Spatial transcriptomics of an innate granuloma in a mouse infection model with Chromobacterium violaceum
Data files
Feb 05, 2025 version files 409.57 MB
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Chemokines-Spatial-FINAL.R
7.40 KB
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mergered8_clustree.rds
409.56 MB
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README.md
2.96 KB
Abstract
From Amason et al., 2024. "Granulomas are defined by the presence of organized layers of immune cells that include macrophages. Granulomas are often characterized as a way for the immune system to contain an infection and prevent its dissemination. We recently established a mouse infection model where Chromobacterium violaceum induces the innate immune system to form granulomas in the liver. This response successfully eradicates the bacteria and returns the liver to homeostasis. Here, we sought to characterize the chemokines involved in directing immune cells to form the distinct layers of a granuloma. We use spatial transcriptomics to investigate the spatial and temporal expression of all CC and CXC chemokines and their receptors within this granuloma response. The expression profiles change dynamically over space and time as the granuloma matures and then resolves. To investigate the importance of monocyte-derived macrophages in this immune response, we studied the role of CCR2 during C. violaceum infection. Ccr2–/– mice had negligible numbers of macrophages, but large numbers of neutrophils, in the C. violaceum-infected lesions. In addition, lesions had abnormal architecture resulting in loss of bacterial containment. Without CCR2, bacteria disseminated and the mice succumbed to the infection. This indicates that macrophages are critical to form a successful innate granuloma in response to C. violaceum."
README: Spatial transcriptomics of an innate granuloma in a mouse infection model with Chromobacterium violaceum
https://doi.org/10.5061/dryad.zpc866thz
Description of the data and file structure
The uploaded data file contains Visium spatial transcriptomics data extracted from C. violaceum-infected mouse liver tissues at various days post-infection. See Methods for further information on this file.
Code/software
From Amason et al., 2024 "Spatial data were generated in Harvest et al., 2023 using the 10X Genomics Visium Platform. We were most interested in the immune cells present within the distinct zones of each lesion, and the adjacent healthy hepatocytes. Therefore, we used Loupe Browser v7.0 to visualize the H&E-stained tissues and manually select spots of interest. We deselected spots that were distant from infected lesions, while selecting the lesions and surrounding healthy hepatocytes. To account for cell-to-cell variation, especially across tissues, pre-processing included normalization using sctransform. To further analyze the spatial transcriptomics dataset of the selected spots, we used the Seurat package in RStudio to analyze gene expression over time and space. UMAP plots, SpatialDimPlots, SpatialFeaturePlots, ggplots, and Violin plots were all used to visualize normalized gene expression data."
Software: RStudio 2024.04.0+735 "Chocolate Cosmos" Release (a00d0e775dbc93e0d79a1bf474e3e8e8de677383, 2024-04-24) for windows
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) RStudio/2024.04.0+735 Chrome/120.0.6099.291 Electron/28.2.6 Safari/537.36, Quarto 1.4.553
The Streamlined Code file (Zenodo) contains all code relevant for generating plots found in Amason et al., 2024. Initial characterization of predominant cell types and/or location of each cluster was performed in Harvest et al., 2023. Relevant cluster abbreviations: Macrophage zone (M), hepatocyte (HEP), representative HEP (rep HEP), necrotic core center (NC-C), NC-periphery (NC-P), coagulative necrosis (CN), CN-macrophage (CN-M), endothelial cell (EC), outside granuloma (OG).
Access information
Data was derived from the following sources:
- Harvest, C. K., Abele, T. J., Yu, C., Beatty, C. J., Amason, M. E., Billman, Z. P., DePrizio, M. A., Souza, F. W., Lacey, C. A., Maltez, V. I., Larson, H. N., McGlaughon, B. D., Saban, D. R., Montgomery, S. A., & Miao, E. A. (2023). An innate granuloma eradicates an environmental pathogen using Gsdmd and Nos2. Nature Communications, 14(1), 6686. https://doi.org/10.1038/s41467-023-42218-1
- Amason M.E., Beatty C.J., Harvest C.K., Saban D.R., Miao E.A. Chemokine expression profile of an innate granuloma. bioRxiv [Preprint]. 2024 Jun 6:2024.01.30.577927. doi: 10.1101/2024.01.30.577927. PMID: 38352492; PMCID: PMC10862903. (publication pending through eLife)
Methods
From Harvest et al., 2023. "Infected mouse liver tissues were harvested at various time points, embedded in OCT, and frozen. Frozen livers were cut to optimal section thickness and placed on a Tissue Optimization Slide to determine permeabilization conditions. Tissues were then placed within a 6.5mm2 field on an expression slide that contained 5000 barcoded probes. The tissues were then fixed and stained with Hoechst and Eosin then permeabilized to release mRNA which binds to spatially barcoded capture probes, allowing for the capture of gene expression information. Captured mRNA from the slide surface was denatured, cleaved, and transferred into a PCR tube. From there, the cDNA was amplified, and standard NGS libraries were prepared. Adapters were ligated to each fragment followed by a sample index PCR. The libraries were sequenced to an average of 50,000 reads/probe on a paired-end, dual-indexed flow cell in the format of 28x10x10×90. Data was then uploaded to analysis packages for visualization. Visium spatial data was analyzed using 10xGenomincs Space Ranger software and visualization through Loupe Browser. Secondary statistical analysis was performed using a Seurat package in R(Studio)."