Journal: Cancer immunology, immunotherapy : CII

Article Title: Comparative analysis of monocytic and granulocytic myeloid-derived suppressor cell subsets in patients with gastrointestinal malignancies

doi: 10.1007/s00262-012-1332-3

Figure Lengend Snippet: CD14+HLA-DR−/low MDSC are increased in patients with GI cancer compared to controls, and this increase is consistent across each method of processing. a Flow cytometry analysis of both fresh and cryopreserved PBMC and whole blood which has undergone red cell lysis in patients with advanced GI cancer (n = 41) and healthy subjects (n = 44). Relative frequency is shown in a while b illustrates the data calculated for estimated absolute number; c representative dot plots of CD14+HLA-DR−/low MDSC in fresh PBMC, cryopreserved PBMC or whole blood; d gating strategy; e gross morphology on cytospin

Article Snippet: For functional analysis, CD14 + HLA-DR −/low , CD14 + HLA-DR + , CD15 + CD14 − CD11b + CD33 + , and CD15 + CD14 − CD11b + CD33 − populations were incubated at different ratios with CD3/CD28 (Miltenyi Biotech)-stimulated CD8 T cells.

Techniques: Flow Cytometry, Lysis

Journal: Cancer immunology, immunotherapy : CII

Article Title: Comparative analysis of monocytic and granulocytic myeloid-derived suppressor cell subsets in patients with gastrointestinal malignancies

doi: 10.1007/s00262-012-1332-3

Figure Lengend Snippet: CD15+CD14− cells but not CD15+CD14−CD11b+CD33+ are increased in patients with GI cancer compared to controls. Flow cytometry analysis of both fresh and cryopreserved PBMC and whole blood which has undergone red cell lysis in patients with advanced GI cancer (n = 41) and healthy subjects (n = 44). a Relative frequency CD15+CD14−;b estimated absolute number CD15+CD14 -; c relative frequency CD15+CD14−CD11b+CD33+; d estimated absolute number CD15+CD14−CD11b+CD33+; e representative dot plots of CD15+CD14−CD11b+CD33+ in fresh PBMC, cryopreserved PBMC or whole blood; f gross morphology on cytospin

Article Snippet: For functional analysis, CD14 + HLA-DR −/low , CD14 + HLA-DR + , CD15 + CD14 − CD11b + CD33 + , and CD15 + CD14 − CD11b + CD33 − populations were incubated at different ratios with CD3/CD28 (Miltenyi Biotech)-stimulated CD8 T cells.

Techniques: Flow Cytometry, Lysis

Journal: Cancer immunology, immunotherapy : CII

Article Title: Comparative analysis of monocytic and granulocytic myeloid-derived suppressor cell subsets in patients with gastrointestinal malignancies

doi: 10.1007/s00262-012-1332-3

Figure Lengend Snippet: Analysis of CD14+HLA-DR−/low MDSC in patients with GI cancer. CD14+HLA-DR−/low, CD14+HLA-DR+, and CD15+CD14−CD11b+CD33+ cells were cocultured at different ratios with autologous anti-CD3/CD28−cells. Supernatant was taken from the cultures before addition of 3H-thymidine and measured for IFN-γ by ELISA. Results shown are representative of 3 independent experiments

Article Snippet: For functional analysis, CD14 + HLA-DR −/low , CD14 + HLA-DR + , CD15 + CD14 − CD11b + CD33 + , and CD15 + CD14 − CD11b + CD33 − populations were incubated at different ratios with CD3/CD28 (Miltenyi Biotech)-stimulated CD8 T cells.

Techniques: Enzyme-linked Immunosorbent Assay

Journal: Cancer immunology, immunotherapy : CII

Article Title: Comparative analysis of monocytic and granulocytic myeloid-derived suppressor cell subsets in patients with gastrointestinal malignancies

doi: 10.1007/s00262-012-1332-3

Figure Lengend Snippet: Correlations CD14+HLA-DR−/low MDSC across method of processing. a Fresh versus cryopreserved PBMC; b PBMC versus whole blood lysis; c whether absolute number or relative frequency calculated

Article Snippet: For functional analysis, CD14 + HLA-DR −/low , CD14 + HLA-DR + , CD15 + CD14 − CD11b + CD33 + , and CD15 + CD14 − CD11b + CD33 − populations were incubated at different ratios with CD3/CD28 (Miltenyi Biotech)-stimulated CD8 T cells.

