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从冷冻保存的滑膜组织中分离的细胞的高维分析方法。

Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue.

机构信息

Hospital for Special Surgery, New York, NY, 10021, USA.

Weill Cornell Medical College, New York, NY, 10065, USA.

出版信息

Arthritis Res Ther. 2018 Jul 11;20(1):139. doi: 10.1186/s13075-018-1631-y.


DOI:10.1186/s13075-018-1631-y
PMID:29996944
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6042350/
Abstract

BACKGROUND: Detailed 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. METHODS: Multiple 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. RESULTS: Upon 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 μg/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. CONCLUSIONS: We 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.

摘要

背景:对类风湿关节炎 (RA) 滑膜细胞进行详细的分子分析,有望鉴定出驱动组织病理学和关节损伤的细胞表型。加速药物研发合作组织 RA/SLE 网络旨在通过对多个靶组织中的细胞进行多维分析,来剖析自身免疫病理学。在能够有效地比较患者样本中单细胞水平的细胞表型之前,需要开发稳健的标准化方案。

方法:多个临床地点将冷冻保存的滑膜组织碎片用 10%二甲基亚砜溶液收集,用于关节置换和滑膜活检。优化了机械和酶解参数,以用于提取活细胞,并保存用于细胞分选和液质联用分析的细胞表面蛋白,以及用于 RNA 测序 (RNA-seq) 的重复性。冷冻保存的滑膜样本在一个中央处理站点,使用定制设计和验证的 35 标志物液质联用分析面板进行集体分析。同时,每个样本都通过流式细胞分选分离为成纤维细胞、T 细胞、B 细胞和巨噬细胞悬浮液,用于批量群体 RNA-seq 和基于平板的单细胞 CEL-Seq2 RNA-seq。

结果:在解离后,冷冻保存的滑膜组织碎片产生了高频率的活细胞,与立即进行处理的样本相当。通过对六个临床采集地点的 30 个关节置换和 20 个活检样本进行的滑膜组织解离优化,得出了一种共识消化方案,使用 100μg/ml 的 Liberase™TL 酶制剂。该方案产生了具有保留的表面标记物和最小 RNA-seq 转录组变异性的免疫和基质细胞谱系。对冷冻保存滑膜细胞的液质联用分析可区分不同的成纤维细胞表型、记忆 B 细胞和分泌抗体细胞的不同群体,以及多个 CD4 和 CD8 T 细胞激活状态。对分选细胞群体的批量 RNA-seq 证明了滑膜淋巴细胞、成纤维细胞和巨噬细胞的稳健分离。单细胞 RNA-seq 产生了超过 1000 个基因/细胞的转录组,包括鉴定出的特征谱系标记物的转录本。

结论:我们已经建立了一种从冷冻保存的滑膜组织中获取具有完整转录组和细胞表面表型的活细胞的稳健方案。开发了一种集中式管道,用于对协作网络中收集的多个滑膜组织样本进行多种高维分析。对来自大型患者队列的此类数据集进行综合分析,可能有助于确定 RA 病理学中的分子异质性,并鉴定新的治疗靶点和生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/f7a584b79a07/13075_2018_1631_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/900301d6f12a/13075_2018_1631_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/356bf86d239c/13075_2018_1631_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/fea9d79b014b/13075_2018_1631_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/55fda536836f/13075_2018_1631_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/1238c0039d72/13075_2018_1631_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/f7a584b79a07/13075_2018_1631_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/900301d6f12a/13075_2018_1631_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/356bf86d239c/13075_2018_1631_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/fea9d79b014b/13075_2018_1631_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/55fda536836f/13075_2018_1631_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/1238c0039d72/13075_2018_1631_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aab/6042350/f7a584b79a07/13075_2018_1631_Fig6_HTML.jpg

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