Journal: Nature Communications

Article Title: Regional and cell specific bioactivity of injectable extracellular matrix biomaterials in myocardial infarction

doi: 10.1038/s41467-025-65351-5

Figure Lengend Snippet: a MI was induced followed by an intramyocardial injection of ECM hydrogel or saline 7 days post-MI. Hearts were then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection (14 days post-MI). Figure created in BioRender, and is licensed under CC BY 4.0 ( https://biorender.com/r54nzgf ). Sample size: n = 2 ECM hydrogel replicates, 7658 spots. b Myocardium (green) was labeled with anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue) with nuclei stained with DAPI (blue). c The adjacent cryosection was used for spatial transcriptomics via 10X Visium, where the infarct-containing ECM hydrogel (red) was found to cluster separately from the infarct alone (cyan). d The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) were found to be immune and vascularly dominating genes compared to the downregulated genes impacting the infarct zone (cyan). e , f All differentially expressed genes in the ECM hydrogel zone (red) and infarct only zone were subjected to GO enrichment. Significance was determined via nonparametric Wilcoxon rank-sum tests with a Benjamini–Hochberg FDR adjustment to determine gene lists ( d ), and via Kolmogoro-Smirnov tests and permutation testing, with Benjamin-Hochberg FDR adjustment ( e , f ). Source data are provided as a Source Data file. ECM extracellular matrix, Neg negative, reg regulation, Pop population, Prolif proliferation, FC fold change.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Injection, Saline, Labeling, Staining

Journal: Nature Communications

Article Title: Regional and cell specific bioactivity of injectable extracellular matrix biomaterials in myocardial infarction

doi: 10.1038/s41467-025-65351-5

Figure Lengend Snippet: a MI is induced followed by an intramyocardial injection of ECM hydrogel or saline 8 weeks post-MI. Hearts are then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection. Figure created in BioRender, and is licensed under CC BY 4.0 ( https://biorender.com/r54nzgf ). Sample size: n = 3 ECM hydrogel replicates, 9594 spots. b Myocardium (green) was labeled with an anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). c An adjacent cryosection to the immunofluorescence image in ( b ) was used for spatial transcriptomics via 10X Visium, where the infarct containing ECM hydrogel (red) was found to cluster separately from the normal infarct zone (cyan). d Top differentially expressed genes for both ECM within infarct (red) and infarct alone (cyan) are shown. e, f A comparison of the two zones reflects the ECM hydrogel activates fibroblasts and is responsible for further vascular development, as demonstrated through GO enrichment. Significance was determined via nonparametric Wilcoxon rank-sum tests with a Benjamini–Hochberg FDR adjustment to determine gene lists ( d ), and via Kolmogoro–Smirnov tests and permutation testing, with Benjamin–Hochberg FDR adjustment ( e, f ). Source data are provided as a Source Data file. ECM extracellular matrix, Neg negative, reg regulation, Pop population, Prolif proliferation, FC fold change.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Injection, Saline, Labeling, Immunofluorescence, Comparison

Journal: Nature Communications

Article Title: Regional and cell specific bioactivity of injectable extracellular matrix biomaterials in myocardial infarction

doi: 10.1038/s41467-025-65351-5

Figure Lengend Snippet: a The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) with integrated subacute and chronic Visium were found to be immune, fibroblast, and vascularly dominating genes compared to the downregulated genes impacting the infarct zone (cyan). Sample size: n = 2 for subacute ECM hydrogel (7658 spots); n = 3 for chronic ECM hydrogel (9594 spots) b The ECM zones in both subacute and chronic models of MI have higher expression of the matrix specific genes relative to the infarct zone. c –f Macrophages ( c ), endothelial cells ( d ), cardiomyocytes ( e ), and fibroblasts ( f ) treated with ECM hydrogel in subacute and chronic MI were subsetted, reclustered, and compared with respect to MI timepoint. Sample size: n = 2 subacute ECM hydrogel (downsampled to 3000 cells), n = 2 chronic ECM hydrogel (downsampled to 3000 cells). Top differentially expressed genes were displayed via Volcano Plot, and the differentially expressed genes were subjected to GO enrichment. g Comparison of transcriptomic findings between subacute and chronic MI. Significance was determined via nonparametric Wilcoxon rank-sum tests with a Benjamini–Hochberg FDR adjustment to determine gene lists ( a, c – f ), and via Kolmogorov–Smirnov tests and permutation testing, with Benjamini–Hochberg FDR adjustment ( c – f ). Source data are provided as a Source Data file. ECM extracellular matrix, neg negative, vasc vascular, pos positive, reg regulation, pop population, prolif proliferation.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Expressing, Comparison

Journal: Nature Communications

Article Title: Macrophage ferroptosis potentiates GCN2 deficiency induced pulmonary venous arterialization

