Journal: EMBO Molecular Medicine

Article Title: IL ‐27 produced during acute malaria infection regulates Plasmodium ‐specific memory CD4 + T cells

doi: 10.15252/emmm.202317713

Figure Lengend Snippet: B6 mice were transferred with PbT‐II cells, infected with Pcc, and treated with control (IgG; n = 1 biological replicate) or anti‐IL‐27 mAb (α‐IL‐27; n = 1 biological replicate) between −1 and 5 days of infection. PbT‐II cells were purified from these mice 7 days after infection and single‐cell RNA sequencing (scRNA‐seq) analysis was performed. Details of the experiments are shown in Fig . UMAP plots of PbT‐II cells from IgG control ( n = 4,030) and anti‐IL‐27 mAb‐treated mice ( n = 7,476) after unsupervised clustering of pooled single‐cell data from the two groups, with clusters colored by gene expression profiles. UMAP clustering of PbT‐II cells colored by cell cycle profiles. Summary graph of proportions of PbT‐II cells in each cluster for IgG and anti‐IL‐27 mAb‐treated mice in (A). Dot plots showing the expression of Th1‐, Tfh‐, Tcmp‐related genes (Ciucci et al , ), and other genes of interest in each UMAP cluster of PbT‐II cells from IgG and anti‐IL‐27 mAb‐treated mice. Dot colors represent the intensity of expression, while dot size represents the proportion of cells with the corresponding expression. Violin plots showing the expression of Th1‐, Tfh‐, Tcmp‐, and proliferation‐associated genes in PbT‐II cells from IgG (light blue) and anti‐IL‐27 mAb (blue) treated mice. Ridge plots showing the expression of published Th1, Tfh, Tmem, and Tcmp CD4 + T cell signatures in each of the UMAP clusters in (A) based on (Ciucci et al , ). Source data are available online for this figure.

Article Snippet: Stained CD4 + T cells were washed using the recommended Cell Wash Protocol 1 in preparation for 10X Single Cell RNA sequencing (Chromium Next GEM Single Cell 5′ v2 Reagent kits (Dual Index); 10X Genomics).

Techniques: Infection, Control, Purification, RNA Sequencing, Gene Expression, Expressing

Journal: EMBO Molecular Medicine

Article Title: IL ‐27 produced during acute malaria infection regulates Plasmodium ‐specific memory CD4 + T cells

doi: 10.15252/emmm.202317713

Figure Lengend Snippet: B6 mice were transferred with PbT‐II cells, infected with Pcc, and were treated with either IgG or anti‐IL‐27 mAb between −1 and 7 days after infection ( n = 1 biological replicate per timepoint). PbT‐II cells were prepared from spleen at day 28 pi, stained for CD4/TCR/CD45.1 and for CD127, KLRG1, and CD49d with TotalSeq antibodies, sort purified, and processed for scRNA‐seq and CITE‐Seq analysis. Details of the experiment are found in Fig . A–G Comparative analysis of scRNA‐seq data from IgG and anti‐IL‐27 mAb‐treated PbT‐II cells. (A) UMAP plot colored of day 28 PbT‐II cells from IgG control ( n = 7,491) and anti‐IL‐27 mAb‐treated mice ( n = 4,944) after unsupervised clustering of pooled single cell data from the two groups, with clusters colored by gene expression profiles. Cluster labels were harmonized to reflect similar gene expression patterns in the clusters at day 7 pi (Fig ) and anti‐IL27 mAb day 7–28 PbT‐II analysis (Fig ). (B) UMAP clustering of PbT‐II cells colored by cell cycle profiles. (C) CITE‐seq analysis of PbT‐II cells for IgG2a (isotype control), CD127, KLRG1, and CD49d, shown in the same UMAP clustering as (A). (D) Proportions (%) of each cluster within PbT‐II cells, with bar graph sizes shown relative to the total number of PbT‐II cells in IgG (36.8 × 10 ) and anti‐IL‐27 mAb treated (265.7 × 10 ) mice. (E) Ridge plots of PbT‐II cells showing the expression of published CD4 + T cell signature genes (Ciucci et al , ). (F) Violin plots comparing the expression of the CD4 + T cell signature genes. (G) Dot plots showing the expression of Th1‐, Tfh‐, Tcmp‐, and proliferation‐associated genes in each cluster. Dot colors represent the intensity of expression, while dot size represents the proportion of cells with the corresponding expression. H Volcano plot of differentially expressed genes between major clusters 1* and 1** within PbT‐II cells from anti‐IL‐27‐treated mice and corresponding Gene Ontology enrichment analysis for the upregulated genes in each group using Metascape. Source data are available online for this figure.

