A TCF4-dependent gene regulatory network confers resistance to immunotherapy in melanoma.

To better understand intrinsic resistance to immune checkpoint blockade (ICB), we established a comprehensive view of the cellular architecture of the treatment-naive melanoma ecosystem and studied its evolution under ICB. Using single-cell, spatial multi-omics, we showed that the tumor microenvironment promotes the emergence of a complex melanoma transcriptomic landscape. Melanoma cells harboring a mesenchymal-like (MES) state, a population known to confer resistance to targeted therapy, were significantly enriched in early on-treatment biopsies from non-responders to ICB. TCF4 serves as the hub of this landscape by being a master regulator of the MES signature and a suppressor of the melanocytic and antigen presentation transcriptional programs. Targeting TCF4 genetically or pharmacologically, using a bromodomain inhibitor, increased immunogenicity and sensitivity of MES cells to ICB and targeted therapy. We thereby uncovered a TCF4-dependent regulatory network that orchestrates multiple transcriptional programs and contributes to resistance to both targeted therapy and ICB in melanoma.

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches.

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.

Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection.

The phenotypic and functional dichotomy between IRF8+ type 1 and IRF4+ type 2 conventional dendritic cells (cDC1s and cDC2s, respectively) is well accepted; it is unknown how robust this dichotomy is under inflammatory conditions, when additionally monocyte-derived cells (MCs) become competent antigen-presenting cells (APCs). Using single-cell technologies in models of respiratory viral infection, we found that lung cDC2s acquired expression of the Fc receptor CD64 shared with MCs and of IRF8 shared with cDC1s. These inflammatory cDC2s (inf-cDC2s) were superior in inducing CD4+ T helper (Th) cell polarization while simultaneously presenting antigen to CD8+ T cells. When carefully separated from inf-cDC2s, MCs lacked APC function. Inf-cDC2s matured in response to cell-intrinsic Toll-like receptor and type 1 interferon receptor signaling, upregulated an IRF8-dependent maturation module, and acquired antigens via convalescent serum and Fc receptors. Because hybrid inf-cDC2s are easily confused with monocyte-derived cells, their existence could explain why APC functions have been attributed to MCs.

Integrated scRNA-Seq Identifies Human Postnatal Thymus Seeding Progenitors and Regulatory Dynamics of Differentiating Immature Thymocytes.

During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone-marrow-derived hematopoietic progenitors that migrate through the bloodstream. The current understanding of the nature of thymic immigrants is largely based on data from pre-clinical models. Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the immature postnatal thymocyte population in humans. Integration of bone marrow and peripheral blood precursor datasets identified two putative thymus seeding progenitors that varied in expression of CD7; CD10; and the homing receptors CCR7, CCR9, and ITGB7. Whereas both precursors supported T cell development, only one contributed to intrathymic dendritic cell (DC) differentiation, predominantly of plasmacytoid dendritic cells. Trajectory inference delineated the transcriptional dynamics underlying early human T lineage development, enabling prediction of transcription factor (TF) modules that drive stage-specific steps of human T cell development. This comprehensive dataset defines the expression signature of immature human thymocytes and provides a resource for the further study of human thymopoiesis.

Osteopontin Expression Identifies a Subset of Recruited Macrophages Distinct from Kupffer Cells in the Fatty Liver.

Metabolic-associated fatty liver disease (MAFLD) represents a spectrum of disease states ranging from simple steatosis to non-alcoholic steatohepatitis (NASH). Hepatic macrophages, specifically Kupffer cells (KCs), are suggested to play important roles in the pathogenesis of MAFLD through their activation, although the exact roles played by these cells remain unclear. Here, we demonstrated that KCs were reduced in MAFLD being replaced by macrophages originating from the bone marrow. Recruited macrophages existed in two subsets with distinct activation states, either closely resembling homeostatic KCs or lipid-associated macrophages (LAMs) from obese adipose tissue. Hepatic LAMs expressed Osteopontin, a biomarker for patients with NASH, linked with the development of fibrosis. Fitting with this, LAMs were found in regions of the liver with reduced numbers of KCs, characterized by increased Desmin expression. Together, our data highlight considerable heterogeneity within the macrophage pool and suggest a need for more specific macrophage targeting strategies in MAFLD.

Single-Cell RNA Sequencing of the T Helper Cell Response to House Dust Mites Defines a Distinct Gene Expression Signature in Airway Th2 Cells.

