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tsne plot  (Natan GmbH)

 
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    Natan GmbH tsne plot
    (A) Schematic graph showing the experimental design. c-Kit−CD45+ (bold) was the sorting gate for E14.5 cells, and CD45+CD11b+ (bold) was for P7 and P60 cells. Other surface markers were recorded as metadata. (B) Representative FACS plots showing the cells sequenced (red or blue). (C) <t>tSNE</t> plot showing 15 clusters and population annotations <t>with</t> <t>microglia-like</t> clusters in bold and the number of cells in parentheses. (D) Overlaying FACS gating information onto the same tSNE plot in (C). The vast majority of P60 microglia are CD45low, while P7 microglia are comprised of both CD45low and CD45hi cells. Almost all cells from non-microglia clusters are CD45hi. (E) Overlaying developmental stage information onto the same tSNE plot in (C). (F) Heatmap showing the top 20 markers (or all markers if less than 20) for each of the 15 clusters. (G) Bar plots showing gene expression levels of two representative markers for each cluster. See also Figure S1, Table S1.
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    Images

    1) Product Images from "Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing"

    Article Title: Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing

    Journal: Neuron

    doi: 10.1016/j.neuron.2018.12.006

    (A) Schematic graph showing the experimental design. c-Kit−CD45+ (bold) was the sorting gate for E14.5 cells, and CD45+CD11b+ (bold) was for P7 and P60 cells. Other surface markers were recorded as metadata. (B) Representative FACS plots showing the cells sequenced (red or blue). (C) tSNE plot showing 15 clusters and population annotations with microglia-like clusters in bold and the number of cells in parentheses. (D) Overlaying FACS gating information onto the same tSNE plot in (C). The vast majority of P60 microglia are CD45low, while P7 microglia are comprised of both CD45low and CD45hi cells. Almost all cells from non-microglia clusters are CD45hi. (E) Overlaying developmental stage information onto the same tSNE plot in (C). (F) Heatmap showing the top 20 markers (or all markers if less than 20) for each of the 15 clusters. (G) Bar plots showing gene expression levels of two representative markers for each cluster. See also Figure S1, Table S1.
    Figure Legend Snippet: (A) Schematic graph showing the experimental design. c-Kit−CD45+ (bold) was the sorting gate for E14.5 cells, and CD45+CD11b+ (bold) was for P7 and P60 cells. Other surface markers were recorded as metadata. (B) Representative FACS plots showing the cells sequenced (red or blue). (C) tSNE plot showing 15 clusters and population annotations with microglia-like clusters in bold and the number of cells in parentheses. (D) Overlaying FACS gating information onto the same tSNE plot in (C). The vast majority of P60 microglia are CD45low, while P7 microglia are comprised of both CD45low and CD45hi cells. Almost all cells from non-microglia clusters are CD45hi. (E) Overlaying developmental stage information onto the same tSNE plot in (C). (F) Heatmap showing the top 20 markers (or all markers if less than 20) for each of the 15 clusters. (G) Bar plots showing gene expression levels of two representative markers for each cluster. See also Figure S1, Table S1.

    Techniques Used: Gene Expression

    (A) tSNE plot (left) and violin plots (right) highlighting two P60 microglia clusters, and examples of differentially expressed genes. (B) RNA in situ showing negative expression of Fos and Egr1 in microglia (Tmem119+), and positive signals from surrounding non-microglia cells. (C) Quantification of fluorescence signals in (B). n=30 cells for each. (D) Pearson correlation between bulk RNA-seq samples from P60 brain regions. (E) Dendrogram showing hierarchical clustering of bulk RNA-seq samples, irrelevant of regions. (F) Numbers of differentially expressed genes between homeostatic microglia from different regions by scRNA-seq and bulk RNA-seq. Scale bar in (B) is 50um. See also Figure S2, Table S2, Table S3.
    Figure Legend Snippet: (A) tSNE plot (left) and violin plots (right) highlighting two P60 microglia clusters, and examples of differentially expressed genes. (B) RNA in situ showing negative expression of Fos and Egr1 in microglia (Tmem119+), and positive signals from surrounding non-microglia cells. (C) Quantification of fluorescence signals in (B). n=30 cells for each. (D) Pearson correlation between bulk RNA-seq samples from P60 brain regions. (E) Dendrogram showing hierarchical clustering of bulk RNA-seq samples, irrelevant of regions. (F) Numbers of differentially expressed genes between homeostatic microglia from different regions by scRNA-seq and bulk RNA-seq. Scale bar in (B) is 50um. See also Figure S2, Table S2, Table S3.

