Stem Cell Transplantation Program, Division of Pediatric Hematology and Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA, 02115, USA.
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA.
Nat Commun. 2018 Mar 1;9(1):892. doi: 10.1038/s41467-018-03214-y.
A better understanding of the cell-fate transitions that occur in complex cellular ecosystems in normal development and disease could inform cell engineering efforts and lead to improved therapies. However, a major challenge is to simultaneously identify new cell states, and their transitions, to elucidate the gene expression dynamics governing cell-type diversification. Here, we present CellRouter, a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data. We demonstrate its versatility by applying CellRouter to single-cell RNA sequencing data sets to reconstruct cell-state transition trajectories during hematopoietic stem and progenitor cell (HSPC) differentiation to the erythroid, myeloid and lymphoid lineages, as well as during re-specification of cell identity by cellular reprogramming of monocytes and B-cells to HSPCs. CellRouter opens previously undescribed paths for in-depth characterization of complex cellular ecosystems and establishment of enhanced cell engineering approaches.
更好地理解正常发育和疾病过程中复杂细胞生态系统中发生的细胞命运转变,可以为细胞工程提供信息,并有助于改善治疗方法。然而,一个主要的挑战是同时识别新的细胞状态及其转变,以阐明调控细胞类型多样化的基因表达动态。在这里,我们提出了 CellRouter,这是一个多方面的单细胞分析平台,通过使用流网络来探索多维单细胞组学数据的亚群结构,从而识别复杂的细胞状态转变轨迹。我们通过将 CellRouter 应用于单细胞 RNA 测序数据集,在造血干细胞和祖细胞 (HSPC) 向红细胞、髓系和淋巴系分化过程中以及通过单核细胞和 B 细胞的细胞重编程向 HSPC 重编程来重建细胞状态转变轨迹,展示了其多功能性。CellRouter 为深入描述复杂细胞生态系统和建立增强的细胞工程方法开辟了以前未知的途径。