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, 38 (1), 31-39

Bringing Renal Biopsy Interpretation Into the Molecular Age With Single-Cell RNA Sequencing


Bringing Renal Biopsy Interpretation Into the Molecular Age With Single-Cell RNA Sequencing

Andrew F Malone et al. Semin Nephrol.


The renal biopsy provides critical diagnostic and prognostic information to clinicians including cases of acute kidney injury, chronic kidney disease, and allograft dysfunction. Today, biopsy specimens are read using a combination of light microscopy, electron microscopy, and indirect immunofluorescence, with a limited number of antibodies. These techniques all were perfected decades ago with only incremental changes since then. By contrast, recent advances in single-cell genomics are transforming scientists' ability to characterize cells. Rather than measure the expression of several genes at a time by immunofluorescence, it now is possible to measure the expression of thousands of genes in thousands of single cells simultaneously. Here, we argue that the development of single-cell RNA sequencing offers an opportunity to describe human kidney disease comprehensively at a cellular level. It is particularly well suited for the analysis of immune cells, which are characterized by multiple subtypes and changing functions depending on their environment. In this review, we summarize the development of single-cell RNA sequencing methodologies. We discuss how these approaches are being applied in other organs, and the potential for this powerful technology to transform our understanding of kidney disease once applied to the renal biopsy.

Keywords: RNA sequencing; biopsy; informatics; microfluidics.

Conflict of interest statement

Conflict of Interest: All authors declare no conflict of interest.


Figure 1
Figure 1. Applying scRNA-seq to human kidney biopsy analysis
A kidney biopsy is first dissociated into a single cell suspension reflecting all cell types present in the biopsy. These cells are coencapsulated with lysis buffer and an oligo-dT containing primer. RNA is isolated through oligo-dT binding, and reverse transcribed (RT) with second strand synthesis into cDNA. This cDNA then can be amplified wither through PCR, or through in vitro transcription (IVT) followed by RT and second strand synthesis. Primers are then added to prepare the library for next generation sequencing. The sequencing data is analyzed to generate a digital count matrix reflecting the gene expression present in every cell from the biopsy. This can be analyzed in many different ways, one of them being cell clustering through dimensionality reduction. This groups cells by an unsupervised clustering approach which compares each cell’s transcriptome and clusters those that are similar. Cell types can then be classified by examining known marker gene expression in each cluster.
Figure 2
Figure 2. Unique Molecular Identifiers (UMI) to correct for amplification bias
Creation of a single cell cDNA library requires amplication of pictograms of cDNA by many orders of magnitude. This is accomplished either by PCR or by in vitro transcription. Either way, bias is introduced if some transcripts undergo preferential amplification. To correct for this, a unique molecular identifier (UMI, which is essentially an oligonucleotide barcode, is added to each cDNA during reverse transcription and before amplification. Once the library is sequenced, these UMIs enable sequencing reads to be assigned to individual transcript molecules. If there is more than one read with the same UMI that maps to the same gene, this represents amplification bias and is collapsed into a single read informatically.
Figure 3
Figure 3. Dissociation and cleanup prior to droplet encapsulation
Proteolytic dissociation of sold tissues such as kidney leads to the presence of many cell fragments and ambient RNA that must be removed prior to droplet encapsulation. This can be achieved by FACS purification, for example including propidium iodide (PI) which will bind to nucleic acids in cell fragments and dead cells. The PI-negative fraction is collected and subject to scRNA-seq. Alternatively, differential gradient separation can be used to separate whole cells from fragments because of their lower density. In either case, cell viability is assessed after the cleanup step (for example by Trypan blue exclusion) prior to droplet encapsulation.

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