Unlocking the potential of extracellular vesicles in nephrology: what does MISEV2023 add?

Extracellular vesicles, small membrane-bound packages secreted by virtually all cells of the body, have become a focus of interest in nephrology over the recent years. After the first characterization of their proteomic and transcriptomic content, scientific attention shifted toward their potential as biomarkers for kidney diseases both as diagnostic and monitoring tools. More recently, researchers have begun exploring whether extracellular vesicles mediate intercellular signaling inside the nephron and between the kidney and other organs throughout the body.

ACE2 and TMPRSS2 in human kidney tissue and urine extracellular vesicles with age, sex, and COVID-19.

SARS-CoV-2 virus infects cells by engaging with ACE2 requiring protease TMPRSS2. ACE2 is highly expressed in kidneys. Predictors for severe disease are high age and male sex.

Urinary Extracellular Vesicles for Non-Invasive Quantification of Principal Cell Damage in Kidney Transplant Recipients.

The objective of the present study was to compare principal cell-specific aquaporin-2 (AQP2) abundances in urinary extracellular vesicles (uEVs) on the first postoperative day in deceased-donor kidney transplant recipients without and with acute kidney injury. We measured uEV markers (CD9 and CD63) and the abundances of proximal tubular sodium-glucose transporter 2, distal tubular sodium/chloride cotransporter, and principal cell-specific aquaporin-2 using Western blotting of urine. uEV-AQP2 levels were normalized to living donor controls.

Benchmarking transcriptome deconvolution methods for estimating tissue- and cell-type-specific extracellular vesicle abundances.

Extracellular vesicles (EVs) contain cell-derived lipids, proteins and RNAs; however, determining the tissue- and cell-type-specific EV abundances in body fluids remains a significant hurdle for our understanding of EV biology. While tissue- and cell-type-specific EV abundances can be estimated by matching the EV's transcriptome to a tissue's/cell type's expression signature using deconvolutional methods, a comparative assessment of deconvolution methods' performance on EV transcriptome data is currently lacking. We benchmarked 11 deconvolution methods using data from four cell lines and their EVs, in silico mixtures, 118 human plasma and 88 urine EVs.