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Background In this paper, we introduce an image analysis approach for spatiotemporal segmentation, quantification, and visualization of movement or contraction patterns in 2D+t and 3D+t microscopy recordings of biological tissues. The development of this pipeline was motivated by the observation of contraction waves in the extra-embryonic membranes of the red flour beetle Tribolium castaneum . These contraction waves are a novel finding, whose origin and function are not yet understood. The objective of the proposed approach is to analyze the dynamics of the extra-embryonic membranes in order to provide quantitative evidence for the existence of contraction waves during late stages of embryonic development. Results We apply the pipeline to live-imaging data of Tribolium embryonic development recorded with light-sheet fluorescence microscopy. The proposed pipeline integrates particle image velocimetry (PIV) for quantitative movement analysis, surface detection, tissue cartography, and algorithmic identification of characteristic movement dynamics. We demonstrate that our approach reliably and efficiently detects contraction waves in both 2D+t and 3D+t recordings and enables automated quantitative analyses, such as measuring the area involved in contractile behavior, wave duration and frequency, spatiotemporal location of the contractile regions, and their relation to the underlying velocity distribution. Conclusions The pipeline will be employed in future work to conduct a large-scale characterization and quantification of contraction wave behavior in Tribolium development and can be readily adapted for the identification and segmentation of characteristic tissue dynamics in other biological systems.

Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can identify specific compartments or regions in a tissue with differential transcript or protein abundance, delineate their interactions, and complement other methods in defining cellular phenotypes. A variety of spatial methodologies are being developed and commercialized; however, these techniques differ in spatial resolution, multiplexing capability, scale/throughput, and coverage. Here, we review the current and prospective landscape of single cell to subcellular resolution spatial omics technologies and analysis tools to provide a comprehensive picture for both research and clinical applications.

Multiplexed RNA sequencing in individual cells is transforming basic and clinical life sciences 1 – 4 . Often, however, tissues must first be dissociated, and crucial information about spatial relationships and communication between cells is thus lost. Existing approaches to reconstruct tissues assign spatial positions to each cell, independently of other cells, by using spatial patterns of expression of marker genes 5 , 6 —which often do not exist. Here we reconstruct spatial positions with little or no prior knowledge, by searching for spatial arrangements of sequenced cells in which nearby cells have transcriptional profiles that are often (but not always) more similar than cells that are farther apart. We formulate this task as a generalized optimal-transport problem for probabilistic embedding and derive an efficient iterative algorithm to solve it. We reconstruct the spatial expression of genes in mammalian liver and intestinal epithelium, fly and zebrafish embryos, sections from the mammalian cerebellum and whole kidney, and use the reconstructed tissues to identify genes that are spatially informative. Thus, we identify an organization principle for the spatial expression of genes in animal tissues, which can be exploited to infer meaningful probabilities of spatial position for individual cells. Our framework (‘novoSpaRc’) can incorporate prior spatial information and is compatible with any single-cell technology. Additional principles that underlie the cartography of gene expression can be tested using our approach. A new computational framework, novoSpaRc, leverages single-cell data to reconstruct spatial context for cells and spatial expression across tissues and organisms, on the basis of an organization principle for gene expression.

A hyperinflammatory ‘cytokine storm’ state termed macrophage activation syndrome (MAS), culminating from a complex interplay of genetics, immunodeficiency, infectious triggers and dominant innate immune effector responses, can develop across disparate entities including systemic juvenile idiopathic arthritis (sJIA) and its counterpart adult-onset Still disease (AOSD), connective tissue diseases, sepsis, infection, cancers and cancer immunotherapy. Classifying MAS using the immunological disease continuum model, with strict boundaries that define the limits of innate and adaptive immunity, at one boundary is MAS with loss of immune function, as occurs in the ‘perforinopathies’ and some cases of sJIA–AOSD. Conversely, at the other boundary, immune hypersensitivity with gain of immune function in MHC class II-associated sJIA–AOSD and with chimeric antigen receptor (CAR) T cell therapy also triggers MAS. This provides a benchmark for evaluating severe inflammation in some patients with COVID-19 pneumonia, which cripples primary type I interferon immunity and usually culminates in a lung-centric ‘second wave’ cytokine-driven alveolitis with associated immunothrombosis; this phenomenon is generally distinct from MAS but can share features with the proposed ‘loss of immune function’ MAS variant. This loss and gain of function MAS model offers immune cartography for a novel mechanistic classification of MAS with therapeutic implications.In this Review, the authors discuss macrophage activation syndrome (MAS) in relation to other cytokine storm scenarios, and provide a framework for understanding MAS within the spectrum of innate and adaptive immunity in the context of gain or loss of immune function.

Morphogenesis, the process through which genes generate form, establishes tissue-scale order as a template for constructing the complex shapes of the body plan. The extensive growth required to build these ordered substrates is fuelled by cell proliferation, which, naively, should destroy order. Understanding how active morphogenetic mechanisms couple cellular and mechanical processes to generate order—rather than annihilate it—remains an outstanding question in animal development. We show that cell divisions are the primary drivers of tissue flow, leading to a fourfold orientationally ordered phase. Waves of anisotropic cell proliferation propagate across the embryo with precise patterning. Defects introduced into the nascent lattice by cell divisions are moved out of the tissue bulk towards the boundary by subsequent divisions. Specific cell proliferation rates and orientations enable cell divisions to organize rather than fluidize the tissue. We observe this using live imaging and tissue cartography to analyse the dynamics of fourfold tissue ordering in the trunk segmental ectoderm of the crustacean Parhyale hawaiensis beginning 72 h after egg lay. The result is a robust, active mechanism for generating global orientational order in a non-equilibrium system that sets the stage for the subsequent development of shape and form.In the crustacean Parhyale hawaiensis, the analysis of the dynamics of fourfold tissue ordering reveals cell divisions as the underlying mechanism.