Techniques: Lysis

Journal: bioRxiv

Article Title: Mouse and human microglial phenotypes in Alzheimer’s disease are controlled by amyloid plaque phagocytosis through Hif1α

doi: 10.1101/639054

Figure Lengend Snippet: a , Schematic of the methodology employed in this study . b , Representative immunofluorescence image of the hippocampus of WT and 5xFAD mice injected with Methoxy-XO4 and stained with Iba1 (AlexaFluor 488, n =6 animals per genotype), scale bar=250 μm, inset 50 μm c , Representative FACS plot (from n =12-19 animals per genotype and age group) showing that XO4 + microglia are present in 6m 5xFAD plaque-affected regions (top panels). d , left, the percentage of XO4 + microglia isolated from plaque-affected regions in 1, 4, and 6m old WT and 5xFAD mice, ( n = 12-19 per genotype and age group; male and female mice pooled) and right, the percentage of XO4 + microglia isolated from plaque-affected and non-affected regions in 6m old male and female WT and 5xFAD mice ( n = 6-8 per genotype), expressed as mean ± SEM. e , PCA of bulk RNA-seq. Cx, Cortex; Cb, Cerebellum f, g Gene cytometry plots showing genes that are differentially expressed between XO4 + and XO4 − microglia and/or genes that are differentially expressed between old (4, 6 month) and young (1 month) microglia. Gene scores are calculated as the product of the log fold change and –log 10 (FDR). Example genes in each quadrant are labelled in red (upregulated over time or phagocytosis) or blue (downregulated). h i , Venn diagram showing the overlap between genes whose expression levels could be explained by the age, region and XO4 covariate as well as GO and KEGG terms associated with XO4 covariate genes. h ii , table showing the 21 core microglial neurodegeneration signature genes and their direction of differential expression in DAM , CD11c + , MGnD and XO4 + microglia. i , heat map of targeted LC-SWATH-MS analysis of detected peptides within DEGs in n =3-5 biological replicates of WT (blue), XO4 − 5xFAD (orange) and XO4 + 5xFAD (green) microglia. j , comparison of RNA and protein expression for selected genes, and quantitation of a tryptic peptide in Aβ in microglia. Data are expressed as mean ± SEM log fold change compared to WT microglia, normalized relative to peptides in Supplementary table 2. p values in d and j were calculated by one-way ANOVA using Tukey’s multiple comparison test.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAria™ III cell sorter.

Techniques: Immunofluorescence, Injection, Staining, Isolation, RNA Sequencing Assay, Cytometry, Expressing, Comparison, Quantitation Assay

Journal: bioRxiv

Article Title: Mouse and human microglial phenotypes in Alzheimer’s disease are controlled by amyloid plaque phagocytosis through Hif1α

doi: 10.1101/639054

Figure Lengend Snippet: a , Dimensionality reduction representation (viSNE, representative of n =3 mice per genotype) of myeloid cells isolated from WT (top) and 5xFAD (bottom) 6m male mice. Microglia (CD11b + CD45 lo CX3CR1 + ) are colored for expression of CD11b, CD45, CX3CR1, Methoxy-XO4, CD115, CD33 and TREM2, whereas remaining myeloid cells are grayscale for clarity. b , PCA of 893 single cells x 1671 feature genes showing the distribution of cells from each FACS-sorted sample. c , PCA plot of single microglia colored by SC3 clusters and composition of automated clusters as a percentage of sequenced FACS-sorted cell populations. d . PCA plots for single microglia colored by expression of selected ageing microglia genes (i-ii), homeostatic (iii) and XO4 + signature genes (iv-v). e, f Diffusion maps pseudotime analysis of microglial populations ordered by their expression of e , ageing DEGs (6m WT v 24m WT, 42 DEGs) or f , phagocytic DEGs (6m 5xFAD XO4 − v 6m 5xFAD XO4 + , 474 DEGs) g , scatter plot showing the relationship between ageing and phagocytosing pseudotime in individual cells, and the density of cells at each point during the ageing (bottom) and phagocytosing (left) trajectories. h , Hierarchical clustering and heat map showing expression of the top 50 DEGs across the 4 SC3 clusters.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAria™ III cell sorter.

