A unique human cord blood CD8+CD45RA+CD27+CD161+ T-cell subset identified by flow cytometric data analysis using Seurat.

Advances in single-cell level analytical techniques, especially cytometric approaches, have led to profound innovation in biomedical research, particularly in the field of clinical immunology. This has resulted in an expansion of high-dimensional data, posing great challenges for comprehensive and unbiased analysis. Conventional manual analysis is thus becoming untenable to handle these challenges. Furthermore, most newly developed computational methods lack flexibility and interoperability, hampering their accessibility and usability. Here, we adapted Seurat, an R package originally developed for single-cell RNA sequencing (scRNA-seq) analysis, for high-dimensional flow cytometric data analysis. Based on a 20-marker antibody panel and analyses of T-cell profiles in both adult blood and cord blood (CB), we showcased the robust capacity of Seurat in flow cytometric data analysis, which was further validated by Spectre, another high-dimensional cytometric data analysis package, and conventional manual analysis. Importantly, we identified a unique CD8+ T-cell population defined as CD8+CD45RA+CD27+CD161+ T cell that was predominantly present in CB. We characterised its IFN-γ-producing and potential cytotoxic properties using flow cytometry experiments and scRNA-seq analysis from a published dataset. Collectively, we identified a unique human CB CD8+CD45RA+CD27+CD161+ T-cell subset and demonstrated that Seurat, a widely used package for scRNA-seq analysis, possesses great potential to be repurposed for cytometric data analysis. This facilitates an unbiased and thorough interpretation of complicated high-dimensional data using a single analytical pipeline and opens a novel avenue for data-driven investigation in clinical immunology.

GPR109A expressed on medullary thymic epithelial cells affects thymic Treg development.

Regulatory T cells (Treg) maintain immune homeostasis due to their anti-inflammatory functions. They can be generated either centrally in the thymus or in peripheral organs. Metabolites such as short-chain fatty acids produced by intestinal microbiota can induce peripheral Treg differentiation, by activating G-protein-coupled-receptors like GPR109A. In this study, we identified a novel role for GPR109A in thymic Treg development. We found that Gpr109a-/- mice had increased Treg under basal conditions in multiple organs compared with WT mice. GPR109A was not expressed on T cells but on medullary thymic epithelial cells (mTECs), as revealed by single-cell RNA sequencing in both mice and humans and confirmed by flow cytometry in mice. mTECs isolated from Gpr109a-/- mice had higher expression of autoimmune regulator (AIRE), the key regulator of Treg development, while the subset of mTECs that did not express Gpr109a in the WT displayed increased Aire expression and also enhanced signaling related to mTEC functionality. Increased thymic Treg in Gpr109a-/- mice was associated with protection from experimental autoimmune encephalomyelitis, with ameliorated clinical signs and reduced inflammation. This work identifies a novel role for GPR109A and possibly the gut microbiota, on thymic Treg development via its regulation of mTECs.

Targeting inflammatory monocytes by immune-modifying nanoparticles prevents acute kidney allograft rejection.

Inflammatory monocytes are a major component of the cellular infiltrate in acutely rejecting human kidney allografts. Since immune-modifying nanoparticles (IMPs) bind to circulating inflammatory monocytes via the specific scavenger receptor MARCO, causing diversion to the spleen and subsequent apoptosis, we investigated the therapeutic potential of negatively charged, 500-nm diameter polystyrene IMPs to prevent kidney allograft rejection. Kidney transplants were performed from BALB/c (H2d) to C57BL/6 (H2b) mice in two groups: controls (allo) and allo mice infused with IMPs. Groups were studied for 14 (acute rejection) or 100 (chronic rejection) days. Allo mice receiving IMPs exhibited superior survival and markedly less acute rejection, with better kidney function, less tubulitis, and diminished inflammatory cell density, cytokine and cytotoxic molecule expression in the allograft and lower titers of donor-specific IgG2c antibody in serum at day 14, as compared to allo mice. Cells isolated from kidneys from allo mice receiving IMPs showed reduced Ly6Chi monocytes, CD11b+ cells and NKT+ cells compared to allo mice. IMPs predominantly bound CD11b+ cells in the bloodstream and CD11b+ and CD11c-B220+ marginal zone B cells in the spleen. In the spleen, IMPs were found predominantly in red pulp, colocalized with MARCO and expression of cleaved caspase-3. At day 100, allo mice receiving IMPs exhibited reduced macrophage M1 responses but were not protected from chronic rejection. IMPs afforded significant protection from acute rejection, inhibiting both innate and adaptive alloimmunity. Thus, our current experimental findings, coupled with our earlier demonstration of IMP-induced protection in kidney ischemia-reperfusion injury, identify IMPs as a potential induction agent in kidney transplantation.

