Pixel-seqV2 Enables Multi-Scale Spatial Transcriptomic Analysis of Tissue Architecture and Kidney Aging

Abstract

Understanding how molecular programs are organized within intact tissues remainsa central challenge in biology. Conventional transcriptomics provides comprehensive molecular information but loses spatial context, whereas imaging preserves tissue architecture but lacks genome-wide molecular resolution. Spatial transcriptomics seeks to bridge this gap; however, existing platforms are constrained by trade-offs among spatial resolution, molecular sensitivity, scalability, and reproducibility. This dissertation presents the development and application of Pixel-seqV2, a scalable, sequencing-based spatial transcriptomics platform designed to enable high- density molecular capture across large tissue areas while preserving near-histological spatial fidelity. Pixel-seqV2 employs patterned flowcell–derived polony gels and stamping-based, substrate replication to achieve reproducible fabrication, tunable probe density, and continuous spatial sampling at micron-scale resolution. Systematic benchmarking demonstrates improved transcript capture efficiency, reduced lateral diffusion, and accurate recovery of RNA organization. Together with a factor-aware, Malat1-guided segmentation framework, these advances enable robust reconstruction of single-cell transcriptomes directly from sequencing-derived spatial data. Using the mouse kidney as a model system, this work illustrates how dense spatial transcriptomic measurements enable biological reasoning across multiple spatial scales. Tissue-wide analyses reconstruct nephron architecture and corticomedullary organization with near-histological clarity. At sub-glomerular resolution, Pixel-seqV2 resolves the internal organization of glomeruli and spatial relationships among interacting vascular and epithelial cell populations. Within anatomically continuous proximal tubules, localized transcriptional micro-niches characterized by Pigr- associated immune-transport programs reveal functional specialization beyond classical nephron segment boundaries. 3 Applying these approaches to aging kidneys reveals that molecular aging is not uniformly distributed across tissue but instead manifests as spatial niche remodeling. Aging is associated with coordinated loss of epithelial metabolic programs, emergence of immune-enriched cortical micro-environments, and heterogeneous decline in glomerular functional states across kidneys collected from multiple mice. These findings support a model in which tissue aging reflects reorganization of spatially localized cellular interactions rather than diffuse molecular deterioration. Together, this dissertation demonstrates that advances in spatial transcriptomic technology enable a transition from spatial measurement toward spatial reasoning. By integrating platform development, computational analysis, and biological application, Pixel-seqV2 establishes a framework for studying how complex tissues organize function, respond to stress, and remodel during aging.