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Abstract: TH-OR44

High Resolution Spatially Resolved Transcriptomic Atlas of Kidney Injury and Repair With Direct RNA Hybridization-Based In Situ Sequencing

Session Information

Category: Acute Kidney Injury

  • 103 AKI: Mechanisms

Authors

  • Wu, Haojia, Division of Nephrology, Department of Medicine, Washington University in St. Louis, St Louis, Missouri, United States
  • Dixon, Eryn E., Division of Nephrology, Department of Medicine, Washington University in St. Louis, St Louis, Missouri, United States
  • Guo, Juanru, Division of Nephrology, Department of Medicine, Washington University in St. Louis, St Louis, Missouri, United States
  • Chitnis, Debashish, 10X Genomics, Pleasanton, California, United States
  • Niesnerova, Anezka, 10X Genomics, Pleasanton, California, United States
  • Xu, Hao, 10X Genomics, Pleasanton, California, United States
  • Rouault, Morgane, 10X Genomics, Pleasanton, California, United States
  • Humphreys, Benjamin D., Division of Nephrology, Department of Medicine, Washington University in St. Louis, St Louis, Missouri, United States

Group or Team Name

  • The Humphreys Lab
Background

Understanding how different kidney cell types contribute to acute kidney injury (AKI) requires knowledge of their spatial organization and connectivity, information that is lost in single cell techniques that rely on cell dissociation. Recent advances in spatial transcriptomic technologies enable visualization of multiplexed transcripts at cellular resolution.

Methods

We performed highly multiplexed direct RNA hybridization based in situ sequencing (dRNA-HybISS) (CARTANA, part of 10X Genomics) on the mouse kidneys from sham, 4h, 12h, 2d, and 6w after bilateral ischemia–reperfusion injury (IRI).

Results

We achieved sub-cellular transcript resolution and were able to map cell type specific markers precisely to their respective cell types (Fig 1). As expected, spatial expression of the injury marker Havcr1 was confined to the PT-S3 segment at 4h, 12h and 2d, and was absent in sham and 6w. We segmented ~400,000 cells from all time points of IRI. Unsupervised clustering revealed 10 major kidney cell types including rare cell types such as podocytes and JGA cells. We were able to reconstruct glomerular cell type organization with podocyte, EC and JGA. We revealed dynamic changes in spatial distribution of immune cell subsets across IRI time course. For example, Cd14+ monocytes were increased in early time points of IRI whereas the Ptprc+ macrophages accumulated only in later time point. Integration with snRNA-seq data increased resolution of our spatial map to 26 kidney cell types, including different PT injury states. We also compare these results to Visium analysis of the same time course, revealing that dRNA-HybISS provided much higher cell resolution including classification of individual rare cell types.

Conclusion

dRNA-HybISS enables in situ identification and spatial mapping of cell types in the kidney. When applying this technique to IRI, we reveal the dynamics of immune cell migration both in time and region during kidney injury and repair.

Funding

  • NIDDK Support