    Techniques Used: In Situ, Expressing, Fluorescence, RNA Sequencing

    (A) tSNE plots demonstrating cell cycle regression and re-clustering of P7 microglia. Cells in all tSNE plots are color coded exactly the same way as in Figure 1C. Numbers of cells in each cluster are given in parentheses. Two tSNE plots in the box (lower left) demonstrate consistency of two analyses (before and after cell cycle regression) and distribution of the original dividing clusters (cluster 3 and 4) into P7-C0, P7-C1 and P7-C2 following cell cycle regression. (B) – (F) showing analysis for the 264 P7-C0 microglia identified in (A). (B) Heatmap (upper panel) showing pseudotime ordering of P7-C0 microglia based on raw phase scores. Each column is a cell, and each row denotes raw scores for a specific cell cycle phase. G0 cells have no dominant phase scores for any phase and were not ordered. Heatmap (lower panel) showing expression levels of identified phase-specific genes. Each column is a cell and each row is a gene. The original identities (bottom bar) are color coded as in (A). (C) Dot plots showing expression levels of phase-specific genes along microglia dividing pseudotime. Genes for each phase are plotted in separate graphs with each dot representing the level of expression for a given gene in a given cell. Curves show average expression of all genes assigned to a phase along dividing pseudotime. Expression of microglial signature genes (Butovsky et al., 2014) is shown at the bottom. (D) The gray pie chart showing overlaps of phase-specific genes identified by the algorithm compared with four published cell cycle gene sets (Grant et al., 2013). Colored pie charts are breakdowns of the genes from each category based on the phase assignment. (E) Table showing gene names identified as “Novel” in (D). Genes that may play a role in cell division are in bold. (F) Heatmap (upper panel) showing pseudotime ordering of P7-C0 microglia by normalized phase scores. The bottom panels show Ankle1 as an example for its expression dynamics along dividing pseudotime. Each dot is a single cell. The smoothened expression is the average expression of Ankle1 computed with a fixed window size (length of ordered cells/10). See also Figure S3, Figure S4, Table S4.
    Figure Legend Snippet: (A) tSNE plots demonstrating cell cycle regression and re-clustering of P7 microglia. Cells in all tSNE plots are color coded exactly the same way as in Figure 1C. Numbers of cells in each cluster are given in parentheses. Two tSNE plots in the box (lower left) demonstrate consistency of two analyses (before and after cell cycle regression) and distribution of the original dividing clusters (cluster 3 and 4) into P7-C0, P7-C1 and P7-C2 following cell cycle regression. (B) – (F) showing analysis for the 264 P7-C0 microglia identified in (A). (B) Heatmap (upper panel) showing pseudotime ordering of P7-C0 microglia based on raw phase scores. Each column is a cell, and each row denotes raw scores for a specific cell cycle phase. G0 cells have no dominant phase scores for any phase and were not ordered. Heatmap (lower panel) showing expression levels of identified phase-specific genes. Each column is a cell and each row is a gene. The original identities (bottom bar) are color coded as in (A). (C) Dot plots showing expression levels of phase-specific genes along microglia dividing pseudotime. Genes for each phase are plotted in separate graphs with each dot representing the level of expression for a given gene in a given cell. Curves show average expression of all genes assigned to a phase along dividing pseudotime. Expression of microglial signature genes (Butovsky et al., 2014) is shown at the bottom. (D) The gray pie chart showing overlaps of phase-specific genes identified by the algorithm compared with four published cell cycle gene sets (Grant et al., 2013). Colored pie charts are breakdowns of the genes from each category based on the phase assignment. (E) Table showing gene names identified as “Novel” in (D). Genes that may play a role in cell division are in bold. (F) Heatmap (upper panel) showing pseudotime ordering of P7-C0 microglia by normalized phase scores. The bottom panels show Ankle1 as an example for its expression dynamics along dividing pseudotime. Each dot is a single cell. The smoothened expression is the average expression of Ankle1 computed with a fixed window size (length of ordered cells/10). See also Figure S3, Figure S4, Table S4.

