Abstract
Current methods for detecting glycoRNAs include metabolic labeling in living cells or animals and RNA-optimized periodate oxidation and aldehyde labeling (rPAL), each of which offers distinct advantages and limitations. Here, we report a relatively simple and rapid approach for detecting native glycoRNAs using direct lectin hybridization. This method involves several straightforward steps, including total RNA isolation, northern blotting, and lectin hybridization. Its advantages include high sensitivity, procedural simplicity, and broad applicability. Using this approach, we profiled glycoRNA expressions in RNA samples derived from human and murine tissues and cell lines and compared the results with those obtained using two established detection methods. We also examined differences in glycoRNA expression under physiological and pathological conditions. Notably, we report for the first time the detection of free glycoRNAs in various human biofluids, including plasma, urine, and amniotic fluid. Overall, our findings demonstrate that this method is reliable and reproducible, providing an alternative tool for studying glycoRNA biology and potentially offering utility for future clinical diagnostics.
Data availability
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Huang, N. et al. Natural display of nuclear-encoded RNA on the cell surface and its impact on cell interaction. Genome Biol. 21, 225 (2020).
Flynn, R. A. et al. Small RNAs are modified with N-glycans and displayed on the surface of living cells. Cell 184, 3109–3124e22 (2021).
Li, Z. et al. Cell-surface RNA forms ternary complex with RNA-binding proteins and Heparan sulfate to recruit immune receptors. Mol. Cell. 85, 4633–4650e11 (2025).
Zhang, N. et al. Cell surface RNAs control neutrophil recruitment. Cell 187, 846–860 (2024).
Li, Y. et al. GlycoRNA-L and glycoRNA-S mediate human monocyte adhesion via binding to Siglec-5. Biochim. Biophys. Acta Mol. Cell. Res. 1872, 120017 (2025).
Graziano, V. R. et al. RNA N-glycosylation enables immune evasion and homeostatic efferocytosis. Nature 645, 784–792 (2025).
Jiang, X. et al. Deciphering the RNA landscapes on mammalian cell surfaces. Protein Cell. 13, pwaf079 (2025).
Abledu, J. K. et al. Cell surface RNA expression modulates alveolar epithelial function. Am. J. Respir. Cell. Mol. Biol. 73, 466–478 (2025).
He, J. et al. The role of cell surface RNAs in hepatocellular carcinoma. Int. J. Biol. Macromol. 330, 147948 (2025).
Xin, B. et al. GlycoRNAs are abundant in glioma and involved in glioma cell proliferation. Oncogenesis 14, 29 (2025).
Xie, Y. et al. The modified RNA base acp3U is an attachment site for N-glycans in glycoRNA. Cell (2024).
Perr, J. et al. RNA-binding proteins and glycornas form domains on the cell surface for cell-penetrating peptide entry. Cell 188, 1878–1895e25 (2025).
Li, L. et al. Protocol for detecting glycornas using metabolic labeling and Northwestern blot. STAR. Protoc. 5, 103321 (2024).
Awofiranye, A. E. et al. N-glycolylated carbohydrates in nature. Glycobiology 32, 921–932 (2022).
Sharma, S. et al. Extracellular exosomal RNAs are glyco-modified. Nat. Cell. Biol. 27, 983–991 (2025).
Ma, Y. et al. Spatial imaging of glycorna in single cells with ARPLA. Nat. Biotechnol. 42, 608–616 (2024).
Ren, T. et al. FRET imaging of glycorna on small extracellular vesicles enabling sensitive cancer diagnostics. Nat. Commun. 16, 3391 (2025).
Gong, Z. et al. Intramolecular proximity-induced amplification for accurate imaging of glycosylated RNAs in living cells and zebrafish. Anal. Chem. 97, 20897–20907 (2025).
Brunner, C. M. et al. Bottom-up investigation of Spatiotemporal glycocalyx dynamics with interferometric scattering microscopy. J. Am. Chem. Soc. 147, 32799–32808 (2025).
Ge, J. et al. Comprehensive and facile strategy for enhanced visualization of sialylated RNA via dual bioorthogonal labeling. ACS Chem. Biol. 20, 1884–1891 (2025).
Hazemi, M. E. et al. An expanded view of RNA modification with carbohydrate-based metabolic probes. JACS Au. 5, 2309–2320 (2025).
Muller, W. A. A physiological role for cell surface glycornas. J. Leukoc. Biol. 115, 996–998 (2024).
Chokkalla, A. K. et al. Immunomodulatory role of glycornas in the brain. J. Cereb. Blood Flow. Metab. 43, 499–504 (2023).
Nachtergaele, S. & Krishnan, Y. New vistas for cell-surface glycornas. N. Engl. J. Med. 385, 658–660 (2021).
Chai, P., Lebedenko, C. G. & Flynn, R. A. RNA crossing membranes: systems and mechanisms contextualizing extracellular RNA and cell surface glycornas. Annu. Rev. Genom. Hum. Genet. 24, 85–107 (2023).
Chevet, E., De Matteis, M. A., Eskelinen, E. L. & Farhan, H. RNA, a new member in the glycan club that gets exposed at the cell surface. Traffic 22, 362–363 (2021).
Porat, J. & Flynn, R. A. Cell surface RNA biology: new roles for RNA-binding proteins. Trends Biochem. Sci. (2025).
Li, H. et al. GlycoRNAs: more than the intersection of glycobiology and RNA biology. Life Med. 3, lnae044 (2024).
Chen, X. et al. Potential function of glycosylated RNA in diseases. Wiley Interdiscip. Rev. RNA. 16, e70031 (2025).
Li, B. et al. GlycoRNAs as emerging drug targets. Trends Pharmacol. Sci. 46, 832–835 (2025).
Montag, N. et al. The emerging role of glycornas in immune regulation and recognition. Immunol. Lett. 276, 107048 (2025).
Kim, H. S. GlycoRNA: a new player in cellular communication. Oncol. Res. 33, 995–1000 (2025).
Acknowledgements
We thank Drs. Tony Wang, Daping Fan, Kun Chen, Jianming Qiu, Shizhen Wang and Cuthbert Simpkins for kindly providing cell lines and/or RNA samples. This project was supported by the National Institutes of Health (R15AI138116, to M.F), UMKC Funding for Excellence (2023, to M.F), SPiRE (2024, to M.F) and UMKC SOM Bridge Fund (2025, to M.F).
Funding
This work was supported by the National Institutes of Health (R15AI138116 to M.F.), UMKC Funding for Excellence (2023 to M.F.), SPiRE (2024 to M.F.), and the UMKC School of Medicine Bridge Fund (2025 to M.F.).
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M.F. conceived, designed and supervised the overall study. Y.L., X.L. and M.F. performed most of the experiments. Y.Q. performed metabolic labeling experiments for mice. T.L. and P.N. help to perform mouse tissue expression experiments, and M.F. wrote the manuscript. M.F., H.M. and P.N. revised the manuscript.
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Li, Y., Qian, Y., Li, X. et al. Lectin-based detection and expression profiling of native glycoRNAs. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40291-2
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DOI: https://doi.org/10.1038/s41598-026-40291-2