Despite advances in technology for tissue characterization, the techniques that are used to analyse kidney biopsy samples have not changed substantially in the past 25 years. Now, Haojia Wu, Andrew Malone and colleagues have used single-cell RNA sequencing (scRNA-seq) to profile a kidney allograft biopsy sample from a patient with mixed T cell-mediated and antibody-mediated rejection (ABMR).

“We used a massively parallel microfluidic droplet technology called InDrops to perform scRNA-seq of the biopsy sample,” says Wu. “This approach allowed us to measure the expression of thousands of genes from thousands of individual cells.” In total, the researchers sequenced 4,487 cells and detected a mean of 1,481 transcripts from 827 genes per cell. They identified 16 different cell types in the allograft sample, including 4 types of tubular cells, various lymphocyte and leukocyte populations, 3 types of stromal cells, endothelial cells and a population of actively proliferating cells. A comparison of the epithelial transcriptome of the allograft with that of healthy adult kidney tissue showed downregulation of terminal differentiation markers and upregulation of pro-inflammatory genes in the allograft.

“We have defined the heterogeneity of cell types and cell states in an allograft biopsy at single-cell resolution,” says Malone. “Our study provides a proof-of-principle for what we believe may be a transformative advance in the way biopsies are read. For example, bulk-tissue resolution profiling has established that endothelial cells have critical roles in ABMR; our single-cell resolution profiling revealed that there are three different endothelial states in mixed rejection: a resting state, an angiogenic state and an Ig phagocytosis state.”

The researchers are now scaling up their scRNA-seq technique to enable the detection of rare cell types and finer distinctions among different cell subtypes. “The goal is to generate clinically useful data sets to improve diagnostic and prognostic accuracy, enable disease subphenotyping and accelerate adoption of molecular biopsy interpretation,” says Wu.