Human dendritic cells (DCs) are derived from distinct circulating precursors that are precommitted to become CD1c+ or CD141+ DCs

Laminarins and their derivatives affect dendritic cell activation and their crosstalk with T cells

This research explores the impact of structural variations in laminarins derived from seaweed on their immunomodulatory properties. Laminarins from Laminaria digitata, L. hyperborea, and Saccharina latissima, were obtained using a two-step water extraction protocol, followed by structural characterization by FT-IR spectroscopy, 1H NMR, and MALDI-TOF MS. The laminarin backbones were confirmed as β-1,3-linked glucans with species-specific percentages of β-1,6-linkages (~10 %, ~4 %, and ~21 %, respectively). Each polymer chain consists of approximately 24 to 25 monomer units, while oligosaccharide fractions, produced using the enzyme LPHase, displayed distinct DP-ranges, degrees of β-1,6-branching and intrachain linkages. Laminarin from L. hyperborea and specific oligosaccharide fractions from L. hyperborea and S. latissima influenced cytokine secretion by dendritic cells (DCs). L. hyperborea laminarin and the fraction LhF5 (DP5-DP8) stimulated increased IL-6 and IL-10 secretion by DCs, suggesting a dual role in promoting inflammation and regulating the immune response. In contrast, LhF5, LhF4 (DP6-DP10), and S. latissima laminari-oligosaccharide fraction SlF3 (DP6-DP9) caused decreased TNFα secretion, reflecting anti-inflammatory potential. Co-culturing of treated DCs and CD4+ T-cells showed that L. hyperborea laminarin caused increased IL-17 and IL-10 secretion, whereas SlF3 caused reduced IL-12p40 and IFN-γ secretion. These findings show that DC maturation and T-cell activation are affected by laminarins of certain size-distribution and branching, implying therapeutic potential for the treatment of inflammatory diseases or vaccine enhancement.

Human type 1 conventional dendritic cells contribute to skin transplant rejection

The skin is the most immunogenic tissue in transplantation and the most difficult tissue in which to induce immune modulation. Batf3-dependent type 1 conventional dendritic cells (cDC1s) are important in initiating rejection in murine skin transplantation. In humans, the CD141+ cDC1 subset is the functional counterpart of the murine Batf3-dependent cDC1s. However, their contribution to the rejection of human skin allografts remains unknown. Using samples from human face and upper extremity transplant recipients, we demonstrated that CD141+ cDC1s are increased and more activated in human skin grafts than native skin tissue from the same individual. Moreover, circulating and tissue CD141+ cDC1s were elevated at rejection time points. Local modulation of graft CD141+ cDC1s decreased HLA-DR expression and increased regulatory T cells, which correlated with a decreased presence of skin allogeneic T cells in a humanized transplantation model. Thus, CD141+ cDC1s play an important role in rejecting human skin allografts, and their local modulation is a promising therapeutic approach.

Cross-priming in cancer immunology and immunotherapy

Cytotoxic T cell immune responses against cancer crucially depend on the ability of a subtype of professional antigen-presenting cells termed conventional type 1 dendritic cells (cDC1s) to cross-present antigens. Cross-presentation comprises redirection of exogenous antigens taken from other cells to the major histocompatibility complex class I antigen-presenting machinery. In addition, once activated and having sensed viral moieties or T helper cell cooperation via CD40-CD40L interactions, cDC1s provide key co-stimulatory ligands and cytokines to mount and sustain CD8+ T cell immune responses. This regulated process of cognate T cell activation is termed cross-priming. In cancer mouse models, CD8+ T cell cross-priming by cDC1s is crucial for the efficacy of most, if not all, immunotherapy strategies. In patients with cancer, the presence and abundance of cDC1s in the tumour microenvironment is markedly associated with the level of T cell infiltration and responsiveness to immune checkpoint inhibitors. Therapeutic strategies to increase the numbers of cDC1s using FMS-like tyrosine kinase 3 ligand (FLT3L) and/or their activation status show evidence of efficacy in cancer mouse models and are currently being tested in initial clinical trials with promising results so far.

Pre-pregnancy obesity is associated with an altered maternal metabolome and reduced Flt3L expression in preterm birth

Mechanisms linking pre-pregnancy obesity to increased preterm birth risk are unclear. Here, we examined the impact of pre-pregnancy obesity on metabolites, Fms-related tyrosine kinase 3 ligand (Flt3L), and proinflammatory cytokine profiles in preterm birth. We used cytokine bead array, ELISA and Gas Chromatography-Mass Spectrometry (GC-MS) to determine cytokine and metabolite profiles in maternal and cord blood samples from 124 pregnant women in Australia, who gave birth at term (n = 86) or preterm (n = 38). Besides the expected variations in birth weight and gestational age, all demographic characteristics, including pre-pregnancy body mass index, were similar between the term and preterm birth groups. Mothers in the preterm birth group had reduced Flt3L (P = 0.002) and elevated IL-6 (P = 0.002) compared with term birthing mothers. Among mothers who gave birth preterm, those with pre-pregnancy obesity had lower Flt3L levels (P = 0.02) compared with lean mothers. Flt3L and IL-6 were similar in cord blood across both groups, but TNFα levels (P = 0.02) were reduced in preterm newborns. Metabolomic analysis revealed significant shifts in essential metabolites in women with pre-pregnancy obesity, some of which were linked to preterm births. Our findings suggest that maternal pre-pregnancy obesity alters the metabolome and reduces Flt3L expression, potentially increasing risk of preterm birth.

An in vitro CD8 T-cell priming assay enables epitope selection for hepatitis C virus vaccines

For the rational design of epitope-specific vaccines, identifying epitopes that can be processed and presented is essential. As algorithm-based epitope prediction is frequently discordant with actually recognized CD8+ T-cell epitopes, we developed an in vitro CD8 T-cell priming protocol to enable the identification of truly and functionally expressed HLA class I epitopes. The assay was established and validated to identify epitopes presented by hepatitis C virus (HCV)-infected cells. In vitro priming of naïve CD8 T cells was achieved by culturing unfractionated PBMCs in the presence of a specific cocktail of growth factors and cytokines, and next exposing the cells to hepatic cells expressing the NS3 protein of HCV. After a 10-day co-culture, HCV-specific T-cell responses were identified based on IFN-γ ELISpot analysis. For this, the T cells were restimulated with long synthetic peptides (SLPs) spanning the whole NS3 protein sequence allowing the identification of HCV-specificity. We demonstrated that this protocol resulted in the in vitro priming of naïve precursors to antigen-experienced T-cells specific for 11 out of 98 SLPs tested. These 11 SLPs contain 12 different HLA-A*02:01-restricted epitopes, as predicted by a combination of three epitope prediction algorithms. Furthermore, we identified responses against 3 peptides that were not predicted to contain any immunogenic HLA class I epitopes, yet showed HCV-specific responses in vitro. Separation of CD8+ and CD8- T cells from PBMCs primed in vitro showed responses only upon restimulation with short peptides. We established an in vitro method that enables the identification of HLA class I epitopes resulting from cross-presented antigens and that can cross-prime T cells and allows the effective selection of functional immunogenic epitopes, but also less immunogenic ones, for the design of tailored therapeutic vaccines against persistent viral infections and tumor antigens.

