Edalat Sam G, Gerber Reto, Houtman Miranda, Lückgen Janine, Teixeira Rui Lourenço, Palacios Cisneros Maria Del Pilar, Pfanner Tamara, Kuret Tadeja, Ižanc Nadja, Micheroli Raphael, Polido-Pereira Joaquim, Saraiva Fernando, Lingam Swathi, Burki Kristina, Burja Blaž, Pauli Chantal, Rotar Žiga, Tomšič Matija, Čučnik Saša, Fonseca João Eurico, Distler Oliver, Calado Ângelo, Romão Vasco C, Ospelt Caroline, Sodin-Semrl Snežna, Robinson Mark D, Frank Bertoncelj Mojca
Center of Experimental Rheumatology, Department of Rheumatology, University Hospital Zurich and University of Zurich, 8952 Schlieren, Switzerland.
Department of Molecular Life Sciences and SIB, Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland.
iScience. 2024 Apr 10;27(6):109707. doi: 10.1016/j.isci.2024.109707. eCollection 2024 Jun 21.
In this study, we optimized the dissociation of synovial tissue biopsies for single-cell omics studies and created a single-cell atlas of human synovium in inflammatory arthritis. The optimized protocol allowed consistent isolation of highly viable cells from tiny fresh synovial biopsies, minimizing the synovial biopsy drop-out rate. The synovium scRNA-seq atlas contained over 100,000 unsorted synovial cells from 25 synovial tissues affected by inflammatory arthritis, including 16 structural, 11 lymphoid, and 15 myeloid cell clusters. This synovial cell map expanded the diversity of synovial cell types/states, detected synovial neutrophils, and broadened synovial endothelial cell classification. We revealed tissue-resident macrophage subsets with proposed matrix-sensing (FOLR2+COLEC12) and iron-recycling (LYVE1+SLC40A1+) activities and identified fibroblast subsets with proposed functions in cartilage breakdown (SOD2SAA1+SAA2+SDC4+) and extracellular matrix remodeling (SERPINE1+COL5A3+LOXL2+). Our study offers an efficient synovium dissociation method and a reference scRNA-seq resource, that advances the current understanding of synovial cell heterogeneity in inflammatory arthritis.
在本研究中，我们优化了用于单细胞组学研究的滑膜组织活检样本解离方法，并创建了炎症性关节炎中人类滑膜的单细胞图谱。优化后的方案能够从微小的新鲜滑膜活检样本中持续分离出高活性细胞，将滑膜活检样本的丢弃率降至最低。滑膜单细胞RNA测序图谱包含来自25个受炎症性关节炎影响的滑膜组织的超过10万个未分类滑膜细胞，包括16个结构细胞簇、11个淋巴细胞簇和15个髓细胞簇。该滑膜细胞图谱扩展了滑膜细胞类型/状态的多样性，检测到滑膜中性粒细胞，并拓宽了滑膜内皮细胞分类。我们揭示了具有假定的基质感知（FOLR2+COLEC12）和铁循环（LYVE1+SLC40A1+）活性的组织驻留巨噬细胞亚群，并鉴定了在软骨破坏（SOD2SAA1+SAA2+SDC4+）和细胞外基质重塑（SERPINE1+COL5A3+LOXL2+）中具有假定功能的成纤维细胞亚群。我们的研究提供了一种高效的滑膜解离方法和一个参考单细胞RNA测序资源，推动了目前对炎症性关节炎中滑膜细胞异质性的理解。
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