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

Journal: Cells

Article Title: scRNA-Seq of Cultured Human Amniotic Fluid from Fetuses with Spina Bifida Reveals the Origin and Heterogeneity of the Cellular Content

doi: 10.3390/cells12121577

Figure Lengend Snippet: Identification of fetal/maternal origin of the cell types detected in the cultured AF samples of this study. ( A ) Violin plot showing the expression of the male-specific gene RPS4Y1 per cluster in the merged analysis of the five AF samples included in the scRNA-seq analysis (two from male and three from female fetuses). The gene was expressed in all clusters, indicating that all detected cell types were of fetal origin (data from AF samples from four fetuses with spina bifida aperta (SBA) and one from a healthy fetus). ( B – F ) Violin plots showing the expression levels of RPS4Y1 per cluster in each of the five AF samples included in the scRNA-seq analysis. The gene was expressed in all clusters in the AF samples from the two male fetuses (m) but was absent in all clusters in the AF samples from the three female fetuses (f), indicating that all detected clusters (and therefore cell types) were of fetal origin. The cell clusters are shown in different colors and the legend indicates the assigned cell type.

Article Snippet: For single-cell transcriptomics analysis of cultured AF cells, the droplet-based 10X Genomics Chromium scRNA-seq platform was used [ ] at the Functional Genomics Center Zurich (University of Zurich, Zurich, Switzerland).

Techniques: Cell Culture, Expressing

Journal: Cells

Article Title: scRNA-Seq of Cultured Human Amniotic Fluid from Fetuses with Spina Bifida Reveals the Origin and Heterogeneity of the Cellular Content

doi: 10.3390/cells12121577

Figure Lengend Snippet: Neural-associated marker expression in one normal AF and in four AF from fetuses with neural tube defects. ( A ) Heatmap with the expression pattern of neural-cell-lineage markers and selected neuron- and neuroglia-associated markers in the 13 clusters and in each of the five AF samples that were subjected to scRNA-seq. The Z score indicates relative expression. ( B ) t-SNE plots of all single cells with the expression of representative neural-cell-lineage-specific marker genes. SOX2 and NES for neural progenitors, GAP43 for neurons and MAP2 for glial cells. Black dashed lines mark the neural clusters of interest. ( C ) Dot plot highlighting the expression of the neural-associated genes from ( A ) in each of the five AF samples included in the scRNA-seq analysis (one AF sample from a normal fetus and four from fetuses with SBA). ( D ) Weighted mean expression score of the neural-cell-lineage marker set from ( A ) in the one normal versus the four SBA samples. The score was computed by the package decoupleR .

Article Snippet: For single-cell transcriptomics analysis of cultured AF cells, the droplet-based 10X Genomics Chromium scRNA-seq platform was used [ ] at the Functional Genomics Center Zurich (University of Zurich, Zurich, Switzerland).

Techniques: Marker, Expressing

Journal: Cell Reports Methods

Article Title: Characterization of cell-fate decision landscapes by estimating transcription factor dynamics

doi: 10.1016/j.crmeth.2023.100512

Figure Lengend Snippet: FateCompass workflow to identify transcriptional regulators during cell-subtype specification (A) scRNA-seq data annotated for different cell types and embedded in a low-dimensional space showing connections to the k nearest neighbors. (B) The direction of differentiation, either from RNA velocity or differentiation potential, is the underlying force to compute transition probabilities between cell states. (C) The dynamic profile of a given gene over the differentiation trajectories ending in a respective final state (A, B, and C). (D) TF binding sites for different motifs across promoters. (E) Linear model of gene regulation where the observed gene expression (E gc ) is modeled as a linear combination of the regulatory sites (N gf ) and the TF activity (A fc ). (F) The dynamic profile of the TF activity for TF 1 , TF 2 , and TF 3 over the differentiation trajectories ending in the final state B. (G) Differential TF activity analysis. Lineage-specific TFs were identified according to three criteria: Z score, variability of TF activity over time, and dynamic correlation between the TF activity and the expression of its mRNA. (H) Lineage-specific TFs identified by FateCompass ordered according to who is active first over the dynamic profiles and constitute the differentiation TF landscape. See also Figures S1 and .

Article Snippet: Bastidas-Ponce et al. profiled pancreatic epithelial cells using a Ngn3-Venus fusion reporter mouse line, sequencing both Venus-positive and Venus-negative (Epcam + ) cells using droplet-based scRNA-seq (10X genomics chromium).

Techniques: Binding Assay, Expressing, Activity Assay