Quantitative trait loci mapping provides insights into the genetic regulation of dendritic cell numbers in mouse tissues

To explore the influence of genetics on homeostatic regulation of dendritic cell (DC) numbers, we present a screen of DCs and their progenitors in lymphoid and non-lymphoid tissues in Collaborative Cross (CC) and Diversity Outbred (DO) mice. We report 30 and 71 loci with logarithm of the odds (LOD) scores >8.18 and ranging from 6.67 to 8.19, respectively. The analysis reveals the highly polygenic and pleiotropic architecture of this complex trait, including many of the previously identified genetic regulators of DC development and maturation. Two SNPs in genes potentially underlying variation in DC homeostasis, a splice variant in Gramd4 (rs235532740) and a missense variant in Orai3 (rs216659754), are confirmed by gene editing using CRISPR-Cas9. Gramd4 is a central regulator of DC homeostasis that impacts the entire DC lineage, and Orai3 regulates cDC2 numbers in tissues. Overall, the data reveal a large number of candidate genes regulating DC homeostasis in vivo.

Identification of macaque dendritic cell precursors in blood and tissue reveals their dysregulation in early SIV infection

Distinct dendritic cell (DC) subsets play important roles in shaping immune responses. Circulating DC precursors (pre-DCs) are more susceptible to HIV infection in vitro, which may explain the inefficiency of immune responses against HIV. However, the interplay between HIV and pre-DC is not defined in vivo. We identify human pre-DC equivalents in the cynomolgus macaque and then analyze their dynamics during simian immunodeficiency virus (SIV) infection to illustrate a sharp decrease of blood pre-DCs in early SIV infection and accumulation in lymph nodes (LNs), where they neglect to upregulate CD83/CD86 or MHC-II. Additionally, SIV infection attenuates the capacity of stimulated LN pre-DCs to produce IL-12p40. Analysis of HIV cohorts provides correlation between costimulatory molecule expression on pre-DCs and T cell activation in spontaneous HIV controllers. These findings pinpoint certain dynamics and functional changes of pre-DCs during SIV infection, providing a deeper understanding of immune dysregulation mechanisms elicited in people living with HIV.

Preprocessing of Single Cell RNA Sequencing Data Using Correlated Clustering and Projection

Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given us insights into cell-cell communication, cell differentiation, and differential gene expression. However, analyzing scRNA-seq data is a challenge due to sparsity and the large number of genes involved. Therefore, dimensionality reduction and feature selection are important for removing spurious signals and enhancing the downstream analysis. We present Correlated Clustering and Projection (CCP), a new data-domain dimensionality reduction method, for the first time. CCP projects each cluster of similar genes into a supergene defined as the accumulated pairwise nonlinear gene-gene correlations among all cells. Using 14 benchmark data sets, we demonstrate that CCP has significant advantages over classical principal component analysis (PCA) for clustering and/or classification problems with intrinsically high dimensionality. In addition, we introduce the Residue-Similarity index (RSI) as a novel metric for clustering and classification and the R-S plot as a new visualization tool. We show that the RSI correlates with accuracy without requiring the knowledge of the true labels. The R-S plot provides a unique alternative to the uniform manifold approximation and projection (UMAP) and t-distributed stochastic neighbor embedding (t-SNE) for data with a large number of cell types.

Therapeutically targeting type I interferon directly to XCR1+ dendritic cells reveals the role of cDC1s in anti-drug antibodies

Conventional type 1 dendritic cells (cDC1s) are superior in antigen cross-presentation and priming CD8+ T cell anti-tumor immunity and thus, are a target of high interest for cancer immunotherapy. Type I interferon (IFN) is a potent inducer of antigen cross-presentation, but, unfortunately, shows only modest results in the clinic given the short half-life and high toxicity of current type I IFN therapies, which limit IFN exposure in the tumor. CD8+ T cell immunity is dependent on IFN signaling in cDC1s and preclinical studies suggest targeting IFN directly to cDC1s may be sufficient to drive anti-tumor immunity. Here, we engineered an anti-XCR1 antibody (Ab) and IFN mutein (IFNmut) fusion protein (XCR1Ab-IFNmut) to determine whether systemic delivery could drive selective and sustained type I IFN signaling in cDC1s leading to anti-tumor activity and, in parallel, reduced systemic toxicity. We found that the XCR1Ab-IFNmut fusion specifically enhanced cDC1 activation in the tumor and spleen compared to an untargeted control IFN. However, multiple treatments with the XCR1Ab-IFNmut fusion resulted in robust anti-drug antibodies (ADA) and loss of drug exposure. Using other cDC1-targeting Ab-IFNmut fusions, we found that localizing IFN directly to cDC1s activates their ability to promote ADA responses, regardless of the cDC1 targeting antigen. The development of ADA remains a major hurdle in immunotherapy drug development and the cellular and molecular mechanisms governing the development of ADA responses in humans is not well understood. Our results reveal a role of cDC1s in ADA generation and highlight the potential ADA challenges with targeting immunostimulatory agents to this cellular compartment.

Emerging Roles for Dendritic Cells in Heart Failure

The field of cardio-immunology has emerged from discoveries that define roles for innate and adaptive immune responses associated with myocardial inflammation and heart failure. Dendritic cells (DCs) comprise an important cellular compartment that contributes to systemic immune surveillance at the junction of innate and adaptive immunity. Once described as a singular immune subset, we now appreciate that DCs consist of a heterogeneous pool of subpopulations, each with distinct effector functions that can uniquely regulate the acute and chronic inflammatory response. Nevertheless, the cardiovascular-specific context involving DCs in negotiating the biological response to myocardial injury is not well understood. Herein, we review our current understanding of the role of DCs in cardiac inflammation and heart failure, including gaps in knowledge and clinical relevance.

The mycosis fungoides cutaneous microenvironment shapes dysfunctional cell trafficking, antitumor immunity, matrix interactions, and angiogenesis

Malignant T lymphocyte proliferation in mycosis fungoides (MF) is largely restricted to the skin, implying that malignant cells are dependent on their specific cutaneous tumor microenvironment (TME), including interactions with non-malignant immune and stromal cells, cytokines, and other immunomodulatory factors. To explore these interactions, we performed a comprehensive transcriptome analysis of the TME in advanced-stage MF skin tumors by single-cell RNA sequencing. Our analysis identified cell-type compositions, cellular functions, and cell-to-cell interactions in the MF TME that were distinct from those from healthy skin and benign dermatoses. While patterns of gene expression were common among patient samples, high transcriptional diversity was also observed in immune and stromal cells, with dynamic interactions and crosstalk between these cells and malignant T lymphocytes. This heterogeneity mapped to processes such as cell trafficking, matrix interactions, angiogenesis, immune functions, and metabolism that affect cancer cell growth, migration, and invasion, as well as antitumor immunity. By comprehensively characterizing the transcriptomes of immune and stromal cells within the cutaneous microenvironment of individual MF tumors, we have identified patterns of dysfunction common to all tumors that represent a resource for identifying candidates with therapeutic potential as well as patient-specific heterogeneity that has important implications for personalized disease management.

