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Updated: Aug 28, 2025
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A Modified Precipitation Method to Isolate Urinary Exosomes
Published on: January 16, 2015
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Identifying stable reference genes in polyethene glycol precipitated urinary extracellular vesicles for RT-qPCR-based
Anula Divyash Singh1, Sreekanth Patnam1, Rajeswari Koyyada2
1Apollo Hospitals Educational and Research Foundation (AHERF), Hyderabad, India; Department of Biomedical Engineering, Indian Institute of Technology Hyderabad (IITH), Kandi, Hyderabad, India.
Transplant Immunology
|September 19, 2022
Summary
This study identifies Beta-2-Microglobulin (B2M) and ribosomal-protein-L13a (RPL13A) as stable reference genes for gene expression analysis in urinary extracellular vesicles (UEVs). These validated reference genes are crucial for accurate biomarker discovery in renal graft dysfunction.
Area of Science:
- Biochemistry
- Molecular Biology
- Genomics
Background:
- Urinary extracellular vesicles (UEVs) contain RNA and are promising sources for gene expression biomarkers.
- Quantitative polymerase chain reaction (qPCR) is a key technique for gene expression analysis.
- Stable reference genes (RGs) are essential for normalizing qPCR data but are lacking for UEVs.
Purpose of the Study:
- To identify and validate stable reference genes for accurate gene expression analysis in urinary extracellular vesicles.
- To establish reliable internal controls for normalizing RNA quantification in UEVs.
Main Methods:
- UEVs were isolated from urine using Polyethylene glycol (PEG6K) precipitation.
- Five candidate RGs (B2M, RPL13A, PPIA, HMBS, GAPDH) were quantified using qPCR.
- RG stability was assessed using RefFinder and validated by analyzing renal graft dysfunction markers.
Main Results:
- UEV isolation yielded vesicles of 30-100 nm size, confirmed by electron microscopy and nanoparticle tracking.
- Beta-2-Microglobulin (B2M) and ribosomal-protein-L13a (RPL13A) were identified as the most stable RGs.
- B2M and RPL13A demonstrated efficiency in normalizing gene expression for renal graft dysfunction biomarkers.
Conclusions:
- B2M and RPL13A are validated as optimal reference genes for mRNA quantification in UEVs.
- These findings provide essential tools for biomarker discovery in renal graft dysfunction using UEVs.
