Journal: Nature

Article Title: The type 2 cytokine Fc–IL-4 revitalizes exhausted CD8 + T cells against cancer

doi: 10.1038/s41586-024-07962-4

Figure Lengend Snippet: a , b , Real-time ECAR analysis ( a ) and average basal glycolysis, glycolytic capacity and reserve ( b ) of ex vivo-induced CD8 + T TE cells ( n = 5 biological replicates). mpH, milli-pH. c , Volcano plot of altered metabolites in ex vivo-induced CD8 + T TE cells treated with Fc–IL-4 ( n = 4 biological replicates) versus PBS ( n = 3 biological replicates). d – f , Experimental setting as described in Fig. . Shown are unsupervised UMAP clustering of PMEL CD8 + TILs based on the 1,667 genes involved in KEGG-defining metabolic pathways ( d ), cell proportion in each cluster ( e ) and systematic expression comparison of carbohydrate metabolisms among top four clusters ( f ). g , h , T cell counts ( g ) and frequencies of granzyme B + IFNγ + ( h ) among ex vivo-induced CD8 + T TE cells with or without 2-DG ( n = 4 biological replicates). i , j , Schematic illustration of single-cell ATAC and gene coprofiling of IL-4 versus PBS-treated ex vivo-induced CD8 + T TE cells and a joint ATAC–gene UMAP ( i ), and volcano plot showing differentially active motifs ( j ). k , l , Experimental setting as described in Fig. . Shown are signalling pathways regulated by DEGs ( k ) and top 20 ranked upstream regulators predicted from DEGs ( l ) in PMEL CD8 + TILs. m , Western blot analysis of indicated proteins in ex vivo-induced CD8 + T TE cells ( n = 3 biological replicates). n – p , Relative basal glycolysis ( n ) ( n = 5 biological replicates), T cell counts ( o ) and granzyme B MFI ( p ) ( n = 3 biological replicates) in Fc–IL-4-treated ex vivo-induced OT1 and OT1 STAT6-KO CD8 + T TE cells (normalized by that in the PBS group) with or without indicated inhibitors. All data represent mean ± s.e.m. and are analysed by two-sided unpaired Student’s t -test ( b and g , h ), two-tailed Mann–Whitney test ( j ), right-tailed Fisher’s exact test ( k ) or one-way ANOVA and Tukey’s test ( n – p ). Schematics in i created using BioRender ( https://Biorender.com ).

Article Snippet: Single-cell coprofiling of epigenomic landscape and gene expression in the same single nuclei was performed using the Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit (10x Genomics).

Techniques: Ex Vivo, Expressing, Comparison, Western Blot, Two Tailed Test, MANN-WHITNEY

Journal: Nature

Article Title: The type 2 cytokine Fc–IL-4 revitalizes exhausted CD8 + T cells against cancer

doi: 10.1038/s41586-024-07962-4

Figure Lengend Snippet: a , Quality assessment of sequenced data from IL-4 or PBS conditions, featuring TSS enrichment score, insert size distribution, unsupervised clustering analysis of ATAC and gene datasets, and corresponding count distribution. Consistent performance is observed with negligible batch effect. b , Gene or ATAC expression UMAP of all the single cells color-coded by their respective conditions. c , d , Expression of functional cytotoxicity ( c ) and survival ( d ) gene markers on the joint UMAP in Fig. , along with comparisons of corresponding accessible peaks between conditions. Statistical analyses were performed using two-sided unpaired Student’s t-test. e , Experimental setting was described in Fig. . Shown is the mechanistic networks associated with the significant activation of selected upstream regulators in Fc–IL-4 treated PMEL CD8 + TILs relative to the PBS condition. z score is computed and used to reflect the predicted activation level (z > 0, activated/upregulated; z < 0, inhibited/downregulated; z ≥ 2 or z ≤ −2 can be considered significant). Statistical analyses are performed using right-tailed Fisher’s Exact Test.

