Profiling host and microbial small RNAs in saliva.

Human saliva represents a complex molecular ecosystem composed of secretions from epithelial and immune cells, together with the oral microbiota. Over the past decade, advances in extracellular vesicle (EV) research and small RNA sequencing have revealed that saliva contains a heterogeneous EV population ranging from 30 to 1,000 nm in diameter. These vesicles transport. proteins, lipids, and nucleic acids, and are active mediators of intercellular and inter-kingdom communication.

Recent sequencing studies have shown that a substantial fraction of small RNAs in salivary EVs originate from bacteria.¹ This finding challenges the traditional boundary between host and microbiome, suggesting that oral microbes continuously release regulatory RNAs capable of influencing host pathways. In parallel, comprehensive reviews of salivary EVs² emphasize their growing potential as diagnostic and mechanistic tools in human disease.

Best practices to isolate EVs from human saliva

Vesicle isolation and verification

• EVs are isolated. from clarified saliva through a combination of low-speed centrifugation to remove cells, followed by ultracentrifugation, size-exclusion chromatography, or iodixanol density-gradient separation. Vesicle identity is validated by transmission electron microscopy and nanoparticle tracking analysis, while Western blotting confirms the presence of canonical EV markers such as CD9, CD63, Alix, and TSG101.
• To confirm that the recovered RNA is vesicle-encapsulated rather than extracellular contamination, samples are treated with RNase prior to detergent lysis. This RNase-protection approach is fully consistent with MISEV 2023 recommendations,³ which also emphasize transparent reporting of controls, detergent treatments, and the use of exogenous RNA spike-ins, such as the miND® spike-in controls, for normalization across preparations.

RNA extraction and library preparation

• EV-associated RNA is typically recovered in the low-nanogram range using phenol-based or silica-membrane kits optimized for short fragments. Library preparation is performed with small RNA-specific kits such as the NEXTFLEX™ Small RNA-Seq Kit v4, which efficiently ligates adapters to RNAs of ~19–200 nt. Consistent library preparation is crucial to minimize ligation bias and preserve comparability between host- and bacterial-derived reads.

Bioinformatic discrimination and analytical rigor

• Because bacterial and human small RNAs overlap in length and nucleotide composition, computational discrimination is essential. Reads are first filtered and trimmed, then sequentially aligned to the human reference genome (GRCh38) and curated RNA databases (miRBase, tRFdb) to identify host RNAs. Unassigned reads are subsequently mapped to representative oral bacterial genomes (Streptococcus, Prevotella, Veillonella, Fusobacterium, Porphyromonas).

Ascensión et al (2025) proposed a consensus workflow combining multiple classifiers (Bowtie2, Kraken2, BWA-MEM) and probabilistic scoring to reduce false bacterial assignments.⁴ Their strategy, designed specifically for extracellular vesicle RNA-seq data, strengthens confidence that bacterial signals reflect genuine vesicular cargo rather than contamination.

Functional insights into salivary vesicular bacterial RNAs

Sequencing of purified salivary EVs from healthy individuals reveals that a considerable proportion of reads map to bacterial genomes, including tRNA-derived fragments, short 5S/16S rRNA fragments, transfer-messenger RNA (tmRNA), and regulatory sRNAs. Conserved sequence motifs among bacterial tRNA-derived fragments (tRFs) indicate regulated biogenesis rather than random cleavage.

Functional evidence from periodontal pathogens further supports the biological activity of these RNAs. Fan et al (2023) demonstrated that Porphyromonas gingivalis outer-membrane vesicles (OMVs) carry small RNAs such as msRNA 45033, which target the human gene CBX5, thereby promoting epithelial apoptosis through epigenetic regulation.⁵ Uemura et al (2022) showed that Pg-OMVs stimulate gingival epithelial cells to secrete IL-6 and IL-8 via the MAPK and STING pathways, an effect dependent on their nucleic-acid cargo.⁶

Extending beyond the oral niche, Xie et al (2024) reported that Pseudomonas aeruginosa OMV-packed sRNAs can enter host cells and modulate innate immune responses, indicating that RNA-mediated cross-kingdom signaling is a conserved phenomenon among bacterial species⁷.

