Surface-Enhanced Raman Scattering for DNA Methylation Analysis in Plant Tissue Culture: Current Evidence, Translational Gaps, and Future Strategies

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Abstract
DNA methylation is a central epigenetic regulator of genome stability, developmental plasticity, and stress adaptation in plant tissue culture systems. During dedifferentiation, callus formation, organogenesis, somatic embryogenesis, transformation, and prolonged subculture, DNA methylation patterns can be extensively remodeled, thereby contributing to regeneration competence and somaclonal variation. To detect such changes, traditional methylation-detection methods, including bisulfite-based sequencing and methylation-sensitive polymerase chain reaction, provide high analytical output but remain labor-intensive (2–3 days), destructive (requiring microgram amounts of DNA), and difficult to deploy as rapid screening tools across large tissue-culture plantlets. Surface-enhanced Raman scattering (SERS) offers a complementary route by coupling molecular fingerprinting with plasmonic signal amplification. Controlled systems have demonstrated highly sensitive detection of methylation-associated molecular signatures, with reported detection limits reaching the nanomolar-to-submicromolar range depending on analyte type, substrate architecture, and measurement conditions. However, these quantitative values primarily come from synthetic DNA or model systems and should be interpreted cautiously when applied to complex plant tissue culture samples. This review critically examines current SERS-based strategies for DNA methylation analysis, emphasizing substrate selection, signal-enhancement mechanisms, SERS enhancement mechanisms, surface functionalization, and computational spectral analysis. SERS has emerged as a promising complementary technology for DNA methylation analysis due to its molecular fingerprinting capability and high sensitivity. However, direct demonstrations of SERS-based DNA methylation detection in plant tissue culture systems remain limited. Current evidence largely originates from synthetic DNA models, purified nucleic acid systems, and non-plant biological applications, providing methodological foundations rather than complete plant validation. Future studies are required to establish plant-specific substrates, calibration strategies, and biological validation workflows.

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