Techniques: Isolation, Expressing, Diffusion-based Assay

Journal: bioRxiv

Article Title: Mouse and human microglial phenotypes in Alzheimer’s disease are controlled by amyloid plaque phagocytosis through Hif1α

doi: 10.1101/639054

Figure Lengend Snippet: a-c UMAP projection of single microglia nuclei from control and AD patient frontal cortex, cases ( n =172 nuclei) and controls ( n =277 nuclei). The microglial population was determined by similarity to known microglial markers . The UMAP projection is colored by a , disease diagnosis b , XO4 + score c , or ageing signature score. Diffusion maps pseudotime analysis of microglial populations ordered by their expression of d , XO4 + DEGs (taking top 10% of respective DE genes regardless of overlap with aging DEGs, 167 DEGs between 5xFAD XO4 + and XO4 − mice) or e , ageing DEGs (top 10% or 167 DEGs between 24M WT and 6M WT mice). f , scatter plot showing the relationship between ageing and XO4 + pseudotime in individual cells and the density of cells at each point during the ageing (left) and XO4 + (bottom) trajectories. g , UMAP projection of single human microglia colored by expression of selected cluster specific-genes. h Hierarchical clustering and heat map showing expression of the overlapping DEGs in each of the 4 mouse microglia clusters with the DEGs between human control and AD microglia. The mouse-human concordance on the direction of change between control and AD (human) or WT and XO4 + populations is shown for each gene ( p =0.000641). i , SCENIC regulon analysis showing that Hif1a and Elf3 are predicted to control the XO4 + gene regulatory network. j , UMAP projection of single human microglia colored by HIF1A regulon activity. k , Fluorescently labeled synaptosome internalization by primary microglia transfected with GFP-tagged inducible HIF1A and/or ELF3 overexpression constructs. The data are presented as mean ± SEM and show the difference in synaptosome internalization between GFP + and GFP − (non-transfected) cells tested from within the same well.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAria™ III cell sorter.

Techniques: Diffusion-based Assay, Expressing, Activity Assay, Labeling, Transfection, Over Expression, Construct

Journal: Nature Communications

Article Title: Interleukin-6 trans-signaling is a candidate mechanism to drive progression of human DCCs during clinical latency

doi: 10.1038/s41467-020-18701-4

Figure Lengend Snippet: a Diagnostic bone marrow aspirates from breast (BrCa, n = 19) or prostate (PC, n = 27) cancer patients (M0- or M1-stage of disease) were either CD45-depleted, enriched for EpCAM, or cultured under sphere conditions. Resulting spheres, CD45-depleted, or EpCAM-enriched BM cells were injected intra-venously (i.v.), intra-femorally (i.f.), sub-cutaneously (s.c.), sub-renally (s.r.), or into the mammary fat pad (mfp) of NOD-scid or NOD-scidIL2Rγ-/- mice. Mice with sub-cutaneous or mammary fat pad injections were palpated weekly. All other mice were observed until signs of illness or were sacrificed after 9 months. Injection routes that led to xenograft formation are highlighted in red. b Immunohistochemistry for estrogen-receptor (ER), progesterone-receptor (PR), prostate-specific antigen (PSA), Ki-67, or H & E staining of M1-DCC-derived xenografts is shown. c Human EpCAM- or cytokeratin 8/18/19-expressing DCCs were detected in the BM of 4/42 mice transplanted with M0-stage patient samples. DCCs from two of the four mice were isolated and their human origin was verified by a PCR specific for human KRT19. Pure mouse or human DNA was used as control. 1, 2 = cytokeratin 8/18/19-positive DCCs; N = cytokeratin 8/18/19-negative BM-cell, P = pool of BM-cells of recipient mouse; m = mouse positive control; h = human positive control, c = non-template control. d Single cell CNA analysis of the EpCAM-expressing DCC isolated at 4 weeks after injection from NSG BM ( c ) and a human hematopoietic cell as control. Red or blue indicate gain or loss of chromosomal regions.

Article Snippet: For xenotransplantations of DCCs, mononuclear cells from BM aspirates of nonmetastasized or metastasized breast or prostate cancer patients were enriched for human EpCAM or depleted of human CD45 + CD33 + CD11b + cells and erythrocytes using a mix of CD45, CD33, CD11b, and glycophorin A microbeads according to the manufacturer’s instructions (Miltenyi Biotec, Germany).

