Biology subjects

Roberts, K.

Publications and source records attributed to Roberts, K..

At least 19 recordsLinked to original sources

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 Cell Viability and Utility Index (CVUI) for wildlife fibroblast biobanking: framework development and preliminary empirical validation

Wildlife biobanking depends on consistent, reproducible cell culture outcomes, yet no standardised framework exists for assessing culture quality across taxa or for integrating quality metrics into institutional collections management systems. Here, we present the Cell Viability and Utility Index (CVUI), a scored pipeline framework validated in a pilot study of 154 culture rounds from 46 species held in the Ian Potter Australian Wildlife Biobank at Museums Victoria Research Institute. The CVUI was adapted from the Wildlife Sperm Index (Jacobs et al., 2026) and assigns weighted scores encompassing four sequential culture stages -- establishment, first passage, expansion, and cryobanking -- with a continuous viability modifier applied at the cryobanking stage. Survival analysis identified individual animal identity as the primary source of variance in culture establishment, whereas taxon was the primary predictor of first-passage success. Beyond first passage, failure rates were too low to reliably assess either effect, with critical attrition concentrated at the earliest pipeline stages. These findings informed the differential weighting of CVUI components and have direct implications for workflow prioritisation and banking strategy. Monitoring can now be targeted at establishment and first passage, the stages where intervention has the greatest impact, with taxon-specific attention warranted at first passage and individual-level attention at establishment, while the robustness of the late-stage protocol means that banking yield is largely determined before a culture reaches P1. Integration of CVUI scores into collections management platforms such as Axiell EMu (Electronic Museum) would transform passive record-keeping into active decision support, enabling real-time quality tracking, early flagging of at-risk cultures, and longitudinal benchmarking of biobank performance across species, collectors, and tissue types. This framework provides a foundation for optimising wildlife fibroblast biobanking protocols, developing taxon-specific culture standards, and expanding standardised quality assessment across wildlife biobanks nationally and internationally.

zoology↗

bioRxiv2026

Spatial lung niches shape Pseudomonas aeruginosa persistence

Chronic Pseudomonas aeruginosa lung infection is a major cause of morbidity and mortality in people with pre-existing lung disease. Once established, infection is rarely eradicated and often persists despite prolonged antimicrobial therapy, but the underlying mechanisms remain poorly understood. To define how P. aeruginosa occupies and adapts to diseased lung tissue, we applied host-pathogen spatial transcriptomics to profile over 23 million lung cells from explanted and resected lungs from people with Cystic Fibrosis (CF) and chronic obstructive pulmonary disease (COPD), mapping bacterial niches and transcriptional states in situ. We found that P. aeruginosa adopted distinct niche-linked states across chronically infected human lung tissue. Bacterial burden was highest in airway lumens, but bacteria also occupied submucosal glands, parenchyma and, unexpectedly, blood vessel lumens in CF tissue. Within airway lumens, two coupled host-pathogen states emerged: an alginate-rich biofilm-like state linked to PI3-positive neutrophil inflammation and host chemical-sensing programmes; and a motile, quorum-sensing state with activated type 6 secretion linked to human ciliary stress, epithelial remodelling and proteolytic injury. Intravascular bacteria co-localised with neutrophils, fibrin and vascular-remodelling signatures, suggesting local breach of barrier integrity and subsequent immune containment. P. aeruginosa also displayed disease-specific cellular associations, with neutrophil-dominated interactions in CF and greater association with macrophages and dendritic cells in COPD. Together, these data reveal chronic P. aeruginosa infection as a spatially partitioned ecosystem in which anatomical microenvironments impose distinct bacterial lifestyles and host inflammatory states. This niche-resolved framework helps explain how persistent infection can diversify within a single lung and suggests that eradication therapies may need to target multiple anatomical and cellular niches to be effective.

immunology↗

bioRxiv2026

Multimodal Hypersampling of the adult human heart resolves tissue-specific cell states and disease-associated variants