Article Snippet: Single-cell coprofiling of epigenomic landscape and gene expression in the same single nuclei was performed using the Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit (10x Genomics).

Techniques: Expressing, Functional Assay, Activation Assay

Journal: Cell Reports Methods

Article Title: Single-cell sequencing of individual retinal organoids reveals determinants of cell-fate heterogeneity

doi: 10.1016/j.crmeth.2023.100548

Figure Lengend Snippet:

Article Snippet: Dissociated cells were subjected to the standard 10x workflow for Single Cell 3′ v3.1 Dual Index Gene Expression kit (Dual Index Kit TT Set A 96 rxns, 10x Genomics, 1000215).

Techniques: Recombinant, Immunostaining, Binding Assay, DNA Purification, Gene Expression, Ligation, Software, Microscopy

Journal: Science immunology

Article Title: Persistent STAT5 activation reprograms the epigenetic landscape in CD4 + T cells to drive polyfunctionality and antitumor immunity

doi: 10.1126/sciimmunol.aba5962

Figure Lengend Snippet: The t-SNE plots generated using scRNAseq data show clear separation of CASTAT5 and control CD4+ T cells (A, left panel), and each of them can be further projected into three sub-clusters based on gene expression profiles (A, right panel). (B) The violin plots show differential expression of 8 polyfunctionality-related genes among the six clusters of CD4+ T cells. (C) The pie charts show the percent of CD4+ T cells expressing varied number (0 to ≥5) of cytokines and cytolytic molecules in each cluster. The number of cells with positive expression of each effector molecule was counted based on the presence or absence of raw sequencing reads mapped to the mRNA sequences of each relevant gene. Cells with at least 1 read mapped to the relevant gene were called as positive for the corresponding gene. (D) Heatmap of top 10 genes expressed in each cluster. The columns represent cells and the rows present genes. Cells are grouped by clusters and top 10 most significant markers are shown. (E) Violin plots of six unique marker genes representing cluster 6. Each dot represents one cell and the violin shows the distribution of probability density at each value. (F) A gene co-expression network specific to cells of cluster 6 is identified using WGCNA.

Article Snippet: To further understand the heterogeneity of the T cell population and the transcriptome associated with polyfunctionality, we conducted single-cell RNA sequencing analysis (scRNAseq) for CASTAT5 and control CD4 + T cells using the 10x Genomics platform.

Techniques: Generated, Control, Gene Expression, Quantitative Proteomics, Expressing, Sequencing, Marker

Journal: Cell reports

Article Title: Altered hepatic metabolism in Down syndrome

doi: 10.1016/j.celrep.2025.116835

Figure Lengend Snippet: (A) Volcano plot summarizing results of whole liver transcriptome analysis of wild-type ( n = 6, 3 females) versus Dp16 ( n = 6, 3 females) mice. Significantly differentially expressed (q < 0.1) genes are colored in red. (B) Bar plot summarizing the results of gene set enrichment analysis of gene expression changes data in (A). (C) Heatmap showing the median Z score of the top 10 leading-edge genes from the epithelial-mesenchymal transition gene set. (D) Sina plots displaying the normalized relative expression (RPKM) of Col1a1 and Eln in wild-type and Dp16 mice. (E) Uniform manifold approximation and projection (UMAP) plot of single-cell RNA sequencing (scRNA-seq) analysis of mouse liver, color coded by cell clusters identified using Seurat. (F) UMAP plot displaying differential cellular abundance of clusters from scRNA-seq analysis of mouse liver. Significant (false discovery rate [FDR] <0.1) clusters are colored by mean fold-change. (G) Sina plots showing the Dp16 versus wild-type abundance of hepatocyte cluster 1 and endothelial cell cluster 2 from scRNA-seq analysis of mouse liver. (H) UMAP plot displaying the epithelial-mesenchymal transition gene set normalized enrichment score (NES) for each cluster. (I) Bubble plot summarizing Col1a1 single-cell expression across clusters and animals, with color representing mean expression and size representing percent of cells with expression. (J) Sina plot displaying the normalized pseudobulk counts of Col1a1 expression within the stellate cell cluster in wild-type and Dp16 animals. (K) Representative images of multiplexed stained liver sections from wild-type and Dp16 mice where DAPI is stained in blue, desmin in red, and smooth muscle actin (SMA) in yellow. Sina plot showing number of desmin+ and SMA+ cells as a percentage of total cells in wild-type mice ( n = 6, 3 females) and Dp16 mice ( n = 6, 3 females). (L) Representative images of picrosirius-red-stained (PSR) liver sections from wild-type ( n = 8, 4 females) and Dp16 ( n = 7, 4 females) mice, imaged under polarized light. Sina plot shows the total percent positive PSR staining in wild-type and Dp16 liver. For (K and L), individual data are presented with a bar at the median, and the p value, as determined by a Mann-Whitney U test, is shown. Scale bars, 100 μm.

