Journal: Diabetes

Article Title: Loss of NADPH Oxidase–Derived Superoxide Skews Macrophage Phenotypes to Delay Type 1 Diabetes

doi: 10.2337/db14-0929

Figure Lengend Snippet: Pancreas-infiltrating macrophages from superoxide-deficient NOD.Rag mice display a decrease in TNF-α and IL-1β synthesis, and a concomitant increase in Arg-1 synthesis after diabetogenic CD4 T-cell transfer. Dot plots of TNF-α– (A), IL-1β–, and Arg-1– expressing (B) macrophages in the pancreata of NOD.Rag and NOD.Rag.Ncf1m1J recipient mice at 7 days post-transfer with NOD.BDC-2.5 CD4 T cells. Dot plots were generated by first gating on granulocytes and then gating on F4/80+ or CD11b+ cells via side scatter. For TNF-α and IL-1β, expression is shown by F4/80+, I-Ag7+ cells while Arg-1 expression by CD11b+, I-Ag7+ cells is displayed. Mean fluorescence intensity (MFI) values of TNF-α and IL-1β were quantified by F4/80+, I-Ag7+ cells, while those of Arg-1 were calculated from CD11b+, I-Ag7+ cells. Data are representative of four independent experiments.

Article Snippet: CD4 T cells were purified by negative selection according to the manufacturer’s instructions via the RoboSep CD4 T-cell isolation kit (STEMCELL Technologies) with >90% purity ( 17 ).

Techniques: Expressing, Generated, Fluorescence

Journal: Diabetes

Article Title: Loss of NADPH Oxidase–Derived Superoxide Skews Macrophage Phenotypes to Delay Type 1 Diabetes

doi: 10.2337/db14-0929

Figure Lengend Snippet: Pancreas-infiltrating macrophages from NOD.Rag mice treated with MnP display a decrease in TNF-α and a concomitant increase in Arg-1 synthesis after diabetogenic CD4 T-cell transfer. Dot plots of TNF-α– (A), IL-1β–, and Arg-1–expressing (B) macrophages in the pancreata of NOD.Rag recipient mice at 7 days post-transfer with NOD.BDC-2.5 CD4 T cells treated with HBSS or MnP. Dot plots were generated by first gating on granulocytes and then gating on F4/80+ or CD11b+ cells via side scatter. Mean fluorescence intensity (MFI) values of TNF-α and IL-1β were quantified by F4/80+, I-Ag7+ cells, while those of Arg-1 mean fluorescence intensity were calculated from CD11b+, I-Ag7+ cells. For TNF-α and IL-1β, expression is shown by F4/80+, I-Ag7+ cells, while Arg-1 expression by CD11b+, I-Ag7+ cells is displayed. Data are representative of four independent experiments.

Article Snippet: CD4 T cells were purified by negative selection according to the manufacturer’s instructions via the RoboSep CD4 T-cell isolation kit (STEMCELL Technologies) with >90% purity ( 17 ).

Techniques: Expressing, Generated, Fluorescence

Journal: bioRxiv

Article Title: Glycolysis downregulation is a hallmark of HIV-1 latency and sensitizes infected cells to oxidative stress

doi: 10.1101/2020.12.30.424810

Figure Lengend Snippet: Panels A-C) primary CD4 + T-cells were activated with α-CD3-CD28 beads and infected with HIV-1 pNL4-3 or mock-infected. Cells were cultured for two weeks post-infection (p.i.) to model different infection stages (days 3-9 p.i., i . e . productive infection; day 14 p.i., i . e . latent infection) and subjected to microarray (A,B; n=2) or RNA-Seq (C; n=3) analysis. Panel A) Gene set enrichment analysis (GSEA) of the expression of the glycolytic pathway (HUMAN-GLYCOLYSIS) in mock-infected or HIV-1 infected cells. B,C) Heatmaps of the relative expression of glycolytic enzymes upon HIV-1 infection. Data are expressed as Log 2 fold change in HIV-1 infected vs mock-infected cells. For microarray data (B) expression values of infected and mock-infected cells at different time points were pooled. For RNA-Seq data (C), expression values in infected cells were normalized using the corresponding time point in mock-infected cells. Adjusted p values (q values) to account for multiple testing were calculated by Significance Analysis of Microarrays [SAM ( Tusher et al , 2001 )] and Deseq2 for RNA-Seq data ( Love et al , 2014 ). Panels D-F) scRNA-Seq of the expression of the entire glycolytic pathway or of glucose phosphate isomerase only ( GPI ) in primary CD4 + T-cells infected in vitro (D,E) or CD4 + T-cells of PLWH (F). In panels D,E, cells were infected with VSVG-HIV-1-GFP and sorted for viral expression as detailed in ( Golumbeanu et al , 2018 ). Following latency establishment, cells were left untreated or HIV-1 expression was reactivated through suberoyl anilide hydroxamic acid (SAHA) or α-CD3-CD28 engagement. Clusters 1 and 2 were identified by principal component analysis as described in ( Golumbeanu et al , 2018 ). In panel F, CD4 + T-cells were isolated from total blood of PLWH under ART as described in ( Cohn et al , 2018 ). Viral expression was reactivated by treatment with phytohemagglutinin (PHA) and cells were sorted using antibodies against Env and Gag. Sorted cells were then subjected to scRNA-Seq analysis. The expression level of the HUMAN-GLYCOLYSIS pathway in Panel D was calculated as the average expression of genes comprising the gene list; expression levels in cluster 1 and 2 were compared using Wilcoxon rank sum test. For panels E-F significance of GPI differential expression level between clusters (E) or between control and Env + Gag + conditions (F) was assessed by Wilcoxon rank sum test encoded in FindMarkers Seurat R function. Panels G,H) Correlation of combined HIV-1 expression and the expression of the entire glycolytic pathway (G) or GPI only (H) in sc-RNA-Seq profiling of untreated HC69 microglial cells. Data were analyzed by Spearman’s correlation coefficients. ** p< 0.01, *** p< 0.001; *** p< 0.0001.

