Single-cell spatial transcriptomics of an inducible destabilized-domain Cre mouse line to target disease associated microglia
Data files
Oct 28, 2025 version files 2.57 GB
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annotated_seurat.RDS
2.57 GB
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README.md
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Abstract
This dataset contains the results from a single-cell spatial transcriptomics experiment performed using Bruker Nanostring CosMx technology on 10µm thick fresh-frozen coronal brain sections from the following groups: 5xFAD hemizygous, Cst7 DD-Cre, Ai14tdTomato double heterozygous (AD, n = 3), and Cst7 DD-Cre/Ai14tdTomato double heterozygous (WT, n = 1) mice treated with TMP, and Cst7 DD-Cre/Ai14tdTomato double heterozygous mice treated with cuprizone (CPZ) and TMP (CPZ, n = 2). The dataset is provided as an .RDS file, which includes raw and corrected counts, along with comprehensive metadata. Metadata includes experimental group, sample ID, cell type annotations, and X-Y coordinates of each cell.
The function of microglia during progression of Alzheimer's disease (AD) can be investigated using mouse models that enable genetic manipulation of microglial subpopulations in a temporal manner. We developed mouse lines that express either Cre recombinase (Cre) for constitutive targeting, or destabilized-domain Cre recombinase (DD-Cre) for inducible targeting from the Cst7 locus (Cst7 DD-Cre) to specifically manipulate disease associated microglia (DAM) and crossed with Ai14 tdTomato cre-reporter line mice. Cst7Cre was found to target all brain resident myeloid cells, due to transient developmental expression of Cst7, but no expression was found in the inducible Cst7 DD-Cre mice. Further crossing of this line with 5xFAD mice combined with dietary administration of trimethoprim to induce DD-Cre activity produces long-term labeling in DAM without evidence of leakiness, with tdTomato-expression restricted to cells surrounding plaques. Using this model, we found that DAMs are a subset of plaque-associated microglia (PAMs) and their transition to DAM increases with age and disease stage. Spatial transcriptomic analysis revealed that tdTomato+ cells show higher expression of disease and inflammatory genes compared to other microglial populations, including non-labeled PAMs. These models allow either complete cre-loxP targeting of all brain myeloid cells (Cst7Cre), or inducible targeting of DAMs, without leakiness (Cst7 DD-Cre).
Dataset DOI: 10.5061/dryad.15dv41p9d
Description of the data and file structure
Sample preparation: Isopentane fresh-frozen brain hemispheres were embedded in OCT compound, and 10 μm thick coronal sections prepared on a cryostat. Six hemibrains were mounted directly onto a VWR Superfrost Plus microscope slide and stored at −80°C until fixation. 5xFAD hemizygous, Cst7 DD-Cre, Ai14tdTomato double heterozygous (n = 3), and Cst7 DD-Cre/Ai14tdTomato double heterozygous (n = 1) mice treated with TMP, and Cst7 DD-Cre/Ai14tdTomato double heterozygous mice treated with cuprizone (CPZ) and TMP (n = 2) were used for spatial transcriptomics. Tissues were processed according to the Nanostring CosMx fresh-frozen slide preparation manual for RNA assays.
Data processing: Spatial transcriptomics datasets were filtered using the AtoMx RNA Quality Control module to flag poorly performing probes, cells, FOVs, and target genes. Datasets were then normalized and scaled using Seurat SCTransform to account for differences in library size across cell types (Hafemeister and Satija 2019; Choudhary and Satija 2022). Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were performed to reduce dimensionality for downstream analysis. Unsupervised clustering at 1.0 resolution yielded 38 clusters for the dataset. Clusters were manually annotated based on gene expression and spatial location.
We have submitted the processed .RDS file, analyzed using the R package Seurat. Sample metadata are stored in annotated_seurat@meta.data.
Files and variables
annotated_seurat.RDS
Row names of metadata (accessed using rownames(seurat@meta.data)) contain unique identifiers for each single cell, formatted as c_[slide]_[fov]_[cell]. Cell type annotations are stored in Idents(seurat). Additional metadata columns are described below:
- fov: Field Of View (FOV) the cell is in
- Area: Number of pixels assigned to a given cell
- AspectRatio: Width divided by height
- x_FOV_px: x position of the cell center within the FOV, measured in pixels
- y_FOV_px: y position of the cell center within the FOV, measured in pixels
- Width: Cell’s maximum length in x dimension (pixels)
- Height: Cell’s maximum length in y dimension (pixels)
- Mean.DAPI: Mean DAPI fluorescence intensity within a given cell (AU)
- Max.DAPI: Max DAPI fluorescence intensity within a given cell (AU)
- Mean.Histone: Mean Histone fluorescence intensity
- Max.Histone: Max Histone fluorescence intensity
- Mean.rRNA: Mean rRNA fluorescence intensity
- Max.rRNA: Max rRNA fluorescence intensity
- Mean.GFAP: Mean GFAP fluorescence intensity
- Max.GFAP: Max GFAP fluorescence intensity
- x_slide_mm: x position of the cell center within the slide, measured in mm
- y_slide_mm: y position of the cell center within the slide, measured in mm
- nCount_RNA: Number of RNA counts
- nFeature_RNA: Number of unique RNA targets
- nCount_negprobes: Number of Negative counts
- nCount_SCT: SCT-corrected number of RNA counts
- nFeature_SCT: SCT-corrected number of unique RNA targets
- nFeature_negprobes: Number of unique Negative targets
- Area.um2: Area of cell (um^2)
- qcCellsFlagged: Cells flagged by AtoMx QC module
- group: Experimental group name
- sample_n: Sample number
Code/software
Files were analyzed using Seurat (https://satijalab.org/seurat/).