Immune cell identifier and classifier (ImmunIC) for single cell transcriptomic readouts

Single cell RNA sequencing has a central role in immune profiling, identifying specific immune cells as disease markers and suggesting therapeutic target genes of immune cells. Immune cell-type annotation from single cell transcriptomics is in high demand for dissecting complex immune signatures from multicellular blood and organ samples. However, accurate cell type assignment from single-cell RNA sequencing data alone is complicated by a high level of gene expression heterogeneity. Many computational methods have been developed to respond to this challenge, but immune cell annotation accuracy is not highly desirable. We present ImmunIC, a simple and robust tool for immune cell identification and classification by combining marker genes with a machine learning method. With over two million immune cells and half-million non-immune cells from 66 single cell RNA sequencing studies, ImmunIC shows 98% accuracy in the identification of immune cells. ImmunIC outperforms existing immune cell classifiers, categorizing into ten immune cell types with 92% accuracy. We determine peripheral blood mononuclear cell compositions of severe COVID-19 cases and healthy controls using previously published single cell transcriptomic data, permitting the identification of immune cell-type specific differential pathways. Our publicly available tool can maximize the utility of single cell RNA profiling by functioning as a stand-alone bioinformatic cell sorter, advancing cell-type specific immune profiling for the discovery of disease-specific immune signatures and therapeutic targets.

Single-cell analysis of myeloid cells in HPV+ tonsillar cancer

The incidence of human papillomavirus-positive (HPV+) tonsillar cancer has been sharply rising during the last decades. Myeloid cells represent an appropriate therapeutic target due to their proximity to virus-infected tumor cells, and their ability to orchestrate antigen-specific immunity, within the tonsil. However, the interrelationship of steady-state and inflammatory myeloid cell subsets, and their impact on patient survival remains unexplored. Here, we used single-cell RNA-sequencing to map the myeloid compartment in HPV+ tonsillar cancer. We observed an expansion of the myeloid compartment in HPV+ tonsillar cancer, accompanied by interferon-induced cellular responses both in dendritic cells (DCs) and monocyte-macrophages. Our analysis unveiled the existence of four DC lineages, two macrophage polarization processes, and their sequential maturation profiles. Within the DC lineages, we described a balance shift in the frequency of progenitor and mature cDC favoring the cDC1 lineage in detriment of cDC2s. Furthermore, we observed that all DC lineages apart from DC5s matured into a common activated DC transcriptional program involving upregulation of interferon-inducible genes. In turn, the monocyte-macrophage lineage was subjected to early monocyte polarization events, which give rise to either interferon-activated or CXCL-producing macrophages, the latter enriched in advanced tumor stages. We validated the existence of most of the single-cell RNA-seq clusters using 26-plex flow cytometry, and described a positive impact of cDC1 and interferon-activated DCs and macrophages on patient survival using gene signature scoring. The current study contributes to the understanding of myeloid ontogeny and dynamics in HPV-driven tonsillar cancer, and highlights myeloid biomarkers that can be used to assess patient prognosis.

Diverse impact of a probiotic strain, Lacticaseibacillus paracasei Shirota, on peripheral mononuclear phagocytic cells in healthy Japanese office workers: a randomized, double-blind, controlled trial

Mononuclear phagocytic cells (MPCs) are classified into monocytes (Mos)/macrophages and dendritic cells (DCs) based on their functions. Cells of MPCs lineage act as immune modulators by affecting effector cells, such as NK cells, T cells, and B cells. This study aimed to investigate the effects of Lacticaseibacillus paracasei strain Shirota (LcS) ingestion on peripheral MPCs, particularly on their expression of functional cell-surface molecules enhanced in healthy adults. Thus, twelve healthy office workers consumed a fermented milk drink containing 1.0 × 10¹¹ cfu of LcS (LcS-FM) or a control unfermented milk drink (CM) once a day for 6 weeks. Peripheral blood mononuclear cells (PBMCs) were prepared from blood samples, and immune cells and functional cell-surface molecules were analyzed. We observed remarkable differences in the expression of HLAABC, MICA, CD40, and GPR43 in plasmacytoid DCs (pDCs) between the LcS-FM and CM groups, whereas no difference was found in CD86 or HLADR expression. The LcS-FM group exhibited higher CD40 expression in both conventional DCs (cDCs) and Mos, especially in type 2 conventional DCs (cDC2s) and classical monocytes (cMos); higher percentages of cMos, intermediate monocytes (iMos), and nonclassical monocytes; and higher numbers of cMos and iMos in PBMCs than the CM group. LcS ingestion increased the expression of HLAABC, MICA, CD40, and GPR43 in pDCs and CD40 in cDCs and Mos, particularly cDC2s and cMos. These results suggest that LcS modulates the function of MPCs that may lead to the regulation of immune effector functions in healthy adults.

In Vitro Generation of Human Dendritic Cell Subsets from CD34+ Cord Blood Progenitors

Dendritic cells (DCs) are professional antigen-presenting cells controlling the activation of T cells and thus regulating adaptive immune response against pathogens or tumors. Modeling human DC differentiation and function is crucial for our understanding of immune response and the development of new therapies. Considering DC rarity in human blood, in vitro systems allowing their faithful generation are needed. This chapter will describe a DC differentiation method based on the co-culture of CD34⁺ cord blood progenitors together with mesenchymal stromal cells (eMSCs) engineered to deliver growth factors and chemokines.

Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics

BACKGROUND

Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation.

RESULTS

We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically.

CONCLUSIONS

ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.

Current knowledge on the early stages of human neutropoiesis

Polymorphonuclear neutrophils are no longer considered as a homogeneous population of terminally differentiated and short-lived cells that belong to the innate immune system only. In fact, data from the past decades have uncovered that neutrophils exhibit large phenotypic heterogeneity and functional versatility that render them more plastic than previously thought. Hence, their precise role as effector cells in inflammation, in immune response and in other pathophysiological processes, including tumors, needs to be better evaluated. In such a complex scenario, common knowledge of the differentiation of neutrophils in bone marrow refers to lineage precursors, starting from the still poorly defined myeloblasts, and proceeding sequentially to promyelocytes, myelocytes, metamyelocytes, band cells, segmented neutrophils, and mature neutrophils, with each progenitor stage being more mature and better characterized. Thanks to the development and utilization of cutting-edge technologies, novel information about neutrophil precursors at stages earlier than the promyelocytes, hence closer to the hematopoietic stem cells, is emerging. Accordingly, this review discusses the main findings related to the very early precursors of human neutrophils and provides our perspectives on human neutropoiesis.

Depletion of Conventional Type-1 Dendritic Cells in Established Tumors Suppresses Immunotherapy Efficacy

The ability of conventional type-1 dendritic cells (cDC1) to cross-present tumor antigens to CD8+ T cells is critical for the induction of antitumor CTLs. Mice that are constitutively deficient in cDC1 cells have been reported to fail to respond to immunotherapy strategies based on checkpoint inhibitors. However, further work is needed to clarify the precise time during immunotherapy treatment that cDC1 cells are required for the beneficial effect of treatment. Here, we used a refined XCR1-DTR-Venus transgenic mouse model to acutely deplete cDC1 cells and trace their behavior using intravital microscopy. Diphtheria toxin-mediated cDC1 depletion prior to immunotherapy treatment with anti-PD-1 and/or anti-CD137 immunostimulatory mAbs completely ablated antitumor efficacy. The efficacy of adoptive T-cell therapy was also hampered by prior cDC1 depletion. After the onset of immunotherapy treatment, depletion of cDC1s only moderately reduced the therapeutic efficacy of anti-PD-1 and anti-CD137 mAbs. Intravital microscopy of liver-engrafted tumors revealed changes in the intratumoral behavior of cDC1 cells in mice receiving immunotherapy, and treatment with diphtheria toxin to deplete cDC1s impaired tumor T-cell infiltration and function. These results reveal that the functional integrity of the cDC1 compartment is required at the onset of various immunotherapies to successfully treat established tumors.

