Biology subjects

Prete, M.

Publications and source records attributed to Prete, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Function-driven geometry directs human pilosebaceous unit development

Single-cell technologies have generated cell censuses of tissues, however, how tissue geometry reflects functional needs remains poorly characterized. The human pilosebaceous unit offers a tractable model, a prenatally-formed complex mini-organ combining hair and sebum production with a stem cell reservoir. Using histomorphology, spatial transcriptomics, and single-cell multiomics on the same human prenatal scalp skin samples (8-19 post-conception weeks), integrated and analyzed using machine learning approaches, we built a spatiotemporal map of pilosebaceous unit development. We demonstrate that epithelial-mesenchymal interactions coordinate cellular fate and organogenesis, using an in vitro hair-bearing skin organoid model to validate this tissue-patterning. In addition, we show sebaceous gland developmental programmes are overcome during tumor formation. Our large-scale multi-modal analysis provides a unique framework for understanding form and function of tissues with applications in tissue engineering and pathology.

developmental biology↗

bioRxiv2026

Multi-scale modeling of human tissues from spatial transcriptomics with TERRA

Spatial transcriptomics maps gene expression at cellular resolution, revealing how cells organize into multicellular niches. Yet computational analyses remain dataset-specific, without a transferable representation of tissue organization that generalizes across datasets, tasks and tissues or predicts how tissues behave under perturbation. We present TERRA, a foundation model pretrained on 112 million human cells profiled by spatial transcriptomics. From a single pretrained backbone, TERRA yields embeddings at the scale of cells, the genes they express and the neighborhoods in which they reside, and supports spatial in silico perturbation, all applied zero-shot to unseen tissues. At the cell level, in newly generated spatial data for developing pancreas, TERRA identified an islet-associated capillary state which we posit represents a developmental precursor of the mature islet microvasculature. At the gene level, in untreated kidney sections, in silico knockout of immune-checkpoint targets predicted a gene program of immune-checkpoint-blockade-associated nephrotoxicity, which we validated in treatment-exposed tissue and recovered in blood. At the neighborhood level, TERRA mapped macrophages across tissues to identify recurring cross-organ niches, which we term archetypes, including a tumor-boundary niche associated with poor prognosis in kidney cancer. Together, TERRA captures the spatial and multicellular logic of human tissue and predicts, in silico, its response to perturbation, providing a multi-scale framework for tissue biology, therapeutic development and clinical application.

genomics↗

bioRxiv2026

A multimodal interrogation of Broca's area in the pediatric and adult human brain

Language is a defining trait of our species, and disruptions in language acquisition can have profound consequences to the individuals affected. Uncovering the neurodevelopmental basis of this complex trait requires detailed molecular and cellular insights into the neocortical areas that support linguistic abilities. Here we performed joint gene expression and chromatin accessibility profiling at single-nucleus resolution (10x Genomics Single cell Multiome) and spatial transcriptomic profiling (Xenium high-plex in situ spatial transcriptomics) of Brocas area alongside adjacent motor cortical areas. We profiled individuals from different ancestries (European and African) and developmental stages (infancy, childhood, adolescence, and adulthood). We provide a high-resolution dissection of the cellular and molecular architecture of Brocas and motor cortical areas across early life stages and anchor the trajectories to the cellular states found in the adult human brain. We identify distinct area- and stage-specific cellular signatures, including a prominent role of glia populations and interneuron subtypes contributing to cytoarchitectonic specializations. Using longitudinal single cell spatial transcriptomic profiling, we orthogonally validate our consensus cell taxonomy and spatially resolve layer enrichment of neuronal and astrocyte subtypes that distinguish Brocas area and motor cortex. We also uncover cell type-specific molecular signatures that distinguish cell developmental trajectories in these cortical areas, including an early molecular code established by differential expression of cadherin genes that might contribute to area-specific intercellular communication. We also identify cell type-specific vulnerabilities to language- related neurodevelopmental and neuropsychiatric disorders, with selective susceptibility of particular somatostatin-positive interneuron subtypes to ASD/ADHD. Finally, evolutionary analysis of differentially accessible regions between Brocas area and motor cortex suggests that genetic mutations that might have contributed to the emergence of linguistic abilities accumulated over the course of million years following the divergence of human and chimpanzee lineages. Together, our study provides a comprehensive molecular, cellular and spatial definition of Brocas area and motor cortex, laying the groundwork for investigations into unique aspects of human cognition and related neurodevelopmental and neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