Article Snippet: Briefly, naive CD4 + T cells were isolated using a RoboSep CD4 + Naïve T cell negative selection kit (STEMCELL Technologies Inc., Vancouver, British Columbia, Canada), and 2□X□10 6 cells were resuspended in 10□mL RPMI medium and stimulated with 10□μg/mL concanavalin A (ConA) (EMD Millipore, Billerica, MA, USA) in the presence of subset-specific cytokines.

Techniques: Infection, Cell Culture, Microarray, RNA Sequencing, Expressing, In Vitro, Isolation, Quantitative Proteomics, Control

Journal: bioRxiv

Article Title: Glycolysis downregulation is a hallmark of HIV-1 latency and sensitizes infected cells to oxidative stress

doi: 10.1101/2020.12.30.424810

Figure Lengend Snippet: Panels A,B. Reactivation from HIV-1 latency (A) and relative cell viability (B) in different cell models following treatment with the Trx inhibitor auranofin (AF; 500 nM), the GSH inhibitor buthionine sulfoximine (BSO; 250 μM), or a combination of the two. The characteristics of the different models adopted are detailed in the Material and Methods section. Each data point represents a mean from at least two independent experiments conducted in the different models. Replicates of all experiments for each cell model are shown in Additional Files 8, 9 and 11, except for the data of monocyte-derived macrophages which were retrieved from ( Shytaj et al , 2013 ). Panel C. Levels of integrated HIV-1 DNA following treatment for 48 h with AF and/or BSO in CD4 + T-cells derived from PLWH under suppressive antiretroviral therapy. Live cells were sorted after treatment, and integrated DNA was measured by Alu-PCR. The latency reactivating agent SAHA was used as a reference compound ( Archin et al , 2012 ). Data were analyzed by non-parametric Friedman’s test followed by Dunn’s post-test (A,C) or two-way ANOVA followed by Tukey’s post-test (B). Solid lines represent the means. * p< 0.05, ** p< 0.01, *** p< 0.001.

Article Snippet: Briefly, naive CD4 + T cells were isolated using a RoboSep CD4 + Naïve T cell negative selection kit (STEMCELL Technologies Inc., Vancouver, British Columbia, Canada), and 2□X□10 6 cells were resuspended in 10□mL RPMI medium and stimulated with 10□μg/mL concanavalin A (ConA) (EMD Millipore, Billerica, MA, USA) in the presence of subset-specific cytokines.

Techniques: Derivative Assay

Journal: Scientific Reports

Article Title: Oral Pathobiont Activates Anti-Apoptotic Pathway, Promoting both Immune Suppression and Oncogenic Cell Proliferation

doi: 10.1038/s41598-018-35126-8

Figure Lengend Snippet: Enriched blood panDCs and gingival tissues of CP patients reveal immunosuppressive state. ( A ) 29 genes associated with transcriptional regulation, inflammation, immunosuppression, cell proliferation, anti-apoptosis and other homeostatic functions were identified from the RNAseq data. Bar graphs show both up- (red) and down- (blue) regulation of genes (≥±2 fold) in ex-vivo isolated and panDC-enriched blood samples from CP patients compared to healthy controls confirmed by TaqManPCR. The overall validation data shows the same trend as in RNAseq analysis. ( B ) H&E of healthy control and CP patient’s gingival tissue. The arrows indicate the infiltrating cells of inflammatory responses; (20X), CT- Connective Tissue, ET- Epithelial Tissue. Results are representative of two experiments (n = 9/group). ( C ) Co-localized expression of pAKT1/pFOXO1, pAKT1/DC-SIGN (receptor for Mfa1) and DC-SIGN/FOXP3 (arrowhead) in gingival connective tissue (marked in b) from CP, compared with healthy control. Images are representative of three independent experiments (Scale bar- 100 µm; pls refer Fig. for independent channel and their quantification measurement of co-localization. ( D ) Immunoblot analysis of p/tAKT1, p/tFOXO1, FOXP3, IDO1, BIM, CXCR4 and SDF1 in gingival tissue of CP compared with healthy control. ( E ) Mfa1 and FimA mRNA in ex-vivo isolated panDCs from CP patients and Healthy control and normalized with the internal control. ( F–H ) Regulation of FOXO1, FOXP3, BIM transcription by FOXO1A or pAKT1. Immunoprecipitation of chromatin from the human FOXO1 ( F ), FOXP3 ( G ) and BIM ( H ) locus in mixed immune cell population from gingival tissues of CP and healthy control with anti-pAKT1 or anti-FOXO1A, followed by qPCR analysis of immunoprecipitants; results are presented relative to input by immunoprecipitation with isotype-matched control antibody. Data are representative of six independent experiments. * P ≤ 0.05, ** P ≤ 0.01.

Article Snippet: Human blood DCs were negatively selected from PBMCs using panDC pre-enrichment kit (Robosep, Stem cell technologies).

Techniques: Ex Vivo, Isolation, Biomarker Discovery, Control, Expressing, Western Blot, Immunoprecipitation