Synaptic adhesion molecules (SAMs) are evolutionarily conserved proteins that play an important role in the form and function of neuronal synapses. Teneurins (Tenms) and latrophilins (Lphns) are well-known cell adhesion molecules that form a transsynaptic complex. Recent studies suggest that Tenm3 and Lphn2 (gene symbol Adgrl2 ) are involved in hippocampal circuit assembly via their topographical expression. However, it is not known whether other teneurins and latrophilins display similar topographically restricted expression patterns during embryonic and postnatal development. Here, we reveal the cartography of all teneurin ( Tenm1-4 ) and latrophilin (Lphn1-3 [ Adgrl1-3 ]) paralog expression in the mouse hippocampus across prenatal and postnatal development as monitored by large-scale single-molecule RNA in situ hybridization mapping. Our results identify a striking heterogeneity in teneurin and latrophilin expression along the spatiotemporal axis of the hippocampus. Tenm2 and Tenm4 expression levels peak at the neonatal stage when compared to Tenm1 and Tenm3, while Tenm1 expression is restricted to the postnatal pyramidal cell layer. Tenm4 expression in the dentate gyrus (DG) exhibits an opposing topographical expression pattern in the embryonic and neonatal hippocampus. Our findings were validated by analyses of multiple RNA-seq datasets at bulk, single-cell, and spatial levels. Thus, our study presents a comprehensive spatiotemporal map of Tenm and Lphn expression in the hippocampus, showcasing their diverse expression patterns across developmental stages in distinct spatial axes.

Multiplexed platforms for multiple epitope detection have emerged in the last years as very powerful tools to study tumor tissues. These revolutionary technologies provide important visual techniques for tumor examination in formalin-fixed paraffin-embedded specimens to improve the understanding of the tumor microenvironment, promote new treatment discoveries, aid in cancer prevention, as well as allowing translational studies to be carried out. The aim of this review is to highlight the more recent methodologies that use multiplexed staining to study simultaneous protein identification in formalin-fixed paraffin-embedded tumor tissues for immune profiling, clinical research, and potential translational analysis. New multiplexed methodologies, which permit the identification of several proteins at the same time in one single tissue section, have been developed in recent years with the ability to study different cell populations, cells by cells, and their spatial distribution in different tumor specimens including whole sections, core needle biopsies, and tissue microarrays. Multiplexed technologies associated with image analysis software can be performed with a high-quality throughput assay to study cancer specimens and are important tools for new discoveries. The different multiplexed technologies described in this review have shown their utility in the study of cancer tissues and their advantages for translational research studies and application in cancer prevention and treatments.

Psoriasis has a complex immune microenvironment yet most spatial analyses remain two dimensional with routine histopathology. We examined whether immunohistochemistry (IHC) combined with three-dimensional (3D) digital reconstruction can quantify the immune-epithelial architecture across the psoriatic spectrum. Serial sections from 15 psoriasis patients (with lesional and peri-lesional skin 1 cm away from the psoriatic plaque) and 52 healthy donors were reconstructed into 174 tissue stacks (10,700 whole-slide images). CD3 + T cells, CD68 + myeloid cells and mast cells were mapped in 3D including their Euclidean distance to dermal–epidermal junction (DEJ). Compared with healthy controls, CD3 + clusters were redistributed towards the superficial dermis, with reduced distance to the DEJ in peri-lesional and lesional skin in psoriatic patients; CD68 + clusters showed a similar superficial shift in established plaques. In contrast, mast cell density and DEJ proximity did not differ between groups. Averaging multiple 2D sections obscured these distributional features, underscoring the value of volumetric analysis in spatial studies. Therefore, high-resolution 3D reconstruction reliably maps the spatial dynamics of T cells, macrophages and mast cells across the psoriatic spectrum. This accessible pipeline extends routine histopathology by providing quantitative 3D spatial metrics that complement routine conventional histology and may inform integration with higher-plex spatial platforms.

The intricate interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Micro biome Cart ography (MicroCart), a framework for simultaneous in situ probing of host and microbiome across multiple spatial modalities. We demonstrate MicroCart by investigating gut host and microbiome changes in a murine colitis model, using spatial proteomics, transcriptomics, and glycomics. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multi-omics. The interaction between the host immune response and the component organisms forming the microbiota is critical during homeostatic but all pathological contexts. Here the authors use a multi-omics spatial approach to dissect and characterise host and microbiome in a murine model of intestinal inflammation.

Spatial transcriptomics has transformed our understanding of gene expression by preserving the spatial context within tissues. This review focuses on the application of spatial transcriptomics in human cardiac tissues, exploring current technologies with a focus on commercially available platforms. We also highlight key studies utilizing spatial transcriptomics to investigate cardiac development, electro-anatomy, immunology, and ischemic heart disease. These studies demonstrate how spatial transcriptomics can be used in conjunction with other omics technologies to provide a more comprehensive picture of human health and disease. Despite its transformative potential, spatial transcriptomics comes with several challenges that limit its widespread adoption and broader application. By addressing these limitations and fostering interdisciplinary collaboration, spatial transcriptomics has the potential to become an essential tool in cardiovascular research. We hope this review serves as a practical guide for researchers interested in adopting spatial transcriptomics, particularly those with limited prior experience, by providing insights into current technologies, applications, and considerations for successful implementation.