Biology subjects

van Unen, V.

Publications and source records attributed to van Unen, V..

8 recordsLinked to original sources

bioRxiv2025

Tissue-embedded CD4⁺ plasticity structures mucosal immunity in IBD-related inflammation

CD4 T helper (Th) cell responses to commensal microbiota are linked to Inflammatory Bowel Disease (IBD), yet how Th programs coexist and evolve in human tissues remains poorly defined. Here, we profiled CD4 memory T cells in intestinal biopsies using immunological and histological approaches to map their phenotypes, functional states, and spatial relationships across disease states. A marked expansion of CD4 T cells concomitant with a ROR{gamma}t Th population with elevated T-bet expression was linked to progression of inflammation. Moreover, Foxp3 cells co-expressing ROR{gamma}t emerged within the inflamed niche, indicating regulatory-Th17 plasticity. Trajectory visualization revealed a potential branched differentiation path towards either regulatory or tissue-resident Th17-like fates, with both termini expressing activation and proliferation markers. Correlation network analysis connected pro-inflammatory CD4 states to T-betGranzyme-B CD8 subsets, indicative of crosstalk between helper and cytotoxic lineages. Histology corroborated this organization, showing frequent interactions between CD4 and CD8 cells in the lamina propria and epithelial border. In functional assays, TCR stimulation during active disease revealed broad suppression of CD4 pro-inflammatory cytokines concomitant with expansion of Foxp3 cells. Conversely, HLA-DR+CD38+ memory subset retained multifunctionality, producing elevated levels of pro-inflammatory cytokines. Together, these results provide insight into a dynamic, tissue-embedded CD4 landscape in IBD. HighlightsO_LIIBD inflammation shapes CD4+ T-cell plasticity and tissue-residency programming. C_LIO_LICorrelated CD4+ and cytotoxic CD8+ T cells co-localize in inflamed mucosa. C_LIO_LIMucosal CD4 memory T cells show hypo-responsiveness in active IBD. C_LIO_LIHLA-DR+CD38+ memory CD4 T cells amplify inflammation via cytokine output. C_LI

immunology↗

bioRxiv2025

A 37-color spectral flow cytometry panel to characterize phenotype and cytokine expression in human intestinal T cells

We developed a 37-color spectral flow cytometry panel to characterize T cell function, with a focus CD4+ T helper (Th) cells, in the human intestine. The panel includes lineage-defining transcription factors, markers for memory status, tissue residency and T cell activation, and 11 cytokines representing multiple Th cell lineages. The panel is currently being used to investigate CD4+ Th cell function in intestinal and peripheral blood samples of inflammatory bowel disease (IBD) patients. The panel could however be applied to investigate both peripheral and tissue-resident T cell function in a range of immune-mediated diseases.

immunology↗

bioRxiv2023

Critical role of down-regulated in adenoma bicarbonate transporter in linaclotide stimulated intestinal bicarbonate secretion

Duodenal bicarbonate secretion is critical to epithelial protection, nutrient digestion/absorption and is impaired in cystic fibrosis (CF). We examined if linaclotide, typically used to treat constipation, may also stimulate duodenal bicarbonate secretion. Bicarbonate secretion was measured in vivo and in vitro using mouse and human duodenum (biopsies and enteroids). Ion transporter localization was identified with confocal microscopy and de novo analysis of human duodenal single cell RNA sequencing (sc-RNAseq) datasets was performed. Linaclotide increased bicarbonate secretion in mouse and human duodenum in the absence of CFTR expression (Cftr knockout mice) or function (CFTRinh-172). NHE3 inhibition contributed to a portion of this response. Linaclotide-stimulated bicarbonate secretion was eliminated by down-regulated in adenoma (DRA, SLC26A3) inhibition during loss of CFTR activity. Sc-RNAseq identified that 70% of villus cells expressed SLC26A3, but not CFTR, mRNA. Loss of CFTR activity and linaclotide increased apical brush border expression of DRA in non-CF and CF differentiated enteroids. These data provide further insights into the action of linaclotide and how DRA may compensate for loss of CFTR in regulating luminal pH. Linaclotide may be a useful therapy for CF individuals with impaired bicarbonate secretion.

physiology↗

bioRxiv2022

Therapeutic modulation of the blood-brain barrier and ischemic stroke by a bioengineered FZD4-selective WNT surrogate

Derangements of the blood-brain barrier (BBB) or blood-retinal barrier (BRB) occur in disorders ranging from stroke, cancer, diabetic retinopathy, and Alzheimers disease. The Norrin/FZD4/TSPAN12 pathway activates WNT/{beta}-catenin signaling, which is essential for BBB and BRB function. However, systemic pharmacologic FZD4 stimulation is hindered by obligate palmitoylation and insolubility of native WNTs and suboptimal properties of the FZD4-selective ligand Norrin. Here, we developed L6-F4-2, a non-lipidated, FZD4-specific surrogate with significantly improved sub-picomolar affinity versus native Norrin. In Norrin knockout (NdpKO) mice, L6-F4-2 not only potently reversed neonatal retinal angiogenesis deficits, but also restored BRB and BBB function. In adult C57Bl/6J mice, post-stroke systemic delivery of L6-F4-2 strongly reduced BBB permeability, infarction, and edema, while improving neurologic score and capillary pericyte coverage. Our findings reveal systemic efficacy of a bioengineered FZD4-selective WNT surrogate during ischemic BBB dysfunction, with general applicability to adult CNS disorders characterized by an aberrant blood-brain barrier.