Full-thickness spatial transcriptomics of the human uterus reveals basalis niche architecture and regeneration gradients during menstrual breakdown

The human endometrium (uterine lining) undergoes cyclical breakdown and scarless regeneration during each menstrual cycle, representing an exceptional model of adult tissue renewal. Regeneration is driven primarily by progenitor cells retained within the deep, basalis compartment during menstruation, yet the full-depth spatiotemporal dynamics of this process have remained understudied due to anatomical and technical limitations. Here, we map spatial gene-expression gradients across the full thickness of the human endometrium, from the myometrial-endometrial boundary to the luminal surface, using high-resolution spatial transcriptomics integrated with single-cell transcriptomics. We profile more than ten million cells from biopsies, hysterectomy samples and menstrual fluid, enriching for the menstrual and proliferative phases, which are underrepresented in previous studies. We show that endometrial breakdown, regeneration and rapid luminal re-epithelialisation are concurrent rather than temporally separated, organised across distinct tissue compartments, revealing a mode of tissue renewal in which shedding and repair operate simultaneously. Continuous basalis-to-luminal transcriptional gradients link progenitor identity, niche signalling, and tissue remodelling, defining a coordinated regenerative axis spanning the full tissue depth. We resolve the basalis epithelial niche at unprecedented molecular resolution, identifying for the first time a discrete, predominantly quiescent progenitor-like epithelial subset and specialised supporting SFRP5+ fibroblasts, both characterised by WNT inhibition, alongside lymphoid aggregates, forming a multi-component architecture that persists after menopause, consistent with a long-lived regenerative reservoir. Together, these findings establish spatial transcriptional gradients as a central organising principle of endometrial renewal, providing a molecular framework for understanding disorders of menstruation, implantation failure, and impaired tissue repair.

cell biology↗

bioRxiv2026

Spatial atlas of the ovary identifies molecular events in primordial follicle activation in humans

The human ovarian reserve is established prenatally, when granulosa cells encapsulate germ cells to form a pool of quiescent primordial follicles, that ultimately determines the female reproductive and endocrine lifespan. From birth to menopause, subsets of these quiescent follicles, located in the thin outer ovarian cortex, are activated and undergo a growth programme with progressive inward migration to the inner cortex, before either undergoing atresia or, during reproductive age, ovulation. Disruption of this process may lead to infertility, metabolic disorders and early menopause, yet early follicle development remains largely poorly understood. Here, we generate the most comprehensive single-cell and spatial multiomics atlas of the human pre- and postnatal ovarian cortex, integrating transcriptomic and chromatin profiles from over four million cells obtained from fetal and newly profiled pediatric and adult donors. We resolve the early granulosa cell trajectory at unprecedented resolution and identify a retinoic acid-associated regulatory switch accompanying follicle activation. We further show that stromal fibroblasts are not homogeneous, but instead form a dynamic scaffold establishing previously unrecognised morphogen and paracrine gradients that organise the cortex into functional niches supporting quiescent, growing, and atretic follicles. Finally, we identify ovarian lipid associated macrophages (oLAMs) that localise around follicles and are likely to support tissue remodelling during folliculogenesis. Together, this atlas provides a foundational blueprint for human ovarian development and homeostasis, and provides a framework for improving strategies in fertility preservation and in vitro follicle maturation.

