Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: Study Design Under BSL-4 containment, we collected blood samples from a total of 21 rhesus monkeys at multiple days post-EBOV inoculation, extracted peripheral blood mononuclear cells (PBMCs), and profiled single-cell transcriptomes and 42 protein markers using Seq-Well and CyTOF. Seq-Well quantifies both host (black) and viral (red) RNA expression, allowing comparisons between infected and bystander cells. Daily clinical parameters (body temperature, clinical signs, and body weight) were also collected for each animal, and complete blood counts were obtained for each blood draw. See also Figure S1 A and .

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: RNA Expression, Infection

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: Quantification of Cytokine Expression and Enrichment of Response Signatures, Related to and ( A ) Average expression values (log e TP10K) of literature-annotated cytokines (columns) across cell types and stages of acute EVD (rows). Values are plotted as a ratio relative to the maximum across cell types and stages. Values that are statistically different from baseline (p < 0.05) are indicated with a blue star. ( B ) Heatmap of rank-sum test statistics for comparison of differential expression log fold-changes of genes in a gene set (rows) compared to genes not in the set. The log fold-changes were defined from differential expression profiles of each cell type at each EVD stage (columns) relative to baseline. Five gene sets were tested — three from the Hallmark database (IFN ALPHA, IFN GAMMA, and TNF ALPHA VIA NFKB) ( Liberzon et al., 2015 ) and 2 constructed from the hallmark sets, as uniquely IFNα-regulated genes in “IFN ALPHA” but not “IFN GAMMA” (“IFN ALPHA - GAMMA”), and vice versa for uniquely IFNγ-regulated (“IFN GAMMA - ALPHA”). See also . ( C ) Fold change (log 2 scale) in average HLA-DR CyTOF intensity on B cells at each DPI relative to baseline for each PBMC sample. Colored lines connect serial samples from the same NHP.

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Expressing, Comparison, Quantitative Proteomics, Construct

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: ISG Suppression, Co-expression of CD14 and CD16, and Expression of Macrophage Genes Are Associated with Monocyte Infectivity (A) Differential expression between infected and bystander monocytes from DPI 5–8. Genes are colored by membership in sets of genes (Mac. Up/Down = up- or downregulated during in vitro differentiation of monocytes into macrophages). See also . (B) UMAP embedding of monocyte gene expression data, colored by (left-to-right) DPI, CD16 expression (log e TP10K), CD14 expression (log e TP10K), and percentage of cellular transcripts mapping to EBOV. (C) Smoothed expression (log e TP10K) of CD14 and CD16 for monocytes during EVD. Boxes: CD14 + , CD16 + , DN, and DP subsets described in the text; numbers: percentage of cells in each subset at that EVD stage. See also A and S5B. (D) CD14 and CD16 protein expression (CyTOF intensity) on monocytes at each DPI. Bivariate kernel density plot with 200 randomly sampled cells is overlaid as a scatterplot. See also Figure S5 C. (E) CD14 and CD16 protein expression (CyTOF intensity) on monocytes in a case of human EVD, colored by Ki67 protein expression for multiple days after symptom onset. See also Figure S5 D. (F) Percentage of assignment of NHP CD14/CD16 subsets at each EVD stage to human myeloid reference populations (BM-MP: bone marrow monocyte progenitors, PBMC-CD16 + : circulating CD16 + monocytes, PBMC-CD14 + : circulating CD14 + monocytes). See also E–S5K. (G) Percentage of infected monocytes in each CD14/CD16 subset in late EVD. Error bars: 95% CI on the mean based on 1,000 bootstraps. (H) Association between macrophage score (x axis) and percentage of infected cells (left y axis, red) and expression of the differentiation marker NR1H3 (right y axis, blue, log e TP10K). We ordered monocytes from late EVD by macrophage score, and averaged percentage of infected cells and NR1H3 expression within 400-cell sliding windows. See also A–S6C. (I) MX1 expression (log e TP10K) in monocytes at baseline, and uninfected bystanders or infected cells in late infection. Boxes: median and interquartile range; whiskers: 2.5 th and 97.5 th percentiles. Statistical significance was assessed by rank-sum test. See also Figure S6 D. (J) Scatterplot of ISG score (y axis) versus percentage of cellular transcripts mapping to EBOV (x axis) for infected monocytes in late EVD (DPI 6–8). Statistical significance was assessed by Spearman ρ.