Integration, exploration, and analysis of high-dimensional single-cell cytometry data using Spectre.

As the size and complexity of high-dimensional (HD) cytometry data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches or experiments are not well incorporated into computational toolkits to allow for streamlined workflows. Here we present Spectre, an R package that enables comprehensive end-to-end integration and analysis of HD cytometry data from different batches or experiments. Spectre streamlines the analytical stages of raw data pre-processing, batch alignment, data integration, clustering, dimensionality reduction, visualization, and population labelling, as well as quantitative and statistical analysis. Critically, the fundamental data structures used within Spectre, along with the implementation of machine learning classifiers, allow for the scalable analysis of very large HD datasets, generated by flow cytometry, mass cytometry, or spectral cytometry. Using open and flexible data structures, Spectre can also be used to analyze data generated by single-cell RNA sequencing or HD imaging technologies, such as Imaging Mass Cytometry. The simple, clear, and modular design of analysis workflows allow these tools to be used by bioinformaticians and laboratory scientists alike. Spectre is available as an R package or Docker container. R code is available on Github (https://github.com/immunedynamics/spectre).

Evaluating spectral cytometry for immune profiling in viral disease.

In conventional fluorescence cytometry, each fluorophore present in a panel is measured in a target detector, through the use of wide band-pass optical filters. In contrast, spectral cytometry uses a large number of detectors with narrow band-pass filters to measure a fluorophore's signal across the spectrum, creating a more detailed fluorescent signature for each fluorophore. The spectral approach shows promise in adding flexibility to panel design and improving the measurement of fluorescent signal. However, few comparisons between conventional and spectral systems have been reported to date. We therefore sought to compare a modern conventional cytometry system with a modern spectral system, and to assess the quality of resulting datasets from the point of view of a flow cytometry user. Signal intensity, spread, and resolution were compared between the systems. Subsequently, the different methods of separating fluorophore signals were compared, where compensation mathematically separates multiple overlapping fluorophores and unmixing relies on creating a detailed fluorescent signature across the spectrum to separate the fluorophores. Within the spectral data set, signal spread and resolution were comparable between compensation and unmixing. However, for some highly overlapping fluorophores, unmixing resolved the two fluorescence signals where compensation did not. Finally, data from mid- to large-size panels were acquired and were found to have comparable resolution for many fluorophores on both instruments, but reduced levels of spreading error on our spectral system improved signal resolution for a number of fluorophores, compared with our conventional system. Furthermore, autofluorescence extraction on the spectral system allowed for greater population resolution in highly autofluorescent samples. Overall, the implementation of a spectral cytometry approach resulted in data that are comparable to that generated on conventional systems, with a number of potential advantages afforded by the larger number of detectors, and the integration of the spectral unmixing approach. © 2020 International Society for Advancement of Cytometry.

The plasticity of inflammatory monocyte responses to the inflamed central nervous system.

