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Single-cell mass cytometry significantly increases the dimensionality of cytometry analysis as compared to fluorescence flow cytometry, providing unprecedented resolution of cellular diversity in tissues. However, analysis and interpretation of these high-dimensional data poses a significant technical challenge. Here, we present cytofkit, a new Bioconductor package, which integrates both state-of-the-art bioinformatics methods and in-house novel algorithms to offer a comprehensive toolset for mass cytometry data analysis. Cytofkit provides functions for data pre-processing, data visualization through linear or non-linear dimensionality reduction, automatic identification of cell subsets, and inference of the relatedness between cell subsets. This pipeline also provides a graphical user interface (GUI) for ease of use, as well as a shiny application (APP) for interactive visualization of cell subpopulations and progression profiles of key markers. Applied to a CD14-CD19- PBMCs dataset, cytofkit accurately identified different subsets of lymphocytes; applied to a human CD4+ T cell dataset, cytofkit uncovered multiple subtypes of TFH cells spanning blood and tonsils. Cytofkit is implemented in R, licensed under the Artistic license 2.0, and freely available from the Bioconductor website, https://bioconductor.org/packages/cytofkit/. Cytofkit is also applicable for flow cytometry data analysis.

The progenitor stage of commitment toward the conventional dendritic cell subsets and the transcriptional networks that control it remain poorly understood. Two articles from Ginhoux and colleagues and Murphy and colleagues offer insight into these processes. Mouse conventional dendritic cells (cDCs) can be classified into two functionally distinct lineages: the CD8α + (CD103 + ) cDC1 lineage, and the CD11b + cDC2 lineage. cDCs arise from a cascade of bone marrow (BM) DC-committed progenitor cells that include the common DC progenitors (CDPs) and pre-DCs, which exit the BM and seed peripheral tissues before differentiating locally into mature cDCs. Where and when commitment to the cDC1 or cDC2 lineage occurs remains poorly understood. Here we found that transcriptional signatures of the cDC1 and cDC2 lineages became evident at the single-cell level from the CDP stage. We also identified Siglec-H and Ly6C as lineage markers that distinguished pre-DC subpopulations committed to the cDC1 lineage (Siglec-H − Ly6C − pre-DCs) or cDC2 lineage (Siglec-H − Ly6C + pre-DCs). Our results indicate that commitment to the cDC1 or cDC2 lineage occurs in the BM and not in the periphery.

Dendritic cells (DCs) are important components of the immune system that form from the bone marrow into two major cell lineages: plasmacytoid DCs and conventional DCs. See et al. applied single-cell RNA sequencing and cytometry by time-of-flight to characterize the developmental pathways of these cells. They identified blood DC precursors that shared surface markers with plasmacytoid DCs but that were functionally distinct. This unsuspected level of complexity in pre-DC populations reveals additional cell types and refines understanding of known cell types. Science , this issue p. eaag3009 In human blood, the immunological dendritic cell lineage contains many predendritic cell populations. Dendritic cells (DC) are professional antigen-presenting cells that orchestrate immune responses. The human DC population comprises two main functionally specialized lineages, whose origins and differentiation pathways remain incompletely defined. Here, we combine two high-dimensional technologies—single-cell messenger RNA sequencing (scmRNAseq) and cytometry by time-of-flight (CyTOF)—to identify human blood CD123 + CD33 + CD45RA + DC precursors (pre-DC). Pre-DC share surface markers with plasmacytoid DC (pDC) but have distinct functional properties that were previously attributed to pDC. Tracing the differentiation of DC from the bone marrow to the peripheral blood revealed that the pre-DC compartment contains distinct lineage-committed subpopulations, including one early uncommitted CD123 high pre-DC subset and two CD45RA + CD123 low lineage-committed subsets exhibiting functional differences. The discovery of multiple committed pre-DC populations opens promising new avenues for the therapeutic exploitation of DC subset-specific targeting.

