Journal: STAR Protocols

Article Title: Optimized protocol for dissociation of mouse intestinal epithelium to viable single-cells

doi: 10.1016/j.xpro.2026.104431

Figure Lengend Snippet: Flow cytometry analysis of cell viability and yield (A) Sorting strategy for total IECs and enterochromaffin (EC) cells from the colon of Chga-GFP mice. After doublet cell and dead cell exclusion, IECs are defined as CD45 - TER-119 - EpCAM + live cells, and EC cells are defined as CHGA-GFP + IECs. (B and C) Comparison of cell viability and yield obtained using the optimized protocol versus the original protocol. Colon and ileum tissues dissected from B6 mice (n = 4 females and 4 males; 8 weeks old) were longitudinally separated into two equal halves and processed in parallel using the two methods. Cell viability and total cell counts were determined by FACS. Data are presented as mean ± SD. ∗∗∗∗ p < 0.0001, unpaired t test.

Article Snippet: APC anti-mouse CD45 (clone 30-F11); working dilution: 1:100 , Tonbo Biosciences , Cat# 20-0451.

Techniques: Flow Cytometry, Comparison

Journal: Frontiers in Immunology

Article Title: Osteopontin from monocyte-derived dendritic cells mediates ozone-induced pulmonary responses in mice

doi: 10.3389/fimmu.2026.1748667

Figure Lengend Snippet: Gene expression and cell–cell communication analysis of CD45-negative and CD45-positive cells on single-cell RNA sequencing analysis in mice exposed to air or ozone. In CD45-negative cells, (A) annotated cell clusters with the algorithm of the Uniform Manifold Approximation and Projection method, (B) top 5 upregulated gene expressions depending on the p-value of targeted cell clusters compared with the entire dataset on a heat map indicating the log 2 fold change values representing the differential gene expression levels, (C) expression levels of spp1 in each cell cluster on a violin plot indicating the log 2 fold change values representing the differential gene expression levels of Spp1 between the selected cluster and all other clusters combined, and (D) top 10 genes significantly expressed in mice exposed to ozone compared with mice exposed to air on a heatmap indicating the log 2 fold change values representing the differential gene expression levels. In CD45-positive cells, (E) annotated cell clusters with the algorithm of the Uniform Manifold Approximation and Projection method, (F) top 5 upregulated gene expressions depending on the p-value of targeted cell clusters compared with the entire dataset on a heat map showing the log 2 fold change values representing the differential gene expression levels, (G) expression levels of spp1 in each cell cluster on a violin plot showing the log 2 fold change values representing the differential gene expression levels of Spp1 between the selected cluster and all other clusters combined, and (H) top 10 genes significantly expressed in mice exposed to ozone compared with mice exposed to air on a heatmap showing the log 2 fold change values representing the differential gene expression levels. On the cell–cell communication analysis called CellChat, (I) signal strengths from each cell in vertical lines as sources to each cell in horizontal lines as targets shown on a heat map. The color scale indicates relative signal strength changes, with red representing increased signal strength and blue representing decreased signal strength. (J) The network diagram of spp1 shows the predicted cell–cell communication between different cell types identified by single-cell RNA sequencing. Each node represents a specific cell type, and the lines represent predicted ligand–receptor interactions. The thickness of the lines indicates the strength of interactions, and colors distinguish the different cell types.

Article Snippet: For flow cytometric analysis (FACS Verse; BD Bioscience), cells were stained with the following antibodies: CD45 (#20-0451-U100, 30-F11, TONBO Biosciences, Tucson, AZ, USA), MHC-II (#107620, M5/114.15.2, BioLegend), CD64 (#139303, X54-5/7.1, BioLegend), and CD11b (Thermo Fisher Scientific).

Techniques: Gene Expression, Single Cell, RNA Sequencing, Expressing