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Murine dermis contains functionally and spatially distinct fibroblast lineages that cease to proliferate in early postnatal life. Here, we propose a model in which a negative feedback loop between extracellular matrix (ECM) deposition and fibroblast proliferation determines dermal architecture. Virtual‐tissue simulations of our model faithfully recapitulate dermal maturation, predicting a loss of spatial segregation of fibroblast lineages and dictating that fibroblast migration is only required for wound healing. To test this, we performed in vivo live imaging of dermal fibroblasts, which revealed that homeostatic tissue architecture is achieved without active cell migration. In contrast, both fibroblast proliferation and migration are key determinants of tissue repair following wounding. The results show that tissue‐scale coordination is driven by the interdependence of cell proliferation and ECM deposition, paving the way for identifying new therapeutic strategies to enhance skin regeneration. Synopsis In vivo live imaging of dermal fibroblasts combined with mathematical modeling shows that fibroblast behaviour switching between two distinct states—proliferating and depositing ECM—defines dermal architecture. These findings are relevant for identifying new therapeutic strategies for skin regeneration. Tissue‐scale coordination in murine dermis is driven by the interdependence of cell proliferation and ECM deposition. The tissue architecture is set by a negative feedback loop between ECM deposition/remodelling and proliferation. Fibroblast lineages lose segregation with age. Fibroblast migration is the critical discriminator between dermal development and wound healing. Graphical Abstract In vivo live imaging of dermal fibroblasts combined with mathematical modeling shows that fibroblast behaviour switching between two distinct states—proliferating and depositing ECM—defines dermal architecture. These findings are relevant for identifying new therapeutic strategies for skin regeneration.

The heterogeneity and the complex cellular architecture have a crucial effect on breast cancer progression and response to treatment. However, deciphering the neoplastic subtypes and their spatial organization is still challenging. Here, we combine single-nucleus RNA sequencing (snRNA-seq) with a microarray-based spatial transcriptomics (ST) to identify cell populations and their spatial distribution in breast cancer tissues. Malignant cells are clustered into distinct subpopulations. These cell clusters not only have diverse features, origins and functions, but also emerge to the crosstalk within subtypes. Furthermore, we find that these subclusters are mapped in distinct tissue regions, where discrepant enrichment of stromal cell types are observed. We also inferred the abundance of these tumorous subpopulations by deconvolution of large breast cancer RNA-seq cohorts, revealing differential association with patient survival and therapeutic response. Our study provides a novel insight for the cellular architecture of breast cancer and potential therapeutic strategies.

The organization of cells into epithelium depends on cell interaction with both the extracellular matrix (ECM) and adjacent cells. The role of cell–cell adhesion in the regulation of epithelial topology is well-described. ECM is better known to promote cell migration and provide a structural scaffold for cell anchoring, but its contribution to multicellular morphogenesis is less well-understood. We developed a minimal model system to investigate how ECM affects the spatial organization of intercellular junctions. Fibronectin micropatterns were used to constrain the location of cell–ECM adhesion. We found that ECM affects the degree of stability of intercellular junction positioning and the magnitude of intra- and intercellular forces. Intercellular junctions were permanently displaced, and experienced large perpendicular tensional forces as long as they were positioned close to ECM. They remained stable solely in regions deprived of ECM, where they were submitted to lower tensional forces. The heterogeneity of the spatial organization of ECM induced anisotropic distribution of mechanical constraints in cells, which seemed to adapt their position to minimize both intra- and intercellular forces. These results uncover a morphogenetic role for ECM in the mechanical regulation of cells and intercellular junction positioning.

Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high‐resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology‐specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain. Synopsis Vesalius is a computational tool for recovering tissue territories from spatial transcriptomics data using image processing technology. Vesalius illustrates how uniform tissue territories can help understanding tissue heterogeneity. Vesalius leverages image analysis to investigate spatial transcriptomics data by embedding the transcriptome into RGB image arrays. Vesalius provides uniform tissue territories from high resolution spatial transcriptomics data. Downstream analysis of isolated tissue territories reveals the finer details of spatial patterning as well as tissue specific gene expression within cell types. Graphical Abstract Vesalius is a computational tool for recovering tissue territories from spatial transcriptomics data using image processing technology. Vesalius illustrates how uniform tissue territories can help understanding tissue heterogeneity.

