Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Mol Syst Biol. 2022 Sep;18(9):e11080. doi: 10.15252/msb.202211080.
Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high-resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology-specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain.
组织架构的特征有望为我们带来对发育、细胞通讯和疾病的深入了解。针对空间转录组学 (ST) 数据,已经开发出了基于转录相似性的基于计算机的空间域检索方法。然而,具有这种假设的域检索方法在由多种细胞类型组成的复杂组织中无法工作。在细胞分辨率的 ST 方法中,这项任务变得特别具有挑战性。我们开发了 Vesalius,通过应用图像处理技术,从 ST 数据中解读组织解剖结构。Vesalius 独特地检测到由多个细胞类型组成的区域,并成功地在包括小鼠大脑、胚胎、肝脏和结肠在内的高分辨率 ST 数据中恢复了组织结构。利用这种组织架构,Vesalius 鉴定了与星形胶质细胞、中间神经元、少突胶质细胞和内嗅皮层细胞相关的特定组织形态和区域特定的基因表达变化。