Over the last three decades it has become increasingly clear that monocytes, originally thought to have fixed, stereotypic responses to foreign stimuli, mediate exquisitely balanced protective and pathogenic roles in disease and immunity. This balance is crucial in core functional organs, such as the central nervous system (CNS), where minor changes in neuronal microenvironments and the production of immune factors can result in significant disease with fatal consequences or permanent neurological sequelae. Viral encephalitis and multiple sclerosis are examples of important human diseases in which the pathogenic contribution of monocytes recruited from the bone marrow plays a critical role in the clinical expression of disease, as they differentiate into macrophage or dendritic cells in the CNS to carry out effector functions. While antigen-specific lymphocyte populations are central to the adaptive immune response in both cases, in viral encephalitis a prominent macrophage infiltration may mediate immunopathological damage, seizure induction, and death. However, the autoimmune response to non-replicating, non-infectious, but abundant, self antigen has a different disease progression, associated with differentiation of significant numbers of infiltrating monocytes into dendritic cells in the CNS. Whilst a predominant presence of macrophages or dendritic cells in the inflamed CNS in viral encephalitis or multiple sclerosis is well described, the way in which the inflamed CNS mobilizes monocytes in the bone marrow to migrate to the CNS and the key drivers that lead to these specific differentiation pathways in vivo are not well understood. Here we review the current understanding of factors facilitating inflammatory monocyte generation, migration and entry into the brain, as well as their differentiation towards macrophages or dendritic cells in viral and autoimmune disease in relation to their respective disease outcomes.

Microarray analysis of gene expression in West Nile virus-infected human retinal pigment epithelium.

PURPOSE: To identify key genes differentially expressed in the human retinal pigment epithelium (hRPE) following low-level West Nile virus (WNV) infection. METHODS: Primary hRPE and retinal pigment epithelium cell line (ARPE-19) cells were infected with WNV (multiplicity of infection 1). RNA extracted from mock-infected and WNV-infected cells was assessed for differential expression of genes using Affymetrix microarray. Quantitative real-time PCR analysis of 23 genes was used to validate the microarray results. RESULTS: Functional annotation clustering of the microarray data showed that gene clusters involved in immune and antiviral responses ranked highly, involving genes such as chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-C motif) ligand 5 (CCL5), chemokine (C-X-C motif) ligand 10 (CXCL10), and toll like receptor 3 (TLR3). In conjunction with the quantitative real-time PCR analysis, other novel genes regulated by WNV infection included indoleamine 2,3-dioxygenase (IDO1), genes involved in the transforming growth factor-ß pathway (bone morphogenetic protein and activin membrane-bound inhibitor homolog [BAMBI] and activating transcription factor 3 [ATF3]), and genes involved in apoptosis (tumor necrosis factor receptor superfamily, member 10d [TNFRSF10D]). WNV-infected RPE did not produce any interferon-γ, suggesting that IDO1 is induced by other soluble factors, by the virus alone, or both. CONCLUSIONS: Low-level WNV infection of hRPE cells induced expression of genes that are typically associated with the host cell response to virus infection. We also identified other genes, including IDO1 and BAMBI, that may influence the RPE and therefore outer blood-retinal barrier integrity during ocular infection and inflammation, or are associated with degeneration, as seen for example in aging.

Impact of Dietary Fiber on West Nile Virus Infection.

Dietary fiber supports healthy gut bacteria and their production of short-chain fatty acids (SCFA), which promote anti-inflammatory cell development, in particular, regulatory T cells. It is thus beneficial in many diseases, including influenza infection. While disruption of the gut microbiota by antibiotic treatment aggravates West Nile Virus (WNV) disease, whether dietary fiber is beneficial is unknown. WNV is a widely-distributed neurotropic flavivirus that recruits inflammatory monocytes into the brain, causing life-threatening encephalitis. To investigate the impact of dietary fiber on WNV encephalitis, mice were fed on diets deficient or enriched with dietary fiber for two weeks prior to inoculation with WNV. To induce encephalitis, mice were inoculated intranasally with WNV and maintained on these diets. Despite increased fecal SCFA acetate and changes in gut microbiota composition, dietary fiber did not affect clinical scores, leukocyte infiltration into the brain, or survival. After the brain, highest virus loads were measured in the colon in neurons of the submucosal and myenteric plexuses. Associated with this, there was disrupted gut homeostasis, with shorter colon length and higher local inflammatory cytokine levels, which were not affected by dietary fiber. Thus, fiber supplementation is not effective in WNV encephalitis.