Naive CD4+ T cells differentiate into functionally diverse T helper (Th) cell subsets. Th2 cells play a pathogenic role in asthma, yet a clear picture of their transcriptional profile is lacking. We performed single-cell RNA sequencing (scRNA-seq) of T helper cells from lymph node, lung, and airways in the house dust mite (HDM) model of allergic airway disease. scRNA-seq resolved transcriptional profiles of naive CD4+ T, Th1, Th2, regulatory T (Treg) cells, and a CD4+ T cell population responsive to type I interferons. Th2 cells in the airways were enriched for transcription of many genes, including Cd200r1, Il6, Plac8, and Igfbp7, and their mRNA profile was supported by analysis of chromatin accessibility and flow cytometry. Pathways associated with lipid metabolism were enriched in Th2 cells, and experiments with inhibitors of key metabolic pathways supported roles for glucose and lipid metabolism. These findings provide insight into the differentiation of pathogenic Th2 cells in the context of allergy.

Stellate Cells, Hepatocytes, and Endothelial Cells Imprint the Kupffer Cell Identity on Monocytes Colonizing the Liver Macrophage Niche.

Macrophages are strongly adapted to their tissue of residence. Yet, little is known about the cell-cell interactions that imprint the tissue-specific identities of macrophages in their respective niches. Using conditional depletion of liver Kupffer cells, we traced the developmental stages of monocytes differentiating into Kupffer cells and mapped the cellular interactions imprinting the Kupffer cell identity. Kupffer cell loss induced tumor necrosis factor (TNF)- and interleukin-1 (IL-1) receptor-dependent activation of stellate cells and endothelial cells, resulting in the transient production of chemokines and adhesion molecules orchestrating monocyte engraftment. Engrafted circulating monocytes transmigrated into the perisinusoidal space and acquired the liver-associated transcription factors inhibitor of DNA 3 (ID3) and liver X receptor-α (LXR-α). Coordinated interactions with hepatocytes induced ID3 expression, whereas endothelial cells and stellate cells induced LXR-α via a synergistic NOTCH-BMP pathway. This study shows that the Kupffer cell niche is composed of stellate cells, hepatocytes, and endothelial cells that together imprint the liver-specific macrophage identity.

A cellular hierarchy in melanoma uncouples growth and metastasis.

Although melanoma is notorious for its high degree of heterogeneity and plasticity1,2, the origin and magnitude of cell-state diversity remains poorly understood. Equally, it is unclear whether growth and metastatic dissemination are supported by overlapping or distinct melanoma subpopulations. Here, by combining mouse genetics, single-cell and spatial transcriptomics, lineage tracing and quantitative modelling, we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying the cell-fate specification and differentiation of the embryonic neural crest. We show that tumorigenic competence is associated with a spatially localized perivascular niche, a phenotype acquired through an intercellular communication pathway established by endothelial cells. Consistent with a model in which only a fraction of cells are fated to fuel growth, temporal single-cell tracing of a population of melanoma cells with a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but, instead, constitute a pool of metastatic initiating cells that switch cell identity while disseminating to secondary organs. Our data provide a spatially and temporally resolved map of the diversity and trajectories of melanoma cell states and suggest that the ability to support growth and metastasis are limited to distinct pools of cells. The observation that these phenotypic competencies can be dynamically acquired after exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues.

SpatialData: an open and universal data framework for spatial omics.

Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.

The Transcription Factor ZEB2 Is Required to Maintain the Tissue-Specific Identities of Macrophages.

Heterogeneity between different macrophage populations has become a defining feature of this lineage. However, the conserved factors defining macrophages remain largely unknown. The transcription factor ZEB2 is best described for its role in epithelial to mesenchymal transition; however, its role within the immune system is only now being elucidated. We show here that Zeb2 expression is a conserved feature of macrophages. Using Clec4f-cre, Itgax-cre, and Fcgr1-cre mice to target five different macrophage populations, we found that loss of ZEB2 resulted in macrophage disappearance from the tissues, coupled with their subsequent replenishment from bone-marrow precursors in open niches. Mechanistically, we found that ZEB2 functioned to maintain the tissue-specific identities of macrophages. In Kupffer cells, ZEB2 achieved this by regulating expression of the transcription factor LXRα, removal of which recapitulated the loss of Kupffer cell identity and disappearance. Thus, ZEB2 expression is required in macrophages to preserve their tissue-specific identities.

The unfolded-protein-response sensor IRE-1α regulates the function of CD8α+ dendritic cells.

The role of the unfolded protein response (UPR) and endoplasmic reticulum (ER) stress in homeostasis of the immune system is incompletely understood. Here we found that dendritic cells (DCs) constitutively activated the UPR sensor IRE-1α and its target, the transcription factor XBP-1, in the absence of ER stress. Loss of XBP-1 in CD11c+ cells led to defects in phenotype, ER homeostasis and antigen presentation by CD8α+ conventional DCs, yet the closely related CD11b+ DCs were unaffected. Whereas the dysregulated ER in XBP-1-deficient DCs resulted from loss of XBP-1 transcriptional activity, the phenotypic and functional defects resulted from regulated IRE-1α-dependent degradation (RIDD) of mRNAs, including those encoding CD18 integrins and components of the major histocompatibility complex (MHC) class I machinery. Thus, a precisely regulated feedback circuit involving IRE-1α and XBP-1 controls the homeostasis of CD8α+ conventional DCs.