Cardiovascular diseases often arise in anatomically specialised regions of the heart that remain poorly represented in existing single-cell and spatial atlas references. Here we profiled 28 regions of the adult human heart from 36 donors, combining paired single-nucleus RNA and chromatin accessibility assays with spatial transcriptomics. The resulting atlas integrates 1,059,175 expression profiles and 452,614 chromatin accessibility profiles, and defines spatial niches across the heart. In cardiac valves, we identify a valve fibroblast-macrophage niche that is polarised to the non-fibrosa surface and expands with age. Aortic stenosis genetic risk was enriched in inflammatory regulatory programmes of the Valve Fibroblast Immune cell state. In pulmonary veins, we define PITX2+ Myocardial Sleeve Cells, a region-restricted cardiomyocyte population in which a fine-mapped 4q25 atrial fibrillation variant intersects a cell type-specific open chromatin region. In coronary arteries, we resolve a RUNX1-marked synthetic smooth muscle layer in the subintima that provides a molecular identity for diffuse intimal thickening, a constitutive feature of the healthy vessel wall and a substrate for atherosclerosis, and show by perturbation in human smooth muscle cells that RUNX1 promotes cell-cycle entry while restraining inflammatory cytokine gene expression. Finally, allele-specific accessibility together with deep learning models fine-tuned to predict regulatory activity from DNA sequence identify cell type-specific regulatory effects at GWAS loci for atrial fibrillation, coronary artery disease and calcific aortic valve stenosis, including a variant whose Valve Fibroblast-specific effect on the polyamine transporter ATP13A3 is opposite in direction to the effect seen in bulk-tissue eQTL references that lack valve cells. Together with these cardiac sequence models and CardioSleuth, an AI-powered exploration engine for cardiac regulatory effects, this atlas links cardiac anatomy, gene regulation and disease genetics at single-cell resolution. By placing genetic risk in its precise cellular and anatomical context, it provides a foundation for mechanistic disease understanding, cell-state-specific therapeutic target nomination, and improved interpretation of inherited cardiovascular risk to inform future therapy and management.

Cell Biology↗

bioRxiv2026

An integrated single cell and spatial omics atlas of human prenatal development

Single cell genomics has enabled analysis of human prenatal development at unprecedented resolution. However, most studies have relied on dissociated tissues during restricted windows of development, limiting insights into how spatially distributed networks of cells, and multicellular niches emerge and adapt to distinct organ microenvironments in situ. Moreover, existing human developmental atlases have not yet been harmonised, and we thus lack a comprehensive catalogue of known cell types in the developing human body. Here, we introduce the Human Developmental Cell Atlas (HDCA), a unified structural, cellular and molecular resource for prenatal human development. The HDCA integrates published and unpublished single cell/nucleus RNAseq atlases across prenatal organs, and includes a newly generated, spatially resolved, multimodal cell atlas of intact human embryos. Spanning 4-22 post conceptional weeks, capturing embryonic and early to mid fetal stages, the HDCA contains [~]4.6 million cells/nuclei which resolve into [~]450 cell types, explorable with a bespoke web portal. For a global overview of the human embryos multicellular communities, we applied unsupervised deep learning to our intact human embryo spatial data, charting 114 tissue niches that are structural and signalling hubs for the cellular interactions of the embryo. Guided by these niches, we profiled cellular networks over space and time, not examinable using single-organ atlases. In so doing, we revealed tissue-specific fibroblast patterning from previously undescribed mesenchyme progenitors, early diversification of organ-specific blood capillaries and lymphatic vasculature, emergence of neural crest cell fates, the formation of placode-and neural crest-derived peripheral sensory neurons, and how tissue niches guide peripheral neuron maturation and axonal migration. The HDCA thus serves as a comprehensive step towards a comprehensive understanding of human prenatal development, and a template towards unravelling the biology of congenital disorders.