SIGNIFICANCE

These findings reveal the intratumoral behavior of cDC1 dendritic cells in transgenic mouse models and demonstrate that the efficacy of immunotherapy regimens is precluded by elimination of these cells.

Human dendritic cell subsets: An updated view of their ontogeny and functional specialization

Human DCs have been divided into several subsets based on their phenotype and ontogeny. Recent high throughput single-cell methods have revealed additional heterogeneity within human DC subsets, and new subpopulations have been proposed. In this review, we provide an updated view of the human DC subsets and of their ontogeny supported by recent clinical studies . We also summarize their main characteristics including their functional specialization.

Reduced peripheral blood dendritic cell and monocyte subsets in MDS patients with systemic inflammatory or dysimmune diseases

BACKGROUND

Systemic inflammatory and autoimmune diseases (SIADs) occur in 10-20% of patients with myelodysplastic syndrome (MDS). Recently identified VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome, associated with somatic mutations in UBA1 (Ubiquitin-like modifier-activating enzyme 1), encompasses a range of severe inflammatory conditions along with hematological abnormalities, including MDS. The pathophysiological mechanisms underlying the association between MDS and SIADs remain largely unknown, especially the roles of different myeloid immune cell subsets. The aim of this study was to quantitatively evaluate peripheral blood myeloid immune cells (dendritic cells (DC) and monocytes) by flow cytometry in MDS patients with associated SIAD (n = 14, most often including relapsing polychondritis or neutrophilic dermatoses) and to compare their distribution in MDS patients without SIAD (n = 23) and healthy controls (n = 7). Most MDS and MDS/SIAD patients had low-risk MDS. Eight of 14 (57%) MDS/SIAD patients carried UBA1 somatic mutations, defining VEXAS syndrome.Compared with MDS patients, most DC and monocyte subsets were significantly decreased in MDS/SIAD patients, especially in MDS patients with VEXAS syndrome. Our study provides the first overview of the peripheral blood immune myeloid cell distribution in MDS patients with associated SIADs and raises several hypotheses: possible redistribution to inflammation sites, increased apoptosis, or impaired development in the bone marrow.

GE-Impute: graph embedding-based imputation for single-cell RNA-seq data

Single-cell RNA-sequencing (scRNA-seq) has been widely used to depict gene expression profiles at the single-cell resolution. However, its relatively high dropout rate often results in artificial zero expressions of genes and therefore compromised reliability of results. To overcome such unwanted sparsity of scRNA-seq data, several imputation algorithms have been developed to recover the single-cell expression profiles. Here, we propose a novel approach, GE-Impute, to impute the dropout zeros in scRNA-seq data with graph embedding-based neural network model. GE-Impute learns the neural graph representation for each cell and reconstructs the cell-cell similarity network accordingly, which enables better imputation of dropout zeros based on the more accurately allocated neighbors in the similarity network. Gene expression correlation analysis between true expression data and simulated dropout data suggests significantly better performance of GE-Impute on recovering dropout zeros for both droplet- and plated-based scRNA-seq data. GE-Impute also outperforms other imputation methods in identifying differentially expressed genes and improving the unsupervised clustering on datasets from various scRNA-seq techniques. Moreover, GE-Impute enhances the identification of marker genes, facilitating the cell type assignment of clusters. In trajectory analysis, GE-Impute improves time-course scRNA-seq data analysis and reconstructing differentiation trajectory. The above results together demonstrate that GE-Impute could be a useful method to recover the single-cell expression profiles, thus enabling better biological interpretation of scRNA-seq data. GE-Impute is implemented in Python and is freely available at https://github.com/wxbCaterpillar/GE-Impute.

IRF8 deficiency induces the transcriptional, functional, and epigenetic reprogramming of cDC1 into the cDC2 lineage

Conventional dendritic cells (cDCs) consist of two major functionally and phenotypically distinct subsets, cDC1 and cDC2, whose development is dependent on distinct sets of transcription factors. Interferon regulatory factor 8 (IRF8) is required at multiple stages of cDC1 development, but its role in committed cDC1 remains unclear. Here, we used Xcre-cre to delete Irf8 in committed cDC1 and demonstrate that Irf8 is required for maintaining the identity of cDC1. In the absence of Irf8, committed cDC1 acquired the transcriptional, functional, and chromatin accessibility properties of cDC2. This conversion was independent of Irf4 and was associated with the decreased accessibility of putative IRF8, Batf3, and composite AP-1-IRF (AICE)-binding elements, together with increased accessibility of cDC2-associated transcription-factor-binding elements. Thus, IRF8 expression by committed cDC1 is required for preventing their conversion into cDC2-like cells.

Indoleamine 2,3-dioxygenase 1 activation in mature cDC1 promotes tolerogenic education of inflammatory cDC2 via metabolic communication

Conventional dendritic cells (cDCs), cDC1 and cDC2, act both to initiate immunity and maintain self-tolerance. The tryptophan metabolic enzyme indoleamine 2,3-dioxygenase 1 (IDO1) is used by cDCs in maintaining tolerance, but its role in different subsets remains unclear. At homeostasis, only mature CCR7⁺ cDC1 expressed IDO1 that was dependent on IRF8. Lipopolysaccharide treatment induced maturation and IDO1-dependent tolerogenic activity in isolated immature cDC1, but not isolated cDC2. However, both human and mouse cDC2 could induce IDO1 and acquire tolerogenic function when co-cultured with mature cDC1 through the action of cDC1-derived l-kynurenine. Accordingly, cDC1-specific inactivation of IDO1 in vivo exacerbated disease in experimental autoimmune encephalomyelitis. This study identifies a previously unrecognized metabolic communication in which IDO1-expressing cDC1 cells extend their immunoregulatory capacity to the cDC2 subset through their production of tryptophan metabolite l-kynurenine. This metabolic axis represents a potential therapeutic target in treating autoimmune demyelinating diseases.

Single-Cell RNA Sequencing Data Clustering by Low-Rank Subspace Ensemble Framework

The rapid development of single-cell RNA sequencing (scRNA-seq)technology reveals the gene expression status and gene structure of individual cells, reflecting the heterogeneity and diversity of cells. The traditional methods of scRNA-seq data analysis treat data as the same subspace, and hide structural information in other subspaces. In this paper, we propose a low-rank subspace ensemble clustering framework (LRSEC)to analyze scRNA-seq data. Assuming that the scRNA-seq data exist in multiple subspaces, the low-rank model is used to find the lowest rank representation of the data in the subspace. It is worth noting that the penalty factor of the low-rank kernel function is uncertain, and different penalty factors correspond to different low-rank structures. Moreover, the single cluster model is difficult to find the cellular structure of all datasets. To strengthen the correlation between model solutions, we construct a new ensemble clustering framework LRSEC by using the low-rank model as the basic learner. The LRSEC framework captures the global structure of data through low-rank subspaces, which has better clustering performance than a single clustering model. We validate the performance of the LRSEC framework on seven small datasets and one large dataset and obtain satisfactory results.