cell biology↗

bioRxiv2026

Self-supervised learning for a gene program-centric view of cell states

Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensional data remains challenging. To enable downstream analyses, many computational approaches compress cell state into a single latent representation. This can obscure the structure of underlying gene programs (GP), defined as coordinated sets of biologically related genes, such as signalling pathway response modules or transcription factor targets. Here, we present Tripso, a self-supervised transformer deep learning model which learns multiple GP-specific embeddings from predefined GPs, while also enabling the discovery of novel, data-driven GPs. Tripso facilitates principled comparisons across development, disease, and experimental systems. Firstly, in a dataset of human hematopoietic cells spanning prenatal development through adulthood and aging and including newly generated data, Tripso resolved age-specific GP patterns, including elevated JAK-STAT activity in pediatric hematopoietic cells and postnatal shifts in IKZF1 GP activity during B cell differentiation. Secondly, leveraging Tripso GP embeddings and comparing in vivo to in vitro data, we hypothesized and experimentally validated that inhibition of the SEC61 translocon improved maintenance of hematopoietic stem cells in culture. Finally, Tripsos capacity for data-driven GP discovery revealed a previously uncharacterized tissue-resident memory T cell GP with increased activity in atopic dermatitis. Its spatial co-localization with sebaceous gland-associated immune niches was demonstrated in spatial transcriptomic and proteomic data. Thus, by moving beyond single embeddings of cellular states, Tripso enables interpretable and actionable discoveries, demonstrating how GP-centric modelling can generate hypotheses with substantial biomedical relevance. By anchoring cellular representations in meaningful GPs, Tripso establishes a principled and biologically grounded framework towards the development of interpretable virtual cell models.

bioinformatics↗

bioRxiv2026

Hidden immune memory niches in inflammatory skin diseases

Disease-associated histopathological features are widely used to identify tissue microenvironments or niches for diagnostics and treatment response in clinical practice. However, despite its widespread use, histopathology does not reveal the full cellular and molecular composition of known pathological niches. Furthermore, the existence of pathological niches that may not be histologically discernible remains unknown. In this study, we generated a spatially-resolved multi-modal molecular atlas of [~]5 million human skin cells (including 113 skin sections profiled using Xenium-5k) and applied deep learning to unbiasedly decode 26 skin niches in health and disease. Several disease-associated niches corresponded to known histopathological features, and we defined their cellular and molecular features, co-localisations, and interactions. Additionally, we discovered an immunologically active role for skin appendageal structures in disease mechanisms, potentially contributing to inflammatory memory, that was not identifiable using standard histopathological analysis. These include a resident memory T cell-rich niche in the sebaceous gland and a plasma cell-rich niche in the sweat gland, analogous to the gland-associated immune niche in lung. Finally, we illustrate how our atlas can be used to generate high-resolution representations using transfer learning, resolving rare T cell and sebocyte subsets not possible in the original studies, validating niche identification, and the spatial enrichment of candidate genes linked to disease-associated genetic variants. Overall, our study links histopathology and atlas-scale genomics to reveal novel insights into inflammatory disease pathogenesis, chronicity, and potentially curative therapeutic avenues, using skin as an exemplar tissue for this approach.

