Proliferation-driven mechanical compression induces signalling centre formation during mammalian organ development.

Localized sources of morphogens, called signalling centres, play a fundamental role in coordinating tissue growth and cell fate specification during organogenesis. However, how these signalling centres are established in tissues during embryonic development is still unclear. Here we show that the main signalling centre orchestrating development of rodent incisors, the enamel knot (EK), is specified by a cell proliferation-driven buildup in compressive stresses (mechanical pressure) in the tissue. Direct mechanical measurements indicate that the stresses generated by cell proliferation are resisted by the surrounding tissue, creating a circular pattern of mechanical anisotropy with a region of high compressive stress at its centre that becomes the EK. Pharmacological inhibition of proliferation reduces stresses and suppresses EK formation, and application of external pressure in proliferation-inhibited conditions rescues the formation of the EK. Mechanical information is relayed intracellularly through YAP protein localization, which is cytoplasmic in the region of compressive stress that establishes the EK and nuclear in the stretched anisotropic cells that resist the pressure buildup around the EK. Together, our data identify a new role for proliferation-driven mechanical compression in the specification of a model signalling centre during mammalian organ development.

High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis.

Single-cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical samples. Current commercially available technologies provide whole transcriptome single-cell, whole transcriptome spatial, or targeted in situ gene expression analysis. Here, we combine these technologies to explore tissue heterogeneity in large, FFPE human breast cancer sections. This integrative approach allowed us to explore molecular differences that exist between distinct tumor regions and to identify biomarkers involved in the progression towards invasive carcinoma. Further, we study cell neighborhoods and identify rare boundary cells that sit at the critical myoepithelial border confining the spread of malignant cells. Here, we demonstrate that each technology alone provides information about molecular signatures relevant to understanding cancer heterogeneity; however, it is the integration of these technologies that leads to deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

Spatial transcriptomic interrogation of the murine bone marrow signaling landscape.

Self-renewal and differentiation of skeletal stem and progenitor cells (SSPCs) are tightly regulated processes, with SSPC dysregulation leading to progressive bone disease. While the application of single-cell RNA sequencing (scRNAseq) to the bone field has led to major advancements in our understanding of SSPC heterogeneity, stem cells are tightly regulated by their neighboring cells which comprise the bone marrow niche. However, unbiased interrogation of these cells at the transcriptional level within their native niche environment has been challenging. Here, we combined spatial transcriptomics and scRNAseq using a predictive modeling pipeline derived from multiple deconvolution packages in adult mouse femurs to provide an endogenous, in vivo context of SSPCs within the niche. This combined approach localized SSPC subtypes to specific regions of the bone and identified cellular components and signaling networks utilized within the niche. Furthermore, the use of spatial transcriptomics allowed us to identify spatially restricted activation of metabolic and major morphogenetic signaling gradients derived from the vasculature and bone surfaces that establish microdomains within the marrow cavity. Overall, we demonstrate, for the first time, the feasibility of applying spatial transcriptomics to fully mineralized tissue and present a combined spatial and single-cell transcriptomic approach to define the cellular components of the stem cell niche, identify cell‒cell communication, and ultimately gain a comprehensive understanding of local and global SSPC regulatory networks within calcified tissue.

A robust platform for integrative spatial multi-omics analysis to map immune responses to SARS-CoV-2 infection in lung tissues.

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid and similar, but a robust platform for deep tissue characterization of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues. Five tissue-profiling technologies were combined by a novel computational mapping methodology to comprehensively characterize and compare the transcriptome and targeted proteome of virus infected and uninfected tissues. By integrating spatial transcriptomics data (Visium, GeoMx and RNAScope) and proteomics data (CODEX and PhenoImager HT) at different cellular resolutions across lung tissues, we found strong evidence for macrophage infiltration and defined the broader microenvironment surrounding these cells. By comparing infected and uninfected samples, we found an increase in cytokine signalling and interferon responses at different sites in the lung and showed spatial heterogeneity in the expression level of these pathways. These data demonstrate that integrative spatial multi-omics platforms can be broadly applied to gain a deeper understanding of viral effects on cellular environments at the site of infection and to increase our understanding of the impact of SARS-CoV-2 on the lungs.

A Suite of Mouse Reagents for Studying Amelogenesis.

Amelogenesis, the formation of dental enamel, is driven by specialized epithelial cells called ameloblasts, which undergo successive stages of differentiation. Ameloblasts secrete enamel matrix proteins (EMPs), proteases, calcium, and phosphate ions in a stage-specific manner to form mature tooth enamel. Developmental defects in tooth enamel are common in humans, and they can greatly impact the well-being of affected individuals. Our understanding of amelogenesis and developmental pathologies is rooted in past studies using epithelial Cre driver and knockout alleles. However, the available mouse models are limited, as most do not allow targeting different ameloblast sub-populations, and constitutive loss of EMPs often results in severe phenotype in the mineral, making it difficult to interpret defect mechanisms. Herein, we report on the design and verification of a toolkit of twelve mouse alleles that include ameloblast-stage specific Cre recombinases, fluorescent reporter alleles, and conditional flox alleles for the major EMPs. We show how these models may be used for applications such as sorting of live stage specific ameloblasts, whole mount imaging, and experiments with incisor explants. The full list of new alleles is available at https://dev.facebase.org/enamelatlas/mouse-models/ .