Additional file 1 of Single-cell transcriptomics of popliteal lymphatic vessels and peripheral veins reveals altered lymphatic muscle and immune cell populations in the TNF-Tg arthritis model
Creators: name: Kenney, H. Mark
name: Wu, Chia-Lung
name: Loiselle, Alayna E.
name: Xing, Lianping
name: Ritchlin, Christopher T.
name: Schwarz, Edward M.
Publisher: name: figshare
Year: 2022
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1 : Supplementary Figure 1. Identification of Ptprc+ immune and Prrx1+ mesenchymal clusters by scRNAseq of tdT+ sorted cells. A feature plot is shown where Ptprc (CD45) identified immune cell populations (A), and Prrx1 defined the mesenchymal cells containing the smooth muscle cell (SMC) populations and fibroblasts (B). Low quality cell clusters that remained in the dataset were identified by relatively high mitochondrial gene expression indicating dead or dying cells, noted by the arrow (C). Blue = high expression, grey = low expression. Supplementary Figure 2. Differentially expressed genes in cell clusters identified with integration of WT and TNF-Tg datasets. The wild-type (WT) and tumor necrosis factor transgenic (TNF-Tg) single-cell RNA-sequencing (scRNAseq) datasets were integrated together, and unsupervised shared nearest neighbor (SNN) clustering in Seurat resolved 20 distinct cell clusters. The top 3 genes (duplicates omitted) for these 20 cell populations are shown as a heatmap, and the cell populations correspond by color and cluster order. The cell numbers for each population are noted in parentheses, and depict the same populations shown in the UMAPs of Fig. 3. The full gene list defining the cell populations is provided in the Supplementary Materials. Supplementary Figure 3. Micro-CT confirmation of severe inflammatory-erosive arthritis in the experimental TNF-Tg mice. Ex vivo micro-computed tomography (μCT) was performed on the ankle joints of the wild-type (WT) (A-B) and tumor necrosis factor transgenic (TNF-Tg) (C-D) mice used in this study. The intact ankle in WT mice (A) shows the expected bone architecture with the talus segmented in blue (B). In contrast, a representative image of a severely eroded ankle in the TNF-Tg mice is depicted (C) with the talus identified in red (D) as an established biomarker of arthritis. The talus bone volumes were quantified in Amira software with a significant decrease in talus volumes in TNF-Tg mice compared to WT (E). An unpaired t-test was used for statistical analysis (**** p &lt; 0.0001). Supplementary Figure 4. Gene expression patterns define various monocyte and macrophage cell populations. Immune cells were first identified by Ptprc (CD45) expression (A), and myeloid cell populations were defined by Itgam (CD11b) enrichment (B). Patrolling monocytes were defined by Cx3cr1 (C), while inflammatory monocytes were identified by Ly6c2 (D) and Ccr2 (E) expression. M1-polarized macrophages were also enriched in Ccr2 and Ccl2 (F), while M2-polarized macrophages were identified by Mrc1 (G, CD206) and Cd163 (H) expression. Notably, the M2-macrophage population was also enriched for Lyve1 (I) known to regulate collagen content in smooth muscle cells [38]. and M2-macrophages were selectively decreased in tumor necrosis factor transgenic (TNF-Tg) mice as noted in Fig. 3. Feature plots overlaying the UMAP are provided to visualize the change in expression (grey = low, blue = high gene expression). Supplementary Figure 5. Additional lymph and angiogenic genes and muscle-related transcription factors selectively expressed in the SMC clusters. Along with the genes indicated in Fig. 4, Vegfa (lymphatic muscle cells (LMCs) 1.10, vascular smooth muscle cells (VSMCs) 1.23 log2 fold-change (log2FC) in A), Vegfd (LMCs 1.47, VSMCs 1.00 log2FC in B), and Angpt1 (LMCs 0.29, VSMCs 0.51 log2FC in C) as factors critical for lymphangiogenesis and angiogenesis were selectively expressed by LMCs and VSMCs compared to all other cell clusters. In addition, Vegfd known to interact with VEGFR3 to promote lymphangiogenesis [56] demonstrated significantly greater expression in the LMC population compared to VSMCs (0.47 log2FC in B). However, Vegfc expression was nearly undetectable in all cell clusters (D). In addition, muscle-related transcription factors such as Prrx1 (LMCs 2.22, VSMCs 2.42 log2FC in E), Twist1 (LMCs 1.71, VSMCs 1.19 log2FC in F), Tead1 (LMCs 0.64, VSMCs 0.38 log2FC in G), Meox2 (LMCs 0.28, VSMCs 0.94 log2FC in H), Id3 (LMCs 2.37, VSMCs 2.66 log2FC in I), and Csrp2 (LMCs 1.06, VSMCs 1.91 log2FC in J) were significantly increased in muscle cell populations compared to all other sequenced cell clusters. While these transcription factors are not individually specific to smooth muscle cells (SMCs), each gene is known to regulate smooth muscle related gene expression and their co-expression in the same cell strongly indicates that the cluster is a muscle cell [47]. Violin plots are shown to demonstrate the effect size