Organismal phenotypes frequently involve multiple organ systems. Histology is a powerful way to detect cellular and tissue phenotypes, but is largely descriptive and subjective. To determine how synchrotron-based X-ray micro-tomography (micro-CT) can yield 3-dimensional whole-organism images suitable for quantitative histological phenotyping, we scanned whole zebrafish, a small vertebrate model with diverse tissues, at ~1 micron voxel resolutions. Micro-CT optimized for cellular characterization (histotomography) allows brain nuclei to be computationally segmented and assigned to brain regions, and cell shapes and volumes to be computed for motor neurons and red blood cells. Striking individual phenotypic variation was apparent from color maps of computed densities of brain nuclei. Unlike histology, the histotomography also allows the study of 3-dimensional structures of millimeter scale that cross multiple tissue planes. We expect the computational and visual insights into 3D cell and tissue architecture provided by histotomography to be useful for reference atlases, hypothesis generation, comprehensive organismal screens, and diagnostics. Diagnosing diseases, such as cancer, requires scientists and doctors to understand how cells respond to different medical conditions. A common way of studying these microscopic cell changes is by an approach called histology: thin slices of centimeter-sized samples of tissues are taken from patients, stained to distinguish cellular components, and examined for abnormal features. This powerful technique has revolutionized biology and medicine. But despite its frequent use, histology comes with limitations. To allow individual cells to be distinguished, tissues are cut into slices less than 1/20th of a millimeter thick. Histology’s dependence upon such thin slices makes it impossible to see the entirety of cells and structures that are thicker than the slice, or to accurately measure three-dimensional features such as shape or volume. Larger internal structures within the human body are routinely visualized using a technique known as computerized tomography, CT for short – whereby dozens of x-ray images are compiled together to generate a three-dimensional image. This technique has also been applied to image smaller structures. However, the resolution (the ability to distinguish between objects) and tissue contrast of these images has been insufficient for histology-based diagnosis across all cell types. Now, Ding et al. have developed a new method, by optimizing multiple components of CT scanning, that begins to provide the higher resolution and contrast needed to make diagnoses that require histological detail. To test their modified CT system, Ding et al. created three-dimensional images of whole zebrafish, measuring three millimeters to about a centimeter in length. Adjusting imaging parameters and views of these images made it possible to study features of larger-scale structures, such as the gills and the gut, that are normally inaccessible to histology. As a result of this unprecedented combination of high resolution and scale, computer analysis of these images allowed Ding et al. to measure cellular features such as size and shape, and to determine which cells belong to different brain regions, all from single reconstructions. Surprisingly, visualization of how tightly the brain cells are packed revealed striking differences between the brains of sibling zebrafish that were born the same day. This new method could be used to study changes across hundreds of cell types in any millimeter to centimetre-sized organism or tissue sample. In the future, the accurate measurements of microscopic features made possible by this new tool may help us to make drugs safer, improve tissue diagnostics, and care for our environment.

Most tumor cells derive from MHC-I-positive normal counterparts and remain positive at early stages of tumor development. T lymphocytes can infiltrate tumor tissue, recognize and destroy MHC class I (MHC-I)-positive cancer cells (“permissive” phase I). Later, MHC-I-negative tumor cell variants resistant to T-cell killing emerge. During this process, tumors first acquire a heterogeneous MHC-I expression pattern and finally become uniformly MHC-I-negative. This stage (phase II) represents a “non-permissive” encapsulated structure with tumor nodes surrounded by fibrous tissue containing different elements including leukocytes, macrophages, fibroblasts, etc. Molecular mechanisms responsible for total or partial MHC-I downregulation play a crucial role in determining and predicting the antigen-presenting capacity of cancer cells. MHC-I downregulation caused by reversible (“soft”) lesions can be upregulated by TH1-type cytokines released into the tumor microenvironment in response to different types of immunotherapy. In contrast, when the molecular mechanism of the tumor MHC-I loss is irreversible (“hard”) due to a genetic defect in the gene/s coding for MHC-I heavy chains (chromosome 6) or beta-2-microglobulin (B2M) (chromosome 15), malignant cells are unable to upregulate MHC-I, remain undetectable by cytotoxic T-cells, and continue to grow and metastasize. Based on the tumor MHC-I molecular analysis, it might be possible to define MHC-I phenotypes present in cancer patients in order to distinguish between non-responders, partial/short-term responders, and likely durable responders. This highlights the need for designing strategies to enhance tumor MHC-I expression that would allow CTL-mediated tumor rejection.

This study investigated the effects of Lacticaseibacillus rhamnosus HN001 supplementation on the architecture and gene expression in small intestinal tissues of piglets used as an animal model for infant humans. Twenty-four 10-d-old entire male piglets (4·3 (sd 0·59) kg body weight) were fed an infant formula (IF) (control) or IF supplemented with 1·3 × 105 (low dose) or 7·9 × 106 (high dose) colony-forming units HN001 per ml of reconstituted formula (n 8 piglets/treatment). After 24 d, piglets were euthanised. Samples were collected to analyse the histology and gene expression (RNAseq and qPCR) in the jejunal and ileal tissues, blood cytokine concentrations, and blood and faecal calprotectin concentrations. HN001 consumption altered (false discovery rate < 0·05) gene expression (RNAseq) in jejunal tissues but not in ileal tissues. The number of ileal goblet cells and crypt surface area increased quadratically (P < 0·05) as dietary HN001 levels increased, but no increase was observed in the jejunal tissues. Similarly, blood plasma concentrations of IL-10 and calprotectin increased linearly (P < 0·05) as dietary HN001 levels increased. In conclusion, supplementation of IF with HN001 affected the architecture and gene expression of small intestine tissue, blood cytokine concentration and frequencies, and blood calprotectin concentrations, indicating that HN001 modulated small intestinal tissue maturation and immunity in the piglet model.

