Biology subjects

Exner, T.

Publications and source records attributed to Exner, T..

8 recordsLinked to original sources

bioRxiv2025

THE IMMUNE RESPONSE AGAINST CANCER IS MODULATED BY STROMAL CELL FIBRONECTIN

Cancer-associated fibroblasts remain poorly understood, with some of them originating from the bone marrow. We therefore took advantage of the diversity of bone marrow stromal cells to shed light on how fibroblasts modulate cancer growth. In two murine cancer models, adding these fibroblasts to tumor cells resulted in smaller lesions. Suppression was enhanced by pretreatment with fibronectin, while genetic deletion of fibronectin in a small subpopulation of stromal cells expressing osterix/sp7 restored growth. The suppressive stromal population showed two more characteristics: the absence of CD31/pecam1 and CD105/endoglin. However, only a decrease in CD105/ENDOGLIN in melanoma patients translated in improved survival. Mechanistically, fibronectin or fibronectin fragments activate integrin 5{beta}1 and TLR4 and increase chemokine production by stromal cells ultimately leading to enhanced recruitment and activity of Ly6G+ myeloid cells without T-cell involvement. This work thus characterizes a beneficial interaction between stromal cells and neutrophils enhancing the immune response against early cancer. HighlightsO_LIStromal cells can be divided into two populations, a tumor supportive one with the potential to stimulate angiogenesis and an inhibitory one with the potential to enhance the immune response C_LIO_LIStromal fibronectin expressing the transduction factor osterix/sp7 produce fibronectin that acts on 5{beta}1 integrin and/or TLR4 on neighboring fibroblasts to modulate Ly6G+ immune cells and suppress tumor growth C_LI One sentence summaryTumor inhibitory fibroblasts have three characteristics and through production of fibronectin act on neighboring cells inducing signaling cascades that ultimately lead to a stronger immune response against early cancer.

cancer biology↗

bioRxiv2025

Deep learning predicts tissue outcomes in retinal organoids

Retinal organoids have become important models for studying development and disease, yet stochastic heterogeneity in the formation of cell types, tissues, and phenotypes remains a major challenge. This limits our ability to precisely experimentally address the early developmental trajectories towards these outcomes. Here, we utilize deep learning to predict the differentiation path and resulting tissues in retinal organoids well before they become visually discernible. Our approach effectively bypasses the challenge of organoid-related heterogeneity in tissue formation. For this, we acquired a high-resolution time-lapse imaging dataset comprising about 1,000 organoids and over 100,000 images enabling precise temporal tracking of organoid development. By combining expert annotations with advanced image analysis of organoid morphology, we characterized the heterogeneity of the retinal pigmented epithelium (RPE) and lens tissues, as well as global organoid morphologies over time. Using this training set, our deep learning approach accurately predicts the emergence and size of RPE and lens tissue formation on an organoid-by-organoid basis at early developmental stages, refining our understanding of when early lineage decisions are made. This approach advances knowledge of tissue and phenotype decision-making in organoid development and can inform the design of similar predictive platforms for other organoid systems, paving the way for more standardized and reproducible organoid research. Finally, it provides a direct focus on early developmental time points for in-depth molecular analyses, alleviated from confounding effects of heterogeneity.

developmental biology↗

bioRxiv2024

Accurate, fast and memory efficient quantification of immune cell phenotypes in cytometry using machine learning

To achieve accurate and reproducible cytometry data analysis, we benchmarked 19 machine learning algorithms for supervised and unsupervised cell classification. The underlying data encompassed 138 million cells from seven independent datasets including conventional flow cytometry, spectral flow cytometry and mass cytometry. We found that tree-based classifiers and in particular Decision Trees, outperformed other approaches in classification accuracy, speed and memory use. High accuracy was achieved even for cell populations rarer than 1% using decision trees. We validated our decision tree-based approach in a clinical setting using diagnostic blood T cell phenotyping of 107 patients. Automatic quantification of CD4 helper T cell phenotypes achieved 99 % accuracy compared to manual expert assessment. Finally, we combined automated data transformation, supervised and unsupervised gating, an application program interface and a user-friendly desktop-application into FACSPy and FACSPyUI, a fast and scalable open-source toolbox for the analysis and visualization of cytometry data.

bioinformatics↗

bioRxiv2024

CytoNormPy enables a fast and scalable removal of batch effects in cytometry datasets.