physiology↗

bioRxiv2021

Human KIR+CD8+ T cells target pathogenic T cells in Celiac disease and are active in autoimmune diseases and COVID-19

Previous reports show that Ly49+CD8+ T cells can suppress autoimmunity in mouse models of autoimmune diseases. Here we find a markedly increased frequency of CD8+ T cells expressing inhibitory Killer cell Immunoglobulin like Receptors (KIR), the human equivalent of the Ly49 family, in the blood and inflamed tissues of various autoimmune diseases. Moreover, KIR+CD8+ T cells can efficiently eliminate pathogenic gliadin-specific CD4+ T cells from Celiac disease (CeD) patients leukocytes in vitro. Furthermore, we observe elevated levels of KIR+CD8+ T cells, but not CD4+ regulatory T cells, in COVID-19 and influenza-infected patients, and this correlates with disease severity and vasculitis in COVID-19. Expanded KIR+CD8+ T cells from these different diseases display shared phenotypes and similar T cell receptor sequences. These results characterize a regulatory CD8+ T cell subset in humans, broadly active in both autoimmune and infectious diseases, which we hypothesize functions to control self-reactive or otherwise pathogenic T cells. One-Sentence SummaryHere we identified KIR+CD8+ T cells as a regulatory CD8+ T cell subset in humans that suppresses self-reactive or otherwise pathogenic CD4+ T cells.

immunology↗

bioRxiv2020

Progenitor identification and SARS-CoV-2 infection in long-term human distal lung organoid cultures

The distal lung contains terminal bronchioles and alveoli that facilitate gas exchange and is affected by disorders including interstitial lung disease, cancer, and SARS-CoV-2-associated COVID-19 pneumonia. Investigations of these localized pathologies have been hindered by a lack of 3D in vitro human distal lung culture systems. Further, human distal lung stem cell identification has been impaired by quiescence, anatomic divergence from mouse and lack of lineage tracing and clonogenic culture. Here, we developed robust feeder-free, chemically-defined culture of distal human lung progenitors as organoids derived clonally from single adult human alveolar epithelial type II (AT2) or KRT5+ basal cells. AT2 organoids exhibited AT1 transdifferentiation potential, while basal cell organoids progressively developed lumens lined by differentiated club and ciliated cells. Organoids consisting solely of club cells were not observed. Upon single cell RNA-sequencing (scRNA-seq), alveolar organoids were composed of proliferative AT2 cells; however, basal organoid KRT5+ cells contained a distinct ITGA6+ITGB4+ mitotic population whose proliferation segregated to a TNFRSF12Ahi subfraction. Clonogenic organoid growth was markedly enriched within the TNFRSF12Ahi subset of FACS-purified ITGA6+ITGB4+ basal cells from human lung or derivative organoids. In vivo, TNFRSF12A+ cells comprised ~10% of KRT5+ basal cells and resided in clusters within terminal bronchioles. To model COVID-19 distal lung disease, we everted the polarity of basal and alveolar organoids to rapidly relocate differentiated club and ciliated cells from the organoid lumen to the exterior surface, thus displaying the SARS-CoV-2 receptor ACE2 on the outwardly-facing apical aspect. Accordingly, basal and AT2 "apical-out" organoids were infected by SARS-CoV-2, identifying club cells as a novel target population. This long-term, feeder-free organoid culture of human distal lung alveolar and basal stem cells, coupled with single cell analysis, identifies unsuspected basal cell functional heterogeneity and exemplifies progenitor identification within a slowly proliferating human tissue. Further, our studies establish a facile in vitro organoid model for human distal lung infectious diseases including COVID-19-associated pneumonia.

cell biology↗

bioRxiv2018

Predicting cell types in single cell mass cytometry data

MotivationMass cytometry (CyTOF) is a valuable technology for high-dimensional analysis at the single cell level. Identification of different cell populations is an important task during the data analysis. Many clustering tools can perform this task, however, they are time consuming, often involve a manual step, and lack reproducibility when new data is included in the analysis. Learning cell types from an annotated set of cells solves these problems. However, currently available mass cytometry classifiers are either complex, dependent on prior knowledge of the cell type markers during the learning process, or can only identify canonical cell types.\n\nResultsWe propose to use a Linear Discriminant Analysis (LDA) classifier to automatically identify cell populations in CyTOF data. LDA shows comparable results with two state-of-the-art algorithms on four benchmark datasets and also outperforms a non-linear classifier such as the k-nearest neighbour classifier. To illustrate its scalability to large datasets with deeply annotated cell subtypes, we apply LDA to a dataset of ~3.5 million cells representing 57 cell types. LDA has high performance on abundant cell types as well as the majority of rare cell types, and provides accurate estimates of cell type frequencies. Further incorporating a rejection option, based on the estimated posterior probabilities, allows LDA to identify cell types that were not encountered during training. Altogether, reproducible prediction of cell type compositions using LDA opens up possibilities to analyse large cohort studies based on mass cytometry data.\n\nAvailabilityImplementation is available on GitHub (https://github.com/tabdelaal/CyTOF-Linear-Classifier).\n\nContacta.mahfouz@lumc.nl

bioinformatics↗

bioRxiv2017

Interactive Visual Analysis of Mass Cytometry Data by Hierarchical Stochastic Neighbor Embedding Reveals Rare Cell Types

Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analysed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry datasets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We applied HSNE to a study on gastrointestinal disorders and three other available mass cytometry datasets. We found that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional datasets.

bioinformatics↗