developmental 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↗

bioRxiv2025

DISCO-seq: 3D single-cell transcriptomics of intact biological systems

Single-cell transcriptomics has transformed tissue analysis, yet current methods struggle to integrate whole-tissue 3D architecture. Conventional techniques restrict molecular profiling to pre-selected 2D sections, losing systemic context and introducing anatomical bias by sampling less than 0.001% of a whole organism. To overcome these challenges, we developed DISCO-seq, a tissue-clearing chemistry that enables superior RNA accessibility compared to fresh or fixed tissues. DISCO-seq integrates whole-organ or organism 3D imaging with both untargeted and targeted transcriptomics, yielding high-quality RNA from cleared tissues comparable to standard samples. We demonstrate its versatility by investigating tumor heterogeneity in a syngeneic glioblastoma mouse model, using 3D imaging to identify spatially distinct microenvironments and characterize their unique transcriptomic signatures. Moreover, DISCO-seq enabled unbiased, whole-body mapping of SARS-CoV-2 S1 protein deposition in mice, followed by transcriptomic profiling of spatially defined niches. By bridgingmesoscale 3D imaging with single-cell transcriptomics, DISCO-seq establishes a paradigm for anatomically contextualized, hypothesis-free tissue interrogation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/693352v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@758ee5org.highwire.dtl.DTLVardef@1f862c6org.highwire.dtl.DTLVardef@1cf3b9org.highwire.dtl.DTLVardef@c5082e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDISCO-seq integrates RNA-preserving tissue-clearing chemistry with whole-organ or organism 3D imaging, enabling anatomically unbiased single-cell transcriptomics. C_LIO_LIDISCO-seq yields RNA quality and transcriptome profiles equivalent to those obtained from matched fresh or fixed tissues. C_LIO_LIDISCO-seq identifies discrete glioblastoma microenvironments and defines their transcriptomic states within the intact brain. C_LIO_LIDISCO-seq enables whole-body mapping of SARS-CoV-2 S1 and uncovers region-specific immune and metabolic responses across anatomical niches. C_LI Supplementary movies can be seen at: http://discotechnologies.org/DISCO-seq/

systems biology↗

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

A connexin 43 targeting peptide prevents blood vessel neointima formation

The gap junction protein connexin 43 (Cx43) is associated with human pathological vascular smooth muscle cell (SMC) proliferation and neointima formation. We previously identified mitogen-activated protein kinase (MAPK) phosphorylation of Cx43 results in binding with the cell cycle protein cyclin E, facilitating neointima formation in mice. However, the specific nature of these interactions and their relevance to human disease have not been elucidated. Using an ex vivo human saphenous vein model of neointima formation, we identified increased MAPK-phosphorylated Cx43 and cyclin E in explant tissues. We used peptide arrays to define a cyclin E-Cx43 binding region and generated CycliCx, a stearate-linked Cx43 phospho-mimetic peptide. In human coronary artery SMC, CycliCx inhibits platelet-derived growth factor-BB (PDGF-{beta})-induced changes in Cx43 trafficking and interactions with cyclin E, and stimulation of proliferation. RNAseq analysis identified CycliCx significantly inhibits PDGF-{beta}-induced proliferative pathways in SMC by limiting PDGF-{beta}-induced early G1/S phase cell cycle progression transcripts. Finally, we show CycliCx limits neointima formation in mice in vivo and in ex vivo human saphenous vein explants. Our data provide strong evidence for selective targeting of Cx43 as a viable therapeutic strategy for preventing neointimal formation in humans.

