The differences between marker expression densities were quantified using the KolmogorovCSmirnov distances (KS). Click here for more data file.(5.9M, PDF) Table S1Overview of the mass cytometry panel. Analysis of Density-normalized Events (SPADE) clusters. A heatmap showing relative marker manifestation for SPADE clusters was generated. The mean of the median manifestation of each marker was identified and classified inside a five-tiered color level, from white (not indicated) to dark red (highly expressed), according to their range of manifestation (5th to 95th percentile) throughout the dataset. Clustering markers are demonstrated in blue. Hierarchical clustering of both the cell clusters and clustering markers were performed and are displayed by dendrograms. image_3.PDF (510K) GUID:?8E1A0277-F2D6-44B7-A00B-00A8D603D48A Number S4: Relative range of marker expression of Spanning-tree Progression Analysis of Density-normalized Events clusters. Graph showing the relative range of marker manifestation of clusters acquired after manual gating of CD4+ T cells. The range of manifestation for each marker (5th to 95th percentiles of manifestation throughout the dataset) are displayed using a five-tiered color scale ranging from white (not indicated) to dark red (highly indicated). Clustering markers are demonstrated in blue. image_4.PDF (157K) GUID:?1399A9E1-9630-4E38-A4A4-A4BE2E5B0EFD Number S5: Cell number in each CD32a+ CD4+ T-cell cluster. This representation shows the number of cells associated with each CD32a+ CD4+ T-cell cluster, no matter sample cell source. Cluster titles are indicated within the production of anti-CD32b antibodies. This work was supported by French authorities Programme dInvestissements IWP-4 dAvenir (PIA) under Give ANR-11-INBS-0008 that account the Infectious Disease Models and Innovative Therapies (IDMIT, Fontenay-aux-Roses, France) infrastructure and PIA give ANR-10-EQPX-02-01 that funds the FlowCyTech facility. Supplementary Material The Supplementary Material for this article can be found on-line at https://www.frontiersin.org/articles/10.3389/fimmu.2018.01217/full#supplementary-material. Number S1Characterization of CD32a and CD32b antibody specificity by mass cytometry. Representative analysis of metal-conjugated CD32a-Dy161 (top panels) and CD32b-Sm149 (lower panels) antibody staining of monocytes, B cells, and CD4+ T cells performed on PBMCs from one healthy donor (out of six) using FlowJo software. Click here for more data file.(515K, PDF) Number S2Gating strategy used to identify CD4+ T cells. Singlets were recognized using cell size vs. Ir191-DNA intercalator and calibration beads were excluded (cells no beads). Living leukocytes were identified by selecting Rhodium (Rh103)Di-negative cells and then CD45+ cells. Finally, CD4+ T cells were recognized by gating on CD3+ CD19? and then CD4+ CD8? cells. Click here for more data file.(2.3M, PDF) Number S3Phenotypic panorama of CD4+ T-cell Spanning-tree Progression Analysis of Density-normalized Events (SPADE) clusters. A heatmap showing relative marker manifestation for SPADE clusters was generated. The mean of the median manifestation of each marker was identified Mouse monoclonal to CD20.COC20 reacts with human CD20 (B1), 37/35 kDa protien, which is expressed on pre-B cells and mature B cells but not on plasma cells. The CD20 antigen can also be detected at low levels on a subset of peripheral blood T-cells. CD20 regulates B-cell activation and proliferation by regulating transmembrane Ca++ conductance and cell-cycle progression and classified inside a five-tiered color level, from white (not indicated) to dark red (highly expressed), according to their range of manifestation (5th to 95th percentile) throughout the dataset. Clustering markers are demonstrated in blue. Hierarchical clustering of both the cell clusters and clustering markers were performed and are displayed by dendrograms. Click here for more data file.(510K, PDF) Number S4Relative range of marker manifestation of Spanning-tree Progression Analysis of Density-normalized Events clusters. Graph showing the relative range of marker manifestation of clusters acquired after manual gating of CD4+ T cells. The range of manifestation for each marker (5th to 95th percentiles of manifestation throughout the dataset) are displayed using a five-tiered color scale ranging from white (not indicated) to dark red (highly indicated). Clustering markers are demonstrated in blue. Click here for more data file.(157K, PDF) Number S5Cell quantity in each CD32a+ CD4+ T-cell cluster. This representation shows the number of cells associated with IWP-4 each CD32a+ CD4+ T-cell cluster, no matter sample cell source. Cluster titles are indicated within the X-axis and the corresponding quantity of cells within the Y-axis. The size of the dots is definitely proportional to the number of cells in the cluster. Click here for more data file.(139K, PDF) Number S6Percentages of CD32a+ CD4+ TN, TCM, and TEff/Mem subsets among CD4+ T cells from HIV-infected individuals and healthy donors. This representation shows the percentage of naive (TN), central memory space (TCM), and effector/memory space (TEff/Mem) CD4+ T cells among CD32a+ CD4+ T cells for main HIV-infected individuals before (main HIV, reddish circles) and after 12?weeks of combination antiretroviral treatment (HIV cART, blue squares) and that of healthy donors (healthy, green triangles). Click here for more data file.(393K, PDF) Number S7Correlation analysis of total CD32a+ CD4+ T-cell cluster and cluster #5 cell abundances IWP-4 with HIV DNA levels. (A) Correlation analysis of total CD32a+ CD4+ T-cell cluster cell abundances with total HIV DNA levels. The HIV DNA weight (log10 copies/106 PBMCs) for each sample are indicated within the X-axis, and the connected percentage of cells relative to CD4+ T cells for CD32a+ CD4+ T-cell clusters within the Y-axis. The Pearson correlation coefficient was equal to 0.4329 (p?=?0.0727). (B) Correlation analysis between cluster #5 cell large quantity and HIV DNA levels. For each sample, the HIV DNA weight (log10.