Raman spectroscopy combined with spectral barcoding distinguished RNA from 20 SARS-CoV-2 variants and subvariants in a laboratory study, suggesting a possible complementary method for studying viral RNA structure.
The research, published in Advanced Science, examined RNA extracted from the original Japanese isolate, the Alpha, Beta, Gamma, Delta, Lambda, Theta, and Mu variants, and 12 Omicron subvariants. Giuseppe Pezzotti of Kansai Medical University and colleagues described the resulting structural fingerprints as a “Raman genome.”
The researchers propagated each viral strain in cell culture before extracting RNA from the culture supernatant. Spectra were collected with a confocal Raman spectrometer using a 532-nm laser. For each RNA sample, the team collected 10 spectra from different locations across an area of approximately 2 mm² and averaged the results.
Measurements covered the Raman shift range from 400 to 1,800 cm⁻¹. The spectra contained signals associated with the phosphodiester backbone, ribofuranose rings, and the RNA bases adenine, cytosine, guanine, and uracil.
Although the overall spectra were similar, the researchers identified differences in signals linked to RNA backbone conformation, phosphate bonds, base pairing, and secondary structure. They used computational deconvolution to separate overlapping spectral bands and convert selected features into barcodes.
Conventional principal component analysis provided limited discrimination and could distinguish only some of the strains. In contrast, the Raman barcodes differed across all 20 samples. The team linked some of these differences to predicted secondary structures generated from nucleotide sequences using RNAfold software.
Signals at approximately 432 and 1,460 cm⁻¹ were associated with structural characteristics including the number of hairpin loops and stem length. These relationships indicate that Raman spectroscopy reflects changes in RNA folding and molecular organization rather than simply measuring the relative abundance of individual bases.
The method does not sequence RNA or identify individual nucleotide substitutions. Instead, it detects the structural effects of sequence variation, including changes in base pairing, stacking, backbone geometry, and hydrogen bonding. The authors therefore presented Raman analysis as a potential complement to next-generation sequencing rather than a replacement.
The study was a proof of concept involving a finite set of purified RNA samples from cell-culture supernatants. Its ability to recognize previously unseen variants or strains separated by only a few mutations remains unknown. Testing is also needed with clinical specimens, which may contain host nucleic acids, proteins, mucus, cellular debris, and variable concentrations of viral RNA.
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