Techniques: Diagnostic Assay, Cell Culture, Injection, Immunohistochemistry, Staining, Derivative Assay, Expressing, Isolation, Control, Positive Control

Journal: Nature Communications

Article Title: Interleukin-6 trans-signaling is a candidate mechanism to drive progression of human DCCs during clinical latency

doi: 10.1038/s41467-020-18701-4

Figure Lengend Snippet: a Fold change in sphere numbers of pre-malignant (MCF 10A) and tumorigenic cell lines (MCF-7, MDA-MB-231) without (MCF 10A parental, n = 8; MDA-MB-231, n = 6) or with mutational activation of PIK3CA (MCF 10A PIK3CAE545K/+, n = 7; MCF-7, n = 6) cultured in the presence or absence of HIL6. Note that MCF 10A PIK3CAE545K/+ cells are isogenic to MCF 10A parental; n.s. = non-significant. b Western blot analyses showing phosphorylation of STAT3Tyr705, AKTSer475 and ERK1/2Thr202/Tyr204 in MCF 10A or MCF 10A PIK3CAE545K/+ cells cultured without or with HIL6 for the indicated time. For quantification, the signal of the phosphorylated protein and total protein was normalized to α-tubulin, then the ratio of phosphorylated to total protein was calculated. The graphs show the fold change in signal ratio over time relative to the control (unstimulated MCF 10A wt = 1). c Sphere numbers of the isogenic cells MCF 10A parental ( n = 8) and MCF 10A PIK3CAE545K/+ ( n = 7) cultured in the absence of HIL6. d Cytokeratin 8/18/19+ DCCs from BM of non-metastasized (M0-stage) HR-positive breast cancer patients and CD45-/EpCAM+/cytokeratin 8/18/19+ CTCs isolated from peripheral blood of metastasized (M1-stage) HR-positive breast cancer patients were sequenced for hotspot-mutations in PIK3CA (Exon 9: E545K, E542K; Exon 20: H1047R, H1047L, M1043I). P values in a , c two-sided Student’s test; d two-sided Fisher’s exact test. All error bars correspond to standard deviation (Mean ± SD).

Article Snippet: For xenotransplantations of DCCs, mononuclear cells from BM aspirates of nonmetastasized or metastasized breast or prostate cancer patients were enriched for human EpCAM or depleted of human CD45 + CD33 + CD11b + cells and erythrocytes using a mix of CD45, CD33, CD11b, and glycophorin A microbeads according to the manufacturer’s instructions (Miltenyi Biotec, Germany).

Techniques: Activation Assay, Cell Culture, Western Blot, Phospho-proteomics, Control, Isolation, Standard Deviation

Journal: BMC Cancer

Article Title: Distinctive grade based on Ki67 index and immune microenvironment of metastatic pancreatic neuroendocrine tumors responding to capecitabine plus temozolomide

doi: 10.1186/s12885-024-13117-5

Figure Lengend Snippet: Image of multispectral fluorescent IHC staining ( A ) CD163 + CD68 + CD206+; ( B ) CD68 + CD86 + CD80+, ( C ) CD11b + CD33+, ( D ) CD4 + CD25+ IHC: immunohistochemical

Article Snippet: Primary antibodies included the following markers: CD68 (GB113150, 1:1000, Servicebio, Wuhan, China), CD80 (305202, 1:3000, BioLegend, San Diego, USA), CD86 (ab269587, 1:100, Abcam, Cambridge, UK), CD163 (16646-1-AP, 1:200, Proteintech, Wuhan, China), CD206 (CST-91992 S, 1:200, Cell Signaling, Danvers, USA), CD11b (21851-1-AP, 1:500, Proteintech, Wuhan, China), CD33 (17425-1-AP, 1:25, Proteintech, Wuhan, China), CD4 (A19018, 1:100, Abclonal, Wuhan, China), and CD25 (ABB109, :200, Abbrab, Shanghai, China).