Circulating CCR2 + monocytes are crucial for maintaining the adult tissue-resident F4/80 hi MHCII hi macrophage pool in the intestinal lamina propria. Here we show that a subpopulation of CCR2-independent F4/80 hi MHCII low macrophages, which are the most abundant F4/80 hi cells in neonates, gradually decline in number in adulthood; these macrophages likely represent the fetal contribution to F4/80 hi cells. In colon adenomas of Apc Min/+ mice, F4/80 hi MHCII low macrophages are not only preserved, but become the dominant subpopulation among tumour-resident macrophages during tumour progression. Furthermore, these pro-tumoural F4/80 hi MHCII low and F4/80 hi MHCII hi macrophages can self-renew in the tumour and maintain their numbers mostly independent from bone marrow contribution. Analyses of colon adenomas indicate that CSF1 may be a key facilitator of macrophage self-renewal. In summary, the tumour microenvironment creates an isolated niche for tissue-resident macrophages that favours macrophage survival and self-renewal. Tissue-resident F4/80 hi macrophages can be found both in normal gut as well as in intestinal tumours. Here the authors show that in the colon these macrophages are CCR2-dependent, while in tumours they gain the ability to self-renew, relying on CSF1 and promoting cancer progression.

Single-cell RNA-sequencing offers unprecedented resolution of the continuum of state transition during cell differentiation and development. However, tools for constructing multi-branching cell lineages from single-cell data are limited. Here we present Mpath, an algorithm that derives multi-branching developmental trajectories using neighborhood-based cell state transitions. Applied to mouse conventional dendritic cell (cDC) progenitors, Mpath constructs multi-branching trajectories spanning from macrophage/DC progenitors through common DC progenitor to pre-dendritic cells (preDC). The Mpath-generated trajectories detect a branching event at the preDC stage revealing preDC subsets that are exclusively committed to cDC1 or cDC2 lineages. Reordering cells along cDC development reveals sequential waves of gene regulation and temporal coupling between cell cycle and cDC differentiation. Applied to human myoblasts, Mpath recapitulates the time course of myoblast differentiation and isolates a branch of non-muscle cells involved in the differentiation. Our study shows that Mpath is a useful tool for constructing cell lineages from single-cell data. The tools for constructing cell lineages from single cell data are limited. Here, the authors present Mpath: an algorithm to derive multi-branching trajectories using neighbourhood-based cell state transitions, and use this to predict developmental trajectories in dendritic and muscle cells.

Myeloid cells show great phenotypic and functional diversity. Newell and colleagues use mass cytometry with a panel of 38 mouse myeloid markers to describe myeloid cell phenotypic diversity in unprecedented depth within eight different tissues. Advances in cell-fate mapping have revealed the complexity in phenotype, ontogeny and tissue distribution of the mammalian myeloid system. To capture this phenotypic diversity, we developed a 38-antibody panel for mass cytometry and used dimensionality reduction with machine learning–aided cluster analysis to build a composite of murine (mouse) myeloid cells in the steady state across lymphoid and nonlymphoid tissues. In addition to identifying all previously described myeloid populations, higher-order analysis allowed objective delineation of otherwise ambiguous subsets, including monocyte-macrophage intermediates and an array of granulocyte variants. Using mice that cannot sense granulocyte macrophage–colony stimulating factor GM-CSF ( Csf2rb −/− ), which have discrete alterations in myeloid development, we confirmed differences in barrier tissue dendritic cells, lung macrophages and eosinophils. The methodology further identified variations in the monocyte and innate lymphoid cell compartment that were unexpected, which confirmed that this approach is a powerful tool for unambiguous and unbiased characterization of the myeloid system.

The unique differentiation of IgE cells suggests unconventional mechanisms of IgE memory. IgE germinal centre cells are transient, most IgE cells are plasma cells, and high affinity IgE is produced by the switching of IgG1 cells to IgE. Here we investigate the function of subsets of IgG1 memory B cells in IgE production and find that two subsets of IgG1 memory B cells, CD80 + CD73 + and CD80 − CD73 − , contribute distinctively to the repertoires of high affinity pathogenic IgE and low affinity non-pathogenic IgE. Furthermore, repertoire analysis indicates that high affinity IgE and IgG1 plasma cells differentiate from rare CD80 + CD73 + high affinity memory clones without undergoing further mutagenesis. By identifying the cellular origin of high affinity IgE and the clonal selection of high affinity memory B cells into the plasma cell fate, our findings provide fundamental insights into the pathogenesis of allergies, and on the mechanisms of antibody production in memory B cell responses. IgE is an important mediator of protective immunity as well as allergic reaction, but how high affinity IgE antibodies are produced in memory responses is not clear. Here the authors show that IgE can be generated via class-switch recombination in IgG1 memory B cells without additional somatic hypermutation.

