Journal: Cancer Immunology, Immunotherapy : CII

Article Title: Cholesterol induction in CD8 + T cell exhaustion in colorectal cancer via the regulation of endoplasmic reticulum-mitochondria contact sites

doi: 10.1007/s00262-023-03555-8

Figure Lengend Snippet: High cholesterol promotes CRC by inducing exhaustion in CD8+ T cells. A Workflow of this part. B histogram of cholesterol (Tc), HDL, LDL, Apo(a) and ApoB contents in CRC patients and healthy individuals (ncontrol = 98; nCRC = 217). C IF assay was used to detect the expression of CTLA-4, PD1 and TIM-3 in CD8+ T cells from peripheral blood in CRC patients with healthy serum cholesterol levels and hypercholesterolemia. D comparison of the peripheral blood cholesterol level between CRC mice model with high cholesterol diets and normal cholesterol diets. E, F Pathological morphology and HE staining of colon tissues from CRC mice model of inflammation induced by AOM/DSS. G Expression of CD69, CTLA-4, PD1 and TIM-3 in CD8+ T cells from non-CRC mice with hypercholesterolemia (high CHOL) and CD8+ T cells from non-CRC mice with normal cholesterol level (Normal CHOL). The red box shows the surface of receptor-positive CD8+ T cells. H Histogram of the contents of the cytokines IFN-γ, TNF-α and IL-2 in peripheral blood from mice in the Normal CHOL group and High CHOL group. I–M MC38 cells were used as the control group, Normal CHOL CD8+ T cells were used as the positive control group, and High CHOL CD8+ T cells were used as the experimental group. The CCK8 method (I) was used to detect the proliferation activity of MC38 cells, a scratch test (J, K) was used to detect the migration ability of MC38 cells, flow cytometry L) was used to detect the percentage of apoptosis in MC38 cells, and Transwell assays (M) were used to detect the invasion ability of MC38 cells. * indicating P < 0.05, ** indicating P < 0.01, *** indicating P < 0.001

Article Snippet: Magnetic cell separation (MACS) of CD8 + T cells from peripheral blood Magnetic isolation of CD8 + T cells from peripheral blood specimens was performed using StraightFrom® Whole Blood CD8 MicroBeads and a human and Whole Blood Column Kit (Miltenyi 130–090-878, Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Expressing, Comparison, Staining, Control, Positive Control, Activity Assay, Migration, Flow Cytometry

Journal: Cancer Immunology, Immunotherapy : CII

Article Title: Cholesterol induction in CD8 + T cell exhaustion in colorectal cancer via the regulation of endoplasmic reticulum-mitochondria contact sites

doi: 10.1007/s00262-023-03555-8

Figure Lengend Snippet: Contact between the endoplasmic reticulum and mitochondria occurs in CRCs at different cholesterol levels. A Workflow of this part. B The expression of CD8+ T cell ERMC proteins (Fis1 and Bap31, MFN2, VAPB and PTPIP51, VDAC1 and IPR3 and GRP75) in the peripheral blood of CRC patients with normal cholesterol and high cholesterol was detected by WB. C–F IF assay was used to detect the expression and location of Fis1 and Bap31, CoX4 and HSP90B1, VAPB and PTPIP51, VDAC1 and IPR3 and GRP75 in CD8+ T cells from CRC patients with normal cholesterol and high cholesterol levels. In the bar chart, * indicates P < 0.05, ** indicates P < 0.01

Article Snippet: Magnetic cell separation (MACS) of CD8 + T cells from peripheral blood Magnetic isolation of CD8 + T cells from peripheral blood specimens was performed using StraightFrom® Whole Blood CD8 MicroBeads and a human and Whole Blood Column Kit (Miltenyi 130–090-878, Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Expressing

Journal: Cancer Immunology, Immunotherapy : CII

Article Title: Cholesterol induction in CD8 + T cell exhaustion in colorectal cancer via the regulation of endoplasmic reticulum-mitochondria contact sites

doi: 10.1007/s00262-023-03555-8

Figure Lengend Snippet: ERS in exhausted CD8+ T cells induced by high cholesterol. A Workflow of this part. B The expression of the CD8+ T cell ERS proteins CHOP and GRP78 in the peripheral blood of CRC patients with normal cholesterol and high cholesterol was detected by WB. C IF assay was used to detect the expression of CHOP and GRP78 in CD8+ T cells from cancerous tissues in CRC patients with normal cholesterol and hypercholesteremia. D Expression of the ERS-related proteins CHOP and GPR78 in mice from each group detected by WB. E Endoplasmic reticulum morphology of different groups of CD8+ T cells observed by transmission electron microscopy. In the normal CHOL group, the rough endoplasmic reticulum distribution was also reduced. In the High CHOL group (CD8+ T cells from mice in the High cholesterol group), the endoplasmic reticulum was rare. In the MC-38/CD8+ T-WT group (MC-38 cells were cocultured with CD8+ T cells from wild-type mice), endoplasmic reticulum disintegration was observed in some parts. In the MC-38/CD8+ T-high CHOL group (coculture of MC-38 cells with CD8 + T cells from mice in the high cholesterol group), the ER was disintegrated. In the CD8+ T-4-PBA group (mice CD8+ T cells treated with the ERS inhibitor 4-PBA), ER structures were less common in the cytoplasm. In the MC-38/CD8+ T-4-PBA group (intervention with the ERS inhibitor 4-PBA in the coculture system of MC-38 cells and mice CD8+T cells), the arrow shows ERS disintegration. F Histogram and flow chart of PD1, TIM-3, CTLA-4 and CD69 expression in spleen T cells from mice in the 3 groups. G Cell proliferation was detected by the CCK-8 method, and differences were observed among the 3 groups of tumor cells (P < 0.05). H Cell invasion ability detected by the Transwell method. I Cell migration detected by a scratch test. J apoptosis was detected by Annexin-V APC/7-AAD double staining. In the bar chart, * indicates P < 0.05, ** indicates P < 0.01, *** indicates P < 0.001