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Expressing, Infection, Quantitative Proteomics, In Vitro, Gene Expression, Marker

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: Extended Characterization of Interferon and Double-Negative CD14 – CD16 – Monocytes, Related to Figure 5 ( A ) Clustermap of pairwise Pearson correlations between cell type clusters at baseline and late EVD. Correlations are computed on average log e TP10K expression values of overdispersed genes. DN and DP monocytes at late EVD are more similar to monocytes (including baseline CD14+s) than other cell types. ( B ) Scatterplot of MAGIC-smoothed expression values (log e TP10K) of CD14 and CD16 for monocytes in baseline, early, mid, and late disease stages. Cells are colored by smoothed expression levels of MKI67 (the gene coding for Ki67 protein). Boxes: CD14+, CD16+, DN, and DP subsets described in the text; numbers: percentage of cells falling into each subset. ( C ) Scatterplot of protein expression (CyTOF intensity) of CD14 and CD16 for 1,000 randomly sampled monocytes at each DPI. Cells are colored by Ki67 expression. Boxes: CD14+, CD16+, DN, and DP subsets described in the text; numbers: percentage of cells falling into each subset. ( D ) Scatterplot of protein expression (CyTOF intensity) of CD14 and CD16 for monocytes during human EVD. Left: monocytes from healthy human controls. Right: monocytes from 3 EVD cases (S1, S2, and S3) at various days post symptom onset. Cells are colored by Ki67 marker intensity. Boxes: CD14+, CD16+, DN, and DP subsets described in the text; numbers: percentage of cells falling into each subset. ( E ) UMAP embedding of healthy human PBMCs dataset, colored by annotated cluster assignment, based on known marker genes. (Plasma.: Plasmablast). ( F ) UMAP embedding of healthy bone marrow cells, colored by cluster assignment, based on marker genes. (HSC: hematopoietic stem cell, Plasma.: Plasmablast, Megakar.: Megakaryocyte, Mono/DC: monocyte and dendritic cell, BM-Macro: bone marrow macrophage). ( G ) UMAP embedding of sub-clustered HSC and monocyte/dendritic lineage cells. (BM: bone marrow, MP: monocyte progenitor) ( H ) Same UMAP embedding as Figure S5 G, but colored by the cluster identity of their nearest neighbor in the human PBMC dataset ( Figure S5 E). ( I ) UMAP embedding of the merged reference dataset of healthy bone marrow HSCs and monocyte lineage cells and PBMCs. Left sub-panel is colored by cluster assignment. Right sub-panels are colored by marker gene expression (log e TP10K). ( J ) Expression profiles of selected genes for human bone marrow monocyte progenitors (BM-MPs) and human circulating monocytes (PBMC-Monos). Circle area: percentage of cells in which the gene was detected; color: average expression ( Z -normalized log e TP10K). ( K ) Expression profiles of selected genes for NHP monocyte subsets at baseline or late EVD for orthologs of the genes in (J). Circle area: percentage of cells in which the gene was detected; color: average expression level ( Z -normalized log e TP10K). CD34 is grayed out because it is detected in <10 cells.

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Expressing, Marker, Clinical Proteomics, Gene Expression

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: Viral Transcriptional Dynamics of Infected Monocytes In Vivo and Ex Vivo (A) Schematic of EBOV challenge of PBMCs ex vivo . See also Figure S7 . (B and C) Percentage of cellular transcripts derived from EBOV (intracellular viral load) in monocytes from PBMCs inoculated with live virus ex vivo (B) or from PBMCs of NHPs infected in vivo (C). See also A–S8D. (D) Schematic of EBOV transcription. The viral RNA-directed RNA-polymerase transcribes each gene sequentially but occasionally releases the genomic RNA template, ending transcription. As a result, transcription frequency decreases from NP to L . (E and F) Proportion of each EBOV gene versus viral load (log 10 scale), ex vivo (E) or in vivo (F). We ordered infected monocytes by viral load and averaged the percentage of each viral gene over 50-cell sliding windows. Bands: mean ± 1 SD. See also E and S8F.

