Novel "Raman genome" concept enables rapid tracking of viruses

A research team led by Distinguished Professor Giuseppe Pezzotti at the Biomedical Engineering Center, Kansai Medical University (Chairman: Toshio Yamashita; President: Tatsuo Kinashi; Japan), has demonstrated that differences in the molecular structures of viral RNA can be captured as "Raman barcodes," enabling the identification of 20 SARS-CoV-2 variants and subvariants. These findings are expected to contribute to the development of a rapid method for identifying newly emerging viral variants. 

The findings were published online in Advanced Science journal on September 30, 2026. 

Background of the research 

The identification and surveillance of viral variants have traditionally relied on RNA sequencing, which provides detailed information about the nucleotide sequence of a virus but requires long procedures using specialized instrumentation, sample processing, and computational analysis. 

However, viral RNA is more than a simple sequence of the four genetic bases. RNA molecules fold into complex three-dimensional structures through interactions between neighboring nucleotides and complementary bases. These secondary structures can influence how RNA behaves biologically and can differ even when the overall nucleotide composition appears remarkably similar. Raman spectroscopy is capable of instantaneously reading such structures. 

The researchers therefore asked a fundamental question: 

Can the molecular vibrations of viral RNA provide a distinctive fingerprint of different viral variants, even when their conventional genetic composition appears highly similar? 

Raman spectroscopy offers a direct way to probe molecular vibrations. Instead of reading the RNA sequence letter by letter, it captures a molecular vibrational fingerprint arising from the RNA backbone, ribose rings, phosphate linkages, and nitrogenous bases. The study introduces the concept of encoding these fingerprints as Raman barcodes, providing the basis for a new concept of a "Raman genome." 

Overview of the research 

RNA nucleotide strands were extracted from 20 SARS-CoV-2 strains, comprising the original Japanese isolate, Alpha, Beta, Gamma, Delta, Lambda, Theta, Mu, and 12 Omicron subvariants. 

The Raman spectra of these RNAs were systematically acquired and mathematically deconvoluted to identify their individual molecular components. Although all samples shared characteristic signals associated with the RNA backbone, ribofuranose rings, phosphate groups, and nitrogenous bases, subtle but reproducible differences emerged among the strains. 

Importantly, these differences were not simply a reflection of differences in the relative abundance of the four RNA bases. The investigated strains showed highly similar base fractions when evaluated from their genome sequences, yet their Raman spectra exhibited markedly different molecular signatures. 

The researchers therefore encoded the characteristic spectral features into Raman barcodes. Unlike conventional principal component analysis, which provided only limited separation, the Raman barcode approach successfully differentiated all 20 investigated strains and subvariants. 

The molecular origins of these differences were further explored by relating specific Raman bands to features of RNA secondary structure, including backbone conformation, nucleotide chain characteristics, ribofuranose dynamics, hairpin formation, stem length, and base-pairing environments. 

Research outcomes 

The study represents a first step toward defining a "Raman genome": a spectroscopic fingerprint capable of characterizing viral RNA according to its molecular architecture rather than solely according to its nucleotide sequence. 

The major scientific advances are: 

1. Molecular discrimination beyond conventional genetic composition 
The study demonstrates that SARS-CoV-2 RNAs with remarkably similar nucleotide compositions can nevertheless exhibit substantially different Raman fingerprints. This indicates that Raman spectroscopy is sensitive to structural information encoded in RNA beyond simple base abundance. 

2. Successful discrimination of 20 SARS-CoV-2 variants and subvariants 
Raman barcodes provided clear discrimination among all 20 investigated strains, including multiple Omicron subvariants, whereas conventional principal component analysis (PCA) showed limited discriminatory capability. 

3. Linking Raman signals to RNA secondary structure 
Rather than treating the Raman spectrum as a purely statistical fingerprint, the study identifies physically interpretable molecular markers associated with ribose vibrations, phosphate linkages, RNA backbone conformation, and hyperchromic or hypochromic responses of nitrogenous bases affected by pairing and secondary structure environments. 

4. A potential new tool for rapid variant screening 
Because the approach is based on Raman analysis of extracted RNA rather than complete RNA sequencing, it could ultimately provide a rapid screening strategy for emerging viral variants. Such an approach would be particularly valuable in emergency and critical-care situations, where obtaining molecular information rapidly can be crucial. 

5. Toward a new generation of molecular diagnostics 
The concept extends Raman spectroscopy from conventional chemical identification toward molecular-scale diagnostics of biological information. Future developments may combine physically interpretable Raman markers with automated spectral analysis, theoretical calculations, and artificial intelligence to create increasingly powerful predictive systems. 

Significance to society 

The findings could contribute to the development of faster and more accessible approaches for viral surveillance and molecular diagnostics. Because Raman analysis can potentially characterize viral RNA without performing complete RNA sequencing, it may ultimately enable rapid screening of emerging variants when timely information is particularly important, such as during outbreaks, epidemics, and emergency or critical-care situations.

More broadly, the "Raman genome" concept could open a new field in molecular medicine and microbiology in which the structural state of nucleic acids is investigated directly through their molecular fingerprints. With further technological development, automation, and integration with artificial intelligence, Raman-based molecular fingerprints could complement conventional sequencing and provide an additional, rapid layer of information for identifying and monitoring emerging pathogens.