Biology subjects

Welsh, E.

Publications and source records attributed to Welsh, E..

3 recordsLinked to original sources

bioRxiv2026

spatialMET: an open and scalable framework for spatial metabolomics analysis

Mass spectrometry imaging (MSI) enables spatially resolved metabolomics in intact tissue sections, but analysis remains challenging at scale. Existing MSI workflows often require users to combine multiple software tools, while others rely on proprietary vendor software that limits interoperability and reproducibility. To address these challenges, we developed spatialMET, an open-source framework that provides an end-to-end workflow for MSI analysis. spatialMET provides a unified platform for preprocessing, spatial domain detection, and visualization. Downstream analyses include differential abundance testing, spatial autocorrelation and gradient analysis, dimensionality reduction, and correlation network analysis. Spatial domain detection uses hcdist, a C-based hierarchical clustering implementation that substantially reduces runtime and memory use relative to existing R-based approaches. spatialMET can be run through an interactive R Shiny application or as a standalone command-line workflow for larger datasets or high-performance computing environments. Applied to mouse small cell lung cancer MALDI-MSI data containing 284,673 pixels, spatialMET identified tumor-associated, stromal, and adjacent lung spatial domains that aligned with matched histology. Differential abundance analysis identified 117 m/z features that differed between tumor and stromal regions, while spatial autocorrelation analyses revealed spatially structured abundance patterns. Applying spatialMET to mouse lung adenocarcinoma data from an entire lung lobe containing 338,477 pixels further demonstrated scalability and captured spatial heterogeneity across tumor and surrounding lung tissue. In summary, spatialMET provides a scalable, open-source framework for end-to-end spatial metabolomics analysis, and it is distributed as a Docker container for reproducible deployment. Source code and installation instructions are available at https://github.com/biodatalab/spatialMET.

bioinformatics↗

bioRxiv2025

Interleukin-36 upregulates type-I interferon responses in systemic lupus erythematosus by promoting the accumulation of self-nucleic acids

IntroductionSeveral studies have reported an up-regulation of interleukin (IL)-36 in the serum of patients with systemic lupus erythematosus (SLE). Here, we sought to define the mechanisms whereby IL-36 may contribute to the over-activation of type I Interferon (IFN) responses observed in SLE. MethodsWe carried out single-cell (sc)RNA-seq in healthy peripheral blood mononuclear cells treated with IL-36 (n=5 donors). We compared the genes and transcriptional networks that were induced by IL-36 with those that were upregulated in a published SLE scRNA-seq dataset (n=33 cases and 11 controls). In follow-up studies, we validated the effects of IL-36 on monocytes by real-time PCR (n=9 donors) and flow-cytometry (n=6). ResultsClassical monocytes were the immune population most affected by IL-36 treatment (n=203 Differentially Expressed Genes). In these cells, IL-36 upregulated transcriptional networks (regulons) driven by IRF7, a key activator of type I IFN responses. A similar upregulation of IRF7 regulons was observed in the monocytes of SLE cases, where measurements of IL-36 and IRF7 activity were significantly correlated (r=0.35, P=0.02). Experimental follow-up studies in human monocytes showed that IL-36 downregulates multiple RNAse genes (RNASE1, RNASE6, RNASET2). IL-36 treatment of monocytes also increased the percentage of apoptotic cells (45% vs 37% in untreated cells; P=0.001), which are a critical source of self-nucleic acids. ConclusionWe find that IL-36 promotes monocyte apoptosis while downregulating self-nucleic acid clearance. Thus, IL-36 contributes to the accumulation of self-nucleic acids, a key driver of type I IFN responses in SLE.

immunology↗

bioRxiv2025

Contrasting roles of host species in tick-pathogen interactions and their influence on Lyme borreliosis hazard across boreal island communities

Predicting the hazard of Lyme borreliosis (LB) is complex due to host-specific effects on tick and pathogen dynamics. To unpick the contributions of cervids and rodents on ticks and Borrelia burgdorferi infection in ticks in boreal region, we analysed data from 41 islands in Finland (2017-2021) with considerable natural variation in the abundances of cervids and rodents, and densities of nymphs (DON: 0-82.5 nymphs/100 m2), nymph infection prevalences (NIP: 0-60%) and densities of infected nymphs (DIN: 0-16.5/100 m2). Using structural equation modelling (SEM), we disentangled direct and indirect effects of host abundances on LB hazard (i.e., DIN). Rodent abundance was associated with higher DIN through its positive effect on NIP (pathogen amplification), while showing no effect on DON. Cervids increased DON (vector amplification) but decreased NIP (pathogen dilution). Our study suggests that in boreal forests the vectors may be supported by very low cervid densities and, as a virtual absence of rodents did not eliminate the pathogen, the pathogen is likely to persist through very low rodent densities. Our study highlights how islands function as a natural mesocosm for rigorous field studies of complex ecological interactions and SEM can serve as a powerful tool to reveal mechanisms driving LB hazard.

ecology↗