Article Snippet: Stained CD4 + T cells were washed using the recommended Cell Wash Protocol 1 in preparation for 10X Single Cell RNA sequencing (Chromium Next GEM Single Cell 5′ v2 Reagent kits (Dual Index); 10X Genomics).

Techniques: Infection, Staining, Purification, Control, Gene Expression, Expressing

Journal: EMBO Molecular Medicine

Article Title: IL ‐27 produced during acute malaria infection regulates Plasmodium ‐specific memory CD4 + T cells

doi: 10.15252/emmm.202317713

Figure Lengend Snippet: B6 mice were transferred with PbT‐II cells, treated with IgG or anti‐IL‐27 mAb on day −1, 2 and 5 for day 7 analysis, while mice were treated with anti‐IL‐27 mAb on day −1, 2, 5, and 7 for day 14 and 28 analysis ( n = 1 biological replicate per timepoint). PbT‐II cells were purified and subjected to single‐cell RNA sequencing (scRNA‐seq) and CITE‐seq analysis. The ProjecTILs algorithm (Andreatta et al , ) was used to analyze CD4 + T cell states of PbT‐II cells based on a published reference atlas (Andreatta et al , ). A Experimental scheme. B Gating strategy for the sorting of PbT‐II cells for the scRNA‐seq experiments: Spleen cells were stained for CD4, TCRβ, and CD45.1 to distinguish PbT‐II cells and for TotalSeq IgG2a, CD127, KLRG1, and CD49d for CITE‐seq analysis. C Flow cytometry profiles for each PbT‐II sample analyzed for single‐cell transcriptomics. D, E Predicted distribution of the projected PbT‐II cells in IgG and anti‐IL‐27 mAb‐treated mice on day 7 (D) and day 28 (E) after Pcc infection as density contours in a UMAP plot of a CD4 + T cell reference map (Andreatta et al , ). The bar graphs represent the proportions of the PbT‐II cells projected in the indicated reference subtype.

Article Snippet: Stained CD4 + T cells were washed using the recommended Cell Wash Protocol 1 in preparation for 10X Single Cell RNA sequencing (Chromium Next GEM Single Cell 5′ v2 Reagent kits (Dual Index); 10X Genomics).

Techniques: Purification, RNA Sequencing, Staining, Flow Cytometry, Single-cell Transcriptomics, Infection

Journal: EMBO Molecular Medicine

Article Title: IL ‐27 produced during acute malaria infection regulates Plasmodium ‐specific memory CD4 + T cells

doi: 10.15252/emmm.202317713

Figure Lengend Snippet: scRNA‐seq data of PbT‐II cells from Pcc‐infected anti‐IL‐27 mAb‐treated mice (day7, 14, and 28) were pooled, and unsupervised clustering was performed. UMAP plot colored by gene expression clustering. Proportions (%) of each cluster for each time point. Feature plots of indicated genes across cell clusters as distributed in UMAP plots. Dot plots showing the expression of Th1‐, Tfh‐, Tmem‐, and proliferation‐associated genes in each cluster. Dot colors represent the intensity of expression, while dot size represents the proportion of cells with the corresponding expression. Ridge plots of PbT‐II cell clusters showing the expression of published CD4 + T cell signature genes (Ciucci et al , ).

Article Snippet: Stained CD4 + T cells were washed using the recommended Cell Wash Protocol 1 in preparation for 10X Single Cell RNA sequencing (Chromium Next GEM Single Cell 5′ v2 Reagent kits (Dual Index); 10X Genomics).