physiology↗

bioRxiv2025

When one race is not enough: a relay model explains multisensory response times

Humans typically respond faster to multisensory signals than to their unisensory components, a phenomenon known as the redundant signal effect (RSE). One of the earliest and most influential accounts, the race model, attributes the RSE to statistical facilitation, which arises from parallel, independent processing across sensory modalities. While this model captures some key features of the RSE, it frequently underestimates the observed speed-up leading to violations of the race model inequality (RMI), a benchmark used to test the models validity. To reconcile this discrepancy, we introduce the relay model, a minimal extension of the race architecture that incorporates cross-modal initiation. In this model, responses result from two sequential race processes, allowing a signal in one modality to trigger the onset of perceptual decision processing in another. This structure retains statistical facilitation as a core principle while introducing a single free model parameter that divides unisensory processing into gating and decision stages. Through simulations and fits to foundational empirical datasets, we show that the relay model captures both the magnitude and distributional shape of the RSE, including RMI violations. It also accounts for changes in the RSE under asynchronous stimulus onsets, a critical test in multisensory integration research. By extending the classical race model with minimal added complexity, the relay model offers a mechanistically explicit and biologically plausible framework for explaining the dynamics of multisensory decision-making. Author SummaryHow does the brain combine information from different senses, like hearing and seeing? For decades, researchers have found that people respond faster when signals from multiple senses occur together than when signals come from a single sense alone. Two main ideas have been proposed to explain this effect: one suggests that the senses operate independently, racing to trigger a response, while the other suggests that they cooperate to enhance processing. In this study, we introduce a new model of multisensory decision-making, called the relay model, which combines elements of both competition and cooperation. We propose that the brain uses a two-stage process: first, the faster sense initiates a second decision process. Then, in that second stage, the faster signal triggers a behavioural response. This relay-like mechanism accelerates responses through competition, while still allowing both senses to cooperate. By capturing key findings from classic experiments, the model offers a new perspective on how the brain combines multisensory information to guide behaviour.

neuroscience↗

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

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

cancer biology↗

bioRxiv2025

Efficiency and localisation of AURKA degradation by PROTACs is modulated by deubiquitinases UCHL5 and target-selective OTUD6A

Proteolysis-targeting chimeras (PROTACs) represent a promising new drug modality for novel therapeutics. However, the cellular mechanisms and regulatory pathways underlying their activity are not fully understood. Here, we unveil the role of deubiquitinases (DUBs) in regulating PROTAC activity, by screening 97 human DUBs for their influence on degradation of cell-cycle kinase AURKA using siRNA-mediated knockdown. Our findings reveal that DUBs OTUD6A and UCHL5 counteract degradation of AURKA by small molecule PROTACs. Further investigation using orthogonal dTAG PROTACs indicates that the PROTAC-opposing effect of OTUD6A is target-specific for AURKA, while UCHL5 counteracts degradation triggered by other PROTACs dependent on ubiquitin ligase adaptor CRBN, but not VHL. Furthermore, we show that differential sensitivity of the nuclear pool of AURKA to PROTAC-mediated degradation is fully explained by the specific subcellular localisation pattern of OTUD6A. These findings enhance our understanding of cellular pathways underpinning the action of PROTACs and indicate that combinations of DUB inhibitors and PROTACs will lead to enhanced target degradation and potential improvement in therapeutic outcomes.

cell biology↗

bioRxiv2025

Improved detection of pre-symptomatic, non-central nervous system TDP-43 pathology in amyotrophic lateral sclerosis using RNA aptamer

