Journal: Cardiovascular research

Article Title: Single-cell profiling reveals age-associated immunity in atherosclerosis.

doi: 10.1093/cvr/cvad099

Figure Lengend Snippet: Figure 1 Aging promotes immunosenescence and atherosclerosis in Ldlr−/− mice. (A) Experimental setup: Ldlr−/− mice aged 3 months (green bars) or 20 months (violet bars) were fed with a standard chow diet (white circles) or a Western diet (grey circles) for 10 weeks. (B) Using flow cytometry, percentages (% from live) of circulating myeloid cells (CD11b+), neutrophils (CD11b+Ly6CintLy6G+), inflammatory monocytes (CD11b+Ly6ChiLy6G−), and (C) circulating CD4+ and CD8+ T-cells were determined (% from live). (D) Splenic naïve (TN: CD44−CD62L+), effector (TEFF: CD44−CD62L−), central memory (TCM: CD44+CD62L+), and effector memory (TEM: CD44+CD62L−) T-cells were quantified as a percentage of CD4+ and CD8+ T-cells and plotted in pie charts. (E) Intracellular cytokine production of interferon-gamma (IFN-γ), interleukin (IL)-4, IL-10, and IL-17 were measured as percentage (mean) of splenic CD4+ and CD8+ T-cells after 4 h of stimulation with PMA and ionomycin. Colour scale is normalized for each cytokine. (F) Circulating CD19+ B-cells were determined with flow cytometry. (G) Total and oxidized LDL (oxLDL)-specific IgM titres were measured in the serum. (H ) Total serum cholesterol levels at sacrifice were measured. (I) Cross sections of the aortic root were stained for lipid and collagen content, and (J ) atherosclerotic lesion volume was quantified. (K) Collagen content and (L) necrotic cores were quantified as percentage of lesion area. (M) Cholesterol crystallization in atherosclerotic lesions was categorized on a scale of 0 (no cholesterol crystallization) to 3, and presence of calcification (purple) or no calcification (grey) was presented as percentage of group. (N) Macrophage content (MOMA-2) was measured as percentage of lesion area. Data are from n = 12–15 mice per group. Statistical significance was tested by one-way ANOVA. Mean ± S.E.M. plotted. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Article Snippet: C D 8 T c el ls Il1 7a + T c el ls T re gs N K T c el ls T c el ls /M C s YC YW OC young chow diet young Western diet old chow diet young chow diet (Cochain, 2018) young Western diet old chow diet Gzmk+ CD8+other CD8+ Nkg7 Ccl5 S100a6 GzmkSatb1 AW112010 S100a4 Id2Lef1 Tcf7 Sell Ccl4Ccr7 Rgs10 Ccr9 0 20 40 60 0.0 2.5 5.0 Log2 fold change NS Log2 FC value p - value and log2 FC chow diet (CD) Western diet (WD) 0 2 4 6 8 10 Natural Killer Cell Signaling Caveolar-mediated Endocytosis Signaling Pathogen Induced Cytokine Storm Signaling Pathway Signaling by Rho Family GTPases Th1 Pathway RHOGDI Signaling Immunogenic Cell Death Signaling Pathway Regulation of Actin-based Motility by Rho Integrin Signaling Th1 and Th2 Activation Pathway -log(p-value) 0 50 100 150 200 # G zm k+ C D 8+ T ce lls * **** * young old Figure 3 Identification of age-associated T-cell populations and gene signatures in atherosclerotic aortas from Ldlr−/− mice. (A) Cd3e+ clusters were extracted from the principal clustering and reclustered, after which the T-cell clusters were identified. (B) UMAP plots and stacked diagrams visualizing the identified T-cell subclusters in young CD, young, WD and old CD aortas, in which Gzmk+CD8+ T-cells are encircled in the dashed red shape. (C ) Dot plot showing the average expression of immune cell cluster-defining markers for each cluster. (D) Heatmap of hierarchically clustered top 25 variable genes across T-cell subclusters. (E) Volcano plot of the differentially expressed genes (DEGs) in the Gzmk+CD8+ T-cell cluster compared to other CD8+ T-cells in clusters 2, 3, 5, and 6. (F ) Top canonical pathways of the Gzmk+CD8+ T-cell cluster compared to CD8+ T-cells in clusters 2, 3, 5, and 6. (G) Heatmap showing average expression of biological process-associated genes in T-cell clusters of young CD, young WD, and old CD Ldlr−/− aortas. (H ) Using flow cytometry, absolute numbers of Ly6C−CD44+Tox+PD-1+ CD8+ T-cells (GzmK+CD8+ T-cells) were measured in aortas of young and aged Ldlr−/− mice (n = 11–15).

