Integrating Metabolic RNA Labeling-Based Time-Resolved Single-Cell RNA Sequencing with Spatial Transcriptomics for Spatiotemporal Transcriptomic Analysis.

Abstract

Metabolic RNA labeling-based time-resolved single-cell RNA sequencing (scRNA-seq) has provided unprecedented tools to dissect the temporal dynamics and the complex gene regulatory networks of gene expression. However, this technology fails to reveal the spatial organization of cells in tissues, which also regulates the gene expression by intercellular communication. Herein, it is demonstrated that integrating time-resolved scRNA-seq with spatial transcriptomics is a new paradigm for spatiotemporal analysis. Metabolic RNA labeling-based time-resolved Well-TEMP-seq is first applied to profile the transcriptional dynamics of glioblastoma (GBM) cells and discover two potential pathways of EZH2-mediated mesenchymal transition in GBM. With spatial transcriptomics, it is further revealed that the crosstalk between CCL2⁺ malignant cells and IL10⁺ tumor-associated macrophages in the tumor microenvironment through an EZH2-FOSL2-CCL2 axis contributes to the mesenchymal transition in GBM. These discoveries show the power of integrative spatiotemporal scRNA-seq to elucidate the complex gene regulatory mechanism and advance the understanding of cellular processes in disease.