Nlrp6- and ASC-Dependent Inflammasomes Do Not Shape the Commensal Gut Microbiota Composition.

The gut microbiota regulate susceptibility to multiple human diseases. The Nlrp6-ASC inflammasome is widely regarded as a hallmark host innate immune axis that shapes the gut microbiota composition. This notion stems from studies reporting dysbiosis in mice lacking these inflammasome components when compared with non-littermate wild-type animals. Here, we describe microbial analyses in inflammasome-deficient mice while minimizing non-genetic confounders using littermate-controlled Nlrp6-deficient mice and ex-germ-free littermate-controlled ASC-deficient mice that were all allowed to shape their gut microbiota naturally after birth. Careful microbial phylogenetic analyses of these cohorts failed to reveal regulation of the gut microbiota composition by the Nlrp6- and ASC-dependent inflammasomes. Our results obtained in two geographically separated animal facilities dismiss a generalizable impact of Nlrp6- and ASC-dependent inflammasomes on the composition of the commensal gut microbiota and highlight the necessity for littermate-controlled experimental design in assessing the influence of host immunity on gut microbial ecology.

Cell type-specific attenuation of brassinosteroid signaling precedes stomatal asymmetric cell division.

In Arabidopsis thaliana, brassinosteroid (BR) signaling and stomatal development are connected through the SHAGGY/GSK3-like kinase BR INSENSITIVE2 (BIN2). BIN2 is a key negative regulator of BR signaling but it plays a dual role in stomatal development. BIN2 promotes or restricts stomatal asymmetric cell division (ACD) depending on its subcellular localization, which is regulated by the stomatal lineage-specific scaffold protein POLAR. BRs inactivate BIN2, but how they govern stomatal development remains unclear. Mapping the single-cell transcriptome of stomatal lineages after triggering BR signaling with either exogenous BRs or the specific BIN2 inhibitor, bikinin, revealed that the two modes of BR signaling activation generate spatiotemporally distinct transcriptional responses. We established that BIN2 is always sensitive to the inhibitor but, when in a complex with POLAR and its closest homolog POLAR-LIKE1, it becomes protected from BR-mediated inactivation. Subsequently, BR signaling in ACD precursors is attenuated, while it remains active in epidermal cells devoid of scaffolds and undergoing differentiation. Our study demonstrates how scaffold proteins contribute to cellular signal specificity of hormonal responses in plants.

Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition.

Single-cell RNA sequencing (scRNA-seq) approaches have transformed our ability to resolve cellular properties across systems, but are currently tailored toward large cell inputs (>1,000 cells). This renders them inefficient and costly when processing small, individual tissue samples, a problem that tends to be resolved by loading bulk samples, yielding confounded mosaic cell population read-outs. Here, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo, aimed at processing low-input samples (<500 cells). We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single-cell suspensions at high capture efficiency (>70%) and at speeds up to 350 cells per hour. To underscore DisCo's unique capabilities, we analyzed 31 individual intestinal organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a+ stem cell population that persists as symmetrical cysts, or spheroids, even under differentiation conditions, and an uncharacterized 'gobloid' subtype consisting predominantly of precursor and mature (Muc2+) goblet cells. To complement this dataset and to demonstrate DisCo's capacity to process low-input, in vivo-derived tissues, we also analyzed individual mouse intestinal crypts. This revealed the existence of crypts with a compositional similarity to spheroids, which consisted predominantly of regenerative stem cells, suggesting the existence of regenerating crypts in the homeostatic intestine. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity in small, individual tissues.

Efficient cytometry analysis with FlowSOM in Python boosts interoperability with other single-cell tools.

MOTIVATION: We describe a new Python implementation of FlowSOM, a clustering method for cytometry data. RESULTS: This implementation is faster than the original version in R, better adapted to work with single-cell omics data including integration with current single-cell data structures and includes all the original visualizations, such as the star and pie plot. AVAILABILITY AND IMPLEMENTATION: The FlowSOM Python implementation is freely available on GitHub: https://github.com/saeyslab/FlowSOM_Python.

Uncertainty-aware single-cell annotation with a hierarchical reject option.