Techniques: Immunohistochemistry, Immunohistochemical staining

Journal: Nature Communications

Article Title: Transcriptional signature in microglia associated with Aβ plaque phagocytosis

doi: 10.1038/s41467-021-23111-1

Figure Lengend Snippet: a Schematic of the methodology employed in this study, created with BioRender.com. M, male, F, female, WT, wild-type, Cx, cortex and subcortical regions, Cb, cerebellum. b Representative immunofluorescence image of the hippocampus (HC) of WT and 5xFAD mice injected with methoxy-XO4 and stained with Iba1 (AlexaFluor 488, n = 6 animals per genotype), scale bar = 250 μm, inset 50 μm. c Representative FACS plot showing that XO4 + microglia are present in 6 m 5xFAD plaque-affected regions (top panels). d Left, the percentage of XO4 + microglia isolated from plaque-affected regions in 1, 4 and 6 m old WT (m, month) and 5xFAD mice (from n = 6 animals per genotype at 1 m; 4 m WT, n = 19 animals; 4 m 5xFAD, n = 22; 6 m WT, n = 14; 6 m 5xFAD n = 14) and right, the percentage of XO4 + microglia isolated from plaque-affected and non-affected regions in 6 m old male and female WT and 5xFAD mice (F, Cx, n = 8 per genotype; M, Cx, n = 6 per genotype; F, Cb, n = 4 per genotype; M, Cb, n = 3 per genotype), expressed as mean ± SEM, *** p = 0.003 and **** p = 4.6 × 10 −5 for 4 m, p = 9 × 10 −6 for 6 m, and p = 5.2 × 10 −5 for F Cx vs Cb by Kruskal-Wallis and Dunn’s multiple comparison tests. e PCA of bulk RNA-seq. Cx, Cortex; Cb, Cerebellum. f , g Gene cytometry plots showing DEGs between XO4 + and XO4 − microglia and/or DEGs expressed between old (4, 6 m) and young (1 m) microglia. Gene scores are calculated as the product of the LFC and –log 10 (FDR). Example genes in each quadrant are labelled in red (upregulated over time or phagocytosis) or blue (downregulated). Gene density low = 0, high = 0.2. h i Venn diagram showing the overlap between genes whose expression levels could be explained by the age, region and XO4 covariate as well as GO and KEGG terms associated with XO4 covariate genes. h ii Table showing the 21 core microglial neurodegeneration signature genes and their direction of differential expression in DAM , CD11c + , MGnD and XO4 + microglia. i Heatmap of targeted LC-SWATH-MS analysis of detected peptides within DEGs in biological replicates of WT (green, n = 4 animals), XO4 − 5xFAD (orange, n = 5) and XO4 + 5xFAD (blue, n = 4) microglia. Colour scale represents log 2 -transformed normalized fold changes compared to WT microglia. clustering method = ward.D2, distance = maximum. j Comparison of RNA and protein expression for selected genes, and quantitation of a tryptic peptide in Aβ in microglia. Data are expressed as mean ± SEM LFC compared to WT microglia, normalized relative to peptides in Supplementary Data . p -Values were calculated by one-way ANOVA using Holm-Sidak’s multiple comparison test. Data are from WT ( n = 4 animals), XO4 − 5xFAD ( n = 5), XO4 + 5xFAD ( n = 4) for protein analyses; WT ( n = 5), XO4 − 5xFAD ( n = 7), XO4 + 5xFAD ( n = 7) for RNA analyses.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAriaTM III cell sorter.

Techniques: Immunofluorescence, Injection, Staining, Isolation, Comparison, RNA Sequencing, Cytometry, Expressing, Quantitative Proteomics, Data-independent acquisition, Transformation Assay, Quantitation Assay

Journal: Nature Communications

Article Title: Transcriptional signature in microglia associated with Aβ plaque phagocytosis

doi: 10.1038/s41467-021-23111-1

Figure Lengend Snippet: a PCA of 893 single cells (6 m WT = 243 cells, 24 m WT = 121 cells, 6 m 5xFAD XO4 − = 95 cells, 6 m 5xFAD XO4 + = 434 cells; m, month) and 1671 feature genes showing the distribution of cells from each FACS-sorted sample. PC, principal component. b PCA plot of single microglia coloured by single cell consensus (SC3) clusters and composition of automated clusters as a percentage of sequenced FACS-sorted cell populations. c PCA plots for single microglia coloured by expression of selected ageing microglia genes (i-ii), homeostatic (iii) and signature genes associated with XO4 + microglia (iv-v). min = 0 for all genes, Defa17 max = 4.77 , Defa24 max = 7.41 , Crybb1 max = 4.13 , Cst7 max = 5.47 , Ccl3 max = 4.89. d , e Diffusion maps pseudotime analysis of microglial populations ordered by their expression of ( d ) ageing DEGs (24 m WT vs 6 m WT, 42 DEGs) or ( e ) phagocytic DEGs (6 m 5xFAD XO4 + vs 6 m 5xFAD XO4 − , 474 DEGs). f Scatter plot showing the relationship between ageing and phagocytosing pseudotime in individual cells, and the density of cells at each point during the ageing (bottom) and phagocytosing (left) trajectories. g Hierarchical clustering and heatmap showing expression of the top 50 DEGs across the 4 SC3 clusters.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAriaTM III cell sorter.

