Biology subjects

Vigilante, A.

Publications and source records attributed to Vigilante, A..

11 recordsLinked to original sources

bioRxiv2025

Mesodermal-niche interactions direct specification and differentiation of pancreatic islet cells in human multilineage organoids

Tissues develop and function within a highly complex microenvironment, where diverse cell types interact in tightly regulated spatial and temporal patterns1,2. Through distinct, relay-like waves of activity, these cells collectively shape tissue formation, ensuring that each component emerges in the right place at the right time1,2. Such coordinated cues establish the structural and biochemical framework that drives cell differentiation and tissue organization. Accurately modelling this process in humans requires the development of complex multicellular systems. Here, we pair spatial transcriptomics of the human foetal pancreas with an induced pluripotent stem cell (iPSC)-based multilineage model that faithfully recapitulate the complex, hierarchical processes underlying human pancreatic islet formation. We show that iPSC-derived pancreatic mesodermal lineages direct endocrine commitment from pancreatic progenitors, by suppressing off-target fates and orchestrating niche-mediated spatio-temporal cues that promote beta-cell differentiation. Our results identify a vascular-rich niche, featuring pancreatic pericytes, which is associated with a neural repulsion program and may contribute to shaping the islet microenvironment. We benchmark our in vitro multilineage organoid system against spatial transcriptomics of the human foetal pancreas. Together, these findings identify the key cellular actors and contact-dependent mechanisms that build the human endocrine pancreas, providing a critical model for studying human islet development and disease.

developmental biology↗

bioRxiv2025

The maternal inflammatory proteome during pregnancy and its role in predicting the risk of spontaneous preterm birth

BackgroundSpontaneous preterm birth (sPTB) is a significant adverse outcome of pregnancy. Being able to identify and improve the management of those who may be at risk requires robust screening methods. The use of circulating molecular markers provides a promising and non-invasive solution to this problem to allow necessary and successful intervention. The role of inflammation has been continuously demonstrated to play a key role in the onset of sPTB with intrauterine inflammation being a key driver. Here we sought out to explore the inflammatory proteome using a nested case-control approach using samples from pregnant participants in the INSIGHT cohort. ObjectivesTo explore the maternal blood proteome in the second trimester using the Olink Explore panel to identify inflammatory proteins associated with sPTB and assess their predictive value, both independently and in combination with cell-free RNA (cfRNA). Study DesignWe conducted a nested case-control study to investigate inflammatory protein profiles during the second trimester of pregnancy. A total of 138 maternal blood plasma samples were analysed using a targeted proteomic assay quantifying 384 inflammation-related proteins. Differential expression analysis and a LASSO-logistic regression model with Leave-One-Out Cross-Validation (LOOCV) were applied to evaluate the association between inflammatory biomarkers and spontaneous preterm birth (sPTB) outcomes. ResultsUsing predictive modelling of the maternal blood proteome, 16 inflammation-related proteins were identified as key discriminators of sPTB risk, with proteins such as PGF, COL9A1, CST7, CXCL6 and GALNT3 emerging as major contributors for predicting sPTB risk. Using inflammation-related maternal proteins alone to predict sPTB (<35 weeks) achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.76 (95% CI: 0.66-0.84). The incorporation of both cfRNA and proteomic data into an integrated model, improved the area under the curve to 0.85 (95% CI: 0.78-0.92). The integrated model highlighted inflammatory biomarkers that are not only implicated in preterm birth but also in essential physiological mechanisms such as placental function, tissue remodelling, and extracellular matrix composition, which are critical to maintaining pregnancy and preventing premature labour. ConclusionsThese findings demonstrate that an integrated approach using both cfRNA and proteomic signatures of the second trimester maternal blood plasma yields a more comprehensive biomarker profile for predicting preterm birth risk. This multimodal strategy not only enhances the predictive accuracy but also captures a broader array of biological signals across multiple organ systems. Compared to relying solely on inflammatory proteome markers, this multiomic method offers a deeper molecular characterisation of preterm birth risk in the maternal blood plasma.