MOTIVATION: Automatic cell type annotation methods assign cell type labels to new datasets by extracting relationships from a reference RNA-seq dataset. However, due to the limited resolution of gene expression features, there is always uncertainty present in the label assignment. To enhance the reliability and robustness of annotation, most machine learning methods address this uncertainty by providing a full reject option, i.e. when the predicted confidence score of a cell type label falls below a user-defined threshold, no label is assigned and no prediction is made. As a better alternative, some methods deploy hierarchical models and consider a so-called partial rejection by returning internal nodes of the hierarchy as label assignment. However, because a detailed experimental analysis of various rejection approaches is missing in the literature, there is currently no consensus on best practices. RESULTS: We evaluate three annotation approaches (i) full rejection, (ii) partial rejection, and (iii) no rejection for both flat and hierarchical probabilistic classifiers. Our findings indicate that hierarchical classifiers are superior when rejection is applied, with partial rejection being the preferred rejection approach, as it preserves a significant amount of label information. For optimal rejection implementation, the rejection threshold should be determined through careful examination of a method's rejection behavior. Without rejection, flat and hierarchical annotation perform equally well, as long as the cell type hierarchy accurately captures transcriptomic relationships. AVAILABILITY AND IMPLEMENTATION: Code is freely available at https://github.com/Latheuni/Hierarchical_reject and https://doi.org/10.5281/zenodo.10697468.

Yolk Sac Macrophages, Fetal Liver, and Adult Monocytes Can Colonize an Empty Niche and Develop into Functional Tissue-Resident Macrophages.

Tissue-resident macrophages can derive from yolk sac macrophages (YS-Macs), fetal liver monocytes (FL-MOs), or adult bone-marrow monocytes (BM-MOs). The relative capacity of these precursors to colonize a niche, self-maintain, and perform tissue-specific functions is unknown. We simultaneously transferred traceable YS-Macs, FL-MOs, and BM-MOs into the empty alveolar macrophage (AM) niche of neonatal Csf2rb(-/-) mice. All subsets produced AMs, but in competition preferential outgrowth of FL-MOs was observed, correlating with their superior granulocyte macrophage-colony stimulating factor (GM-CSF) reactivity and proliferation capacity. When transferred separately, however, all precursors efficiently colonized the alveolar niche and generated AMs that were transcriptionally almost identical, self-maintained, and durably prevented alveolar proteinosis. Mature liver, peritoneal, or colon macrophages could not efficiently colonize the empty AM niche, whereas mature AMs could. Thus, precursor origin does not affect the development of functional self-maintaining tissue-resident macrophages and the plasticity of the mononuclear phagocyte system is largest at the precursor stage.

IRF8 Transcription Factor Controls Survival and Function of Terminally Differentiated Conventional and Plasmacytoid Dendritic Cells, Respectively.

Interferon regulatory factor-8 (IRF8) has been proposed to be essential for development of monocytes, plasmacytoid dendritic cells (pDCs) and type 1 conventional dendritic cells (cDC1s) and remains highly expressed in differentiated DCs. Transcription factors that are required to maintain the identity of terminally differentiated cells are designated "terminal selectors." Using BM chimeras, conditional Irf8(fl/fl) mice and various promotors to target Cre recombinase to different stages of monocyte and DC development, we have identified IRF8 as a terminal selector of the cDC1 lineage controlling survival. In monocytes, IRF8 was necessary during early but not late development. Complete or late deletion of IRF8 had no effect on pDC development or survival but altered their phenotype and gene-expression profile leading to increased T cell stimulatory function but decreased type 1 interferon production. Thus, IRF8 differentially controls the survival and function of terminally differentiated monocytes, cDC1s, and pDCs.

Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

Dendritic cells (DCs) are professional antigen-presenting cells that hold great therapeutic potential. Multiple DC subsets have been described, and it remains challenging to align them across tissues and species to analyze their function in the absence of macrophage contamination. Here, we provide and validate a universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues. The use of a minimal set of lineage-imprinted markers was sufficient to subdivide DCs into conventional type 1 (cDC1s), conventional type 2 (cDC2s), and plasmacytoid DCs (pDCs) across tissues and species. This way, a large number of additional markers can still be used to further characterize the heterogeneity of DCs across tissues and during inflammation. This framework represents the way forward to a universal, high-throughput, and standardized analysis of DC populations from mutant mice and human patients.

Functions of the RIP kinase family members in the skin.

The receptor interacting protein kinases (RIPK) are a family of serine/threonine kinases that are involved in the integration of various stress signals. In response to several extracellular and/or intracellular stimuli, RIP kinases engage signaling cascades leading to the activation of NF-κB and mitogen-activated protein kinases, cell death, inflammation, differentiation and Wnt signaling and can have kinase-dependent and kinase-independent functions. Although it was previously suggested that seven RIPKs are part of the RIPK family, phylogenetic analysis indicates that there are only five genuine RIPKs. RIPK1 and RIPK3 are mainly involved in controlling and executing necroptosis in keratinocytes, while RIPK4 controls proliferation and differentiation of keratinocytes and thereby can act as a tumor suppressor in skin. Therefore, in this review we summarize and discuss the functions of RIPKs in skin homeostasis as well as the signaling pathways involved.