The recognition that disease-associated proteinopathies can manifest in peripheral organs outside the central nervous system preceding the onset of neurological symptoms, has transformed our understanding of Parkinsons disease, in wide terms of pathogenesis, detection and diagnosis. For amyotrophic lateral sclerosis, non-motor symptoms, and non-central nervous system pathologies are gaining increased recognition but remain incompletely understood. Here, using a TDP-43 RNA aptamer and a Stathmin-2 cryptic exon transcript BaseScopeTM ISH probe, we identify widespread peripheral organ TDP-43 pathology prior to motor symptom onset in a discovery cohort of ante-mortem tissues from people who went on to develop ALS. Peripheral organs exhibiting both TDP-43 toxic gain- and loss-of function include muscle, lymph node, gallbladder, colon and with notably high incidence, skin. Given the accessibility of skin as a readily biopsiable tissue, representing a promising substrate for the detection of disease-associated proteinopathies and the development of minimally invasive biomarkers, we established an extended cohort of ante-mortem skin samples for TDP-43 pathology validation and further investigation. In skin biopsies taken during life from 17 individuals who went on to develop ALS we identify TDP-43 pathology from all 17 individuals in a wide distribution of anatomical sites, up to 26.5 years before ALS diagnosis - a presymptomatic period comparable to that observed for skin -synucleinopathy in Parkinsons disease. TDP-43 pathology was most abundant in skin biopsies from the back and shoulder, with sweat and sebaceous glands showing the highest involvement. TDP-43 pathology was also associated with structural changes. As skin -synucleinopathy has been established as a biomarker for both the detection of Parkinsons disease and the differentiation of Parkinsons disease from multiple system atrophy, we propose that skin TDP-43 likewise holds diagnostic and discrimination potential for diseases characterised by TDP-43 proteinopathy. Short AbstractPeripheral manifestations of neurodegenerative disease can precede neurological symptoms and serve as biomarkers, as shown by -synuclein in the skin of individuals who later develop Parkinsons disease. In amyotrophic lateral sclerosis (ALS), however, the distribution and diagnostic potential of peripheral TDP-43 pathology remain unclear. Using a TDP-43 RNA aptamer and a cryptic STMN2 BaseScope probe, we examined ante-mortem tissues from individuals who later developed ALS. In a discovery cohort, we detected widespread pre-symptomatic TDP-43 pathology across multiple organs, with skin emerging as the most consistent site. We then validated these findings in a validation cohort comprising 17 individuals, all of whom exhibited TDP-43 pathology enriched in sweat glands and structural changes detectable up to 26.5 years before ALS diagnosis. These findings establish skin as a robust and accessible site of pre-symptomatic TDP-43 pathology, supporting its potential as a minimally invasive biomarker for early diagnosis and disease stratification in ALS. SummaryMuch like skin -synucleinopathy has transformed biomarker development in Parkinsons disease, this study identifies skin TDP-43 pathology as a promising early marker of ALS. The results open avenues for earlier diagnosis and stratification in a disease where intervention is most needed before symptoms appear. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/648122v2_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@14cc6c0org.highwire.dtl.DTLVardef@18c69f7org.highwire.dtl.DTLVardef@1811265org.highwire.dtl.DTLVardef@dea8bc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIPresymptomatic TDP-43 pathology occurs across a range on non-CNS peripheral organ systems including skin, gastrointestinal tract and lymph nodes prior to motor symptom onset in people who went on to develop ALS. C_LIO_LIIn skin, presymptomatic TDP-43 pathology is associated with structural changes and can be detected up to 26.5 years prior to motor symptoms in ALS. C_LIO_LIAs for Parkinsons disease, shoulder and back represents optimal skin sampling sites for pre-symptomatic pathology in ALS. C_LIO_LISweat and sebaceous glands present with high levels of TDP-43 pathology, offering a promising biomarker target for early pathology detection. C_LI One Sentence SummaryUsing distinct biomarker discovery and validation ante-mortem tissue cohorts, we provide evidence of pre-symptomatic TDP-43 pathology across diverse non-CNS peripheral tissues, including skin decades before ALS symptom onset, highlighting skin TDP-43 pathology as a potential early biomarker for ALS and related TDP-43 proteinopathies