Techniques: Infection, Gene Expression, Expressing

Journal: EMBO Molecular Medicine

Article Title: IL ‐27 produced during acute malaria infection regulates Plasmodium ‐specific memory CD4 + T cells

doi: 10.15252/emmm.202317713

Figure Lengend Snippet:

Article Snippet: Stained CD4 + T cells were washed using the recommended Cell Wash Protocol 1 in preparation for 10X Single Cell RNA sequencing (Chromium Next GEM Single Cell 5′ v2 Reagent kits (Dual Index); 10X Genomics).

Techniques: Marker, Staining, FACS, Purification, Software, Cell Isolation

Journal: medRxiv

Article Title: Single cell long read whole genome sequencing reveals somatic transposon activity in human brain

doi: 10.1101/2024.11.11.24317113

Figure Lengend Snippet: Overall metrics of genomic data obtained in scWGS experiments of studied brains A) . Breadth of coverage for each of the analyzed cell types, including long-read ONT sequencing and short-read scWGS Illumina sequencing of the same dMDA single-cell DNA. For single cells, analyzed regions are limited to >=5x depth of coverage, while for bulk all covered regions are included. B) Mosaic SNV detected in long- read scWGS and bulk ONT MSA1 sample located within an exon of LRRK2 - a gene important in monogenic Parkinson’s disease. C) SVs (insertions and deletions) detected across the 3 studied brains in long-read scWGS and bulk ONT samples. The first category shows all bulk variants across the genome, while the remaining 4 categories are limited to regions covered >=5x in single cell-samples and variants from those regions in corresponding bulk. D) Mosaic deletion detected in long-read MSA1 ONT single cell samples as well as in low frequency in corresponding long-read ONT bulk tissue sample. The deletion overlaps ACTL6A gene, encoding actin-related protein associated with Non-Specific Syndromic Intellectual Disability and Torticollis. E) A comparison of variant allele frequency (VAF) in long-read ONT bulk samples and the ratio of single cells where the variant is detected to the total number of single cells covering the variant locus in long-read ONT scWGS experiments. High VAF population variants were removed. Most of the remaining variants are mosaic in bulk, as represented by the heatmap concentration in the lower half of the chart.

Article Snippet: To summarize, we demonstrated the utility of long-read single cell whole genome sequencing using Oxford nanopore to study SNV, InDel and SV mutations across 18 single cells derived from 3 brains.

Techniques: Sequencing, Illumina Sequencing, Comparison, Variant Assay, Concentration Assay

Journal: Cell Stem Cell

Article Title: Three-Dimensional Human Alveolar Stem Cell Culture Models Reveal Infection Response to SARS-CoV-2

doi: 10.1016/j.stem.2020.10.004

Figure Lengend Snippet: RNA-Sequencing Analyses of Infected h3ACs and h3BCs (A) Heatmap of the most variable 100 genes among three groups of h3ACs at 0, 1, and 3 dpi. (B) Volcano plot showing differentially expressed genes between h3ACs at 0 and 3 dpi. (C) Transcriptional changes of interferon genes in infected h3ACs by transcripts per million (TPM) values. (D) IF imaging for upregulated MX1 (green). The intensity of MX1 significantly increases in infected h3ACs (p value < 0.001). n = 11 for control and n = 13 for infected h3ACs. (E) Proportion of viral RNA reads in h3AC and h3BC transcriptomes. (F) Example of a missense mutation (NC_045512.2: 3,177C > U) detected from a h3BC transcriptome at 3 dpi.

Article Snippet: To understand transcriptional changes in infected h3ACs at single-cell resolution, we employed a 10X Genomics single-cell RNA sequencing (RNA-seq) platform for h3ACs in five different conditions (uninfected; MOI of 0.1 at 4, 16, and 60 hpi [hours post-infection]; and MOI of 1.0 at 60 hpi).

Techniques: RNA Sequencing, Infection, Imaging, Control, Mutagenesis

Journal: Cell Stem Cell

Article Title: Three-Dimensional Human Alveolar Stem Cell Culture Models Reveal Infection Response to SARS-CoV-2

doi: 10.1016/j.stem.2020.10.004

Figure Lengend Snippet:

Article Snippet: To understand transcriptional changes in infected h3ACs at single-cell resolution, we employed a 10X Genomics single-cell RNA sequencing (RNA-seq) platform for h3ACs in five different conditions (uninfected; MOI of 0.1 at 4, 16, and 60 hpi [hours post-infection]; and MOI of 1.0 at 60 hpi).