immunology↗

bioRxiv2026

Predicting how perturbations reshape cellular trajectories with PerturbGen

A major challenge in biology is predicting how cells transition between states over time and how perturbations disrupt these transitions. Understanding such dynamics is critical for identifying interventions that reverse pathological programs or reprogram cells toward desired states. Although recent computational approaches can predict single-cell perturbation responses in silico, they cannot predict responses across dynamic cell trajectories, for example how early perturbations reconfigure later cell states. To address this gap, we introduce PerturbGen, a generative foundation model trained on over 100 million single-cell transcriptomes that predicts perturbation responses along cellular trajectories. PerturbGen predicts how genetic perturbation at source state shapes downstream states, alters gene programs and trajectories across time, for example in differentiation or disease progression. We apply PerturbGen to three newly generated multi-condition human single-cell datasets spanning immune responses, hematopoiesis and skin development. In an in vivo immune challenge, PerturbGen predicts that knocking out an IL1B signal in myeloid cells attenuates later cytokine-interferon programs, with downstream changes consistent with a reversal of IL-1{beta} stimulation signature. In hematopoiesis, anchoring perturbation-induced programs to human genetics enables simulation of monogenic blood disorders, recapitulates established disease-associated biology whilst systematically revealing lineage-specific programs, including in lineages where this was not previously possible. In skin organoids, PerturbGen predicted that Wnt activation enhances stromal differentiation recapitulating the trajectory observed in human prenatal skin, findings that were functionally validated by experimentally activating Wnt signaling. Together, PerturbGen extends modeling of gene perturbations from static to dynamic cellular systems. We envision PerturbGen enabling the creation of in silico, trajectory-aware perturbation atlases and virtual cells across diverse biological scenarios, supporting optimization of disease models and prioritization of candidate molecular interventions for therapeutic discovery.

bioinformatics↗

bioRxiv2025

A spatial transcriptomic atlas of autism-associated genes identifies convergence in the developing human thalamus

Autism is a highly heritable neurodevelopmental condition that manifests across a wide phenotypic spectrum. Rare and de novo loss-of-function mutations strongly predispose to autism and co-occurring developmental and intellectual disabilities in over 10% of autistic individuals. Understanding whether these variants converge on specific regional brain circuits or widely alter human brain development is crucial to understanding the etiology of profound autism. To date, transcriptomic atlases have mainly implicated the developing cerebral cortex, yet other brain areas have received relatively little attention. Here, we present a single-cell resolution spatial transcriptomic atlas of 250 autism susceptibility genes during human brain development. Profiling over 10 million cells across the midgestation forebrain, we found convergence of these genes across a small number of regional programs. The developing thalamus showed the most prevalent expression of autism susceptibility genes, followed by germinal zones throughout the brain. Within the thalamus, excitatory neurons showed the most enriched expression, which varied across thalamic nuclei harboring distinct circuits. Across the germinal zones, neural progenitors in the medial ganglionic eminences that generate parvalbumin- and somatostanin-positive interneurons showed highest expression. Our findings reveal the prevalent expression of autism associated genes beyond the developing cerebral cortex and implicate the developing human thalamus as a major hub of autism susceptibility.

neuroscience↗

bioRxiv2025

Decoding human B cell ontogeny in prenatal and adult bone marrow and in vitro models via single-cell multiomics

In humans, the bone marrow becomes the primary site for B lymphopoiesis during the second trimester of pregnancy and continues throughout life. Prenatal and adult B cell progenitors play distinct roles in the aetiology and pathology of paediatric and adult hematopoietic malignancies, though the molecular drivers of these differences remain unclear. Here, we created a comprehensive multiomics atlas of over 500k cells covering immune and stromal compartment from prenatal and adult bone marrow, enabling high-resolution analysis of the cell-intrinsic and cell-extrinsic processes that modulate prenatal and adult B lymphopoiesis. Even though B cells follow broadly similar developmental trajectories, we identify a novel postnatal lateCLP subset equivalent to prenatal preProB cells, and uncover prenatal cells carry several signatures characteristic of leukemias, including enhanced proliferation, higher RAG1/RAG2 activity, extrinsic B cell signals such as IL7, and lower retention signals in the bone marrow. We also developed and characterised, at both cellular and molecular levels, a new experimental framework for generating B cell precursors from human induced pluripotent stem cells (hiPSCs), and show that it faithfully recapitulates key stages of B cell differentiation. Together, our single-cell multiomics atlas of B lymphopoiesis in vivo and in vitro offers detailed insights into the unique molecular features of prenatal and adult B cell lymphopoiesis, and serves as a powerful resource for investigating the early events that contribute to haematological disorders.