MotivationWe present a python implementation of the widely used CytoNorm algorithm for the removal of batch effects. ResultsOur implementation ran up to 85% faster than its R counterpart, while being fully compatible with common single-cell data structures and -frameworks of python. We extend the previous functionality by adding common clustering algorithms and provide key visualizations of the algorithm and its evaluation. Availability and implementationThe CytoNormPy implementation is freely available on GitHub: https://github.com/TarikExner/CytoNormPy.

bioinformatics↗

bioRxiv2023

Distinct Functional States of Neutrophils by Actin Disassembly and NF-kB/STAT3 Signaling

Polymorphonuclear neutrophils (PMNs) can differentiate into distinct states, which can either exacerbate or resolve inflammation. Our study shows that mice challenged with TLR agonists exhibited PMN differentiation along two major paths characterized by the expression of CCR5 or PD-L1. Similar differentiation was observed in the blood of severe COVID-19 patients and the synovial fluid of osteoarthritis patients. Prolonged in vitro priming of human PMNs modeled the differentiation paths. Actin disassembly favored CCR5 upregulation, while NF-kB activation stabilized the actin cytoskeleton and suppressed the development of CCR5+ PMNs. Additionally, PD-L1 upregulation was triggered by STAT3 signaling and NF-kB activation. Functionally, CCR5 expressing PMNs were pro-NETotic, while PD-L1+ PMNs showed immunosuppressive functions by inhibiting T cell proliferation via PD1. Together, PMN differentiation depended on the priming conditions, and the balance between actin disassembly and NF-kB/STAT3 activation translated the present micro-milieu into phenotypic and functional diversification of PMNs. SynopsisNeutrophils underwent phenotypical and functional diversification both in vivo and in vitro. Actin disassembly led to the generation of CCR5high neutrophils with increased spontaneous NETosis, whereas NF-kB and STAT3 induced PD-L1 expression with T-cell suppressive properties as a deviation from the default pathway. O_LIPMN of mice challenged with TLR agonists develop two distinct phenotypes, CCR5high and PD-L1high. C_LIO_LICCR5 and PD-L1-defined neutrophil phenotypes were found in blood of patients with severe COVID-19 and in the synovial fluid of osteoarthritis patients. C_LIO_LIIn vitro priming induced a similar bifurcation of PMN phenotypes marked by either CCR5 or PD-L1. C_LIO_LIActin disassembly preceded canonical development of CCR5+ PMN. C_LIO_LINF-kB halted actin disassembly by LPL regulation. C_LIO_LIDuring neutrophil priming, STAT3 aided NF-kB in the expression of PD-L1. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/548975v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@10305f3org.highwire.dtl.DTLVardef@17bada8org.highwire.dtl.DTLVardef@c61021org.highwire.dtl.DTLVardef@14ce7f3_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Human and murine neutrophils share core transcriptional programs in both homeostatic and inflamed contexts

Neutrophils are frequently studied in murine models, but the extent to which findings translate to humans remains poorly defined. Here, we performed an integrative transcriptomic analysis of 11 murine and 13 human datasets. In homeostasis, neutrophils exhibited the highest number of lineage-specific genes and the greatest degree of correlated expression among genes with one-to-one orthologs (r = 0.79, P < 2.2 x 10-16) compared to other leukocytes. In inflammation, neutrophils displayed considerable transcriptional diversity, but shared a core inflammation program across a broad range of conditions which was conserved between species. This core program included genes encoding IL-1 family members, CD14, IL-4R, CD69 and PD-L1. Chromatin accessibility of core inflammation genes increased significantly in blood compared to bone marrow and further with migration from blood to tissue. Transcription factor enrichment analysis nominated members of the NF-{kappa}B family and AP-1 complex as important drivers of the core inflammation program, and HoxB8 neutrophils with JUNB knockout showed a significantly reduced expression of core inflammation genes at baseline and upon stimulation. In vitro perturbations confirmed surface protein upregulation of core inflammation members in both species. Together, we demonstrate substantial transcriptional conservation in neutrophils in homeostasis and identify a core inflammation program conserved across species. This systems biology approach can be leveraged to improve transitions between the murine and human context. Key PointsO_LIThe transcriptome of resting neutrophils is substantially conserved between humans and mice C_LIO_LIA core inflammation program in neutrophils is shared across a broad range of conditions and conserved across humans and mice C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=52 SRC="FIGDIR/small/516246v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1f6b40borg.highwire.dtl.DTLVardef@1a67bb4org.highwire.dtl.DTLVardef@1039a8forg.highwire.dtl.DTLVardef@1982d10_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Aging and interferon gamma response drive the phenotype of neutrophils in the inflamed joint

