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

TL;DR

This study identifies five mRNA transcripts that can be used as reliable reference genes for normalizing mRNA levels in extracellular vesicles, helping standardize EV research.

Contribution

The study identifies five consistently abundant and stable reference transcripts across diverse EV sources for normalization in EV mRNA analysis.

Findings

Eleven shared transcripts were identified among the top 50 most abundant in EVs from twelve cell sources.

Five transcripts (TMSB4X, ACTB, GAPDH, VIM, and FTL) were validated as stable reference genes using RT-qPCR and sequencing.

The reference transcripts were confirmed to associate with EVs and showed applicability in biomarker studies across multiple biofluids.

Abstract

Extracellular vesicles (EVs) have been investigated intensively because of their potential as biomarkers of disease and their versatility as bioengineered therapeutic nanoparticles. EVs carry diverse biomolecular cargo, but absolute quantification has been challenging due to a lack of established molecular standards. Reliable identification of these has proven difficult owing to a scarcity of standardized global data sets spanning the heterogeneity of EV subtypes and cell sources. To identify reference messenger RNA (mRNA) transcripts, we analyze oligo-dT primed RNA-sequencing data from EVs originating from twelve different cell sources isolated using differential centrifugation followed by ultrafiltration. We identify 11 transcripts that are shared amongst the 50 most abundant in EVs from all of these cell sources. Following RT-PCR and deeper sequencing analysis, five transcripts warranted further investigation as molecular standards: TMSB4X, ACTB, GAPDH, VIM, and FTL. As such, we subjected the RT-qPCR results from two independent oligo-dT cDNA synthesis methods to stability assessment using the RefFinder analysis tool, conducted a proof-of-concept normalization on the levels of the variably expressed gene RAB13 and compared quantification of engineered mRNA loading with that of digital PCR. We confirmed the EV association of reference transcripts with EVs by performing gradient centrifugation followed by RT-qPCR and full-length mRNA analysis. To judge the applicability of these genes as reference transcripts for biomarker studies, we performed RNA-sequencing on EVs isolated from plasma by differential ultracentrifugation, and four other minimally processed biofluids. These findings confirm the applicability of these genes as molecular standards for EV-mRNA analysis and will aid in the standardization of EV research by establishing molecular reference genes that can be employed in diverse contexts.

Figures