The glycosylation signature of human urinary extracellular vesicles
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Cells of virtually all organs and tissues are known to release large numbers of subcellular particles called extracellular vesicles (EVs) into bodily fluids such as blood and urine. There has been a growing interest in isolation of urine EVs (uEVs) as a source of diagnostic and prognostic tests for kidney disease. While the protein and nucleic acid composition of human uEVs has been extensively characterised, their content of carbohydrates (glycans) is less well studied. The overarching goal of this thesis was to define the normal surface glyan profile of human uEVs and determine whether it is altered in kidney diseases. Initially, an ultra-centrifugation (UC)-based method was shown to be superior to a centrifugal concentration method for isolating high-quality uEVs from healthy human urine. The resulting uEVs were then analysed for binding of carbohydrate-specific proteins (lectins) using two techniques – flow cytometry and lectin microarray (LM). It was shown that uEVs express a broad, complex array of different glycans on their surfaces. Next, a new method was developed to sub-divide uEVs into density-based fractions while eliminating contamination by non-vesicle protein. Using LM, electron microscopy and nanoparticle tracking, density-based uEV fractions were shown to vary in size and to have specific differences in surface glycosylation. The surface glycosylation profiles of uEV fractions from healthy adults were then compared to those from patients with the kidney condition glomerulonephritis (GN). It was found that mid- and high-density uEV fractions of GN patients were larger and had altered binding of five specific lectins. Novel contributions of the thesis include: (a) Methodologies for uEV isolation and analysis of EV glycosylation. (b) Detailed surface glyan profiles of healthy human uEVs and of density-based uEV sub-fractions. (c) Evidence for kidney disease-specific alterations to uEV surface glycan content that may be of value for future urine biomarker development.
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