Single-cell analysis uncovers fibroblast heterogeneity and criteria for fibroblast and mural cell identification and discrimination
Single-cell analysis uncovers fibroblast heterogeneity and criteria for fibroblast and mural cell identification and discrimination
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单细胞分析揭示成纤维细胞异质性以及成纤维细胞和壁细胞识别和区分的标准
DOI：
10.1038/s41467-020-17740-1
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发表时间：
2020-08-07
影响因子：
16.6
通讯作者：
Betsholtz, Christer
中科院分区：
文献类型：
--
作者：
Muhl, Lars;Genove, Guillem;Betsholtz, Christer
在成年脊椎动物中，许多重要的细胞类型都有间充质起源，包括成纤维细胞和血管壁细胞。尽管它们在生物学上的重要性是毋庸置疑的，但器官内和器官之间间充质细胞的异质性水平虽然得到了认可，但尚未被详细分析。在这里，我们比较了成纤维细胞和血管壁细胞在四个小鼠肌肉器官中的单细胞转录图谱：心脏、骨骼肌、肠和膀胱。我们揭示了区分成纤维细胞和壁细胞的基因表达特征，并为细胞亚型鉴定提供了分子特征。我们观察到成纤维细胞在器官间和器官内的显著异质性，主要反映了细胞外基质成分表达的差异。成纤维细胞亚型定位于离散的解剖位置，为生理功能和调节信号通路提供了新的预测(S)。我们的数据揭示了定义不清的细胞类别的多样性，并为更好地理解它们在生理和病理过程中的作用提供了基础。定义和区分成纤维细胞和血管壁细胞一直是具有挑战性的。在这里，使用单细胞RNA测序和组织成像，作者提供了细胞类型分类的分子基础，并揭示了这些细胞类型的器官间和器官内多样性。
Many important cell types in adult vertebrates have a mesenchymal origin, including fibroblasts and vascular mural cells. Although their biological importance is undisputed, the level of mesenchymal cell heterogeneity within and between organs, while appreciated, has not been analyzed in detail. Here, we compare single-cell transcriptional profiles of fibroblasts and vascular mural cells across four murine muscular organs: heart, skeletal muscle, intestine and bladder. We reveal gene expression signatures that demarcate fibroblasts from mural cells and provide molecular signatures for cell subtype identification. We observe striking inter- and intra-organ heterogeneity amongst the fibroblasts, primarily reflecting differences in the expression of extracellular matrix components. Fibroblast subtypes localize to discrete anatomical positions offering novel predictions about physiological function(s) and regulatory signaling circuits. Our data shed new light on the diversity of poorly defined classes of cells and provide a foundation for improved understanding of their roles in physiological and pathological processes. To define and distinguish fibroblasts from vascular mural cells have remained challenging. Here, using single-cell RNA sequencing and tissue imaging, the authors provide a molecular basis for cell type classification and reveal inter- and intra-organ diversity of these cell types.