systems biology↗

bioRxiv2025

A single cell ATAC-seq atlas uncovers dynamic changes in chromatin accessibility during cell fate specification at the neural plate border

During development, dynamic changes in gene expression and chromatin architecture drive the transition from progenitors to specialised cell types. Here we use single cell ATAC sequencing (scATAC-seq) to investigate changes in chromatin accessibility as neural plate border cells segregate into neural, neural crest and placode cells. We developed a Nextflow pipeline, single cell Advanced Chromatin Exploration (scACE), which integrates scATAC-seq and scRNA-seq data to identify cell state specific accessibility profiles and groups of chromatin regions with coordinated dynamic behaviour, termed accessibility modules (AMs). We find that progenitors are characterised by broadly open chromatin, reflecting their broad potential to generate any ectodermal derivative. As development proceeds, cell-type-specific chromatin signatures are established. Inferring an enhancer-centric gene regulatory network, we predict Foxk2 as new regulator for placode specification and verify this prediction experimentally. Foxk2 target enhancers are open in placodal, but not any other ectodermal cells. This finding suggests that on a regulatory level, cells can use different strategies to control fate choice: differential accessibility of enhancers and broad accessibility controlled by differentially expressed transcription factors.

developmental biology↗

bioRxiv2025

Spatially organized cellular communities shape functional tissue architecture in the pancreas

Organ function depends on the precise spatial organization of cells across multiple scales, from individual cells to cellular communities that form specialized local niches and, ultimately, complex higher-order structures. While the identities of individual cell are increasingly well-defined, our understanding of how these diverse cell types are spatially distributed and communicate remains incomplete. In this study, we combine single-cell and spatial transcriptomic analyses to map pancreatic cell populations across space and time, from embryonic development to adult homeostasis in mice. Using these comprehensive maps, we systematically resolve spatial heterogeneity among pancreatic cell types and uncover basic tissue niches, which emerge as epithelial-mesenchymal units. We further characterize these niches functionally in both mouse and human models. We demonstrate that the mesenchymal lineage initially diversifies into various subtypes with specialized supportive roles during embryonic development. However, this complexity gradually diminishes over time, ultimately converging into a limited number of fibroblast sub-types in adult tissue. Our findings shed light on how different progenitor lineages co-develop and organize into structured communities that establish a mature, functional pancreas. This foundational framework could inform strategies for in vitro organogenesis and tissue-engineering in the context of pancreatic diseases.

developmental biology↗

bioRxiv2024

Rejuvenating aged osteoprogenitors for bone repair

Aging is marked by a decline in tissue regeneration, posing significant challenges to an increasingly older population. Here, we investigate age-related impairments in calvarial bone healing and introduce a novel two-part rejuvenation strategy to restore youthful repair. We demonstrate that aging negatively impacts the calvarial bone structure and its osteogenic tissues, diminishing osteoprogenitor number and function and severely impairing bone formation. Notably, increasing osteogenic cell numbers locally fails to rescue repair in aged mice, identifying the presence of intrinsic cellular deficits. Our strategy combines Wnt-mediated osteoprogenitor expansion with intermittent fasting, which leads to a striking restoration of youthful levels of bone healing. We find that intermittent fasting improves osteoprogenitor function, benefits that can be recapitulated by modulating NAD+ dependent pathways or the gut microbiota, underscoring the multifaceted nature of this intervention. Mechanistically, we identify mitochondrial dysfunction as a key component in age-related decline in osteoprogenitor function and show that both cyclical nutrient deprivation and Nicotinamide mononucleotide rejuvenate mitochondrial health, enhancing osteogenesis. These findings offer a promising therapeutic avenue for restoring youthful bone repair in aged individuals, with potential implications for rejuvenating other tissues.

cell biology↗

bioRxiv2024

Rapid and memory-efficient analysis and quality control of large spatial transcriptomics datasets

