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Kidney Week

Abstract: PO0388

Spatially Resolved Transcriptomics Reveal Temporal Dynamics of Gene Expression Changes in a Model of Female AKI

Session Information

Category: Acute Kidney Injury

  • 103 AKI: Mechanisms

Authors

  • Dixon, Eryn E., Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Wu, Haojia, Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Wilson, Parker C., Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Muto, Yoshiharu, Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Humphreys, Benjamin D., Washington University in St Louis School of Medicine, St Louis, Missouri, United States
Background

Preclinical studies of acute kidney injury (AKI) have focused on male rodents leaving a substantial gap in our understanding of AKI in females. Single cell transcriptomic studies are remarkably powerful, but the loss of positional information with tissue dissociation handicaps our interpretation. Therefore, we applied the 10X Genomics spatial transcriptomic solution, Visium, to investigate interactions between cell types in their physiological orientation during injury.

Methods

We performed bilateral ischemia reperfusion injury (Bi-IRI) on female C57BL/6J mice. Kidneys were collected at acute and late injury timepoints. The efficacy of IRI cross-clamp was validated by transdermal GFR measurements using FITC-sinistrin. Sequencing libraries were created from flash frozen kidney tissues, sequenced by NovaSeq, and integrated with corresponding images using SpaceRanger.

Results

New analytic pipelines SPOTlight and Giotto, enriched with gene expression data from our previously published single cell RNA transcriptomic atlas of mouse injury, significantly enhanced the visualization and resolution of spatial data in our female Bi-IRI model. Spatial libraries detected 16,856 unique genes across all injury timepoints. Integration with scRNAseq increased resolution of specific underrepresented cell types, such as macrophages, T cells, and fibroblasts. Key visualization tools demonstrated changes in the temporal and spatial expression of differentiation markers, including Krt20 and Vim, after injury. Spatial interaction analyses of macrophages and T cell related genes, such as Lyn and Tmem30b, revealed dynamic cell type interaction changes in addition to specific interactions with a proinflammatory and pro-fibrotic proximal tubule injury-induced cell state. We prioritized cell-cell interactions based on physical proximity and validated these results by immunofluorescence. We curated an online data visualization tool to provide broad access of this dataset to the community.

Conclusion

We present the first comprehensive spatial transcriptomic atlas for a female mouse model of AKI along a time course after ischemic injury. We leveraged this spatial transcriptomic dataset to investigate cell type interaction changes, revealing previously unknown cellular dynamics of macrophages and T cells in the proximal tubule.

Funding

  • NIDDK Support