Article Snippet: Fixed liver single cell suspensions were hybridized with the Next GEM Single Cell Fixed RNA Mouse Transcriptome Probe Kit (10X Genomics), according to manufacturer instructions, and loaded into a Chromium X (10X Genomics) microfluidics instrument to generate an oil emulsion with partitioned nanoliter-scale droplets, each ideally containing a barcoded gel bead and a single cell, along with enzyme Master Mix (10X Genomics) for probe pair ligation and gel bead primer barcode extension.

Techniques: Gene Expression, Expressing, Single Cell, RNA Sequencing, Staining, MANN-WHITNEY

Journal: Cell reports

Article Title: Altered hepatic metabolism in Down syndrome

doi: 10.1016/j.celrep.2025.116835

Figure Lengend Snippet: (A) Heatmap showing the median Z score of the leading-edge genes from the IFN gamma response gene set from wild-type and Dp16 liver bulk transcriptome analysis. (B) Sina plot displaying relative expression (RPKM) of Cxcl9 in wild-type and Dp16 liver bulk transcriptome analysis. (C) UMAP plot displaying the IFN gamma response gene set normalized enrichment score (NES) for each cluster. (D) Bubble plot displaying the mean expression and the percent of cells per cluster expressing Cxcl9 in wild-type and Dp16 mice. (E) Sina plot displaying the log 2 of the normalized counts of Cxcl9 expression within endothelial cell cluster 1 in wild-type and Dp16 animals. (F) Representative images of H&E-stained liver sections from adult wild-type, Dp16, and Dp16 2xIFNRs mice. Scale bars, 100 μm. (G) Sina plots showing liver pathology scoring from adult wild-type ( n = 13, 6 females), Dp16 ( n = 12, 5 females), and Dp16 2xIFNRs ( n = 13, 7 females) mice. p values, determined by a Mann-Whitney U test, are shown. (H) Sina plot displaying the grams/deciliter of plasma albumin from adult wild-type ( n = 6, 4 females), Dp16 ( n = 6, 2 females), and Dp16 2xIFNRs ( n = 8, 1 female) mice. p values, as determined by a Mann-Whitney U test, are shown. (I) Heatmap displaying the median Z score of plasma bile acids in adult wild-type ( n = 9, 4 females), Dp16 ( n = 13, 6 females), and Dp16 2xIFNRs ( n = 10, 5 females) mice. For (B and E), Benjamini-Hochberg adjusted p value ( q value) are indicated. For (B, E, and G), individual data are presented with a bar at the median.

Article Snippet: Fixed liver single cell suspensions were hybridized with the Next GEM Single Cell Fixed RNA Mouse Transcriptome Probe Kit (10X Genomics), according to manufacturer instructions, and loaded into a Chromium X (10X Genomics) microfluidics instrument to generate an oil emulsion with partitioned nanoliter-scale droplets, each ideally containing a barcoded gel bead and a single cell, along with enzyme Master Mix (10X Genomics) for probe pair ligation and gel bead primer barcode extension.

