Ontogeny-independent expression of LPCAT2 in granuloma macrophages during experimental visceral leishmaniasis

This deposit contains the processed data and analysis scripts accompanying the manuscript "Ontogeny-independent expression of LPCAT2 in granuloma macrophages during experimental visceral leishmaniasis" by Dey, Cao et al. The study integrates spatial transcriptomics (10x Visium), mass spectrometry imaging (MSI), single-cell RNA sequencing (scRNA-seq), and proteomics to characterise hepatic granulomas in a murine model of visceral leishmaniasis (Leishmania donovani). A novel role for LPCAT2-mediated phospholipid remodelling in granuloma-associated macrophages is identified, independent of macrophage ontogeny. Deposited files: File Description integrated_sd2705_dims15_res0.4.rds Pre-processed, integrated scRNA-seq Seurat object (8 samples: 4 infected, 2 naive pools). Used by scRNAseq_downstream_analysis.Rmd. integrated_d28_cohort_dims30_res_0.4.Rds Pre-processed, integrated spatial transcriptomics (Visium) Seurat object (7 capture areas: 4 infected, 4 naive). Used by spatial_downstream_analysis.Rmd. coregistration.zip Co-registered mass spectrometry imaging (MSI) lipid intensities mapped to Visium spot barcodes. Contains per-sample CSVs for negative and positive ion modes (8 mice: I2, I3, I4, I5, N1, N2, N3, N4), cell2location cell-type abundance estimates, and m/z-to-lipid species identification. scripts.zip R Markdown notebooks, Python scripts, and supporting files for reproducing all analyses. Also available on GitHub: https://github.com/jipsi/spatial_lipid_gene Raw data availability: Raw Visium spatial transcriptomics data: GEO accession GSE290324 Raw scRNA-seq data: GEO accession GSE290325 Software requirements: R ≥ 4.2.2 with Seurat ≥ 4.3.0 Python ≥ 3.8 with cell2location (for spatial deconvolution; GPU recommended) Keywords: spatial transcriptomics, mass spectrometry imaging, single-cell RNA-seq, visceral leishmaniasis, granuloma, LPCAT2, phospholipid remodelling, cell2location, Seurat License: MIT