Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 121; no. 32; p. e2406842121
• Main Authors: Cheng, Yu-Chen, Zhang, Yun, Tripathi, Shubham, Harshavardhan, B. V., Jolly, Mohit Kumar, Schiebinger, Geoffrey, Levine, Herbert, McDonald, Thomas O., Michor, Franziska
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 06.08.2024
• Subjects: Biological Sciences; Cell cycle; Cell lineage; Cell Lineage - genetics; Cell proliferation; CRISPR; Enhancer of Zeste Homolog 2 Protein - genetics; Enhancer of Zeste Homolog 2 Protein - metabolism; Epithelial-Mesenchymal Transition - genetics; Gene expression; Gene sequencing; Genes; Humans; Physical Sciences; RNA transport; Single-Cell Analysis - methods; Time measurement; Trajectory analysis; Trajectory measurement; Trajectory optimization; Transforming Growth Factor beta - metabolism; Up-regulation; EMT; scRNA-seq; cell fate
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.2406842121

Exploring the complexity of the epithelial-to-mesenchymal transition (EMT) unveils a diversity of potential cell fates; however, the exact timing and mechanisms by which early cell states diverge into distinct EMT trajectories remain unclear. Studying these EMT trajectories through single-cell RNA sequencing is challenging due to the necessity of sacrificing cells for each measurement. In this study, we employed optimal-transport analysis to reconstruct the past trajectories of different cell fates during TGF-beta-induced EMT in the MCF10A cell line. Our analysis revealed three distinct trajectories leading to low EMT, partial EMT, and high EMT states. Cells along the partial EMT trajectory showed substantial variations in the EMT signature and exhibited pronounced stemness. Throughout this EMT trajectory, we observed a consistent downregulation of the EED and EZH2 genes. This finding was validated by recent inhibitor screens of EMT regulators and CRISPR screen studies. Moreover, we applied our analysis of early-phase differential gene expression to gene sets associated with stemness and proliferation, pinpointing ITGB4 , LAMA3 , and LAMB3 as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that CENPF , CKS1B , and MKI67 showed significant upregulation in the high EMT trajectory. While the first group of genes aligns with findings from previous studies, our work uniquely pinpoints the precise timing of these upregulations. Finally, the identification of the latter group of genes sheds light on potential cell cycle targets for modulating EMT trajectories.