Techniques: Western Blot, Flow Cytometry, Staining, Crystallization Assay

Journal: bioRxiv

Article Title: Simultaneous inhibition of human CD4 and 4-1BB biogenesis suppresses cytotoxic T lymphocyte proliferation

doi: 10.1101/2020.12.30.424816

Figure Lengend Snippet: (A) PBMCs were stimulated with mitomycin C inactivated RPMI1788 cells (MLR), CD3/CD28 beads or PHA and exposed to CADA (10 μM). Supernatants were collected on day 5 (MLR; n=5) or day 3 (beads and PHA; n=4) post stimulation and cytokine levels were determined by Bio-Plex assay. Bars represent mean ± SD, with individual values shown as open (DMSO) or solid (CADA) symbols. Note that cytokine levels in the MLR samples are plotted on a logarithmic scale. Welch’s corrected t-tests were performed to compare CADA to DMSO with *p<0.05. (B) PBMCs were pre-incubated with CADA (10 μM) or DMSO during 3 days, after which they were activated by CD3/CD28 beads or PHA. Cell surface CD28 expression was measured on gated CD4 + T cells by flow cytometry on d3 post activation. Cell surface expression of OX40 and 4-1BB was measured on total PBMCs by flow cytometry on d2 post activation. Panels represent intra-donor treatment effect of CADA on receptor expression for 4 donors of PBMCs (indicated separately). Paired t-tests were performed to compare CADA to DMSO with *p<0.05. Figure supplement 1. CADA reduces the upregulation of CD28 on activated lymphocytes.

Article Snippet: For the quantification of the cytokines IL-2, IFN-γ and TNF-α Cytokine Human ProcartaPlex Panel kits (Invitrogen, Thermo Fisher Scientific) were used following manufacturer’s protocol.

Techniques: Plex Assay, Incubation, Expressing, Flow Cytometry, Activation Assay

Journal: bioRxiv

Article Title: A 50-gene high-risk profile predictive of COVID-19 and Idiopathic Pulmonary Fibrosis mortality originates from a genomic imbalance in monocyte and T-cell subsets that reverses in survivors with post-COVID-19 Interstitial Lung Disease

doi: 10.1101/2023.10.22.563156

Figure Lengend Snippet: A . Study design of the 50-gene signature and cytokine analysis in COVID-19 patients (Cohort 1). B. Heatmap of COVID-19 patients based on the 50-gene signature discriminates three risk groups (low, intermediate, and high) based on SAMS. Every column represents a patient, and every row represents a gene. Log-based two-color scale is adjacent to the heatmap. Red denotes increased expression and green denotes decreased expression. Gene expression data is represented as Log2 normalized expression values. C-D. Time to death and time to discharge by day 60 in hospitalized patients with COVID-19, respectively. E-H. Plasma cytokine concentrations (IL6, IP-10, SPP1 and TGFβ) in low, intermediate, and high-risk profile patients with COVID-19 at days 2, 6 and 13 post admission. The data is presented as an average of triplicate values ± SEM for each group. Two-way ANOVA test (GraphPad software) Tukey’s multiple comparisons were used; * p<0.05. I. Study design of 7-gene signature analysis by RT-qPCR in PBMCs from COVID-19 patients (Cohort 2). J. Heatmap of COVID-19 patients based on the 50-gene signature discriminates three risk groups (low, intermediate, and high) based on SAMS Up scores. Heatmap nomenclature is the same as in . K-L. Time to death and time to discharge by day 60 in hospitalized patients with COVID-19 respectively in cohort two. The data is presented as an average of triplicated TUs values ± SEM for each group. * p<0.05

Article Snippet: We measured cytokine concentrations of 121 plasma samples from COVID-19 patients from Cohort 1 using a customized, Bioplex 200 compatible, human cytokine panel including, IL6, IP10, SPP1 and TGFβ-1 (#FCSTM18-06, R&D Systems).

Techniques: Expressing, Software, Quantitative RT-PCR