Techniques: Expressing, Staining, MANN-WHITNEY, Clinical Proteomics

Journal: Cell reports

Article Title: Altered hepatic metabolism in Down syndrome

doi: 10.1016/j.celrep.2025.116835

Figure Lengend Snippet: (A) Volcano plots summarizing the results of transcriptome analysis of livers from Dp16 versus wild-type mice fed a low-fat diet (LFD) and from Dp16 mice versus wild-type fed a high-fat diet (HFD) (wild-type LFD n = 10, 4 females, Dp16 LFD n = 8, 4 females, wild-type HFD n = 14, 4 females, Dp16 HFD n = 13, 4 females). Points in blue are in the MMU16 region triplicated in Dp16 mice. (B) Venn diagrams displaying the overlap in the significant differentially expressed genes in the Dp16 triplicated region between HFD fed mice and LFD mice (top) or in the differentially expressed genes that are not triplicated in Dp16 mice (bottom). (C) Scatterplot comparing GSEA NES values for signatures in the livers of Dp16 versus wild-type mice on LFD ( x axis) and Dp16 versus wild-type mice on HFD diet ( y axis). (D) Scatterplots comparing the fold changes of leading-edge genes from the cholesterol homeostasis, fatty acid metabolism, and adipogenesis hallmark gene sets for Dp16 versus wild-type mice on LFD ( x axis) and Dp16 versus wild-type on HFD ( y axis). (E) Sina plots displaying the log 2 (RPKM) of various genes. Horizontal bars indicate median values. Benjamini-Hochberg adjusted p -values ( q values) are indicated. For (C–E), points are colored according to significant in both groups (red), significant in the LFD group only (green), significant in the HFD group only (yellow), or not significant in any group (gray). Significance is defined as q < 0.1 using GSEA or DESeq2.

Article Snippet: Fixed liver single cell suspensions were hybridized with the Next GEM Single Cell Fixed RNA Mouse Transcriptome Probe Kit (10X Genomics), according to manufacturer instructions, and loaded into a Chromium X (10X Genomics) microfluidics instrument to generate an oil emulsion with partitioned nanoliter-scale droplets, each ideally containing a barcoded gel bead and a single cell, along with enzyme Master Mix (10X Genomics) for probe pair ligation and gel bead primer barcode extension.

Techniques:

Journal: Journal of hepatology

Article Title: Adipose tissue macrophage dysfunction is associated with a breach of vascular integrity in NASH.

doi: 10.1016/j.jhep.2023.10.039

Figure Lengend Snippet: Fig. 1. Single-cell map of human VAT macrophages. (A) Workflow of the experimental pipeline. Human visceral adipose tissue was collected from patients undergoing cholecystectomy and bariatric surgery, NAFLD-stratified based on liver histology, and the stromal vascular fraction enzymatically isolated. The cells were sorted based on CD45, CD11b, and HLA-DR positivity and analyzed using 10X Genomics Chromium droplet single-cell RNA sequencing. The cells were then clustered based on marker genes and downstream analysis was performed. (B) Annotated UMAP map of 35,405 myeloid cells from the VAT of lean (n = 3) and obese patients with normal liver histology (n = 4), NAFL (n = 4) and NASH (n = 5), showing ResVAMs, MMacs, TransMacs, preInfMacs, Mon, ncMon and cDCs. (C) Heatmap showing the top 20 marker genes for the myeloid populations. Indicated are individual cluster markers and the total number of genes characterized. The expression is indicated by color saturation, the cluster and disease identity are marked by individual coloring. (D) Violin plots showing the expression of selected marker genes in myeloid cells,

Article Snippet: The cells were sorted based on CD45, CD11b, and HLA-DR positivity and analyzed using 10X Genomics Chromium droplet single-cell RNA sequencing.

Techniques: Isolation, RNA Sequencing, Marker, Expressing