Fig 2: HIV particle capture and Siglec-1 colocalization with p24 in HIV-1-infected MDM (top row), iPSC-MG1 (middle row), and MMG (bottom row). Immunofluorescence microscopy is shown examining Siglec-1 colocalization with p24. The cell types were infected with a biological stock of HIV-1BaL at an MOI of 0.5. On day 8 post infection, cells were fixed and immunolabeled for HIV-1 p24 (green), Siglec-1 (red) and DAPI was used as a nuclear marker. Scale bar = 10 µm

Fig 3: In-depth characterization of the myeloid cells in the peripheral blood of COVID-19 patients(A) t-SNE plots of normalized expression of the indicated markers across a maximum of 1,000 neutrophils per patient (n = 22 healthy controls, 27 mild COVID-19 patients, and 29 severe COVID-19 patients).(B) t-SNE plot generated as indicated in (A) and colored by disease severity.(C) Left: t-SNE plot generated as indicated in (A) and colored by CD16 expression level based on manual assignment of PhenoGraph clusters. Right: boxplot showing the frequency of CD16low neutrophils in COVID-19 patients and healthy controls. Statistical analyses were performed with a Mann-Whitney-Wilcoxon test corrected for multiple testing using the Holm method, and p values are shown if the results were significant (p < 0.05).(D) t-SNE plots of normalized expression of the indicated markers across a maximum of 1,000 monocytes per patient.(E) t-SNE plots generated as indicated in (D) colored by disease severity (top) and by clusters identified with the PhenoGraph algorithm (bottom).(F) Contour plots showing the distribution of a subset of 10,000 cells from the indicated clusters for a selected set of markers. For this analysis, classical monocytes M1–M7 were merged in a single cluster.(G) Heatmap of the normalized marker expression in PhenoGraph monocyte clusters. The frequency of each cluster in patients with mild and severe disease and in healthy controls is indicated as a stacked histogram to the right of the heatmap. Cell numbers for each cluster are plotted to the right of the stacked histogram.(H) Overlaid histograms showing arcsinh transformed counts on a linear axis for selected markers for the CD169+-activated monocyte clusters.(I) Overlaid histograms showing arcsinh transformed counts on a linear axis for the indicated markers for the classical monocyte clusters. Values in the plot indicate median untransformed count intensities.In (H) and (I), values on the plot indicate the median raw ion count intensity for each cluster and marker indicated.

Fig 4: Flow Panel characterizing CD11b, CD45, CX3CR1, CD68, CD317 and CD169 for the different microglial cell types and MDMs as labelled on the left. Blue histogram represents isotype-control antibodies, red histograms represent the specific staining for markers indicated at the top of the figure

Fig 5: CD169 monocytes are enriched in SARS-CoV-2-infected patients(A) Heatmap of the 15 monocyte metaclusters defined after FlowSOM analysis.(B) Relative abundance of metaclusters among monocytes for each patient and hierarchical clustering of COVID-19-ARDS+ (n = 12, green), COVID-19+ARDS+ (n = 13, blue), and COVID-19+ARDS- (n = 17, red).(C) Abundance of metaclusters differentially expressed between groups, among singlet cells analyzed.(D) Expression of the corresponding markers (mean metal intensity) for background (gray), Mo11 and Mo181 (orange), and Mo243 and Mo180 (blue) metaclusters.(E) Abundance of Mo22, Mo180, and Mo243 and expression of CD169 (box and whiskers with 10th and 90th percentiles).(F) Uniform manifold approximation and projection (UMAP) from scRNA-seq of COVID-19 patients (COVID-19) and healthy donors (healthy) highlighting CD14 and CD169 expression (data adapted from Wilk et al.25). Kruskal-Wallis test with Dunn’s multiple comparison correction, *p < 0.05, **p < 0.01, ***p < 0.001.