10 research outputs found

    Single-Cell Analysis of Human Mononuclear Phagocytes Reveals Subset-Defining Markers and Identifies Circulating Inflammatory Dendritic Cells

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    Human mononuclear phagocytes comprise phenotypically and functionally overlapping subsets of dendritic cells (DCs) and monocytes, but the extent of their heterogeneity and distinct markers for subset identification remains elusive. By integrating high-dimensional single-cell protein and RNA expression data, we identified distinct markers to delineate monocytes from conventional DC2 (cDC2s). Using CD88 and CD89 for monocytes and HLA-DQ and FcΔRIα for cDC2s allowed for their specific identification in blood and tissues. We also showed that cDC2s could be subdivided into phenotypically and functionally distinct subsets based on CD5, CD163, and CD14 expression, including a distinct subset of circulating inflammatory CD5−CD163+CD14+ cells related to previously defined DC3s. These inflammatory DC3s were expanded in systemic lupus erythematosus patients and correlated with disease activity. These findings further unravel the heterogeneity of DC subpopulations in health and disease and may pave the way for the identification of specific DC subset-targeting therapies. Using high-dimensional protein and RNA single-cell analyses, Dutertre et al. analyze human dendritic cell and monocyte subsets and identify markers that delineate them and unravel their heterogeneity. They also reveal the presence of inflammatory CD14+ DC3s, a subset of cDC2s, that correlate with disease progression and may be functionally involved in systemic lupus erythematosus immunopathology. © 2019 Elsevier Inc

    Single-Cell Analysis of Human Mononuclear Phagocytes Reveals Subset-Defining Markers and Identifies Circulating Inflammatory Dendritic Cells

    No full text
    Human mononuclear phagocytes comprise phenotypically and functionally overlapping subsets of dendritic cells (DCs) and monocytes, but the extent of their heterogeneity and distinct markers for subset identification remains elusive. By integrating high-dimensional single-cell protein and RNA expression data, we identified distinct markers to delineate monocytes from conventional DC2 (cDC2s). Using CD88 and CD89 for monocytes and HLA-DQ and FcΔRIα for cDC2s allowed for their specific identification in blood and tissues. We also showed that cDC2s could be subdivided into phenotypically and functionally distinct subsets based on CD5, CD163, and CD14 expression, including a distinct subset of circulating inflammatory CD5−CD163+CD14+ cells related to previously defined DC3s. These inflammatory DC3s were expanded in systemic lupus erythematosus patients and correlated with disease activity. These findings further unravel the heterogeneity of DC subpopulations in health and disease and may pave the way for the identification of specific DC subset-targeting therapies. Using high-dimensional protein and RNA single-cell analyses, Dutertre et al. analyze human dendritic cell and monocyte subsets and identify markers that delineate them and unravel their heterogeneity. They also reveal the presence of inflammatory CD14+ DC3s, a subset of cDC2s, that correlate with disease progression and may be functionally involved in systemic lupus erythematosus immunopathology. © 2019 Elsevier Inc

    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

    No full text
    These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

    No full text
    These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

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    These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

    Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

    No full text
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