Microfluidic Squeezing Enables MHC Class I Antigen Presentation by Diverse Immune Cells to Elicit CD8+ T Cell Responses with Antitumor Activity

CD8+ T cell responses are the foundation of the recent clinical success of immunotherapy in oncologic indications. Although checkpoint inhibitors have enhanced the activity of existing CD8+ T cell responses, therapeutic approaches to generate Ag-specific CD8+ T cell responses have had limited success. Here, we demonstrate that cytosolic delivery of Ag through microfluidic squeezing enables MHC class I presentation to CD8+ T cells by diverse cell types. In murine dendritic cells (DCs), squeezed DCs were ∼1000-fold more potent at eliciting CD8+ T cell responses than DCs cross-presenting the same amount of protein Ag. The approach also enabled engineering of less conventional APCs, such as T cells, for effective priming of CD8+ T cells in vitro and in vivo. Mixtures of immune cells, such as murine splenocytes, also elicited CD8+ T cell responses in vivo when squeezed with Ag. We demonstrate that squeezing enables effective MHC class I presentation by human DCs, T cells, B cells, and PBMCs and that, in clinical scale formats, the system can squeeze up to 2 billion cells per minute. Using the human papillomavirus 16 (HPV16) murine model, TC-1, we demonstrate that squeezed B cells, T cells, and unfractionated splenocytes elicit antitumor immunity and correlate with an influx of HPV-specific CD8+ T cells such that >80% of CD8s in the tumor were HPV specific. Together, these findings demonstrate the potential of cytosolic Ag delivery to drive robust CD8+ T cell responses and illustrate the potential for an autologous cell-based vaccine with minimal turnaround time for patients.

Functionally Mature CD1c+ Dendritic Cells Preferentially Accumulate in the Inflammatory Arthritis Synovium

Objective

To examine the role of synovial CD1c+DCs in patients with Inflammatory Arthritis (IA) with a specific focus on the transcriptional and maturation signatures that govern their function.

Methods

RNA sequencing was performed on healthy control (HC) peripheral blood (PB), IA PB, and IA synovial fluid (SF) CD1c+DCs. Multiparametric flow-cytometry and SPICE analysis were used to examine site [SF and Synovial Tissue (ST) CD1c+DCs] and disease specific characteristics of CD1c+DCs, while functional assays such as antigen processing, activation, and MMP production were also performed.

Results

Increased frequency of CD1c+DCs (p<0.01) with a concomitant increase in CD80, CCR7 (p<0.01), and CXCR3 (p<0.05) expression was identified in IA PB compared to HC PB. Enrichment of CD1c+DCs was identified in IA synovial tissue (ST) (p<0.01) and IA SF (p<0.0001) compared to IA PB, while RNAseq revealed distinct transcriptional variation between PB and SF CD1c+DCs. Flow cytometry revealed increased expression of CD83, CD80, PD-L1, and BTLA (all p<0.05) in IA SF CD1c+DCs compared to PB, while SPICE identified synovial cells with unique co-expression patterns, expressing multiple DC maturation markers simultaneously. Functionally, synovial CD1c+DCs are hyper-responsive to TLR7/8 ligation (p<0.05), have decreased antigen processing capacity (p=0.07), and display dysregulated production of MMPs. Finally, examination of both synovial CD1c+DCs and synovial CD141+DCs revealed distinct maturation and transcriptomic profiles.

Conclusion

Synovial CD1c+DCs accumulate in the inflamed IA synovium in a variety of distinct poly-maturational states, distinguishing them transcriptionally and functionally from CD1c+DCs in the periphery and synovial CD141+DCs.

High-throughput single-cell RNA-seq data imputation and characterization with surrogate-assisted automated deep learning

Single-cell RNA sequencing (scRNA-seq) technologies have been heavily developed to probe gene expression profiles at single-cell resolution. Deep imputation methods have been proposed to address the related computational challenges (e.g. the gene sparsity in single-cell data). In particular, the neural architectures of those deep imputation models have been proven to be critical for performance. However, deep imputation architectures are difficult to design and tune for those without rich knowledge of deep neural networks and scRNA-seq. Therefore, Surrogate-assisted Evolutionary Deep Imputation Model (SEDIM) is proposed to automatically design the architectures of deep neural networks for imputing gene expression levels in scRNA-seq data without any manual tuning. Moreover, the proposed SEDIM constructs an offline surrogate model, which can accelerate the computational efficiency of the architectural search. Comprehensive studies show that SEDIM significantly improves the imputation and clustering performance compared with other benchmark methods. In addition, we also extensively explore the performance of SEDIM in other contexts and platforms including mass cytometry and metabolic profiling in a comprehensive manner. Marker gene detection, gene ontology enrichment and pathological analysis are conducted to provide novel insights into cell-type identification and the underlying mechanisms. The source code is available at https://github.com/li-shaochuan/SEDIM.

Visualization and Analysis of Single cell RNA-seq Data by Maximizing Correntropy based Non-negative Low Rank Representation

The exploration of single cell RNA-sequencing (scRNA-seq) technology generates a new perspective to analyze biological problems. One of the major applications of scRNA-seq data is to discover subtypes of cells by cell clustering. Nevertheless, it is challengeable for traditional methods to handle scRNA-seq data with high level of technical noise and notorious dropouts. To better analyze single cell data, a novel scRNA-seq data analysis model called Maximum correntropy criterion based Non-negative and Low Rank Representation (MccNLRR) is introduced. Specifically, the maximum correntropy criterion, as an effective loss function, is more robust to the high noise and large outliers existed in the data. Moreover, the low rank representation is proven to be a powerful tool for capturing the global and local structures of data. Therefore, some important information, such as the similarity of cells in the subspace, is also extracted by it. Then, an iterative algorithm on the basis of the half-quadratic optimization and alternating direction method is developed to settle the complex optimization problem. Before the experiment, we also analyze the convergence and robustness of MccNLRR. At last, the results of cell clustering, visualization analysis, and gene markers selection on scRNA-seq data reveal that MccNLRR method can distinguish cell subtypes accurately and robustly.

Human Hepatitis B Virus Negatively Impacts the Protective Immune Crosstalk Between Natural Killer and Dendritic Cells

BACKGROUND AND AIMS

Natural killer (NK) cells play a crucial role in the clearance of human viruses but their activity is significantly impaired in patients infected with chronic hepatitis B (CHB). Cooperation with dendritic cells (DCs) is pivotal for obtaining optimal NK cell antiviral function; thus, we investigated whether HBV might impact the ability of DCs to sustain NK cell functions.