MHC class I-related molecule MR1 presents riboflavin- and folate-related metabolites to mucosal-associated invariant T cells, but it is unknown whether MR1 can present alternative antigens to other T cell lineages. In healthy individuals we identified MR1-restricted T cells (named MR1T cells) displaying diverse TCRs and reacting to MR1-expressing cells in the absence of microbial ligands. Analysis of MR1T cell clones revealed specificity for distinct cell-derived antigens and alternative transcriptional strategies for metabolic programming, cell cycle control and functional polarization following antigen stimulation. Phenotypic and functional characterization of MR1T cell clones showed multiple chemokine receptor expression profiles and secretion of diverse effector molecules, suggesting functional heterogeneity. Accordingly, MR1T cells exhibited distinct T helper-like capacities upon MR1-dependent recognition of target cells expressing physiological levels of surface MR1. These data extend the role of MR1 beyond microbial antigen presentation and indicate MR1T cells are a normal part of the human T cell repertoire. White blood cells called T cells recognize germs and infected cells, and get rid of other cells in the body that look different to healthy cells – for example, tumor cells. These activities all depend on a molecule called the T cell receptor (or TCR for short), which is found on the surface of the T cells. Each TCR interacts with a specific complex on the surface of the target cell. One of the molecules recognized by the TCR is known as MHC class I-related (shortened to MR1). This molecule attracts TCRs to infected cells, but it was not know if the MR1 molecule could attract TCRs to cancer cells too. Lepore et al. now show that there are indeed T cells in humans that recognize cancer cells through interaction with the MR1 molecules produced by the cancer cells. This new group of T cells has been named MR1T, and the cells can be easily detected in the blood of healthy individuals. The cells can be classified as a new cell population based on their capacity to recognize MR1 and how they react with different types of cancer cells. Importantly, the MR1 that attracts these TCRs is the same in all people, and so the same TCR may recognize MR1-expressing cancer cells from different patients. The next challenge is to identify MR1T cells that recognize and kill cancer cells from different tissues. These studies will hopefully pave the way for new and broader strategies to combat cancer.

Dengue is a growing global concern with 390 million people infected each year. Dengue virus (DENV) is transmitted by mosquitoes, thus host cells in the skin are the first point of contact with the virus. Human skin contains several populations of antigen-presenting cells which could drive the immune response to DENV in vivo: epidermal Langerhans cells (LCs), three populations of dermal dendritic cells (DCs), and macrophages. Using samples of normal human skin we detected productive infection of CD14(+) and CD1c(+) DCs, LCs and dermal macrophages, which was independent of DC-SIGN expression. LCs produced the highest viral titers and were less sensitive to IFN-β. Nanostring gene expression data showed significant up-regulation of IFN-β, STAT-1 and CCL5 upon viral exposure in susceptible DC populations. In mice infected intra-dermally with DENV we detected parallel populations of infected DCs originating from the dermis and migrating to the skin-draining lymph nodes. Therefore dermal DCs may simultaneously facilitate systemic spread of DENV and initiate the adaptive anti-viral immune response.

Metastatic spread is the leading cause of cancer mortality. Breast cancer (BCa) metastatic recurrence can happen years after removal of the primary tumor. Here we show that Ubc13, an E2 enzyme that catalyzes K63-linked protein polyubiquitination, is largely dispensable for primary mammary tumor growth but is required for metastatic spread and lung colonization by BCa cells. Loss of Ubc13 inhibited BCa growth and survival only at metastatic sites. Ubc13 was dispensable for transforming growth factor β (TGFβ)-induced SMAD activation but was required for activation of non-SMAD signaling via TGFβ-activating kinase 1 (TAK1) and p38, whose activity controls expression of numerous metastasis promoting genes. p38 activation restored metastatic activity to Ubc13-deficient cells, and its pharmacological inhibition attenuated BCa metastasis in mice, suggesting it is a therapeutic option for metastatic BCa. Significance We demonstrate that ubiquitin-conjugating enzyme Ubc13, whose expression is elevated in primary and metastatic breast cancer (BCa), promotes metastatic spread of BCa cells by controlling their lung-colonizing ability while having little effect on primary tumor growth. Mechanistically, Ubc13 is required for TGFβ-induced non-SMAD signaling via TAK1 and p38, a pathway that is first activated in the primary tumor. An Ubc13- and p38-dependent metastatic gene signature was identified, explaining how p38 may control metastasis and providing a measure for monitoring the effectiveness of pharmacologic p38 inhibition, which inhibits the growth of established metastatic lesions. We suggest that p38 inhibition should be considered as a potential treatment for metastatic BCa.