    Techniques Used: Expressing

    (A) Violin plots showing some top up-regulated genes in P7-C1 (PAM) compared with the other two clusters. (B) RNA in situ (RNAscope) showing that Spp1 and Gpnmb signals mainly overlap in the corpus callosum (CC, inset) and white matter region of cerebellum (CB), and they also overlap with the microglia marker Cx3cr1. (C) RNA in situ showing that Gpnmb+Cx3cr1+ microglia are positive for Igf1 in CC (inset) and CB white matter. Microglia in the cortex (CTX), hippocampus (HIP) and striatum (STR) are negative for Gpnmb and Igf1 (arrow heads). Gpnmb+Cx3cr1+Igf1+ cells in the lateral ventricle (LV) (asterisk) and Igf1+Cx3cr1− neural cells (arrows) are also labeled. (D) RNA in situ showing that Gpnmb+Cx3cr1+ microglia are intermingled with Mbp+ oligodendrocytes in the developing white matter. (E) Immunohistochemistry showing CLEC7A expression by P7-C1 (PAM) in the developing white matter and near ventricles. TH: thalamus. (F) FACS plot showing P7 cerebellar GPNMB+CLEC7A+ cells (orange box) isolated for scRNA-seq. (G) Histograms showing higher levels of LILRB4 and CD63 surface expression in GPNMB+CLEC7A+ microglia compared with GPNMB−CLEC7A−cells. (H) tSNE plot showing clustering result (dashed circles) after combining GPNMB+CLEC7A+ cells with the originally sequenced P7 microglia. The arrow indicates gradual changes of transcriptomes from postnatal immature state (P7-C0) towards more polarized GPNMB+CLEC7A+ state. (I) Violin plots showing further up-or down-regulation of differentially expressed genes in P7-GPNMB+CLEC7A+ compared with P7-C1 microglia by scRNA-seq. (J) Pseudotime analysis of P7 microglia together with P7-GPNMB+CLEC7A+ and P60 homeostatic microglia showing developmental trajectories from P7-C0/P7-C1 mixed starting point to P7-GPNMB+CLEC7A+ early postnatal PAM branch (via P7-C1) and to P60 homeostatic branch (via P7-C0). Each dot is a cell. (K) Gene expression dynamics for two trajectories in (J) along developmental pseudotime, when the PAM branch gradually turns on disease-associated genes and down-regulates homeostatic genes. Scale bars: 50um in (B)-(D), 500um in (E). See also Figure S5, Table S5.
    Figure Legend Snippet: (A) Violin plots showing some top up-regulated genes in P7-C1 (PAM) compared with the other two clusters. (B) RNA in situ (RNAscope) showing that Spp1 and Gpnmb signals mainly overlap in the corpus callosum (CC, inset) and white matter region of cerebellum (CB), and they also overlap with the microglia marker Cx3cr1. (C) RNA in situ showing that Gpnmb+Cx3cr1+ microglia are positive for Igf1 in CC (inset) and CB white matter. Microglia in the cortex (CTX), hippocampus (HIP) and striatum (STR) are negative for Gpnmb and Igf1 (arrow heads). Gpnmb+Cx3cr1+Igf1+ cells in the lateral ventricle (LV) (asterisk) and Igf1+Cx3cr1− neural cells (arrows) are also labeled. (D) RNA in situ showing that Gpnmb+Cx3cr1+ microglia are intermingled with Mbp+ oligodendrocytes in the developing white matter. (E) Immunohistochemistry showing CLEC7A expression by P7-C1 (PAM) in the developing white matter and near ventricles. TH: thalamus. (F) FACS plot showing P7 cerebellar GPNMB+CLEC7A+ cells (orange box) isolated for scRNA-seq. (G) Histograms showing higher levels of LILRB4 and CD63 surface expression in GPNMB+CLEC7A+ microglia compared with GPNMB−CLEC7A−cells. (H) tSNE plot showing clustering result (dashed circles) after combining GPNMB+CLEC7A+ cells with the originally sequenced P7 microglia. The arrow indicates gradual changes of transcriptomes from postnatal immature state (P7-C0) towards more polarized GPNMB+CLEC7A+ state. (I) Violin plots showing further up-or down-regulation of differentially expressed genes in P7-GPNMB+CLEC7A+ compared with P7-C1 microglia by scRNA-seq. (J) Pseudotime analysis of P7 microglia together with P7-GPNMB+CLEC7A+ and P60 homeostatic microglia showing developmental trajectories from P7-C0/P7-C1 mixed starting point to P7-GPNMB+CLEC7A+ early postnatal PAM branch (via P7-C1) and to P60 homeostatic branch (via P7-C0). Each dot is a cell. (K) Gene expression dynamics for two trajectories in (J) along developmental pseudotime, when the PAM branch gradually turns on disease-associated genes and down-regulates homeostatic genes. Scale bars: 50um in (B)-(D), 500um in (E). See also Figure S5, Table S5.

