Spatial transcriptomics and the kidney

Abstract

Purpose of review: The application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed.

Recent findings: Spatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets.

Summary: Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.

Figure 1:. Cell type mapping in spatial transcriptomics.

A) H+E image with a glomerulus and a transition from the distal tubule (DCT) into a collecting duct (CD). B) Podocin (NPHS2) is expressed in the glomerulus. The thiazide sensitive sodium chloride cotransporter (SLC12A3) expression decreases from right to left as the DCT transitions to CD. C) Schematic indicating that transfer scores are calculated for >100 snRNAseq clusters based on all genes expressed and then mapped onto the spatial transcriptomics sample in Seurat version 3, deconvoluting the proportion of expression in each spot corresponding to a snRNAseq cluster. D) Glomerular spots contain signature from podocytes (POD) and glomerular endothelial cells (EC-GC). Damaged POD (dPOD = cell state) signature is also seen. From right to left, a gradual transition is seen from DCT and connecting tubule (CNT) signatures to CD intercalated (MIC-A) and principal cell (tPC-IC) signatures.