Biology subjects

Ten, F. W.

Publications and source records attributed to Ten, F. W..

7 recordsLinked to original sources

bioRxiv2026

Evolution of SARS-CoV-2 reshapes upper airway immunity in children

Children were relatively protected from severe COVID-19 during the early pandemic a phenomenon linked to rapid and heightened innate immune responses in the upper-airways. Although adult upper-airway antiviral responses varied across successive SARS-CoV-2 waves, whether viral evolution similarly reshaped pediatric mucosal immunity remains unclear. Here we used single-cell transcriptomics to profile 229,533 upper-airway cells from 68 unvaccinated children including 17 uninfected controls, spanning the wild-type SARS-CoV-2, Alpha, Delta and Omicron waves. Epithelial interferon responses were primarily determined by time since symptom onset but were, unlike in adults, independent of disease severity. During early infection, anti-viral responses differed across variants without following a progressive pattern of attenuation. Alpha and Delta elicited the strongest interferon programs across epithelial and immune cell populations, whereas Omicron exhibited a shift towards macrophage cytokine signaling and T-cell cytotoxicity. These findings reveal variant-specific remodeling of pediatric upper-airway immunity that fundamentally differs from that described in adults.

immunology↗

bioRxiv2025

Latent plasticity of the human pancreas across development, health, and disease.

The pancreas plays a central role in major human diseases, yet our understanding of its cellular diversity and plasticity remains incomplete. Here, we present a single-cell multiomics atlas of the human pancreas, profiling over four million cells and nuclei from 57 donors across fetal development, adult homeostasis, and type 2 diabetes (T2D). Integrating sc/snRNA-seq, snATAC-seq, VASA-seq, spatial transcriptomics (Xenium), and multiplexed proteomics (CODEX), we resolve gene expression, chromatin accessibility, and spatial organization at high resolution. We identify transcriptionally plastic centroacinar-like cells (pCACs) in adults with fetal-like features, delineate endocrine and exocrine lineage trajectories during development, and uncover HNF1A-defined beta cell epigenetic states. In T2D, we observe shifts in beta cell subtypes and altered regulatory programs. Glucose perturbation of healthy islets reveals cell-type-specific adaptation and stress responses. This atlas provides a foundational framework to understand pancreas biology and the role of cellular plasticity in regeneration and disease.

genomics↗

bioRxiv2024

Tbx1 stabilizes differentiation of the cardiopharyngeal mesoderm and drives morphogenesis in the pharyngeal apparatus

BackgroundTBX1 is required for the development of the pharyngeal apparatus. In the mouse, fish, and ascidian, Tbx1 is a marker of cardiopharyngeal mesoderm (CPM), a cell population that provides progenitors to the heart and branchiomeric muscles. However, in mammals: a) the molecular cascade that drives the diversification of this multipotent cell population, and b) the role of Tbx1 therein, are not well defined. Material and methodsWe used in vitro differentiation of WT and Tbx1-/- mouse embryonic stem cells into precardiac mesoderm, and performed single cell RNA-seq and ATAC-seq at two differentiation stages. We then used WT and Tbx1-/- mouse embryos for in vivo validation of the key findings. Results and conclusionsWe found that the response to loss of TBX1 is cell sub-population-specific, both in terms of gene expression and chromatin remodeling. We show that Tbx1 regulates chromatin accessibility and gene expression of an ancient transcriptional module that orchestrates the development of the trunk, pharynx and heart across evolution. This module is co-regulated and includes genes encoding the conserved transcription factor families of Tea Shirt (Tshz), Sine Oculis (Six), Eye absent (Eya), and Ebf/Collier. Analysis of putative regulatory regions of these genes, which were selected using a machine-learning computational procedure, predicted a feed-forward regulatory relationship between TBX1 and SIX factors that drives or stabilizes the module. Most surprisingly, we found a drift in the differentiation trajectory of the Tbx1 mutant CPM that led to a relative expansion of cells with epithelial-like transcriptional features in the cell culture model and in mouse embryos. We conclude that TBX1 is a critical factor for maintaining the transcriptional profile of the CPM.

developmental biology↗

bioRxiv2021

Deep molecular characterization linked to drug response profiling of pancreatic ductal adenocarcinoma using patient-derived organoids.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high drug resistance and poor prognosis. Novel therapeutic and stratification strategies are urgently needed. Here, we present an integration of in-depth genomic and transcriptomic characterization with drug screening and clinical outcome based on a catalogue of 51 patient-derived tumor organoids (PDOs) from resected PDAC. Known PDAC molecular subtypes and their prognostic value are conserved in organoids. Integration of transcriptomic and drug response profiles suggest a metabolism-mediated modulations of drug resistance. Copy number alterations on chromosome 13q and wild-type status of TP53 emerged as potential novel genomic biomarkers for sensitivity to 5-FU and oxaliplatin treatment, respectively. Functional testing of targeted drugs in PDOs revealed its additional value for genome-driven personalized oncology. Co-deletion of TP53/POLR2A increased vulnerability to RNA polymerase II inhibition, pointing to a promising target for personalized treatment in PDAC. SignificancePatient-derived PDAC organoids hold great promise as surrogate tumor models for personalized oncology. By integrating highly granular molecular, drug sensitivity and clinical data, we demonstrate that PDOs are valid models for molecular characterization and response prediction that also enable identification of novel drug sensitivity biomarkers and resistance mechanisms in PDAC.

cancer biology↗

bioRxiv2020

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished classical pancreatic tumors from basal-like tumors with more aggressive clinical behaviour. We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report classical and basal-like cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with classical subtype cells concentrated at the endpoint of this hierarchy. In an imaging-based drug screen, expression of classical subtype genes also correlates with better response to clinical drugs. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

cancer biology↗

bioRxiv2019

Gene set inference from single-cell sequencing data using a hybrid of matrix factorization and variational autoencoders

Recent advances in single-cell RNA sequencing (scRNA-Seq) have driven the simultaneous measurement of the expression of 1,000s of genes in 1,000s of single cells. These growing data sets allow us to model gene sets in biological networks at an unprecedented level of detail, in spite of heterogenous cell populations. Here, we propose an unsupervised deep neural network model that is a hybrid of matrix factorization and conditional variational autoencoders (CVA), which utilizes weights as matrix factorizations to obtain gene sets, while class-specific inputs to the latent variable space facilitate a plausible identification of cell types. This artificial neural network model seamlessly integrates functional gene set inference, experimental batch effect correction, and static gene identification, which we conceptually prove here for three single-cell RNA-Seq datasets and suggest for future single-cell-gene analytics.

bioinformatics↗

bioRxiv2019

Single nucleus RNA sequencing maps acinar cell states in a human pancreas cell atlas

Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been established, due to the local concentration of hydrolytic enzymes that can rapidly degrade cells and RNA upon resection. Here we innovated single-nucleus RNA sequencing protocols, and profiled more than 120,000 cells from adult and neonatal human donors to create the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents. Adult and neonatal pancreata shared common features, including the presence of previously undetected acinar subtypes, but also showed marked differences in the composition of the endocrine, endothelial, and immune compartments. Spatial cartography, including cell proximity mapping through in situ sequencing, revealed dynamic developmental cell topographies in the endocrine and exocrine pancreas. Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology, and provides a crucial reference set for future comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

genomics↗