immunology↗

bioRxiv2025

Mapping and reprogramming microenvironment-induced cell states in human disease using generative AI

Tissue microenvironments reprogram local cellular states in disease, yet current computational spatial methods remain descriptive and do not simulate tissue perturbation. We present MintFlow, a generative AI algorithm that learns how the tissue microenvironment influences cell states and predicts how tissue perturbations can reprogram them. Applied to three human diseases, MintFlow uncovered distinct pathogenic spatial reprogramming in inflammatory and tumor microenvironments. In atopic dermatitis, MintFlow identified a novel, spatially-imprinted, type 2 (IL13+ITGAE+) epidermal T resident memory cell population (type 2 TRM), and decoded signaling pathways within the perivascular lymphoid niche. In melanoma, MintFlow identified fibrotic stroma resembling keloid scar tissue. In kidney cancer, MintFlow resolved immunosuppressed CD8+ T cell states within tertiary lymphoid structures. Furthermore, MintFlow enabled in silico perturbations of disease-relevant cell states and tissue environments. Regulatory T cell modulation in atopic dermatitis was predicted to suppress the pro-inflammatory tissue environment, supporting manipulation of these cells as a therapeutic target. In kidney cancer, in silico T cell replacement recapitulated immune checkpoint blockade, while spatially targeted macrophage depletion reverted immunosuppressed T cell states. The corresponding gene programs correlated with survival in large kidney cancer patient cohorts. Together, these findings position MintFlow as a tool for unbiased disease mechanism prediction and in silico perturbation, accelerating translational hypothesis generation and guiding therapeutic strategies.

genomics↗

bioRxiv2025

An atlas of TF driven gene programs across human cells

Combinations of transcription factors (TFs) regulate gene expression and determine cell fate. Much effort has been devoted to understanding TF activity in different tissues and how tissue-specificity is achieved. However, ultimately gene regulation occurs at the single cell level and the recent explosion in the availability of single cell gene expression data now makes it possible to understand TF activity at this granular level of resolution. Here, we leverage a large collection of Human Cell Atlas (HCA) single cell data to explore TF activity by examining cell-type and tissue-specific sets of target genes, or regulons. We compile a regulon atlas, CellRegulon, and map the activity of TFs in an extensive set of healthy adult and foetal tissues spanning hundreds of cell types. Using CellRegulon, we describe dynamic patterns of co-regulation, associate TF-modules with different cellular functions and characterise the distribution of active TFs and TF families across cell types. We show that CellRegulon can link disease gene expression signatures to cell types and TFs relevant to the disease. Finally, using a newly generated multiome dataset of the adult lung, we show how CellRegulon can be extended into an enhancer-gene regulatory network (eGRN) to improve cell-type associations with genetic risk loci for diseases, such as childhood onset asthma, COPD and IPF, and to identify high risk gene modules. Our database for easy download and interactive exploration allows researchers to understand key gene modules activated at cell type transitions and will therefore be valuable for tasks such as cell type engineering (https://www.cellregulondb.org).

genetics↗

bioRxiv2025

Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics

Metabolism supplies energy, building blocks, and signaling molecules vital for cell function and communication, but methods to directly measure it at single-cell and/or spatial resolutions remain technically challenging and inaccessible for most researchers. Single-cell and spatial transcriptomics offer high-throughput data alternatives with a rich ecosystem of computational tools. Here, we present scCellFie, a computational framework to infer metabolic activities from human and mouse transcriptomic data at single-cell and spatial resolution. Applied to [~]30 million cell profiles, we generated a comprehensive metabolic atlas across human organs, identifying organ- and cell-type-specific activities. In the endometrium, scCellFie reveals metabolic programs contributing to healthy tissue remodeling during the menstrual cycle, with temporal patterns replicated in data from in vitro cultures. We also uncover disease-associated metabolic alterations in endometriosis and endometrial carcinoma, linked to proinflammatory macrophages, and metabolite-mediated epithelial cell communication, respectively. Ultimately, scCellFie provides a scalable toolbox for extracting interpretable metabolic functionalities from transcriptomic data.