doi: 10.1038/s41467-025-64035-4

Figure Lengend Snippet: a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues. The two control samples represent the upper and lower halves of the same slide (stitched together). Scale bar = 2 mm. b Spatial mapping of tissue region clusters (Alveoli, Bronchi, Vessel, Unspecified) on spatial transcriptomics spots from Control (left) and PVOD (right) lung samples. c Violin plot showing HMOX1 expression levels across tissue regions in Control and PVOD lung samples. P values were determined via two-sided Wilcoxon rank-sum test. d Violin plots depicting expression of arterial endothelial markers ( KDR, CXCL12 ) and venous related marker ( ACKR1 ) in vessel regions comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. e Violin plots showing arterial and venous endothelial gene set scores in vessel regions of Control versus PVOD samples. P values were determined via two-sided Wilcoxon rank-sum test. f Volcano plot of differentially expressed genes in vessel regions between PVOD and Control groups. P values were determined via two-sided Wilcoxon rank-sum test with Benjamini–Hochberg correction for multiple testing. Significance thresholds were set at |log2 fold change| > 0.5 and adjusted p -value < 0.05. The top 5 upregulated and top 5 downregulated genes are annotated in the plot. GO biological processes ( g ) and KEGG pathways ( h ) significantly enriched (FDR < 0.05) from upregulated genes in PVOD vessel regions. P values were calculated using the hypergeometric test with Benjamini–Hochberg correction for multiple testing. Ten relevant terms associated with pulmonary vascular disease are shown, ranked by combined score. Dot size represents the percentage of genes in the gene set, and dot color indicates –log10(FDR). i Volcano plot of transcription factor activity differences (z-score normalized AUC scores) between Control and PVOD vessel regions analyzed by the limma method. j Violin plot showing ETS1 AUC scores in Control and PVOD vessel regions. k Violin plot of ETS1 expression in venous endothelial cells from scRNA-seq data comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. l ETS1 transcription factor binding motif (metacluster_183.1) obtained from the cisTarget motif collection (v10nr_clust). m Spatial distribution of cell type proportions (EC_arterial, EC_venous, Macrophages, Muscular cells, Fibroblasts) inferred by RCTD deconvolution. Color intensity corresponds to the relative abundance of each cell type, with darker colors indicating higher proportions. n Heatmaps showing Pearson correlation between RCTD cell type scores and cell death pathway gene set scores in Alveoli (top) and Vessel (bottom) region of the PVOD lung sample (* P < 0.05, ** P < 0.01, *** P < 0.001). P values are indicated in the figures. Source data are provided as a file.

Article Snippet: Fig. 6 Spatial transcriptomics reveals enhanced venous arterialization and ETS1-mediated gene regulation in PVOD lung vessels. a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues.

Techniques: Staining, Control, Expressing, Marker, Activity Assay, Binding Assay

Journal: Frontiers in Allergy

Article Title: MRGPRX2-expressing mast cells are increased in the GI tract of individuals with active inflammatory bowel disease and hereditary α-tryptasemia

doi: 10.3389/falgy.2025.1726096

Figure Lengend Snippet: Mast cells from IBD patients with HαT demonstrate increased MRGPRX2 expression. Spatial transcriptomics (10x Xenium) was performed on 8 descending colon biopsies from the University of Pennsylvania IBD biobank (4 HαT, 4 non-HαT; balanced UC/CD). (A) UMAP embedding showing major cellular populations. (B) Mast cells (MCs), defined as TPSAB1 + MS4A2 + KIT + , are more abundant in HαT samples. (C) Feature map of isolated MCs demonstrating increased MRGPRX2 transcript levels in HαT. (D) Digital droplet PCR (ddPCR) of representative tissues from the same cohort confirms upregulated MRGPRX2 expression in HαT vs. non-HαT. (E) Spatial transcriptomics images showing increased MRGPRX2 transcripts (red dots) in HαT-positive IBD tissue compared with non-HαT tissue. (F) ddPCR validation on matched samples (HαT: n = 4; non-HαT: n = 4) showing elevated MRGPRX2 mRNA. (G) Pseudobulk differential expression demonstrates significantly increased MRGPRX2 in HαT samples. For transcriptomic analyses, differential expression was calculated using DESeq2 with Benjamini–Hochberg FDR correction (FDR < 0.05). Effect sizes are shown as log₂ fold-change with 95% CIs. For ddPCR comparisons, Welch's t -test was used with Cohen's d reported.

Article Snippet: Spatial transcriptomics cohort , 8 , 4 , 4 , Severe IBD: UC ( n = 4), CD ( n = 4)—balanced across HαT and non-HαT , Descending colon , 10x Visium Spatial Transcriptomics + scRNA-binning , Selected from genotyped cohort; used to evaluate MC abundance and MRGPRX2 expression patterns..

Techniques: Expressing, Isolation, Biomarker Discovery, Quantitative Proteomics

Journal: Frontiers in Allergy

Article Title: MRGPRX2-expressing mast cells are increased in the GI tract of individuals with active inflammatory bowel disease and hereditary α-tryptasemia

doi: 10.3389/falgy.2025.1726096

Figure Lengend Snippet: Individuals with IBD and HαT exhibit increased SIGLEC8 expression in colon tissue. Spatial transcriptomics and pseudobulk analysis were performed on 8 representative descending colon samples (4 HαT, 4 non-HαT; balanced UC/CD). (A) Pseudobulk counts aggregated by sample show higher SIGLEC8 expression in the HαT group (Wilcoxon test; Cohen's d and 95% CI reported). (B) Volcano plot of DESeq2 pseudobulk differential expression analysis contrasting non-HαT (blue) and HαT (red) samples. Genes surpassing FDR < 0.05 (Benjamini–Hochberg correction) are highlighted. SIGLEC8 is prominently upregulated in HαT, consistent with findings from CyTOF and ddPCR validation.

Article Snippet: Spatial transcriptomics cohort , 8 , 4 , 4 , Severe IBD: UC ( n = 4), CD ( n = 4)—balanced across HαT and non-HαT , Descending colon , 10x Visium Spatial Transcriptomics + scRNA-binning , Selected from genotyped cohort; used to evaluate MC abundance and MRGPRX2 expression patterns..

Techniques: Expressing, Quantitative Proteomics, Biomarker Discovery