The 10x Visium spatial transcriptomics platform has been widely adopted due to its established analysis pipelines, robust community support, and manageable data output. However, technologies like 10x Visium have the limitation of being low-resolution, and recently spatial transcriptomics platforms with subcellular resolution have proliferated. Such high-resolution datasets pose significant computational challenges for data analysis, with regards to memory requirement and processing speed. Here, we introduce Pseudovisium, a Python-based framework designed to facilitate the rapid and memory-efficient analysis, quality control and interoperability of high-resolution spatial transcriptomics data. This is achieved by mimicking the structure of 10x Visium through hexagonal binning of transcripts. Analysis of 47 publicly available datasets concluded that Pseudovisium increased data processing speed and reduced dataset size by more than an order of magnitude. At the same time, it preserved key biological signatures, such as spatially variable genes, enriched gene sets, cell populations, and gene-gene correlations. The Pseudovisium framework allows accurate simulation of Visium experiments, facilitating comparisons between technologies and guiding experimental design. Specifically, we found high concordance between Pseudovisium (derived from Xenium or CosMx) and Visium data from consecutive tissue slices. We further demonstrate Pseudovisiums utility by performing rapid quality control on large-scale datasets from Xenium, CosMx, and MERSCOPE platforms, identifying similar replicates, as well as potentially low-quality samples and probes. The common data format provided by Pseudovisium also enabled direct comparison of metrics across 6 spatial transcriptomics platforms and 59 datasets, revealing differences in transcript capture efficiency and quality. Lastly, Pseudovisium allows merging of datasets for joint analysis, as demonstrated by the identification of shared cell clusters and enriched gene sets in the mouse brain using data from multiple spatial platforms. By lowering the computational requirements and enhancing interoperability and reusability of spatial transcriptomics data, Pseudovisium democratizes analysis for wet-lab scientists and enables novel biological insights.

bioinformatics↗

bioRxiv2021

Endocardium-to-coronary artery differentiation during heart development and regeneration involves sequential roles of Bmp2 and Cxcl12/Cxcr4.

Regenerating coronary blood vessels has the potential to ameliorate ischemic heart disease, yet there is currently no method of stimulating clinically effective cardiac angiogenesisis. Endocardial cells-- a particularly plastic cell type during development--line the heart lumen and are natural coronary vessel progenitors. Their intrinsic angiogenic potential is lost in adults, but studying the endocardial- to-coronary developmental pathway could identify methods of re-instating this process in diseased hearts. Here, we use a combination of mouse genetics and scRNAseq of lineage-traced endothelial cells to identify novel regulators of endocardial angiogenesis and precisely assess the role of Cxcl12/Cxcr4 signaling. Time-specific lineage tracing demonstrated that endocardial cells differentiated earlier than previously thought, largely at mid-gestation. A new mouse line reporting the activity of Cxcr4 revealed that, despite widespread Cxcl12 and Cxcr4 expression, only a small subset of these coronary endothelial cells activated the receptor, which were mostly in arteries. In accordance with these two findings, Cxcr4 deletion in the endocardial lineage only affected artery formation and only when deleted before mid-gestation. Integrating scRNAseq data of coronary endothelial cells from the endocardial lineage at both mid- and late-gestation identified a transitioning population that was specific to the earlier timepoint that specifically expressed Bmp2. Recombinant Bmp2 stimulated endocardial angiogenesis in an in vitro explant assay and in neonatal mouse hearts upon myocardial infarction. Our data shed light on how understanding the molecular mechanisms underlying endocardial-to-coronary transitions can identify new potential therapeutic targets that could promote revascularization of the injured heart.

developmental biology↗

bioRxiv2020

Quantitative lineage analysis identifies a long-term progenitor niche for the hepato-pancreato-biliary organ system