bioinformatics↗

bioRxiv2024

Spatiotemporal map of the developing human reproductive tract at single-cell resolution

The human reproductive tract plays an essential role in species perpetuation. Its development involves complex processes of sex specification, tissue patterning and morphogenesis, which, if disrupted, can cause lifelong health issues, including infertility. Here, we generated an extensive single-cell and spatial multi-omic atlas of the human reproductive tract during prenatal development, which allowed us to answer questions that smaller-scale, organ-focused experiments could not address before. We identified potential regulators of sexual dimorphism in reproductive organs, pinpointing novel genes involved in urethral canalisation of the penis, with relevance to hypospadias. By combining histological features with gene expression data, we defined the transcription factors and cell signalling events required for the regionalisation of the Mullerian and Wolffian ducts. This led to a refinement of how the HOX code is established in the distinct reproductive organs, including increased expression of thoracic HOX genes in the rostral mesenchyme of the fallopian tube and epididymis. Our study further revealed that the epithelial regionalisation of the fallopian tube and epididymis required for sperm maturation in adulthood is established early in development. In contrast, later events in gestation or postnatally are necessary for the regionalisation of the uterocervical canal epithelium. By mapping sex-specific reproductive tract regionalisation and differentiation at the cellular level, our study offers valuable insights into the causes and potential treatments of reproductive disorders.

developmental biology↗

bioRxiv2024

Single Cell Integration Characterises Metaplasia in Inflammatory Intestinal Diseases

The gastrointestinal (GI) tract consists of connected organs, from the oral cavity to rectum, which function to ensure efficient nutrient uptake and barrier immunity. Diseases of the GI tract affect millions worldwide and as such there are now over 25 published single cell RNA-sequencing (scRNAseq) datasets surveying the GI tract, profiling specific anatomical regions, cell lineages, ages and diseases. To consolidate these efforts, we harmonised and integrated scRNAseq datasets across the whole GI tract from developing and adult human tissues, as well as newly generated data from preterm gut. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated QC approach (scAutoQC). In total, our healthy reference contains [~]1.1 million cells which we annotated to a total of 137 fine-grained cell states. We anchor 13 published and 1 unpublished GI disease datasets covering gastric and colorectal (CRC) cancers, celiac disease, ulcerative colitis (UC) and Crohns disease (CD) to this reference, taking our atlas to a total of 1.6 million cells. We provide our atlas as a valuable resource to the community (available at gutcellatlas.org). Using this resource, we discover epithelial cell metaplasia arising from stem cells across intestinal inflammatory diseases (celiac, UC and CD) and CRC with transcriptional similarity to cells of the gastric and Brunners glands. Whilst previously linked to mucosal healing, we now implicate these cells in inflammation through recruitment of immune cells including T cells and neutrophils, and through direct interactions with T cells. Overall, we discover a shift in paradigm whereby changes in stem cells during inflammation lead to altered mucosal tissue architecture, which in turn contributes to ongoing inflammation. These findings highlight that in addition to barrier function, epithelial cells actively contribute to progression of inflammation which may be a function applicable to other tissues and diseases.