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Infection, In Vivo, Ex Vivo, Derivative Assay, Virus

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet: EBOV Infection Downregulates Host Antiviral Genes and Upregulates Putative Pro-viral Genes (A and B) Association between host gene expression and viral load within infected monocytes from PBMCs 24 HPI treated with live virus ex vivo (A) or from PBMCs of NHPs in vivo on DPI 5–8 (B). See also . (C and D) Select negatively (C) and positively (D) associated genes in monocytes from ex vivo infections. We ordered infected cells by viral load and averaged gene expression (log e TP10K) over 100-cell sliding windows; Spearman correlation (ρ) is given in the legend. Boxplots show gene expression in uninfected cells (boxes: median and interquartile range; whiskers: 2.5 th and 97.5 th percentiles). See also G and S8H.

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Infection, Gene Expression, Virus, Ex Vivo, In Vivo

Journal: Cell

Article Title: Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

doi: 10.1016/j.cell.2020.10.002

Figure Lengend Snippet:

Article Snippet: Human healthy PBMC scRNA-Seq , 10X , https://support.10xgenomics.com/single-cell-gene-expression/datasets “Aggregate of 8 Chromium Connect channels and 8 manual channels,” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor (Next GEM),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (v3 chemistry),” “5k Peripheral blood mononuclear cells (PBMCs) from a healthy donor with cell surface proteins (Next GEM),” “10k PBMCs from a Healthy Donor - Gene Expression and Cell Surface Protein,” “10k PBMCs from a Healthy Donor (v3 chemistry)”.

Techniques: Virus, Recombinant, Lysis, Electron Microscopy, Infection, Gene Expression, Sequencing, Software

Journal: medRxiv

Article Title: Rituximab counteracts loss of tolerance in membranous nephropathy patients through NK-mediated Treg induction

doi: 10.1101/2025.10.10.25337710

Figure Lengend Snippet: In vitro , rituximab is able to induce directly Treg on isolated T cells and requires a specific cellular environnement with at least B and NK cells to promote these regulatory cells. a-d) Quantification of Treg cells (CD127 low , CD25 high ) (a) or Th17 (IL17+) (c) among peripheral CD4+ cells by flow cytometry (n=10) or IL-10 (n=26) (b) and IL17a (n=22) (d) cytokine levels by ELISA from MN patients’ peripheral blood cell in vitro treated (Rtx) or not (NT) by rituximab and after non specific stimulation. e-g) Quantification of Treg induction index comparing in vitro rituximab treatment of whole blood cells with either isolated T cells (e) , B and T cells (f) or T, B and NK cells (g) from healthy donors (n=8-9) and after non specific stimulation. Treg induction index (TII= (Rtx-NT)/NT) was analysed in all experiments using flow cytometry (CD4+, Foxp3+, CD25high). Data are represented as median with interquartile range. P values were determined using paired Wilcoxon test (e-g) . NT: non-treated cells; Rtx: rituximab treated cells.

Article Snippet: NK, T or B cells were isolated according to manufacturer’s instructions from five milliliters of peripheral blood samples from adult healthy donors using, respectively, MACSxpress Whole Blood NK Cell Isolation Kit (cat# 130-127-695), MACSprepTM HLA T (cat# 130-117-890) or B (cat# 130-110-130) Cell Isolation Kit (Miltenyi).