Article Snippet: Magnetic cell separation (MACS) of CD8 + T cells from peripheral blood Magnetic isolation of CD8 + T cells from peripheral blood specimens was performed using StraightFrom® Whole Blood CD8 MicroBeads and a human and Whole Blood Column Kit (Miltenyi 130–090-878, Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Expressing, Transmission Assay, Electron Microscopy, CCK-8 Assay, Migration, Double Staining

Journal: Cancer Immunology, Immunotherapy : CII

Article Title: Cholesterol induction in CD8 + T cell exhaustion in colorectal cancer via the regulation of endoplasmic reticulum-mitochondria contact sites

doi: 10.1007/s00262-023-03555-8

Figure Lengend Snippet: Exhaustion of CD8+ T cells induced by high cholesterol showed structural and functional changes in ERMCs. A Workflow of this part. B Confocal immunofluorescence microscopy of mitochondria and ER of CD8+ T cells in the normal cholesterol group, high cholesterol group, normal CHOL CRC group, and high CHOL CRC group. Among these groups, the nucleus was blue, mitochondrial probe was green, and the ER probe was red. The higher the yellow overlap in the merged diagram is, the greater the colocalization of mitochondria and endoplasmic reticulum. C The expression of the mitochondrial fusion protein MFN2 in CD8+ T cells from the 4 groups was detected by Western blot. D–F Co-immunoprecipitation was performed to clarify the interaction between Fis1 and Bap31, VAPB and PTPIP51, and VDAC1 and IPR3 and GRP75 proteins of ERMCs in CD8+ T cells. Input refers to the protein content in cells, and IP refers to the protein content measured by the antigen antibody response. G, Immunofluorescence was performed to clarify the expression and location of MFN2 and CoX4 and HSP90B1, VAPB and PTPIP51, and VDAC1 and IPR3 and GRP75 in CD8+ T cells. The nucleus (blue) and other colors correspond to the probe colors of each molecule. The more orange parts in the combined figure, the more molecules are located in the cell

Article Snippet: Magnetic cell separation (MACS) of CD8 + T cells from peripheral blood Magnetic isolation of CD8 + T cells from peripheral blood specimens was performed using StraightFrom® Whole Blood CD8 MicroBeads and a human and Whole Blood Column Kit (Miltenyi 130–090-878, Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Functional Assay, Immunofluorescence, Microscopy, Expressing, Western Blot, Immunoprecipitation

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: Gut microbes

Article Title: Fusobacterium nucleatum -driven CX3CR1 + PD-L1 + phagocytes route to tumor tissues and reshape tumor microenvironment.

doi: 10.1080/19490976.2024.2442037

Figure Lengend Snippet: Figure 5: Fn induces PD-L1 expression in phagocytes, and PD-L1+ neutrophils exhibit immunosuppressive functions. (a-c) flow cytometry analysis (a, b) and western blot analysis (c) of PD-L1 expression in PMNs. (d and e) flow cytometry analysis (d) and western blot analysis (e) of PD-L1 protein expression in PMNs. (f) if staining of Fn (red) and PD-L1 (green) in Fn (MOI 10:1, 12 h)-infected PMNs. Right panel: quantification of PD-L1 expression. Scale bars: 25 μm. (g) Western blot analysis of protein expression in PMNs infected with Fn (MOI 10:1) for 15, 30, 60, and 120 min. (h and i) western blot analysis of protein expression in PMNs. Cells were pretreated with 30 nM TPCA-1 (h) or 100 μM NSC74859 (i) and infected with Fn for 1 h. (j) Schematic diagram showing that CD3+ T-cells were cocultured with human peripheral blood PMNs (1:1) or with an anti-PD-L1 antibody (20 μg/ml) for 48 h. (k and l) Representative flow cytometry and statistical analysis of T-cell- proliferation (k) and iFn-γ production (l) are shown (n = 3). (m) Schematic drawing of T-cell/ crc cell coculture system. (n-p) flow cytometry assay of apoptosis rates (n) and the statistical analysis (o) or CCK-8 assay of the cell viability rate of HCT116 and RKO cells (p). (q) Numbers of viable Fn were enumerated in PMNs by the gradient dilution coating method. PBS treatment was set as control (con). Data are presented as the mean ± SEM, p values were determined by one-way ANOVA (a, b, d, k, l, and o-q), and two-sided unpaired t-test (f). ns: no significant difference, *p < 0.05, **p < 0.01, ***p < 0.001 for groups connected by horizontal lines or versus con.

Article Snippet: Human peripheral blood neutrophils (PMNs) and human peripheral blood mononuclear cells (PBMCs) were isolated by a human peripheral blood neutrophil isolation kit (Solarbio, Beijing, China), and then monocytes (MCs) were isolated from PBMCs by discarding the supernatant after adhering to the walls for 1 h. The procedure was performed according to the protocol provided by the manufacturer.

Techniques: Expressing, Flow Cytometry, Western Blot, Staining, Infection, CCK-8 Assay, Control