Characterization of small RNA in human extracellular vesicles.

Extracellular vesicles (EVs), including exosomes and microvesicles, are membrane-bound particles released by virtually all cell types into the extracellular space. They mediate the horizontal transfer of their cargo molecules, enabling the movement of proteins, lipids, and nucleic acids between cells in a manner that bypasses classical signalling pathways. This mechanism allows EVs to modulate the behaviour of recipient cells across short or long distances and between different tissue types. Due to these properties EVs are attracting a lot of attention as tools for disease research.

The molecular complexity of EVs reflects this functional diversity. For example, surface proteomic analyses have identified over 1,200 distinct membrane proteins in human EVs with high confidence, including tetraspanins, integrins, adhesion molecules, and >80 cell-type–specific receptors^1,2. This rich surface composition not only influences EV targeting and uptake but also underscores the challenge of isolating well-defined EV populations.

The cargo composition of EVs is also very complex. Understanding the diversity and specificity of EV cargo is essential for advancing their application as biomarkers and therapeutic agents. This review outlines current knowledge about EV small RNA cargo in humans, emphasizing tissue-specific traits and quantitative data supported by recent literature³.

Small RNAs are among the most functionally relevant RNA species found in EV, acting as potent regulators of gene expression in recipient cells. While EVs contain a complex mix of RNA classes (including mRNA, tRNA fragments, lncRNA, YRNA and rRNA fragments), miRNAs constitute a major and well-characterized component of the small RNA cargo.

Small RNA diversity in human EVs

When characterizing small RNA content in human EV three specialized databases provide complementary insights, each with distinct strengths. EVmiRNA focuses exclusively on microRNA expression profiles in EVs, aggregating over 460 small RNA-seq datasets across 17 human diseases and tissues, and allowing users to explore tissue-specific and condition-specific miRNA abundance patterns with high resolution⁴.

In contrast, EVAtlas offers a broader scope, integrating data from over 2,000 RNA-seq samples across 24 biological conditions and multiple biofluids, and profiling not only miRNAs but also other non-coding RNA classes including piRNAs, YRNAs, tRNA fragments, and snoRNAs. This makes it particularly useful for exploring the full complexity of EV RNA cargo⁵.

While databases like EVmiRNA and EVAtlas catalog presence and abundance, EVPsort offers insight into how miRNAs are selectively sorted into EVs. EVPsort is based ondifferential expression analysis across ~500 paired datasets of parent cells and EV samples, to identify RNAs preferentially loaded into EVs. This enables researchers to investigate sorting mechanisms and functional targeting^6,7. Together, these databases provide a robust framework for interpreting EV small RNA content across biological contexts and for designing EV-based biomarker discovery studies in humans.

For researchers working in human blood exosomes there is an additional resource known as exoRBase, a repository of circRNA, lncRNA and mRNA derived from RNA-seq data analyses.

Table 1. Summary of small RNA diversity based on EVmiRNA, EVAtlas and EVPsort databases. Number of species detected assume deep sequencing (>25 M reads per library). Shallower studies detect lower number of species.

The picture emerging from these resources indicates that miRNAs is a major component of human EV. Reads mapping to miRNA account for most small RNA mapping reads in EVs, whereas rRNA fragments often dominate when analyzing absolute read counts (~60%)4. Other small RNAs (tRNA, Y RNA, sn/snoRNA, piRNA) contribute increasingly in cell-type- or condition-specific scenarios.

General landscape of miRNA content across biofluids

The concentration of EVs and the relative abundance of its miRNA content vary with tissue origin, physiological state, and biofluid environment. In general miRNA represent a modest proportion of EV cargo (typically between 2–6% of total mass).

The biofluid with the lowest miRNA content in EV is typically cerebrospinal fluid or bronchoalveolar lavage. These fluids show both lower EV concentrations and reduced miRNA diversity (~300–500 species), partly due to lower overall RNA yield and the restricted cellular origins (neuronal/glial for cerebrospinal fluid, pulmonary for bronchoalveolar lavage)^5,6.

In contrast, plasma stands out as the biofluid with the highest miRNA content, exhibiting both the highest EV concentration and broadest miRNA diversity (up to 1,500–2,600 species identified) It contains a rich array of ubiquitous and tissue-specific miRNAs, reflecting systemic circulation and input from diverse organs^3,5.

According to EVmiRNA, a subset of ~30% of miRNA species consistently shows high expression and they are ubiquitously sorted into EVs, regardless of biological context. Beyond this core lies significant diversity^7,8 (Table 2).

Table 2. Examples of specific miRNA founds in EV coming from different biofluids

Conclusion

The small RNA content of human extracellular vesicles is highly dynamic, shaped by tissue origin, physiological condition, and biofluid environment. With tools like EVmiRNA, EVAtlas, and EVPsort, researchers now have access to powerful datasets to dissect this complexity and link EV miRNA signatures to disease states and biological pathways. These tools together with advances in EV isolation and small RNA profiling techniques, will help unlocking the potential of extracellular vesicles for disease research.