Techniques: In Vitro, Isolation, Flow Cytometry, Enzyme-linked Immunosorbent Assay

Journal: medRxiv

Article Title: Rituximab counteracts loss of tolerance in membranous nephropathy patients through NK-mediated Treg induction

doi: 10.1101/2025.10.10.25337710

Figure Lengend Snippet: In vitro , Treg induction by rituximab relied on cytokine factors secreted by NK cells during ADCC-mediated B cell depletion. a) Quantification of Treg induction index comparing treatment of isolated T cells from healthy donors (N=7) with complemented medium derived from B cells (CM B cells) or a pool of B and NK cells (CM B + NK cells) treated or not with rituximab. b) Quantification of Treg induction index comparing treatment of isoled T cells with complemented medium pre-treated with galunisertib or emapalumab and derived from a pool of B and NK cells treated with rituximab (N=6). c-e) Quantification of Treg induction index (c) CD16 expression levels of NK cells (CD45+CD3-CD19-) (d) or CD56 high CD16 dim/- (e) using flow cytometry comparing treatment of peripheral blood samples of healthy donors (N=7) with rituximab or obinutuzumab after non specific stimulation. f) Representative CD56/CD16 flow cytometry plot of peripheral blood samples treated with rituximab or obinutuzumab after non specific stimulation. Treg induction index (TII= (Rtx-NT)/NT) was analysed in all experiments using flow cytometry (CD4+, Foxp3+, CD25high). P values were determined using paired T-test (a) , paired Wilcoxon test (c) or paired RM one-way ANOVA test with Tukey’s post-hoc correction (b; d-e) . NT: non-treated cells; Rtx: Rituximab treated cells; Obi: Obinutuzumab; MFI: mean fluorescence intensity

Article Snippet: NK, T or B cells were isolated according to manufacturer’s instructions from five milliliters of peripheral blood samples from adult healthy donors using, respectively, MACSxpress Whole Blood NK Cell Isolation Kit (cat# 130-127-695), MACSprepTM HLA T (cat# 130-117-890) or B (cat# 130-110-130) Cell Isolation Kit (Miltenyi).

Techniques: In Vitro, Isolation, Derivative Assay, Expressing, Flow Cytometry, Fluorescence

Journal: PLoS pathogens

Article Title: TGF-β1 down-regulation of NKG2D/DAP10 and 2B4/SAP expression on human NK cells contributes to HBV persistence.

doi: 10.1371/journal.ppat.1002594

Figure Lengend Snippet: Figure 2. Deficient NK cell function in IT patients. (A) Deficient NK cell cytotoxicity from IT patients. NK cell cytotoxicity was assessed in primary NK cells from IT, IA, and IN patients and healthy controls using a 51Cr-release assay with K562 target cells. (B) Results show the mean 6 SEM values in 19 patients and 5 controls. Values for IT patients were less than controls (P= 0.0384). (C) Positive correlation between NK cell cytotoxicity and the percentage of NK cells expressing NKG2D and 2B4. (D) Fresh PBMCs were stimulated with/without IL-12 as described in the Materials and Methods. After 16 h, IFN-c production was determined using flow cytometry by gating on CD32CD56+ NK cells. A representative dot plot displaying intracellular IFNc staining in NK cells with the subsets indicated is shown. (E) Cumulative data are shown. (F, G) Fresh PBMCs from patients before treatment (black) or after treatment (white) were stimulated with IL-12 for 16 h. IFNc (F) and CD107a (G) production was determined using flow cytometry by gating on CD32CD56+ NK cells. (H) Induction of ex vivo NK cell cytotoxic activity after in vivo administration of antiviral treatment with nucleoside analogues until ALT reached normal levels. NK cytotoxicity was determined ex vivo by measuring the lysis of 51Cr-labelled target cells before treatment (red) or after treatment (green). Cumulative data are shown. doi:10.1371/journal.ppat.1002594.g002

Article Snippet: Flow cytometric analysis Fresh human peripheral blood mononuclear cells (PBMCs) were isolated from peripheral blood by Ficoll-Isopaque (Solarbio, China) gradient centrifugation.

Techniques: Cell Function Assay, Release Assay, Expressing, Flow Cytometry, Staining, Ex Vivo, Activity Assay, In Vivo, Analogues, Lysis