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Abstract: TH-OR42

Spatial Transcriptomics (ST): Integrating Molecular Profiles with Histomorphology in Kidney Tissue Sections

Session Information

Category: Pathology and Lab Medicine

  • 1601 Pathology and Lab Medicine: Basic

Authors

  • Raghubar, Arti M., The University of Queensland, Saint Lucia, Queensland, Australia
  • Pham, Duy Truong, The University of Queensland, Saint Lucia, Queensland, Australia
  • Tan, Xiao, The University of Queensland, Saint Lucia, Queensland, Australia
  • Grice, Laura F., The University of Queensland, Saint Lucia, Queensland, Australia
  • Lam, Pui Yeng, The University of Queensland, Saint Lucia, Queensland, Australia
  • Crawford, Joanna, The University of Queensland, Saint Lucia, Queensland, Australia
  • Andersen, Stacey, The University of Queensland, Saint Lucia, Queensland, Australia
  • Yoon, Sohye, The University of Queensland, Saint Lucia, Queensland, Australia
  • Holland, Samuel Edward, The University of Queensland, Saint Lucia, Queensland, Australia
  • Francis, Leo, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
  • Combes, Alexander N., Monash University Monash Biomedicine Discovery Institute, Clayton, Victoria, Australia
  • Kassianos, Andrew J., Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
  • Healy, Helen G., Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
  • Nguyen, Quan, The University of Queensland Institute for Molecular Bioscience, Saint Lucia, Queensland, Australia
  • Mallett, Andrew John, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
Background

Advances in sequencing methods have increased available molecular information on dissociated cells and tissues. Spatially linking this molecular information with histomorphology is needed to understand a complex organ like the kidney, in both health and disease.

Methods

Here we used the commercially available 10x Genomics ST platform to investigate the spatially resolved transcriptome expressions in fetal (n=2), adult male (n=3) and female (n=3) mouse frozen kidney and a healthy human cortical frozen kidney tissue sections. We utilised Space Ranger (10x Genomics), Seurat and stLearn analysis pipelines to explore the spatial transcriptome expression within the kidney tissue sections. Furthermore, we confirmed the robustness of our ST data against matched publicly available mouse and human kidney scRNA-seq data.

Results

We identified a unique transcriptome plasticity in fetal and adult mouse kidneys, and healthy human cortical kidney tissue. Further dimensional reduction identified transcriptome clusters which correlated with distinct developing kidney structures in fetal mouse kidney tissue, functional cortical and medulla regions in adult mouse kidney tissue, and scarred and non-scarred regions in human cortical kidney tissue.

Conclusion

ST is a non-dissociative sequencing and imaging method which allows molecular profiles to be integrated with histomorphology of frozen kidney tissue sections. This provides a novel opportunity to inform physiological and non-physiological conditions at the cell-cell, nephron and tissue levels.

ST provides transcriptome expression within intact kideny tissue sections. (A) H&E stained human cortical kidney tissue with scarred and non-scarred regions. (B) The same human cortical kidney tissue with the transcript capture spots coloured by clustering using t-SNE projection demonstrates distinct transcriptome expression in scarred and non-scarred regions.

Funding

  • Government Support - Non-U.S.