pathology↗

bioRxiv2025

Injury Induced Connexin 43 Expression Regulates Endothelial Wound Healing

Endothelial cell (EC) injury is a major contributing factor to vascular surgical failure. As such, understanding the mechanisms of endothelial healing is essential to the development of vascular therapeutics and procedures. Gap junctions formed by connexin 43 (Cx43) are implicated in regulating skin wound healing, but their role in endothelial healing is unknown. Secondary analysis of RNAseq data from in vivo injured mouse aortas (GEO: GSE115618), identified significant Cx43 upregulation in EC post-injury. We developed a novel in vivo model of EC injury using mouse carotid artery ligation to test the role of Cx43. We identified that EC immediately adjacent to the wound edge upregulate Cx43 protein expression, predominantly at cell-cell junctions. We show significantly delayed EC healing in a mouse model of inducible EC-specific Cx43 deletion (EC-Cx43 KO) at 24 hr post ligation. Single cell RNAseq analysis of 10,829 cells from 18 hr injured EC-WT and EC-Cx43 KO carotids revealed a Cx43-associated reduction in enrichment of EC pathways associated with migration, proliferation, and ERK/MAPK signaling pathways. Finally, the importance of Cx43 phosphorylation on EC healing was tested in mice with single-point alanine mutations (phospho-null) in known phosphorylation sites that alter Cx43 channel assembly and opening. Mice containing alanine mutations at ERK phosphorylated Cx43 serines (Cx43S255/262/279/282A) reduces healing rates similar to EC-Cx43 KO. These data suggest that EC injury-induced Cx43 upregulation, and subsequent Cx43 gap junction-mediated cell-to-cell communication are required for normal EC migration during wound healing after vascular injury. New and NoteworthyThese findings demonstrate for the first time that mechanical injury to large artery endothelium induces the expression of gap junction protein Cx43. This upregulation improves migratory and proliferative capacity of endothelial cells at the wound edge, facilitating timely wound closure. This phenomenon is dependent on appropriate gap junction function and turnover.

physiology↗

bioRxiv2025

Optimisation of Xenium automated in situ sequencing for PAXgene-fixed tissue samples

Spatial transcriptomics has transformed the study of gene expression in tissue samples, yet its application to non- standard sample preservation formats beyond fresh frozen and FFPE remains underexplored. PAXgene fixation offers advantages for genomic studies by preserving DNA and RNA without crosslinking but poses challenges for high-quality spatial transcriptomics. Here, we present an optimised workflow for applying Xenium, an automated in situ sequencing platform, to PAXgene-fixed paraffin-embedded (PFPE) tissues. Using our newly developed Xenium Tissue Optimisation (XTO) protocol, we systematically tested permeabilisation conditions across multiple mouse and human tissues. We show that pepsin digestion effectively enhances RNA accessibility in PFPE samples, with tuneable digestion times for tissue-specific optimisation, though a compromise may need to be reached between transcript detection rates and maintaining tissue integrity and morphological staining. Our results indicate that, under optimal conditions, PFPE samples can yield comparable or superior spatial RNA transcript detection to formalin-fixed paraffin-embedded (FFPE) samples. This study provides a framework for adapting in situ sequencing to PFPE tissues, broadening the applicability of spatial transcriptomics to archival and prospective sample collections. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/637091v2_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@646dbforg.highwire.dtl.DTLVardef@1613178org.highwire.dtl.DTLVardef@1f6d48eorg.highwire.dtl.DTLVardef@1fcdb8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2024

A single cell and spatial genomics atlas of human skin fibroblasts in health and disease

Fibroblasts are critical cells that shape the architecture and cellular ecosystems in multiple tissues. Understanding fibroblast heterogeneity and their spatial context in health and disease has enormous clinical relevance. In this study, we constructed a spatially-resolved atlas of human skin fibroblasts from healthy skin and 23 skin disorders. We define 6 major skin fibroblast populations in health and a further three skin disease-specific fibroblast subtypes, and demonstrate the fibroblast composition in different types of skin disease. We characterise a human-specific fibroblastic reticular cell (FRC)-like subtype in the skin perivascular niche and postulate their origin from prenatal skin lymphoid tissue organiser (LTo)-like cells. We also show that inflammatory myofibroblasts (IL11+MMP1+CXCL5+IL7R+) are a conserved fibroblast subtype in inflammatory disorders and cancers across multiple human tissues. We provide a harmonised nomenclature for skin fibroblasts that integrates previous findings from human skin and other tissues.

cell biology↗