APPROACH AND RESULTS

Human DCs were poor stimulators of interferon-gamma (IFN-γ) production by NK cells when exposed to HBV, while maintaining the capability to trigger NK cell cytotoxicity. HBV prevented DC maturation but did not affect their expression of human leukocyte antigen class I, thus allowing DCs to evade NK cell lysis. Tolerogenic features of DCs exposed to HBV were further supported by their increased expression of IL-10 and the immunosuppressive enzyme indoleamine 2,3-dioxygenase, which contributed to the impairment of DC-mediated NK cell IFN-γ production and proliferation, respectively. HBV could also inhibit the expression of inducible immunoproteasome (iP) subunits on DCs. In fact, NK cells could induce iP subunit expression on DCs, but they failed in the presence of HBV. Remarkably, circulating blood DC antigen1 (BDCA1)⁺ DCs isolated from patients with CHB were functionally compromised, hence altering, in turn, NK cell responses.

CONCLUSIONS

The abnormal NK-DC interplay caused by HBV may significantly impair the efficacy of antiviral immune response in patients with CHB.

Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data based on Non-negative Matrix Factorization

The development of single-cell RNA sequencing (scRNA-seq) technology has made it possible to measure gene expression levels at the resolution of a single cell, which further reveals the complex growth processes of cells such as mutation and differentiation. Recognizing cell heterogeneity is one of the most critical tasks in scRNA-seq research. To solve it, we propose a non-negative matrix factorization framework based on multi-subspace cell similarity learning for unsupervised scRNA-seq data analysis (MscNMF). MscNMF includes three parts: data decomposition, similarity learning, and similarity fusion. The three work together to complete the data similarity learning task. MscNMF can learn the gene features and cell features of different subspaces, and the correlation and heterogeneity between cells will be more prominent in multi-subspaces. The redundant information and noise in each low-dimensional feature space are eliminated, and its gene weight information can be further analyzed to calculate the optimal number of subpopulations. The final cell similarity learning will be more satisfactory due to the fusion of cell similarity information in different subspaces. The advantage of MscNMF is that it can calculate the number of cell types and the rank of Non-negative matrix factorization (NMF) reasonably. Experiments on seven real scRNA-seq datasets show that MscNMF can effectively perform clustering tasks and extract useful genetic markers. To verify its clustering performance, the framework is compared with other latest clustering algorithms and satisfactory results are obtained. The code of MscNMF is free available for academic https://github.com/wangchuanyuan1/project-MscNMF).

Commitment to dendritic cells and monocytes

Dendritic cells (DCs) and monocytes are widely conserved immune cells in vertebrates that arise from hematopoietic stem cells via intermediate progenitors. The progenitors that strictly give rise to DCs or monocytes have been recently identified both in humans and in mice, thereby revealing their differentiation pathways. Advances in analysis technologies have further deepened our understanding of the development of DCs and monocytes from progenitor population-based to individual progenitor cell-based commitment. Since DC-committed progenitors, common DC progenitors (CDPs) and precursor conventional cDCs (pre-cDCs) do not differentiate into monocytes, DCs are a distinct lineage from monocytes, although monocytes can acquire DC-like functions upon activation at tissues where they arrive.

Adaptive Total-Variation Regularized Low-Rank Representation for Analyzing Single-Cell RNA-seq Data

High-throughput sequencing of single-cell gene expression reveals a complex mechanism of individual cell's heterogeneity in a population. An important purpose for analyzing single-cell RNA sequencing (scRNA-seq) data is to identify cell subtypes and functions by cell clustering. To deal with high levels of noise and cellular heterogeneity, we introduced a new single cell data analysis model called Adaptive Total-Variation Regularized Low-Rank Representation (ATV-LRR). In scRNA-seq data, ATV-LRR can reconstruct the low-rank subspace structure to learn the similarity of cells. The low-rank representation can not only segment multiple linear subspaces, but also extract important information. Moreover, adaptive total variation also can remove cell noise and preserve cell feature details by learning the gradient information of the data. At the same time, to analyze scRNA-seq data with unknown prior information, we introduced the maximum eigenvalue method into the ATV-LRR model to automatically identify cell populations. The final clustering results show that the ATV-LRR model can detect cell types more effectively and stably.

Dendritic Cells Are the Intriguing Players in the Puzzle of Idiopathic Pulmonary Fibrosis Pathogenesis

Idiopathic pulmonary fibrosis (IPF) is the most devastating progressive interstitial lung disease that remains refractory to treatment. Pathogenesis of IPF relies on the aberrant cross-talk between injured alveolar cells and myofibroblasts, which ultimately leads to an aberrant fibrous reaction. The contribution of the immune system to IPF remains not fully explored. Recent evidence suggests that both innate and adaptive immune responses may participate in the fibrotic process. Dendritic cells (DCs) are the most potent professional antigen-presenting cells that bridge innate and adaptive immunity. Also, they exert a crucial role in the immune surveillance of the lung, where they are strategically placed in the airway epithelium and interstitium. Immature DCs accumulate in the IPF lung close to areas of epithelial hyperplasia and fibrosis. Conversely, mature DCs are concentrated in well-organized lymphoid follicles along with T and B cells and bronchoalveolar lavage of IPF patients. We have recently shown that all sub-types of peripheral blood DCs (including conventional and plasmacytoid DCs) are severely depleted in therapy naïve IPF patients. Also, the low frequency of conventional CD1c⁺ DCs is predictive of a worse prognosis. The purpose of this mini-review is to focus on the main evidence on DC involvement in IPF pathogenesis. Unanswered questions and opportunities for future research ranging from a better understanding of their contribution to diagnosis and prognosis to personalized DC-based therapies will be explored.

Select hyperactivating NLRP3 ligands enhance the TH1- and TH17-inducing potential of human type 2 conventional dendritic cells

The detection of microorganisms and danger signals by pattern recognition receptors on dendritic cells (DCs) and the consequent formation of inflammasomes are pivotal for initiating protective immune responses. Although the activation of inflammasomes leading to secretion of the cytokine IL-1β is typically accompanied by pyroptosis (an inflammatory form of lytic programmed cell death), some cells can survive and exist in a state of hyperactivation. Here, we found that the conventional type 2 DC (cDC2) subset is the major human DC subset that is transcriptionally and functionally poised for inflammasome formation and response without pyroptosis. When cDC2 were stimulated with ligands that relatively weakly activated the inflammasome, the cells did not enter pyroptosis but instead secreted IL-12 family cytokines and IL-1β. These cytokines induced prominent T helper type 1 (T_H1) and T_H17 responses that were superior to those seen in response to Toll-like receptor (TLR) stimulation alone or to stronger, classical inflammasome ligands. These findings not only define the human cDC2 subpopulation as a prime target for the treatment of inflammasome-dependent inflammatory diseases but may also inform new approaches for adjuvant and vaccine development.

Inflammasomes in dendritic cells: Friend or foe?

Inflammasomes are cytosolic multiprotein complexes that crucially contribute to host defense against pathogens but are also involved in the pathogenesis of autoinflammatory diseases. Inflammasome formation leads to activation of effector caspases (caspase-1, 4, 5, or 11), the proteolytic maturation of IL-1β and IL-18 as well as cleavage of the pore-forming protein Gasdermin D. Dendritic cells are major regulators of immune responses as they bridge innate and adaptive immunity. We here summarize the current knowledge on inflammasome expression and formation in murine bone marrow-, human monocyte-derived as well as murine and human primary dendritic cells. Further, we discuss both, the beneficial and detrimental, involvement of inflammasome activation in dendritic cells in cancer, infections, and autoimmune diseases. As inflammasome activation is typically accompanied by Gasdermin d-mediated pyroptosis, which is an inflammatory form of programmed cell death, inflammasome formation in dendritic cells seems ill-advised. Therefore, we propose that hyperactivation, which is inflammasome activation without the induction of pyroptosis, may be a general model of inflammasome activation in dendritic cells to enhance Th1, Th17 as well as cytotoxic T cell responses.

