (LAG-3, PD-1) molecules. By therapeutically co-targeting these molecules on the TAI cell subsets in vivo by agonistic and antagonist antibodies, we were able to enhance PD-L1 blockade therapy as evidenced by an increased number of TAI cells within the tumor micro-environment and improved tumor protection. Moreover, TAI cells were also found in the tumor-microenvironment of colorectal cancer patients. Conclusions This study shows the presence of T cell subsets in the tumor micro-environment expressing both activating and inhibitory receptors. These TAI cells can be targeted by combined immunotherapy leading to improved survival.

During healthy pregnancy, a balanced microenvironment at the maternal-fetal interface with coordinated interaction between various immune cells is necessary to maintain immunological tolerance. While specific decidual immune cell subsets have been investigated, a system-wide unbiased approach is lacking. Here, mass cytometry was applied for data-driven, in-depth immune profiling of the total leukocyte population isolated from first, second, and third trimester decidua, as well as maternal peripheral blood at time of delivery. The maternal-fetal interface showed a unique composition of immune cells, different from peripheral blood, with significant differences between early and term pregnancy samples. Profiling revealed substantial heterogeneity in the decidual lymphoid and myeloid cell lineages that shape gestational-specific immune networks and putative differentiation trajectories over time during gestation. Uncovering the overall complexity at the maternal-fetal interface throughout pregnancy resulted in a human atlas that may serve as a foundation upon which comprehension of the immune microenvironment and alterations thereof in pregnancy complications can be built.

Multi-parametric flow and mass cytometry allows exceptional high-resolution exploration of the cellular composition of the immune system. A large panel of computational tools have been developed to analyze the high-dimensional landscape of the data generated. Analysis frameworks such as FlowSOM or Cytosplore incorporate clustering and dimensionality reduction techniques and include algorithms allowing visualization of multi-parametric cytometric analysis. To additionally provide means to quantify specific cell clusters and correlations between samples, we developed an R-package, called cytofast, for further downstream analysis. Specifically, cytofast enables the visualization and quantification of cell clusters for an efficient discovery of cell populations associated with diseases or physiology. We used cytofast on mass and flow cytometry datasets based on the modulation of the immune system upon immunotherapy. With cytofast, we rapidly generated visual representations of group-related immune cell clusters and showed correlations with the immune system composition. We discovered macrophage subsets that significantly decrease upon cancer immunotherapy and distinct prime-boost effects of prophylactic vaccines on the myeloid compartment. Cytofast is a time-efficient tool for comprehensive cytometric analysis to reveal immune signatures and correlations. Cytofast is available at Bioconductor. Keywords: Flow and mass cytometry analysis, R-based package, High-dimensional analysis, Single-cell analysis, Visualization tool

Single cell profiling yields high dimensional data of very large numbers of cells, posing challenges of visualization and analysis. Here the authors introduce a method for analysis of mass cytometry data that can handle very large datasets and allows their intuitive and hierarchical exploration.

The relationship between human cytomegalovirus (HCMV) infections and accelerated immune senescence is controversial. Whereas some studies reported a CMV-associated impaired capacity to control heterologous infections at old age, other studies could not confirm this. We hypothesized that these discrepancies might relate to the variability in the infectious dose of CMV occurring in real life. Here, we investigated the influence of persistent CMV infection on immune perturbations and specifically addressed the role of the infectious dose on the contribution of CMV to accelerated immune senescence. We show in experimental mouse models that the degree of mouse CMV (MCMV)-specific memory CD8+ T cell accumulation and the phenotypic T cell profile are directly influenced by the infectious dose, and data on HCMV-specific T cells indicate a similar connection. Detailed cluster analysis of the memory CD8+ T cell development showed that high-dose infection causes a differentiation pathway that progresses faster throughout the life span of the host, suggesting a virus–host balance that is influenced by aging and infectious dose. Importantly, short-term MCMV infection in adult mice is not disadvantageous for heterologous superinfection with lymphocytic choriomeningitis virus (LCMV). However, following long-term CMV infection the strength of the CD8+ T cell immunity to LCMV superinfection was affected by the initial CMV infectious dose, wherein a high infectious dose was found to be a prerequisite for impaired heterologous immunity. Altogether our results underscore the importance of stratification based on the size and differentiation of the CMV-specific memory T cell pools for the impact on immune senescence, and indicate that reduction of the latent/lytic viral load can be beneficial to diminish CMV-associated immune senescence.

Auto-reactive CD8 T-cells play an important role in the destruction of pancreatic β-cells resulting in type 1 diabetes (T1D). However, the phenotype of these auto-reactive cytolytic CD8 T-cells has not yet been extensively described. We used high-dimensional mass cytometry to phenotype autoantigen- (pre-proinsulin), neoantigen- (insulin-DRIP) and virus- (cytomegalovirus) reactive CD8 T-cells in peripheral blood mononuclear cells (PBMCs) of T1D patients. A panel of 33 monoclonal antibodies was designed to further characterise these cells at the single-cell level. HLA-A2 class I tetramers were used for the detection of antigen-specific CD8 T-cells. Using a novel Hierarchical Stochastic Neighbor Embedding (HSNE) tool (implemented in Cytosplore), we identified 42 clusters within the CD8 T-cell compartment of three T1D patients and revealed profound heterogeneity between individuals, as each patient displayed a distinct cluster distribution. Single-cell analysis of pre-proinsulin, insulin-DRIP and cytomegalovirus-specific CD8 T-cells showed that the detected specificities were heterogeneous between and within patients. These findings emphasize the challenge to define the obscure nature of auto-reactive CD8 T-cells.