Dysbiosis in imiquimod-induced psoriasis alters gut immunity and exacerbates colitis development.

Psoriasis has long been associated with inflammatory bowel disease (IBD); however, a causal link is yet to be established. Here, we demonstrate that imiquimod-induced psoriasis (IMQ-pso) in mice disrupts gut homeostasis, characterized by increased proportions of colonic CX3CR1hi macrophages, altered cytokine production, and bacterial dysbiosis. Gut microbiota from these mice produce higher levels of succinate, which induce de novo proliferation of CX3CR1hi macrophages ex vivo, while disrupted gut homeostasis primes IMQ-pso mice for more severe colitis with dextran sulfate sodium (DSS) challenge. These results demonstrate that changes in the gut environment in psoriasis lead to greater susceptibility to IBD in mice, suggesting a two-hit requirement, that is, psoriasis-induced altered gut homeostasis and a secondary environmental challenge. This may explain the increased prevalence of IBD in patients with psoriasis.

Dietary protein increases T-cell-independent sIgA production through changes in gut microbiota-derived extracellular vesicles.

Secretory IgA is a key mucosal component ensuring host-microbiota mutualism. Here we use nutritional geometry modelling in mice fed 10 different macronutrient-defined, isocaloric diets, and identify dietary protein as the major driver of secretory IgA production. Protein-driven secretory IgA induction is not mediated by T-cell-dependent pathways or changes in gut microbiota composition. Instead, the microbiota of high protein fed mice produces significantly higher quantities of extracellular vesicles, compared to those of mice fed high-carbohydrate or high-fat diets. These extracellular vesicles activate Toll-like receptor 4 to increase the epithelial expression of IgA-inducing cytokine, APRIL, B cell chemokine, CCL28, and the IgA transporter, PIGR. We show that succinate, produced in high concentrations by microbiota of high protein fed animals, increases generation of reactive oxygen species by bacteria, which in turn promotes extracellular vesicles production. Here we establish a link between dietary macronutrient composition, gut microbial extracellular vesicles release and host secretory IgA response.

Dietary carbohydrate, particularly glucose, drives B cell lymphopoiesis and function.

While diet modulates immunity, its impact on B cell ontogeny remains unclear. Using mixture modeling, a large-scale isocaloric dietary cohort mouse study identified carbohydrate as a major driver of B cell development and function. Increasing dietary carbohydrate increased B cell proportions in spleen, mesenteric lymph node and Peyer's patches, and increased antigen-specific immunoglobulin G production after immunization. This was linked to increased B lymphopoiesis in the bone marrow. Glucose promoted early B lymphopoiesis and higher total B lymphocyte numbers than fructose. It drove B cell development through glycolysis and oxidative phosphorylation, independently of fatty acid oxidation in vitro and reduced B cell apoptosis in early development via mTOR activation, independently of interleukin-7. Ours is the first comprehensive study showing the impact of macronutrients on B cell development and function. It shows the quantitative and qualitative interplay between dietary carbohydrate and B cells and argues for dietary modulation in B cell-targeting strategies.

High-Dimensional Fluorescence Cytometry.

The immune system consists of a complex network of cells, all expressing a wide range of surface and/or intracellular proteins. Using flow cytometry, these cells can be analyzed by labeling with fluorophore-conjugated antibodies. The recent expansion of fluorescence flow cytometry technology, in conjunction with the ever-expanding understanding of the complexity of the immune system, has led to the generation of larger high-dimensional fluorescence flow cytometry panels. However, as panel size and complexity increases, so too does the difficulty involved in constructing high-quality panels, in addition to the challenges of analyzing such high-dimensional datasets. As such, this unit seeks to review the key principles involved in building high-dimensional panels, as well as to guide users through the process of building and analyzing quality panels. Here, cytometer configuration, fluorophore brightness, spreading error, antigen density, choosing the best conjugates, titration, optimization, and data analysis will all be addressed. © 2017 by John Wiley & Sons, Inc.