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

Overview

Journal Semin Nephrol

Specialty Nephrology

Date 2018 Jan 3

PMID 29291760

Citations 25

Authors

Andrew F Malone

Haojia Wu

Benjamin D Humphreys

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

The cellular landscape of the normal kidney allograft: Main players balancing the alloimmune response.

McDaniels J, Shetty A, Rousselle T, Bardhi E, Maluf D, Mas V Front Transplant. 2024; 1:988238.

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Single-cell RNA sequencing and kidney organoid differentiation.

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Single-cell transcriptomics: A new tool for studying diabetic kidney disease.

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Detection of infiltrating fibroblasts by single-cell transcriptomics in human kidney allografts.

Suryawanshi H, Yang H, Lubetzky M, Morozov P, Lagman M, Thareja G PLoS One. 2022; 17(6):e0267704.

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