    Techniques Used: In Situ, RNAscope, Marker, Labeling, Immunohistochemistry, Expressing, Isolation, Gene Expression

    (A) Single optical section of a confocal image (full stack in Movie S1) showing engulfment of nuclei by CLEC7A+ microglia in the P7 cerebellar white matter. Images from the X-Z and Y-Z axes are shown on the top and sides, respectively. (B) 3D reconstruction of a CLEC7A+ microglia (asterisk in (A)) engulfing a pyknotic nucleus. Arrow points to the microglia nucleus in transparent rendering of the CX3CR1-GFP channel. (C) Phagocytosis on slice culture sections showing that pH-sensitive beads were engulfed by CLEC7A+ microglia in CC (arrow heads) and CB white matter but rarely in other regions. Arrow points to beads-eaten CLEC7A+ cells near ventricles. (D) Quantification of the phagocytosis assay in (C). n=5 sections (3 fields for each section). *** P<0.001, ** P<0.01, * P<0.05. WM: white matter. (E) Immunostaining of P7 corpus callosum (CC) showing interactions between early postnatal PAM and MBP+ oligodendrocytes (arrows). Asterisks label cCASP3+ oligodendrocytes. Arrow head points to cCASP3+ inclusion in microglia. (F) Single optical section of a confocal image showing engulfment of cCASP3+ oligodendrocytes (inset) by CLEC7A+ microglia in the P7 CC. Images from the X-Z and Y-Z axes are shown on the top and left, respectively. The microglial cell (asterisk) physically contacting an oligodendrocyte is 3D reconstructed in (G). (H) Quantification for percentage of each cell type interacting with CLEC7A+ cells in CC. n=3 sections each. ** P<0.01, * P<0.05. (I) Mbp and Gfap transcripts in different P7 populations by scRNA-seq. tSNE plots (same as in Figure 6H) on the right highlight cells that have detectable Mbp or Gfap expression. Scale bars: 50um in (A), (E) and (F); 500um in (C); 10um in (B) and (G). Data are represented as mean ± SEM in (D) and (H). See also Figure S7, Table S6, Table S7, Movie S1, Movie S2.
    Figure Legend Snippet: (A) Single optical section of a confocal image (full stack in Movie S1) showing engulfment of nuclei by CLEC7A+ microglia in the P7 cerebellar white matter. Images from the X-Z and Y-Z axes are shown on the top and sides, respectively. (B) 3D reconstruction of a CLEC7A+ microglia (asterisk in (A)) engulfing a pyknotic nucleus. Arrow points to the microglia nucleus in transparent rendering of the CX3CR1-GFP channel. (C) Phagocytosis on slice culture sections showing that pH-sensitive beads were engulfed by CLEC7A+ microglia in CC (arrow heads) and CB white matter but rarely in other regions. Arrow points to beads-eaten CLEC7A+ cells near ventricles. (D) Quantification of the phagocytosis assay in (C). n=5 sections (3 fields for each section). *** P<0.001, ** P<0.01, * P<0.05. WM: white matter. (E) Immunostaining of P7 corpus callosum (CC) showing interactions between early postnatal PAM and MBP+ oligodendrocytes (arrows). Asterisks label cCASP3+ oligodendrocytes. Arrow head points to cCASP3+ inclusion in microglia. (F) Single optical section of a confocal image showing engulfment of cCASP3+ oligodendrocytes (inset) by CLEC7A+ microglia in the P7 CC. Images from the X-Z and Y-Z axes are shown on the top and left, respectively. The microglial cell (asterisk) physically contacting an oligodendrocyte is 3D reconstructed in (G). (H) Quantification for percentage of each cell type interacting with CLEC7A+ cells in CC. n=3 sections each. ** P<0.01, * P<0.05. (I) Mbp and Gfap transcripts in different P7 populations by scRNA-seq. tSNE plots (same as in Figure 6H) on the right highlight cells that have detectable Mbp or Gfap expression. Scale bars: 50um in (A), (E) and (F); 500um in (C); 10um in (B) and (G). Data are represented as mean ± SEM in (D) and (H). See also Figure S7, Table S6, Table S7, Movie S1, Movie S2.

