Identification of robust and abundant reference transcripts for EV mRNA cargo normalization.

Area of Science:

• Biotechnology
• Molecular Biology
• Nanomedicine

Background:

• Extracellular vesicles (EVs) show promise as disease biomarkers and therapeutic nanoparticles.
• Accurate quantification of EV cargo is hindered by a lack of standardized molecular reference standards.
• Heterogeneity of EV subtypes and cell sources complicates reliable identification.

Purpose of the Study:

• To identify and validate stable messenger RNA (mRNA) transcripts for use as reference genes in extracellular vesicle (EV) research.
• To establish molecular standards for accurate EV quantification and facilitate biomarker discovery.

Main Methods:

• RNA-sequencing of EVs from twelve cell sources using oligo-dT priming.
• RT-qPCR, deeper sequencing, and stability assessment (RefFinder) for candidate transcript validation.
• Gradient centrifugation and digital PCR for EV association and quantification confirmation.

Main Results:

• Identified 11 shared abundant transcripts; five (TMSB4X, ACTB, GAPDH, VIM, FTL) validated as stable reference candidates.
• Confirmed EV association and stability across different isolation methods and biofluids (including plasma).
• Demonstrated utility for normalizing variably expressed genes and comparing quantification methods.

Conclusions:

• Validated TMSB4X, ACTB, GAPDH, VIM, and FTL as reliable molecular reference standards for EV mRNA analysis.
• These reference genes are applicable across diverse EV subtypes and biofluids, aiding standardization.
• Findings support improved accuracy in EV biomarker studies and therapeutic development.