Techniques: Recombinant, Virus, Red Blood Cell Lysis, Modification, Membrane, Electron Microscopy, SYBR Green Assay, Purification, Plasmid Preparation, Viability Assay, Cytotoxicity Assay, RNA Sequencing, Transmission Assay, Software, Microscopy, Control, Sequencing, Infection

Journal: Cancers

Article Title: Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics

doi: 10.3390/cancers13194885

Figure Lengend Snippet: Flowchart depicting the strategy for selection and interrogation of Lin−/Lin+ cell populations from mBC patients. Patient blood samples were collected into sodium-EDTA tubes, and each sample was sub-divided. ( a ) One portion of the blood sample was processed for isolating Lin−/Lin+ cell populations via FACs, followed by RNA Sequencing or scRNA-Sequencing. See “ ” for details. ( b ) A 7.5 mL portion of the blood sample was transferred to an AccuCyte collection tube for RareCyte analysis.

Article Snippet: We addressed these issues by devising an experimental strategy for capturing all CTCs, then performing not only standard RNA Sequencing (RNA-Seq), but also, notably, comprehensive and unbiased single-cell RNA sequencing analyses (scRNA-Seq; 10x Genomics Chromium) on blood samples collected from mBC patients.

Techniques: Selection, RNA Sequencing, Sequencing

Journal: Cancers

Article Title: Heterogeneity of Circulating Tumor Cell Neoplastic Subpopulations Outlined by Single-Cell Transcriptomics

doi: 10.3390/cancers13194885

Figure Lengend Snippet: RNA-Seq of FACS Lin−/Lin+ cell populations. Blood was collected from normal human donors and 19 mBC patients. PBMCs were isolated and sorted as described, followed by RNA-Seq of collected cells. ( a ) A volcano graph showing genes with significant log2 fold change and −log10 ( p value) for the normal PBMCs (green dots) in comparison with the Lin+ population from 15 mBC patients (red dots). ( b ) Heat maps of gene expression showing significant differences between normal human PBMCs (left/ blue) and Lin+ cells (right/ yellow) from patients. Patient 8 provided two samples 3 months apart. ( c ) A volcano graph showing genes with significant log2 fold change and −log10 ( p value) for the Lin− populations (green dots) in comparison with the Lin+ population (red dots). ( d ) Heat maps of gene expression, indicating differences between the Lin+ (yellow) and Lin− (blue) populations from mBC patients. ( e – h ) Heat maps for patients grouped by hormone receptor status (shown above the map) ( e ) ER+/PR+/Her2+ ( f ) ER+/PR+/Her2− ( g ) ER+/PR−/Her2−, and ( h ) ER−/PR−/Her2+. Other subtypes had less than three patients in the overall set. All heat maps were done with unsupervised clustering.

Article Snippet: We addressed these issues by devising an experimental strategy for capturing all CTCs, then performing not only standard RNA Sequencing (RNA-Seq), but also, notably, comprehensive and unbiased single-cell RNA sequencing analyses (scRNA-Seq; 10x Genomics Chromium) on blood samples collected from mBC patients.

