DynaST-seq: A Transcriptome-wide Spatio-temporal Approach for Profiling Gene Expression Dynamics in Tissues

Understanding the molecular mechanisms of spatio-temporal gene expression is crucial for elucidating the dynamic processes that maintain tissue integrity, regulate cellular states, and drive biological responses. Despite recent advances in spatial transcriptomics, most approaches lack temporal resolution, limiting insights into dynamic gene expression. Here, we present DynaST-seq, an advanced spatio-temporal transcriptomics technology that integrates metabolic RNA labeling with spatial transcriptomics, enabling high-resolution, transcriptome-wide profiling of RNA dynamics across space and time. The high-resolution capabilities of DynaST-seq reveal finer tissue structures, such as vasculature, and provide a detailed understanding of cellular composition and RNA dynamics at the single-cell level. With its high sensitivity to newly synthesized RNA, DynaST-seq facilitates early detection of cellular responses to injury, offering detailed insights into processes such as oxidative stress, mitochondrial dysfunction, lipid dysmetabolism, and inflammatory responses during acute kidney injury (AKI). Our analysis identified rapidly responding transcription factors regulating AKI-related biological processes and uncovered enhanced interactions in regions of elevated RNA metabolic activity. This approach offers novel insights into tissue architecture, cellular behavior, and the regulatory networks underlying dynamic biological processes, holding a great promise for a wide range of biomedical applications. As a control, mouse tissues were not labled by 4sU, and analyzed by DynasT-seq. In the experimental group, live mice were labeled by injection, and tissue was collected for DynasT-seq analysis. Tissues from ischemia-reperfusion-treated mice were injection-labeled and analyzed by DynasT-seq.