genomics↗

bioRxiv2024

A multiomic atlas of human early skeletal development

Bone and joint formation in the developing skeleton rely on co-ordinated differentiation of progenitors in the nascent developing limbs and joints. The cell states, epigenetic processes and key regulatory factors underlying their lineage commitment to osteogenic and other mesenchymal populations during ossification and joint formation remain poorly understood and are largely unexplored in human studies. Here, we apply paired single-nuclei transcriptional and epigenetic profiling of 336,000 droplets, in addition to spatial transcriptomics, to construct a comprehensive atlas of human bone, cartilage and joint development in the shoulder, hip, knee and cranium from 5 to 11 post-conception weeks. Spatial mapping of cell clusters to our highly multiplexed in situ sequencing (ISS) data using our newly developed tool ISS-Patcher revealed new cellular mechanisms of zonation during bone and joint formation. Combined modelling of chromatin accessibility and RNA expression allowed the identification of the transcriptional and epigenetic regulatory landscapes that drive differentiation of mesenchymal lineages including osteogenic and chondrogenic lineages, and novel chondrocyte cell states. In particular, we define regionally distinct limb and cranial osteoprogenitor populations and trajectories across the fetal skeleton and characterise differential regulatory networks that govern intramembranous and endochondral ossification. We also introduce SNP2Cell, a tool to link cell-type specific regulatory networks to numerous polygenic traits such as osteoarthritis. We also conduct in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential pathogenic cell states and disease mechanisms involved. This work forms a detailed and dynamic regulatory atlas of human fetal skeletal maturation and advances our fundamental understanding of cell fate determination in human skeletal development.

developmental biology↗

bioRxiv2023

A spatial human thymus cell atlas mapped to a continuous tissue axis

T cells develop from circulating precursors, which enter the thymus and migrate throughout specialised sub-compartments to support maturation and selection. This process starts already in early fetal development and is highly active until the involution of the thymus in adolescence. To map the micro-anatomical underpinnings of this process in pre- vs. post-natal states, we undertook a spatially resolved analysis and established a new quantitative morphological framework for the thymus, the Cortico-Medullary Axis. Using this axis in conjunction with the curation of a multimodal single-cell, spatial transcriptomics and high-resolution multiplex imaging atlas, we show that canonical thymocyte trajectories and thymic epithelial cells are highly organised and fully established by post-conception week 12, pinpoint TEC progenitor states, find that TEC subsets and peripheral tissue genes are associated with Hassalls Corpuscles and uncover divergence in the pace and drivers of medullary entry between CD4 vs. CD8 T cell lineages. These findings are complemented with a holistic toolkit for spatial analysis and annotation, providing a basis for a detailed understanding of T lymphocyte development.

immunology↗

bioRxiv2023

Multi-scale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma

Our understanding of how human skin cells differ according to anatomical site and tumour formation is limited. To address this we have created a multi-scale spatial atlas of healthy skin and basal cell carcinoma (BCC), incorporating in vivo optical coherence tomography, single cell RNA sequencing, spatial global transcriptional profiling and in situ sequencing. Computational spatial deconvolution and projection revealed the localisation of distinct cell populations to specific tissue contexts. Although cell populations were conserved between healthy anatomical sites and in BCC, mesenchymal cell populations including fibroblasts and pericytes retained signatures of developmental origin. Spatial profiling and in silico lineage tracing support a hair follicle origin for BCC and demonstrate that cancer-associated fibroblasts are an expansion of a POSTN+ subpopulation associated with hair follicles in healthy skin. RGS5+ pericytes are also expanded in BCC suggesting a role in vascular remodelling. We propose that the identity of mesenchymal cell populations is regulated by signals emanating from adjacent structures and that these signals are repurposed to promote the expansion of skin cancer stroma. The resource we have created is publicly available in an interactive format for the research community. Significance statementSingle cells RNA sequencing has revolutionised cell biology, enabling high resolution analysis of cell types and states within human tissues. Here, we report a comprehensive spatial atlas of adult human skin across different anatomical sites and basal cell carcinoma (BCC) - the most common form of skin cancer - encompassing in vivo optical coherence tomography, single cell RNA sequencing, global spatial transcriptomic profiling and in situ sequencing. In combination these modalities have allowed us to assemble a comprehensive nuclear-resolution atlas of cellular identity in health and disease.

cell biology↗