Sorting and packaging of RNA into extracellular vesicles shape intracellular transcript levels

Area of Science:

• Molecular Biology
• Cell Biology
• Genomics

Background:

• Extracellular vesicles (EVs) mediate intercellular communication by transferring RNA, including mRNA and long noncoding RNA (lncRNA).
• While short RNAs in EVs have been extensively studied, the properties and functions of longer RNA transcripts remain less explored.
• The impact of EV export on the transcriptome of the exporting cells has not been thoroughly investigated.

Purpose of the Study:

• To comprehensively analyze mRNA and lncRNA transcripts within endothelial EVs under various conditions.
• To investigate the characteristics and sorting mechanisms of long RNA transcripts enriched in EVs.
• To determine the influence of EV export on the cellular transcriptome.

Main Methods:

• Global analysis of mRNA and lncRNA transcripts in endothelial EVs and exporting cells.
• Characterization of RNA stability-related sequence and structure features.
• Investigation of RNA-binding protein involvement (e.g., HNRNPA2B1) in RNA sorting.
• Assessment of cellular transcriptome changes following EV secretion inhibition.

Main Results:

• EV-enriched long RNA transcripts exhibit distinct stability features, including shorter length and higher exon density.
• HNRNPA2B1 binding motifs are enriched in EV-specific long RNAs, suggesting its role in sorting.
• EV export significantly alters the abundance of cellular mRNA and lncRNA transcripts, with inverse correlations observed.
• Inhibition of EV secretion leads to increased intracellular levels of highly exported transcripts.
• Different EV secretion inhibitors differentially affect the cellular transcriptome, indicating diverse EV subtypes.

Conclusions:

• EV export actively shapes the transcriptome of the exporting cells.
• RNA sorting into EVs is a critical mechanism for regulating cellular RNA homeostasis.
• This study proposes a new paradigm where EV packaging contributes to cellular long RNA abundance profiles.