    Techniques Used: Phagocytosis Assay, Immunostaining, Expressing

    Related Articles

    Gene Expression:

    Article Title: Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing
    Article Snippet: .. Furthermore, according to the developmental stages, these 7 microglia clusters were segregated into unidirectionally shifted domains on the tSNE plot, consistent with progressive changes in gene expression during microglial development ( ) ( Matcovitch-Natan et al., 2016 ). ..



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    Automatic analysis of the 2P microscopy images of infected cells using SARS-CoV-2 variants D614G and B.1.1.7. A Purple contours indicate the areas automatically defined as particles during this analysis. B , C , E , F Spider charts showing the effects of B variant, C virus titer, E dye concentration, and F photomultiplier tube (PMT) relative voltage on the range-normalized values of seven different image parameters obtained from 2P microscopy images. The error bars for the spider charts can be found in Supplementary Fig. 7. D The image parameter called “relative signal area” shows a significant increase at virus titers higher than TCID 50 10 –3 mL −1 . G The image parameter called “image mean intensity” for the two studied variants at high virus titer (TCID 50 > 10 –3 mL −1 ) at 0.05 μM and 0.5 μM dye concentration. H t -Distributed stochastic neighbor embedding (t-SNE) 2D plot obtained from all the seven image parameters recorded at 0.5 µM dye concentration shows three clusters depending on the virus variant and titer. Inset shows that the three groups, namely no or low infection, infection with D614G variant, and infection with B.1.1.7 variant are clearly separated along the first dimension. I Classification of the images corresponding to different variants at various virus titer in three clusters by seven-dimensional Gaussian mixture model clustering (error bars show standard deviation; significance levels as * p ≤ 0.1; ** p ≤ 0.05; *** p ≤ 0.01.)

    Journal: Cellular & Molecular Biology Letters

    Article Title: Monitoring correlates of SARS-CoV-2 infection in cell culture using a two-photon-active calcium-sensitive dye

    doi: 10.1186/s11658-024-00619-0

    Figure Lengend Snippet: Automatic analysis of the 2P microscopy images of infected cells using SARS-CoV-2 variants D614G and B.1.1.7. A Purple contours indicate the areas automatically defined as particles during this analysis. B , C , E , F Spider charts showing the effects of B variant, C virus titer, E dye concentration, and F photomultiplier tube (PMT) relative voltage on the range-normalized values of seven different image parameters obtained from 2P microscopy images. The error bars for the spider charts can be found in Supplementary Fig. 7. D The image parameter called “relative signal area” shows a significant increase at virus titers higher than TCID 50 10 –3 mL −1 . G The image parameter called “image mean intensity” for the two studied variants at high virus titer (TCID 50 > 10 –3 mL −1 ) at 0.05 μM and 0.5 μM dye concentration. H t -Distributed stochastic neighbor embedding (t-SNE) 2D plot obtained from all the seven image parameters recorded at 0.5 µM dye concentration shows three clusters depending on the virus variant and titer. Inset shows that the three groups, namely no or low infection, infection with D614G variant, and infection with B.1.1.7 variant are clearly separated along the first dimension. I Classification of the images corresponding to different variants at various virus titer in three clusters by seven-dimensional Gaussian mixture model clustering (error bars show standard deviation; significance levels as * p ≤ 0.1; ** p ≤ 0.05; *** p ≤ 0.01.)

    Article Snippet: Seven parameters characterizing the detected particles on the images were defined for each image: (i) relative signal area, (ii) image mean intensity, (iii) mean of the threshold area, (iv) maximum particle intensity, (v) average particle size, (vi) particle percentage area, and (vii) particle mean intensity. t -Distributed stochastic neighbor embedding (t-SNE) 2D plot was obtained in MATLAB using the built-in “tsne” function with default random number generation, a perplexity value of 10, and exaggeration value of 50 on all seven parameters of images acquired with 0.5 μM dye concentration (Supplementary Fig. 12).

    Techniques: Microscopy, Infection, Variant Assay, Virus, Concentration Assay, Standard Deviation