ObjectivesNeutrophils are typically the most abundant leukocyte in arthritic synovial fluid. We sought to understand changes that occur in neutrophils as they migrate from blood to joint. MethodsWe performed RNA sequencing of neutrophils from healthy human blood, arthritic blood, and arthritic synovial fluid, comparing transcriptional signatures with those from murine K/BxN serum transfer arthritis. We employed mass cytometry to quantify protein expression and sought to reproduce the synovial fluid phenotype ex vivo in cultured healthy blood neutrophils. ResultsBlood neutrophils from healthy donors and patients with active arthritis exhibited largely similar transcriptional signatures. By contrast, synovial fluid neutrophils exhibited more than 1,600 differentially expressed genes. Gene signatures identified a prominent response to interferon gamma (IFN{gamma}), as well as to tumor necrosis factor, interleukin 6, and hypoxia, in both humans and mice. Mass cytometry also found healthy and arthritic donor blood neutrophils largely indistinguishable but revealed a range of neutrophil phenotypes in synovial fluid defined by downregulation of CXCR1 and upregulation of Fc{gamma}RI, HLA-DR, PD-L1, ICAM-1 and CXCR4. Reproduction of key elements of this signature in cultured blood neutrophils required both IFN{gamma} and prolonged culture. ConclusionsCirculating neutrophils from arthritis patients resemble those from healthy controls, but joint fluid cells exhibit a network of changes, conserved across species, that implicate IFN{gamma} response and aging as complementary drivers of the synovial neutrophil phenotype. KEY MESSAGESO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LINeutrophils are central in the effector phase of inflammatory arthritis but their phenotypic heterogeneity in inflamed synovial fluid is poorly understood. C_LI What does this study add?O_LIRNA-seq and mass cytometry identify a hallmark phenotype of neutrophils in synovial fluid consisting of upregulated ICAM-1, HLA-DR, PD-L1, Fc receptors and CXCR4. C_LIO_LITranscriptomics highlight an IFN{gamma} response signature conserved across humans and mice. C_LIO_LIIn vitro experiments implicate aging and IFN{gamma} as complementary factors orchestrating the synovial fluid neutrophil phenotype. C_LI How might this impact on clinical practice or future developments?O_LIUnderstanding the specific features of neutrophils in the arthritic joint may disclose opportunities for safe therapeutic targeting of this lineage. C_LI

immunology↗

bioRxiv2018

An alternative membrane topology permits lipid droplet localization of peroxisomal fatty acyl-CoA reductase 1

Fatty acyl-CoA reductase 1 (Far1) is an ubiquitously expressed peroxisomal membrane protein generating fatty alcohols required for the biosynthesis of ether lipids.\n\nLipid droplet localization of human Far1 was observed by fluorescence microscopy under conditions of increased triglyceride synthesis in tissue culture cells. This unexpected finding was supported further by correlative light electron microscopy and subcellular fractionation. Selective permeabilization and N-glycosylation tagging suggest that Far1 is able to assume two different membrane topologies, differing in the orientation of the short hydrophilic C-terminus towards the lumen or the cytosol, respectively. Two closely spaced hydrophobic domains are contained within the C-terminal region. When analyzed separately, the second domain was sufficient for the localization of a fluorescent reporter to lipid droplets. Targeting of Far1 to lipid droplets was not impaired in either pex19 or TRC40/ASNA1 CRISPR/Cas9 knockout cells.\n\nIn conclusion, our data suggest that Far1 is a novel member of the rather exclusive group of dual topology membrane proteins. At the same time, Far1 shows lipid metabolism-dependent differential subcellular localizations to peroxisomes and lipid droplets.

cell biology↗