Journal: Journal of Cellular and Molecular Medicine

Article Title: CSF‐1R inhibition disrupts the dialog between leukaemia cells and macrophages and delays leukaemia progression

doi: 10.1111/jcmm.15916

Figure Lengend Snippet: LAMs accumulate in the BM and spleen of T‐ALL mice. A, Schematic illustration of the experimental design. Approximately 2 × 10 6 EL4 cells were transplanted into C57BL/6 mice. When the mice developed T‐ALL at 7 d after EL4 transplantation, CD11b + Ly6G − macrophages were analysed by flow cytometry. B, The ratio of CD11b + Ly6G − macrophages in the BM cells derived from mice transplanted with EL4 cells (right panel), compared to control mice (left panel). C, Ratio of CD11b + Ly6G − macrophages in the spleen derived from mice transplanted with EL4 cells (right panel), compared to control mice (left panel). D, Bar graph shows the absolute numbers of CD11b + Ly6G − macrophages in the BM (left, n = 3) or spleen (right, n = 3) of leukaemic mice, compared to control (out of 10 4 cells acquired by FACS). E, Liver and spleen sections of control (left) or leukaemia mice (right) were stained using an anti‐CD68 antibody to identify macrophages (brown staining). F, Frequency of CD68 + macrophages in the liver (left, n = 5) or spleen (right, n = 5) of control or leukaemia mice

Article Snippet: The antibodies used in present study were FITC anti‐mouse/human CD11B Antibody (Biolegend, Cat. No. 101205, USA), APC anti‐mouse F4/80 Antibody (Biolegend, Cat. No. 123116, USA), APC anti‐mouse CD206 (MMR) Antibody (Biolegend, Cat. No. 141707, USA) and PE anti‐mouse Ly6G Monoclonal Antibody (Elabscience, Cat. No. E‐AB‐F1108D, China).

Techniques: Transplantation Assay, Flow Cytometry, Derivative Assay, Control, Staining

Journal: Journal of Cellular and Molecular Medicine

Article Title: CSF‐1R inhibition disrupts the dialog between leukaemia cells and macrophages and delays leukaemia progression

doi: 10.1111/jcmm.15916

Figure Lengend Snippet: Combination therapy significantly reduces the abundance of LAMs. A, Representative FACS plots showing the ratio of CD11b + Ly6G − macrophages in the BM derived from different treatment groups. B, Representative FACS plots showing the ratio of CD11b + Ly6G − macrophages in the spleen derived from different treatment groups. C, Absolute numbers of CD11b + Ly6G − macrophages in the BM (left) or spleen (right) from different treatment groups (out of 10 4 cells acquired by FACS), (n = 3). D, Liver and spleen sections of different treatment groups were stained using an anti‐CD68 antibody to identify macrophages. E, Frequency of CD68 + macrophages in the liver (left) or spleen (right) of different treatment groups (n = 5). F, Level of IL‐10 in serum of mice from different treatment groups (n = 3)

Article Snippet: The antibodies used in present study were FITC anti‐mouse/human CD11B Antibody (Biolegend, Cat. No. 101205, USA), APC anti‐mouse F4/80 Antibody (Biolegend, Cat. No. 123116, USA), APC anti‐mouse CD206 (MMR) Antibody (Biolegend, Cat. No. 141707, USA) and PE anti‐mouse Ly6G Monoclonal Antibody (Elabscience, Cat. No. E‐AB‐F1108D, China).

Techniques: Derivative Assay, Staining

Journal: bioRxiv

Article Title: Altered DNA methylation underlies monocyte dysregulation and innate exhaustion memory in sepsis

doi: 10.1101/2023.08.30.555580

Figure Lengend Snippet: (A) Experimental paradigm and FlowSOM analysis of monocytic lineage populations (CD11b + ; Ly6g-) in bone marrow samples collected from control (CTRL) or cecal slurry (CS)-injected mice at experimental day 7 (d7). Percentages to the right of each FlowSOM population indicate the percentage of cells for each condition clustering in that population. UMAP visualizations were prepared using flow cytometry data for the indicated markers (n = 8 CTRL and 12 CS d7 mice). (B) Flow cytometry mean fluorescence intensity (MFI) for exhaustion markers in FlowSOM Population 1. Box plots indicate median MFI values (n = 8-12; one-way ANOVA with Sidak’s multiple comparisons test; **** p-adj. < 0.0001; *** < 0.001; * < 0.05). (C) qRT-PCR for key exhaustion gene expression in CTRL and CS d6 or d7 monocytes. Expression levels were normalized to the geometric mean of Ube2l3 , Oaz1 , and Nktr . Data points represent separate mice, with mean expression +/- STD indicated (n = 3-9; one-way ANOVA with Sidak’s multiple comparisons test; differences are not significant unless otherwise specified; see Appendix for exact p-values). (D) Correlation heatmap for DNA methylation at differentially methylated CpG probes in CTRL or CS bone marrow monocytes (significance defined by ≥ 5% difference in % 5mC vs. CTRL; FDR < 10%; n = 7 CTRL, 4 CS d6, 6 CS d7, and 4 CS d12 mice). (E) Venn diagrams for differentially methylated CpG probes in CS bone marrow monocytes at experimental days 6, 7, and 12. (F) Volcano plot for altered DNA methylation at DMRs in CS d7 bone marrow monocytes versus CTRL. Probes are colored based on observed differential methylation state in CS d7 monocytes (red: hypermethylated; blue: hypomethylated). Dotted lines indicate the change in DNA methylation (+/- 5%) and adjusted p-value (< 0.1) cut-offs for DMRs. Nearest linked genes are indicated for select DMRs. (G) Promoter ( Fgfbp3 , miR21a , Cd36 ) or enhancer ( Il10, Socs3, Morrbid, Klf4, Foxp1, Nrp2 ) DMRs for immunologically significant genes in CTRL or CS monocytes. Illumina BeadChip probe IDs are indicated for each DMR.

Article Snippet: For Panel 2, cells were stained with antibodies against Ly6C (Pacific Blue; Biolegend #128014), CD11b (BV650; BD Biosciences #563402), Ly6g (PE-Cy5.5; Elabscience #E- AB-F1108I), CXCR2 (Alexa Fluor 488; R&D Systems # FAB2164G), CD68 (APC-Fire750; Biolegend #137041), CD172a (BV510; BD Biosciences #740159), CX3CR1 (PE-Cy7; Biolegend #149016), F4/80 (BV711; BD Biosciences #565612), CD38 (BV750; BD Biosciences #747103), PD-L1 (BV421; BD Biosciences #564716), MARCO (Alexa Fluor 647; R&D Systems #FAB29561R), FAS (BV605; Biolegend #152612), MHCII (PerCP; Biolegend #107624), CD168 (PE; Novus #NBP1-76538PE), and TREM2 (Alexa Fluor 700; R&D Systems #FAB17291N).

Techniques: Control, Injection, Flow Cytometry, Fluorescence, Quantitative RT-PCR, Gene Expression, Expressing, DNA Methylation Assay, Methylation