Spatiotemporal control of leukocyte dynamics within tissues is critical for successful innate and adaptive immune responses. Homeostatic trafficking and coordinated infiltration into and within sites of inflammation and infection rely on signaling in response to extracellular cues that in turn controls a variety of intracellular protein networks regulating leukocyte motility, migration, chemotaxis, positioning, and cell–cell interaction. In contrast to mesenchymal cells, leukocytes migrate in an amoeboid fashion by rapid cycles of actin polymerization and actomyosin contraction, and their migration in tissues is generally referred to as low adhesive and nonproteolytic. The interplay of actin network expansion, contraction, and adhesion shapes the exact mode of amoeboid migration, and in this review, we explore how leukocyte subsets potentially harness the same basic biomechanical mechanisms in a cell-type-specific manner. Most of our detailed understanding of these processes derives from in vitro migration studies in three-dimensional gels and confined spaces that mimic geometrical aspects of physiological tissues. We summarize these in vitro results and then critically compare them to data from intravital imaging of leukocyte interstitial migration in mouse tissues. We outline the technical challenges of obtaining conclusive mechanistic results from intravital studies, discuss leukocyte migration strategies in vivo, and present examples of mode switching during physiological interstitial migration. These findings are also placed in the context of leukocyte migration defects in primary immunodeficiencies. This overview of both in vitro and in vivo studies highlights recent progress in understanding the molecular and biophysical mechanisms that shape robust leukocyte migration responses in physiologically complex and heterogeneous environments.

Analyses of patients with early-stage, treatment-naïve triple-negative breast cancer (TNBC) have demonstrated that high glucocorticoid receptor (GR) expression in primary tumors is associated with poor prognosis. We previously observed that GR-high primary TNBCs exhibited significantly increased numbers of tumor-infiltrating regulatory T cells (Tregs) compared with GR-low tumors. To further investigate GR-associated immunologic features, we leveraged imaging mass cytometry (IMC) to profile additional immune cell phenotypes and spatial architecture in GR-high versus GR-low primary TNBC. Tumor-infiltrating immune cells were profiled in formalin-fixed paraffin-embedded (FFPE) core biopsies from five untreated GR-high and four GR-low TNBC tumors using IMC with a 21-antibody panel. Regions of interest (ROI) were selected within pan-cytokeratin-positive tumor nests. Data underwent unsupervised clustering, and cell types were identified based on protein expression profiles. Analyses compared cell-type abundance and spatial interactions in GR-high versus GR-low tumors. GR-high tumors exhibited significantly greater Treg infiltration within tumor nests than GR-low tumors. GR-high TNBC also showed a comparatively greater abundance of activated memory CD8+ T cells, cytotoxic CD4+ T cells, and effector memory CD4+ T cells. In contrast, GR-low tumors exhibited relatively greater representation of HLA-ABC-positive (HLA-ABC+) cancer cells as well as early-activated dendritic cells (DCs) and natural killer (NK) cells. Spatial analysis revealed that Tregs in GR-high tumors colocalized more frequently with proliferating tumor cells relative to Tregs in GR-low tumors. NK cells in GR-high tumors displayed relatively less colocalization with proliferating tumor cells. Compared with GR-low disease, treatment-naïve GR-high primary TNBC exhibits a more immunosuppressive tumor microenvironment characterized by greater Treg density, closer Treg-cancer cell proximity, reduced NK cell infiltration, impaired immune surveillance, and decreased abundance of HLA-ABC+ cancer cells. These findings implicate TNBC cell GR signaling as immunosuppressive, likely through mechanisms resulting in both differential immune cell enrichment and altered spatial organization.

Mammary gland development, functional differentiation, and homeostasis are orchestrated and sustained by a balance of biochemical and biophysical cues from the organ’s microenvironment. The three-dimensional microenvironment of the mammary gland, predominantly ‘encoded’ by a collaboration between the extracellular matrix (ECM), hormones, and growth factors, sends signals from ECM receptors through the cytoskeletal intracellular matrix to nuclear and chromatin structures resulting in gene expression; the ECM in turn is regulated and remodeled by signals from the nucleus. In this chapter, we discuss how coordinated ECM deposition and remodeling is necessary for mammary gland development, how the ECM provides structural and biochemical cues necessary for tissue-specific function, and the role of the cytoskeleton in mediating the extra—to intracellular dialogue occurring between the nucleus and the microenvironment. When operating normally, the cytoskeletal-mediated dynamic and reciprocal integration of tissue architecture and function directs mammary gland development, tissue polarity, and ultimately, tissue-specific gene expression. Cancer occurs when these dynamic interactions go awry for an extended time.