Single cell-based studies have revealed tremendous cellular heterogeneity in stem cell and progenitor compartments, suggesting continuous differentiation trajectories with intermixing of cells at various states of lineage commitment and notable degree of plasticity during organogenesis1-5. The hepato-pancreato-biliary organ system relies on a small endoderm progenitor compartment that gives rise to a variety of different adult tissues, including liver, pancreas, gallbladder, and extra-hepatic bile ducts6, 7. Experimental manipulation of various developmental signals in the mouse embryo underscored an important cellular plasticity in this embryonic territory6, 8. This is also reflected in the existence of human genetic syndromes as well as congenital or environmentally-caused human malformations featuring multiorgan phenotypes in liver, pancreas and gallbladder6, 8. Nevertheless, the precise lineage hierarchy and succession of events leading to the segregation of an endoderm progenitor compartment into hepatic, biliary, and pancreatic structures are not yet established. Here, we combine computational modelling approaches with genetic lineage tracing to assess the tissue dynamics accompanying the ontogeny of the hepato-pancreato-biliary organ system. We show that a long-term multipotent progenitor domain persists at the border between liver and pancreas, even after pancreatic fate is specified, contributing to the formation of several organ derivatives, including the liver. Moreover, using single-cell RNA sequencing we define a specialized niche that possibly supports such long-term cell fate plasticity.

developmental biology↗

bioRxiv2019

Cell Tracking Profiler: a user-driven analysis framework for evaluating 4D live cell imaging data

Accurate measurements of cell morphology and behaviour are fundamentally important for understanding how disease, molecules and drugs affect cell function in vivo. Using muscle stem cell (muSC) responses to injury in zebrafish as our biological paradigm we have established a ground truth for muSC cell behaviour. This revealed that variability in segmentation and tracking algorithms from commonly used programs are error-prone, leading us to develop a fast semi-automated image analysis pipeline that allows user defined parameters for segmentation and correction of cell tracking. Cell Tracking Profiler (CTP) operates through the freely available Icy platform, and allows user-managed cell tracking from 3D time-lapsed datasets to provide measures of cell shape and movement. Using dimensionality reduction methods, multiple correlation and regression analyses we identify myosin II-dependent parameters of muSC behaviour during regeneration. CTP and the associated statistical tools we have developed thus provide a powerful framework for analysing complex cell behaviour in vivo from 4D datasets. SummaryAnalysis of cell shape and movement from 3D time-lapsed datasets is currently very challenging. We therefore designed Cell Tracking Profiler for analysing cell behaviour from complex datasets and demonstrate its effectiveness by analysing stem cell behaviour during muscle regeneration in zebrafish.

cell biology↗

bioRxiv2018

Single-cell analysis identifies EpCAM+/CDH6+/TROP-2- cells as human liver progenitors.

The liver is largely composed of hepatocytes and bile duct epithelial cells (BECs). Controversy exists as to whether a liver stem/progenitor cell capable of renewing both hepatocytes and BECs exists. Single cell RNA sequencing of freshly isolated human foetal and healthy adult liver identified hepatocyte, hepatoblast and liver progenitor cell (hLPC) populations. hLPCs, found at the interface between hepatocytes and bile ducts in both foetal and adult tissue, were distinguishable from BECs by their negative expression of TROP-2. Prospective isolation followed by in vitro culture demonstrated their potential for expansion and bi-lineage differentiation. The hLPC expression signature was also conserved within expanded cell populations specific to certain cases of liver injury and cancer. These data support the idea of a true progenitor existing within healthy adult liver that can be activated upon injury. Further work to define the mechanisms regulating hLPC behaviour could advance understanding of human development and disease.

cell biology↗

bioRxiv2018

Identifying the genetic basis of variation in cell behaviour in human iPS cell lines from healthy donors

Large cohorts of human iPSCs from healthy donors are potentially a powerful tool for investigating the relationship between genetic variants and cellular phenotypes. Here we integrate high content imaging, gene expression and DNA sequence datasets for over 100 human iPSC lines to identify the genetic basis of inter-individual variability in cell behaviour. By applying a dimensionality reduction approach, Probabilistic Estimation of Expression Residuals (PEER), we identified genes that correlated in expression with intrinsic (genetic) and extrinsic (ECM) factors. However, variation in mRNA levels could not account for outlier cell behaviour. Instead, we identified rare, deleterious SNVs in the coding sequence of genes involved in ECM adhesion that occurred in cell lines that were outliers for one or more phenotypes such as cell spreading. These also correlated with altered germ layer differentiation on micropatterned surfaces. Our study thus establishes a strategy for integrating genetic and cell biological measurements for high-throughput analysis.

cell biology↗