Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart

Summary Resilience to cardiac stress is essential for health, yet the relationship between cardiomyocyte (CM) stress response and local microenvironment remains unclear. Here, we combined MERFISH spatial transcriptome profiling with Cellouette , an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload. Highlights Cellouette provides accurate segmentation for single-cell spatial transcriptomics in cardiac tissue. Pressure overload creates spatial gradients of cardiomyocyte pro-fibrotic states. Cardiomyocyte pro-fibrotic progression is linked to changes in local cell composition and gene expression. Transcriptional states of non-muscle cells predict metabolic state of adjacent cardiomyocytes.