Additional, complementary in vivo and cellular evidence comes from Fusobacterium nucleatum OMVs. In a rat periodontitis model, Fn-OMVs alone were sufficient to exacerbate alveolar bone loss and drive NLRP3 inflammasome activation in periodontal ligament stem cells, demonstrating that OMVs can independently trigger periodontal pathology and robust inflammatory signaling.⁸ Beyond the oral cavity, Fn-OMVs were also shown to reprogram tumour-associated macrophage metabolism (tryptophan/Kynurenine axis) and blunt immunotherapy responses, underscoring that bacterial vesicular RNAs and their cargo can shape host immunity systemically.⁹  

Collectively, the available data establish saliva as a dynamic ecosystem where vesicles of bacterial and human origin coexist and may exchange cargo. The parallel enrichment of bacterial tRFs and host miRNAs involved in inflammatory regulation suggests a coordinated molecular response within the oral mucosal environment. Bacterial RNAs possess the potential to modulate host signalling pathways, while host EV microRNAs could reciprocally influence microbial gene expression.

Conclusion

Salivary extracellular vesicles contain a mixed repertoire of host and bacterial small RNAs that together orchestrate a continuous molecular dialogue between humans and their resident microbiota. Evidence from sequencing, microscopy, and functional assays demonstrates that bacterial RNAs are authentic vesicular components capable of influencing host gene expression, while host miRNAs contribute reciprocal regulatory input. This realization reframes saliva as a biological interface of RNA-based communication.

Small RNA sequencing,. coupled with rigorous analytical frameworks, is uncovering the full extent of this interaction, offering a powerful route toward non-invasive biomarker discovery and a deeper understanding of host–microbiome homeostasis.

References

1. Tong, F., et al. (2023). Characteristics of Human and Microbiome RNA Profiles in Saliva. RNA Biol. 20(1):398-408. doi: 10.1080/15476286.2023.2229596.
2. Wu, J., et al. (2023). Salivary Extracellular Vesicles: Biomarkers and Beyond in Human Diseases. Int J Mol Sci. 10;24(24):17328. doi: 10.3390/ijms242417328.
3. Welsh, J., et al. (2024). Minimal information for studies of extracellular vesicles (MISEV2023): from basic to advanced approaches. J Extracell Vesicles. 13, e12404. doi:10.1002/jev2.12404.
4. Ascensión, L., et al. (2025). A proposed workflow to robustly analyze bacterial transcripts in RNAseq data from extracellular vesicles. Front Microbiol. 20;16:1486661. doi: 10.3389/fmicb.2025.1486661.
5. Fan, R., et al. (2023). Porphyromonas gingivalis Outer Membrane Vesicles Promote Apoptosis via msRNA-Regulated DNA Methylation in Periodontitis. Microbiol Spectr. 11(1):e0328822. doi: 10.1128/spectrum.03288-22.
6. Uemura, Y., et al. (2022). Porphyromonas gingivalis Outer Membrane Vesicles Stimulate Gingival Epithelial Cells to Induce Pro-Inflammatory Cytokines via the MAPK and STING Pathways. Biomedicines.10(10), 2643. doi: 10.3390/biomedicines10102643
7. Xie, Z., et al. (2024). Pseudomonas aeruginosa outer membrane vesicle-packed sRNAs can enter host cells and regulate innate immune responses. Microb Pathog.188:106562. doi: 10.1016/j.micpath.2024.106562.
8. Zhang, L., et al. (2024). Outer Membrane Vesicles Derived From Fusobacterium nucleatum Trigger Periodontitis Through Host Overimmunity. Adv Sci (Weinh).11(47):e2400882. doi: 10.1002/advs.202400882.
9. Li, W., et al. (2025). Fusobacterium nucleatum-Derived Outer Membrane Vesicles Promote Immunotherapy Resistance via Changes in Tryptophan Metabolism in Tumour-Associated Macrophages. J Extracell Vesicles. 14(4):e70070. doi: 10.1002/jev2.70070.