Techniques: Expressing, Diffusion-based Assay

Journal: Nature Communications

Article Title: Transcriptional signature in microglia associated with Aβ plaque phagocytosis

doi: 10.1038/s41467-021-23111-1

Figure Lengend Snippet: a – c UMAP projection of single microglia nuclei from control and AD patient entorhinal and frontal cortex samples, combined by integrating data from – , comprising 102 patients; AD ( n = 5891 microglia nuclei), mild AD ( n = 1591 microglia nuclei), controls ( n = 2988 microglia nuclei), Other Dementia ( n = 3 microglia nuclei) and TREM2 R62H variant ( n = 1458 microglia nuclei). Clustering and analysis of signature scores is performed using Seurat v3. UMAP projection is coloured by ( a ) study of origin, ( b ) Seurat cluster and ( c ) XO4 + score. d Box plots for gene signature scores in each human microglial cluster for the AD vs Trem2KO AD signature, AD vs WT signature , DAM vs homeostatic, and DAM2 vs DAM1 signatures . The lower, middle and upper hinges represent the lower quartile, median and upper quartile, respectively, while the upper and lower whiskers extend ±1.5 times of the interquartile range from the hinges. For each signature score category, pairwise Wilcoxon test between each cluster and base mean was computed. Multiple testing was corrected for using Bonferroni correction. * p < 0.05, ** p < 0.01; *** p < 0.001, **** p < 0.0001, exact p values are provided in the Source data. e The proportion of cells in Clusters 10 and 11 in patients with any cells in Cluster 10 or Cluster 11, respectively (please see Supplementary Fig. for sample size details), grouped according to disease status and/or TREM2 genotype ( * p = 0.047, Wilcoxon Test with No AD as reference). The lower, middle, and upper hinges represent the lower quartile, median and upper quartile, respectively, while the upper and lower whiskers extend ±1.5 times of the interquartile range from the hinges. f Cluster 10 and Cluster 11 DEGs relative to all other human microglia clusters (adjusted p -value < 0.05). Genes of interest associated with XO4 + microglia are highlighted in red. g Heatmap of enriched KEGG pathways in the human microglial Seurat clusters, coloured by log 2 (-log 10 (adjusted p -value)). h Fluorescently labelled synaptosome internalization by human primary microglia treated with AF647-labelled fAβ. The data are mean ± SEM of 3 independent biological replicates and are expressed as fold change in synaptosome internalization relative to non-treated microglia. Differences are reported between AF488-fAβ + and AF488-fAβ − cells tested from within the same well. i Histograms showing fluorescence intensity of HIF1A intracellular staining in AF488-fAβ + and AF488-fAβ − human primary microglia assayed from within the same well. Secondary antibody control cells are stained with AF647 secondary antibodies alone. j Fluorescently labelled synaptosome internalization by primary microglia transfected with GFP-tagged inducible HIF1A and/or ELF3 overexpression constructs. The data are the mean ± SEM of 5 independent biological replicates and are expressed as fold change in synaptosome internalization between GFP + and GFP − (non-transfected) cells tested from within the same well. * p = 0.0188, *** p = 0.0002 by two-way ANOVA and Sidak’s multiple comparison test on the raw synaptosome internalization percentages.

Article Snippet: The cell pellet was then stained with antibodies to microglial cell surface markers (CD11b-BV650, 1:200 Biolegend, #141723; CD45-BV786, 1:200, BD Biosciences #564225; CX3CR1-FITC, 1:100, Biolegend, #149019; CD11a, 1:20, BD Biosciences, #558191, TREM2-APC, 1:10, R&D Systems, #FAB17291N; CD33-PE, 1:20, eBioscience, #12-0331-82; CD115-BV711, 1:40, Biolegend, #135515) for isolation using the FACSAriaTM III cell sorter.

Techniques: Control, Variant Assay, Fluorescence, Staining, Transfection, Over Expression, Construct, Comparison