The More, the Merrier: DC3s Join the Human Dendritic Cell Family

Recent studies have reported additional subpopulations of human dendritic cells (DCs), but whether they are distinct subsets has been unclear. In this issue of Immunity, Cytlak et al. and Bourdely et al. show that DC3s possess a specific precursor and represent a separate DC lineage.

Dendritic Cell Regulation of T Helper Cells

As the professional antigen-presenting cells of the immune system, dendritic cells (DCs) sense the microenvironment and shape the ensuing adaptive immune response. DCs can induce both immune activation and immune tolerance according to the peripheral cues. Recent work has established that DCs comprise several phenotypically and functionally heterogeneous subsets that differentially regulate T lymphocyte differentiation. This review summarizes both mouse and human DC subset phenotypes, development, diversification, and function. We focus on advances in our understanding of how different DC subsets regulate distinct CD4⁺ T helper (Th) cell differentiation outcomes, including Th1, Th2, Th17, T follicular helper, and T regulatory cells. We review DC subset intrinsic properties, local tissue microenvironments, and other immune cells that together determine Th cell differentiation during homeostasis and inflammation.

Heterogeneous populations from in vitro cultures of antigen presenting cells in pigs

Dendritic cells (DCs) are the most potent antigen presenting cells (APCs). Because of the difficulty in obtaining these cells directly from tissues, different sources of DCs are frequently used for in vitro experimentation and many of their biological and functional characteristics were studied using these systems. Until recently, it was assumed that specific culture conditions polarized the differentiation of either DCs or macrophages (Macs); however, it was shown that some DC culture systems in other species generate heterogeneous cell populations that can be identified according to their CD11c and MHC class II (MHC-II) expression. Following this approach, porcine DCs were directly isolated from peripheral blood or differentiated in vitro by culturing bone marrow (BM) progenitor cells or blood monocytes treated with growth factors. Mostly homogeneous monocyte-derived DCs (MoDCs) were obtained with similar phenotype and phagocytic characteristics to that of blood DCs. On the contrary, BM-derived DC (BMDC) cultures generated two distinct heterogeneous populations identified as MHC-II⁺ and MHC-II⁺⁺ cells. BMDCs MHC-II⁺ had similar phenotypic and phagocytic characteristics to those of MoDCs and blood DCs. However, BMDCs MHC-II⁺⁺ population expressed a higher amount of surface markers and transcribed genes associated with Macs-lineage exhibiting a higher phagocytic capacity than all the other cells. Noteworthy, every cell system expressed different genetic signatures. These results will help interpreting and re-interpreting data obtained using in vitro systems.

Hypomethylating Agents and Immunotherapy: Therapeutic Synergism in Acute Myeloid Leukemia and Myelodysplastic Syndromes

Decitabine and guadecitabine are hypomethylating agents (HMAs) that exert inhibitory effects against cancer cells. This includes stimulation of anti-tumor immunity in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) patients. Treatment of AML and MDS patients with the HMAs confers upregulation of cancer/testis antigens (CTAs) expression including the highly immunogenic CTA NY-ESO-1. This leads to activation of CD4⁺ and CD8⁺ T cells for elimination of cancer cells, and it establishes the feasibility to combine cancer vaccine with HMAs to enhance vaccine immunogenicity. Moreover, decitabine and guadecitabine induce the expression of immune checkpoint molecules in AML cells. In this review, the accumulating knowledge on the immunopotentiating properties of decitabine and guadecitabine in AML and MDS patients are presented and discussed. In summary, combination of decitabine or guadecitabine with NY-ESO-1 vaccine enhances vaccine immunogenicity in AML patients. T cells from AML patients stimulated with dendritic cell (DC)/AML fusion vaccine and guadecitabine display increased capacity to lyse AML cells. Moreover, decitabine enhances NK cell-mediated cytotoxicity or CD123-specific chimeric antigen receptor-engineered T cells antileukemic activities against AML. Furthermore, combination of either HMAs with immune checkpoint blockade (ICB) therapy may circumvent their resistance. Finally, clinical trials of either HMAs combined with cancer vaccines, NK cell infusion or ICB therapy in relapsed/refractory AML and high-risk MDS patients are currently underway, highlighting the promising efficacy of HMAs and immunotherapy synergy against these malignancies.

Reduced frequencies and functional impairment of dendritic cell subsets and non-classical monocytes in myelodysplastic syndromes

In myelodysplastic syndromes (MDS) the immune system is involved in pathogenesis as well as in disease progression. Dendritic cells (DC) are key players of the immune system by serving as regulators of immune responses. Their function has been scarcely studied in MDS and most of the reported studies didn't investigate naturally occurring DC subsets. Therefore, we here examined the frequency and function of DC subsets and slan+ non-classical monocytes in various MDS risk groups. Frequencies of DC as well as of slan+ monocytes were decreased in MDS bone marrow (BM) compared to normal bone marrow (NBM) samples. Transcriptional profiling revealed down-regulation of transcripts related to pro-inflammatory pathways in MDS-derived cells as compared to NBM. Additionally, their capacity to induce T cell proliferation was impaired. Multidimensional mass cytometry showed that whereas healthy donor-derived slan+ monocytes supported Th1/Th17/Treg differentiation/expansion their MDS-derived counterparts also mediated substantial Th2 expansion. Our findings point to a role for an impaired ability of DC subsets to adequately respond to cellular stress and DNA damage in the immune escape and progression of MDS. As such, it paves the way toward potential novel immunotherapeutic interventions.

Genetic models of human and mouse dendritic cell development and function

Dendritic cells (DCs) develop in the bone marrow from haematopoietic progenitors that have numerous shared characteristics between mice and humans. Human counterparts of mouse DC progenitors have been identified by their shared transcriptional signatures and developmental potential. New findings continue to revise models of DC ontogeny but it is well accepted that DCs can be divided into two main functional groups. Classical DCs include type 1 and type 2 subsets, which can detect different pathogens, produce specific cytokines and present antigens to polarize mainly naive CD8+ or CD4+ T cells, respectively. By contrast, the function of plasmacytoid DCs is largely innate and restricted to the detection of viral infections and the production of type I interferon. Here, we discuss genetic models of mouse DC development and function that have aided in correlating ontogeny with function, as well as how these findings can be translated to human DCs and their progenitors.

Dendritic Cells Revisited

Dendritic cells (DCs) possess the ability to integrate information about their environment and communicate it to other leukocytes, shaping adaptive and innate immunity. Over the years, a variety of cell types have been called DCs on the basis of phenotypic and functional attributes. Here, we refocus attention on conventional DCs (cDCs), a discrete cell lineage by ontogenetic and gene expression criteria that best corresponds to the cells originally described in the 1970s. We summarize current knowledge of mouse and human cDC subsets and describe their hematopoietic development and their phenotypic and functional attributes. We hope that our effort to review the basic features of cDC biology and distinguish cDCs from related cell types brings to the fore the remarkable properties of this cell type while shedding some light on the seemingly inordinate complexity of the DC field.