Techniques: RNA Sequencing, Isolation, Comparison, Gene Expression

Journal: The Journal of Infectious Diseases

Article Title: Measles Virus Infects and Programs MAIT Cells for Apoptosis

doi: 10.1093/infdis/jiaa407

Figure Lengend Snippet: MAIT cells express the highest levels of SLAMF1/CD150 among PBMC subsets. A, Publicly available scRNA-Seq data from 11 769 PBMCs were analyzed. The 9432 cells that passed quality control filters are visualized on a t-SNE projection (left panel) demonstrating clusters corresponding to CD14+ monocytes (n = 2992), CD16+ monocytes (n = 328), cDCs (n = 74), pDCs (n = 68), NK cells (n = 544), B cells (n = 1419), CD4+ T cells (n = 2643), CD8+ T cells (n = 720), MAIT cells (n = 592), and platelets (n = 52). Each dot represents a single cell. The expression of SLAMF1 across indicated clusters, quantified as normalized and scaled count data, is shown in a violin plot (right panel), in which dots represent single cells and widths denote cell densities. B and C, MAIT cells and other peripheral blood T cell subsets were examined for CD150 expression. MAIT and iNKT cells were identified by MR1 tetramer staining (PubMed IDs 24101382 and 24695216) and CD1d tetramer staining (PubMed IDs 10839805 and 10974039), respectively. Open and filled histograms correspond to the staining of PBMCs with anti-CD150 and isotype control, respectively, after gating on CD3+MR1 tetramer+ MAIT cells (B). The frequencies of CD150+ cells and the gMFI of CD150 staining (C) in indicated T cell subsets are summarized using Box-and-Whisker plots, with each symbol representing an individual donor. *, *** and **** denote differences with P < .05, P < .001, and P < .0001, respectively, using matched one-way ANOVA with Dunnett post-hoc analysis. D, PBMCs (n = 4) were left untreated or stimulated with rhIL-12 plus rhIL-18. The frequencies of MAIT cells expressing CD150, CD69, or CD46 were determined 24 hours later by flow cytometry. ** denotes a difference with P < .05 by paired Student t test. Abbreviations: 5-OP-RU, 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil; APC, allophycocyanin; cDC, classic dendritic cell; FITC, fluorescein isothiocyanate; gMFI, geometric mean fluorescence intensity; iNKT, invariant natural killer T cell; MAIT, mucosa-associated invariant T cell; MR1, MHC-related protein 1; NK cell, natural killer cell; NS, not significant; PBMC, peripheral blood mononuclear cell; pDC, plasmacytoid pre-dendritic cell; PE, phycoerythrin; rhIL, recombinant human interleukin; scRNA-Seq, single-cell RNA sequencing; TCM, central memory T cell; TEM, effector memory T cell; TN, naive T cell; t-SNE, t-distributed stochastic neighbor embedding.

Article Snippet: Transcriptomic Analysis of Peripheral Blood Mononuclear Cells The pbmc_10k_v3 dataset, consisting of single-cell RNA sequencing (scRNA-Seq) data from 11 769 peripheral blood mononuclear cells (PBMCs), was created by 10x Genomics ( https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/pbmc_10k_v3 ).

Techniques: Control, Expressing, Staining, Whisker Assay, Flow Cytometry, Fluorescence, Recombinant, RNA Sequencing

Journal: American Journal of Respiratory and Critical Care Medicine

Article Title: Secretory Cells Dominate Airway CFTR Expression and Function in Human Airway Superficial Epithelia

doi: 10.1164/rccm.202008-3198OC

Figure Lengend Snippet: CFTR (cystic fibrosis transmembrane conductance regulator)-expressing cell types in normal human large airway epithelial (LAE) and small airway epithelial (SAE) cells in an independent replicate cohort. (A) Schematic of airway locations where LAE and SAE cells were collected for 10x Genomics single-cell RNA sequencing. Matched LAE and SAE cells were obtained from eight donors. (B) Regional source of conducting airway epithelial cells on the uniform manifold approximation and projection (UMAP). (C) Clustering of combined LAE and SAE cells into nine conducting airway epithelial cell types by UMAP. Each cluster was assigned to one of the Drop-Seq single-cell RNA-sequencing cell clusters (Figure 1) on the basis of the prediction score as shown in Figure E5. (D) Pie charts depicting the cell-type composition among LAE or SAE cells. (E) Cellular distribution of CFTR+ cells on the combined LAE and SAE cells by UMAP. (F) Pie charts depicting the proportion of each cell type identified among CFTR+ LAE or SAE cells. (G) Violin plots depicting CFTR expression in CFTR+ conducting airway epithelial cells of LAE or SAE regions. The difference between regions was compared using the nonparametric two-sided Wilcoxon rank-sum test. (H) Violin plots depicting CFTR expression in CFTR+ cells per each cell type in LAE or SAE cells. (I) Pie charts depicting the total contribution of each cell type to CFTR expression in LAE or SAE cells. For definition of abbreviations, see Figure 2.

Article Snippet: G. Carraro and B.R.S. performed 10X Genomics single-cell RNA sequencing.

Techniques: Expressing, RNA Sequencing