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Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

ABSTRACT: 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.

SUBMITTER: Guilliams M

PROVIDER: S-EPMC5040826 | biostudies-other | 2016 Sep

REPOSITORIES: biostudies-other

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Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

Guilliams Martin M Dutertre Charles-Antoine CA Scott Charlotte L CL McGovern Naomi N Sichien Dorine D Chakarov Svetoslav S Van Gassen Sofie S Chen Jinmiao J Poidinger Michael M De Prijck Sofie S Tavernier Simon J SJ Low Ivy I Irac Sergio Erdal SE Mattar Citra Nurfarah CN Sumatoh Hermi Rizal HR Low Gillian Hui Ling GHL Chung Tam John Kit TJK Chan Dedrick Kok Hong DKH Tan Ker Kan KK Hon Tony Lim Kiat TLK Fossum Even E Bogen Bjarne B Choolani Mahesh M Chan Jerry Kok Yen JKY Larbi Anis A Luche Hervé H Henri Sandrine S Saeys Yvan Y Newell Evan William EW Lambrecht Bart N BN Malissen Bernard B Ginhoux Florent F

Immunity 20160913 3

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 ...[more]

PMID: 27637149

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Project description:BackgroundDetailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.MethodsMultiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq.ResultsUpon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~?30 arthroplasty and ~?20 biopsy samples yielded a consensus digestion protocol using 100 ?g/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.ConclusionsWe have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

Dataset Information

Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

Publications

Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

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