The Whole Body as the System in Systems Immunology

The human immune system is comprised of a diverse and interactive network of specialized cells localized in diverse tissues throughout the body, where they mediate protection against pathogens and environmental insults while maintaining tissue homeostasis. Although much of our understanding of human immunology has derived from studies of peripheral blood, recent work utilizing human tissue resources and innovative computational methods have employed a whole-body, systems-based approach, revealing tremendous complexity and heterogeneity of the immune system within individuals and across the population. In this review, we discuss how tissue localization, developmental and age-associated changes, and conditions of health and disease shape the immune response, as well as how improved understanding of interindividual and tissue-specific immunity can be leveraged for developing targeted therapeutics.

Impact of similarity metrics on single-cell RNA-seq data clustering

Advances in high-throughput sequencing on single-cell gene expressions [single-cell RNA sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from complex samples. A common goal in scRNA-seq data analysis is to discover and characterise cell types, typically through clustering methods. The quality of the clustering therefore plays a critical role in biological discovery. While numerous clustering algorithms have been proposed for scRNA-seq data, fundamentally they all rely on a similarity metric for categorising individual cells. Although several studies have compared the performance of various clustering algorithms for scRNA-seq data, currently there is no benchmark of different similarity metrics and their influence on scRNA-seq data clustering. Here, we compared a panel of similarity metrics on clustering a collection of annotated scRNA-seq datasets. Within each dataset, a stratified subsampling procedure was applied and an array of evaluation measures was employed to assess the similarity metrics. This produced a highly reliable and reproducible consensus on their performance assessment. Overall, we found that correlation-based metrics (e.g. Pearson's correlation) outperformed distance-based metrics (e.g. Euclidean distance). To test if the use of correlation-based metrics can benefit the recently published clustering techniques for scRNA-seq data, we modified a state-of-the-art kernel-based clustering algorithm (SIMLR) using Pearson's correlation as a similarity measure and found significant performance improvement over Euclidean distance on scRNA-seq data clustering. These findings demonstrate the importance of similarity metrics in clustering scRNA-seq data and highlight Pearson's correlation as a favourable choice. Further comparison on different scRNA-seq library preparation protocols suggests that they may also affect clustering performance. Finally, the benchmarking framework is available at http://www.maths.usyd.edu.au/u/SMS/bioinformatics/software.html.

Transcriptional and Functional Analysis of CD1c+ Human Dendritic Cells Identifies a CD163+ Subset Priming CD8+CD103+ T Cells

Dendritic cells (DCs) are antigen-presenting cells controlling T cell activation. In humans, the diversity, ontogeny, and functional capabilities of DC subsets are not fully understood. Here, we identified circulating CD88-CD1c+CD163+ DCs (called DC3s) as immediate precursors of inflammatory CD88-CD14+CD1c+CD163+FcεRI+ DCs. DC3s develop via a specific pathway activated by GM-CSF, independent of cDC-restricted (CDP) and monocyte-restricted (cMoP) progenitors. Like classical DCs but unlike monocytes, DC3s drove activation of naive T cells. In vitro, DC3s displayed a distinctive ability to prime CD8+ T cells expressing a tissue homing signature and the epithelial homing alpha-E integrin (CD103) through transforming growth factor β (TGF-β) signaling. In vivo, DC3s infiltrated luminal breast cancer primary tumors, and DC3 infiltration correlated positively with CD8+CD103+CD69+ tissue-resident memory T cells. Together, these findings define DC3s as a lineage of inflammatory DCs endowed with a strong potential to regulate tumor immunity.

Plasmacytoid dendritic cells in the eye

Plasmacytoid dendritic cells (pDCs) are a unique subpopulation of immune cells, distinct from classical dendritic cells. pDCs are generated in the bone marrow and following development, they typically home to secondary lymphoid tissues. While peripheral tissues are generally devoid of pDCs during steady state, few tissues, including the lung, kidney, vagina, and in particular ocular tissues harbor resident pDCs. pDCs were originally appreciated for their potential to produce large quantities of type I interferons in viral immunity. Subsequent studies have now unraveled their pivotal role in mediating immune responses, in particular in the induction of tolerance. In this review, we summarize our current knowledge on pDCs in ocular tissues in both mice and humans, in particular in the cornea, limbus, conjunctiva, choroid, retina, and lacrimal gland. Further, we will review our current understanding on the significance of pDCs in ameliorating inflammatory responses during herpes simplex virus keratitis, sterile inflammation, and corneal transplantation. Moreover, we describe their novel and pivotal neuroprotective role, their key function in preserving corneal angiogenic privilege, as well as their potential application as a cell-based therapy for ocular diseases.

The Role of Dendritic Cells During Infections Caused by Highly Prevalent Viruses

Dendritic cells (DCs) are a type of innate immune cells with major relevance in the establishment of an adaptive response, as they are responsible for the activation of lymphocytes. Since their discovery, several reports of their role during infectious diseases have been performed, highlighting their functions and their mechanisms of action. DCs can be categorized into different subsets, and each of these subsets expresses a wide arrange of receptors and molecules that aid them in the clearance of invading pathogens. Interferon (IFN) is a cytokine -a molecule of protein origin- strongly associated with antiviral immune responses. This cytokine is secreted by different cell types and is fundamental in the modulation of both innate and adaptive immune responses against viral infections. Particularly, DCs are one of the most important immune cells that produce IFN, with type I IFNs (α and β) highlighting as the most important, as they are associated with viral clearance. Type I IFN secretion can be induced via different pathways, activated by various components of the virus, such as surface proteins or genetic material. These molecules can trigger the activation of the IFN pathway trough surface receptors, including IFNAR, TLR4, or some intracellular receptors, such as TLR7, TLR9, and TLR3. Here, we discuss various types of dendritic cells found in humans and mice; their contribution to the activation of the antiviral response triggered by the secretion of IFN, through different routes of the induction for this important antiviral cytokine; and as to how DCs are involved in human infections that are considered highly frequent nowadays.

Dendritic Cells Currently under the Spotlight; Classification and Subset Based upon New Markers

Dendritic cells (DCs) are considered as a subset of mononuclear phagocytes that composed of multiple subsets with distinct phenotypic features. DCs play crucial roles in the initiation and modulation of immune responses to both allo- and auto-antigens during pathogenic settings, encompassing infectious diseases, cancer, autoimmunity, transplantation, as well as vaccination. DCs play a role in preventing autoimmunity via inducing tolerance to self-antigens. This review focus on the most common subsets of DCs in human. Owing to the low frequencies of DC cells in blood and tissues and also the lack of specific DC markers, studies of DCs have been greatly hindered. Human DCs arise by a dedicated pathway of lympho-myeloid hematopoiesis and give rise into specialized subtypes under the influence of transcription factors that are specific for each linage. In humans, the classification of DCs has been generally separated into the blood and cutaneous subsets, mainly because these parts are more comfortable to examine in humans.