Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species
By M. Guilliams, Charles-Antoine Dutertre, Charlotte L. Scott, N. McGovern, D. Sichien, S. Chakarov, S. van Gassen, Jinmiao Chen, Michael Poidinger, Sofie De Prijck and 22 more. Immunity, 2016
752 citations recorded by the source corpus.
Summary Dendritic cells (DCs) are professional antigen-presenting cells that hold great therapeutic potential. Multiple DC subsets have been described, and it remains challenging to align them across tissues and species to analyze their function in the absence of macrophage contamination. Here, we provide and validate a universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues. The use of a minimal set of lineage-imprinted markers was sufficient to subdivide DCs into conventional type 1 (cDC1s), conventional type 2 (cDC2s), and plasmacytoid DCs (pDCs) across tissues and species. This way, a large number of additional markers can still be used to further characterize the heterogeneity of DCs across tissues and during inflammation. This framework represents the way forward to a universal, high-throughput, and standardized analysis of DC populations from mutant mice and human patients.
Subfields: Immunology
View Paper: https://www.semanticscholar.org/paper/5ed9dc53c27698972953816980ed44ccc440d081
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In Immunology
Citations in the corpus
- High‐Dimensional Single‐Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease (2018, neutral): “Both cDC2s and cDC1s expanded to a similar extent with Flt3L treatment (Figure 4H) and moreover cDC1s were IRF8IRF4 and cDC2s were IRF8 IRF4 (Figure 4I), as previously predicted (Guilliams et al., 2016).”
- Single cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species (2019, result): “To assess hDC1–3, we compared their gene expression profiles to those of bulk-sorted classical DCs, which comprise cDC1 (defined as XCR1+ CADM1+ by flow cytometry) and cDC2 (CD1A+ CD172A+) (Eisenbarth, 2019; Guilliams et al., 2016). cDC1 are efficient antigen cross-presenters to CD8+ T cells, wherea”
- OMIP-044: 28-color immunophenotyping of the human dendritic cell compartment (2018, background): “However, only recently studies have focused on the myeloid populations present in human nonlymphoid tissues, showing similarities as well as functional differences to the murine system (6).”
- Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation (2019, background): “Although CD64/Fcgr1 is often solely expressed by macrophages and monocytes (22), cDC2 can also express CD64 in certain tissues (38) or under specific inflammatory conditions (13).”
- Self-renewing resident cardiac macrophages limit adverse remodeling following myocardial infarction (2018, neutral): “…presenting cell (APC) cluster (cluster 6) that expressed some macrophage and DC genes (Adgre1, C1qc, C1qa, MHC-II genes, Itgax) but not lineage defining genes (Fcgr1, Maf, Mertk, Dpp4, Flt3, Zbtb46) 22, 23 ; nor did this cluster have high expression of pDC genes (Siglech, Bst2, Ly6c2, Irf8) (Fig.”
- Single-Cell Analysis of Crohn’s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy (2019, result): “We identified two clusters of conventional DCs, including CD1c+/DC2 (expressing CD1C, CD1D, CLEC10A, FCER1A, FCGR2B) and CD141+/DC1 (expressing BATF3, CLEC9A, XCR1, CADM1, CLNK, C1orf54) (Figure 2C), consistent with high-resolution single-cell analyses in recent studies (Guilliams et al., 2016; See ”