between SMC populations compared to all other cell clusters. Wilcoxon rank sum test was performed between the different cell types for statistical analysis with false discovery rate (FDR) &lt; 2.87E-67 for all comparisons. Sample sizes: LMCs = 1,985 cells, VSMCs = 1,331 cells, Other = 5,563 cells. Supplementary Figure 6. LMC and VSMC clusters express fibroblast-like genes similar to myofibroblasts, but not pericyte genes. To confirm a lack of contamination by pericytes, canonical pericyte markers such as Cspg4 (A), Mcam (B), and Ngfr (C) were nearly undetectable throughout the dataset. Note that cell sorting of tdT+ cells from Cspg4-Cre;Ai9-tdTomato as in Fig. 1 does not presume active Cspg4 expression, but instead that tdTomato (tdT)+ cells at one time expressed Cspg4. On the other hand, non-specific fibroblast markers were highly enriched in the muscle cell populations, such as Dcn (lymphatic muscle cells (LMCs) 5.25, vascular smooth muscle cells (VSMCs) 5.48 log2 fold-change (log2FC) in D), Fbln2 (LMCs 2.12, VSMCs 2.31 log2FC in E), and Pdgfra (LMCs 2.29, VSMCs 2.35 log2FC in F). The various validations of muscle cell identity in Fig. 1, 2, and 4 and Supplementary Figures 5 and 7 suggest that these peripheral muscle cell populations may cluster closely with fibroblasts by single-cell transcriptomics, yet exhibit distinct features to differentiate them from traditional fibroblasts. Violin plots are shown to demonstrate the effect size between muscle cell populations compared to all other cell clusters. Wilcoxon rank sum test was performed between the different cell types for statistical analysis with false discovery rate (FDR) &lt; 2.23E-308 and the lower limit possible in R. Sample sizes: LMCs = 1,985 cells, VSMCs = 1,331 cells, Other = 5,563 cells. Supplementary Figure 7. Differentially expressed genes between LMC and VSMC clusters. The lymphatic muscle cell (LMC) and vascular smooth muscle cell (VSMC) clusters from the wild-type (WT) and tumor necrosis factor transgenic (TNF-Tg) integrated datasets in Fig. 3 were subclustered, and then re-integrated for analysis of differential gene expression between the populations with minimally supervised clustering (A). The top 10 differentially expressed genes between LMCs and VSMCs are shown as a heatmap (B), and the full list of gene expression is provided in the Supplementary Materials. Notable genes, such as Cst3 (2.60 log2 fold-change (log2FC) in C), Mgp (2.75 log2FC in D), and Bgn (2.11 log2FC in E), were significantly increased in VSMCs compared to LMCs, while Ackr3 (1.39 log2FC in F) was selective for LMCs relative to VSMCs. Feature plots overlaying the UMAP are provided to visualize the change in expression (grey = low, blue = high gene expression), while violin plots are shown to demonstrate the effect size between muscle cell populations. Wilcoxon rank sum test was performed between the different cell types for statistical analysis with false discovery rate (FDR) &lt; 2.53E-227 for all comparisons. Sample sizes: LMCs = 1,850 cells, VSMCs = 1,466 cells. Supplementary Figure 8. Lack of Acta2 expression in LMC and VSMC clusters. Acta2 (alpha smooth muscle actin (αSMA)) is a well-established canonical marker for smooth muscle cells (SMCs), and immunohistochemistry for αSMA has been routinely used by us and others to study lymphatic muscle cells (LMCs) and vascular smooth muscle cells (VSMCs) in lymphatic and blood vessels in situ and ex vivo (Fig. 4 and [22, 43, 75, 82]). Transcriptomic studies of large arteries have also used Acta2 expression as a phenotypic marker of SMC clusters in single-cell RNA-sequencing (scRNAseq) datasets [80, 83]. However, our scRNAseq data showed that Acta2 expression is nearly undetectable in freshly harvested and sequenced popliteal lymphatic vessel (PLV)-LMCs and superficial saphenous vein (SSV)-VSMCs (A, B). A feature plot overlaying the UMAP is provided to visualize the change in expression (grey = low, blue = high gene expression), while a violin plot is shown to demonstrate the negligible Acta2 expression in all sequenced cell populations. We also generated Acta2-Cre;Ai9-tdTomato (tdT) (C-D) and Acta2-CreER;Ai9-tdT (E-J) reporter mice to evaluate endogenous Acta2 gene promoter activity in LMCs and VSMCs in vivo. PLVs (dashed arrow) and adjacent SSVs (solid arrow) from a 3-month-old Acta2-Cre;Ai9-tdT mouse, and a 5-month-old Acta2-CreER;Ai9-tdT mouse (after tamoxifen induction, as previously described [22]) were harvested and immunostained for αSMA and visualized by whole mount immunofluorescent microscopy. High-magnification images of the regions with the highest tdT expression are shown. Remarkably, despite LMC and VSMC αSMA protein expression detected by immunostaining (green), tdT (red) in both reporter models was not ubiquitously expressed in SMCs of both PLVs and SSVs. Taken together, these findings suggest relatively low Acta2 mRNA expression in LMCs and VSMCs of lower limb vessels in adult mice.