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Niedobitek, G.

Publications and source records attributed to Niedobitek, G..

2 recordsLinked to original sources

The spatial landscape of infectious mononucleosis tonsils

Primary Epstein-Barr virus (EBV) infection remains incompletely understood, particularly in relation to the nature of in vivo latency patterns and their influence on the immune microenvironment. Here, we present the first multiomic single-cell spatial atlas of palatine tonsils from individuals with infectious mononucleosis (IM). We identify rare EBV infection of epithelial cells, challenging the prevailing assumption that primary infection is restricted to B- and T-cells. Moreover, our detailed analysis suggests a spatiotemporal transition of EBV latency programs, with distinct viral gene expression patterns corresponding to specific tissue microenvironments-a dynamic process previously inferred but not directly mapped in human tissues. We found that cells expressing the EBV-encoded protein LMP1 form an immunosuppressive niche that is rich in IDO1+PDL1+ macrophages and relatively depleted of T-cells. Furthermore, the T-cells that do infiltrate LMP1+ regions exhibit signatures consistent with an activated and cytotoxic phenotype, providing new insights into how LMP1 shapes immune evasion. Taken together, our data redefine the spatial and functional organisation of primary EBV infection, integrating latency plasticity, epithelial tropism, and microenvironmental immunosuppression into a unified framework, as well as providing a data-rich framework for understanding viral persistence and immune evasion.

immunology↗

CellMAPS: A no-code model-based customisable multiplex image analysis workflow

Although multiplex imaging allows simultaneous mapping of complex tissue architectures and cellular phenotypes, the dearth of user-friendly robust image analysis workflows remains a significant limitation to its widespread use, restricting multiplex imaging to laboratories with image analysis expertise. Here, we introduce a no-code model-based customisable suite, CellMAPS, which allows both image processing and spatial analyses by non-specialists. We also developed new tools for tissue de-arraying, image normalisation and cell segmentation to increase usability and reduce analysis subjectivity. We have also introduce new spatial analysis tools for the partition of tissue architectures and cellular microenvironments. We demonstrate the capabilities of CellMAPS in various diseases captured using different multiplex imaging platforms. Overall, CellMAPS provides a platform for inexperienced laboratories to implement multiplex imaging and complex spatial analyses, which ultimately should lead to the broader adoption of these technologies in the biomedical field.

bioinformatics↗