How Light Is Helping Us Detect SARS-CoV-2
In the relentless fight against COVID-19, scientists are wielding a powerful, non-invasive tool that uses light to uncover the virus's hidden secrets.
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has underscored a critical need for rapid, accurate, and accessible diagnostic tools. While RT-PCR remains the gold standard, it is often time-consuming and requires complex laboratory infrastructure. Enter spectroscopic analysis—a powerful technique that uses light to interrogate matter at a molecular level. This article explores how scientists are harnessing various forms of spectroscopy to detect the virus's unique fingerprint, offering a promising avenue for faster, reagent-free testing and a deeper understanding of the virus itself 1 .
At its core, spectroscopy involves the interaction between light and matter. When light hits a sample, it can be absorbed, reflected, or scattered in ways that are unique to the sample's molecular composition. This creates a "chemical fingerprint" that can be used to identify the substance.
This technique relies on the inelastic scattering of light. When a monochromatic laser beam hits a sample, most photons are scattered at the same energy. However, a tiny fraction interacts with the molecular bonds, causing a shift in energy that corresponds to the vibrational modes of those bonds. The resulting "Raman shift" provides detailed information about the molecular structure of the virus 1 .
Unlike Raman, IR spectroscopy measures the absorption of infrared light by molecules. Different chemical bonds absorb specific frequencies of IR light, which correspond to their vibrational energies. The most common type used in viral detection is Fourier-Transform Infrared (FTIR) spectroscopy, often coupled with an Attenuated Total Reflection (ATR) module, which allows for the analysis of liquid samples with minimal preparation 5 6 .
A landmark study published in Scientific Reports in 2021 demonstrated the tremendous potential of FTIR spectroscopy combined with machine learning for detecting SARS-CoV-2 3 . This experiment is a perfect example of how a simple concept can be leveraged for powerful results.
The researchers collected nasopharyngeal swab samples from 280 patients. These samples were placed in a viral transport medium (VTM) to preserve the virus's integrity 3 .
Following standard protocols, RNA was automatically extracted from the samples. This step is crucial as it purifies the target molecule (viral RNA) from other biological material 3 .
A mere 3 μL of the extracted RNA was placed directly onto the crystal of an ATR-FTIR spectrometer. The instrument then scanned the sample, collecting its infrared absorption spectrum across a wide range of wavenumbers (600–4500 cm⁻¹) in about 1.5 minutes 3 6 .
The raw spectral data, consisting of thousands of data points, showed no visually obvious differences between positive and negative samples. The researchers then applied sophisticated machine learning algorithms, including sparse classification techniques, to identify subtle, distinguishing patterns in the spectra that were invisible to the naked eye 3 .
The results were striking. The FTIR-based method, guided by machine learning, achieved a diagnostic performance of 97.8% accuracy, 97% sensitivity, and 98.3% specificity when compared to the standard RT-PCR results 3 . This means the test was exceptionally good at correctly identifying both infected and non-infected individuals.
| Metric | Definition | Result |
|---|---|---|
| Accuracy | The overall proportion of correct identifications | 97.8% |
| Sensitivity | The ability to correctly identify positive cases (true positive rate) | 97% |
| Specificity | The ability to correctly identify negative cases (true negative rate) | 98.3% |
The success of FTIR is part of a wider effort employing various spectroscopic techniques. The table below summarizes the performance of different methods as reported in various studies, showcasing the versatility of this approach.
| Sample Type | Technique | Analyte | Sensitivity | Specificity | Accuracy |
|---|---|---|---|---|---|
| Human Saliva | ATR-FTIR | Proteins | 99.2% | 100% | 99.6% |
| Human Sera | Raman | IgM and IgG | 84.0% | 95.0% | 90.3% |
| Human Saliva | SERS | Proteins | >90% | >90% | >90% |
| Exhaled Breath | Mass Spectrometry | Volatile Organic Compounds | 90% | 94% | 93% |
This supercharged version of Raman spectroscopy uses nanostructured metal surfaces to amplify the Raman signal by factors as high as 10¹⁰ 6 .
While not strictly an optical spectroscopy, this technique analyzes the mass-to-charge ratio of ions to identify molecules 1 .
A 2025 study used infrared spectroscopy to characterize the secondary structure of the spike protein in the Beta variant 4 .
The following table lists key materials and reagents commonly used in spectroscopic analysis of SARS-CoV-2, illustrating the practical side of this research.
| Item | Function in Research | Example Use Case |
|---|---|---|
| Viral Transport Medium (VTM) | Preserves viral RNA integrity after sample collection from swabs. | Used to store nasopharyngeal swab samples before FTIR or PCR analysis 2 3 . |
| Gold/Silver Nanoparticles | Acts as a substrate to enhance the Raman signal in SERS. | Functionalized in microfluidic devices or with antibodies to capture and amplify the virus's signal . |
| ACE2 Receptor Proteins | Used to functionalize sensors for specific virus capture. | Immobilized on gold nanoneedles in "virus-traps" to selectively bind the spike protein for SERS detection . |
| Anti-Spike Antibodies | Binds specifically to the SARS-CoV-2 spike protein for targeted detection. | Conjugated to gold nanoparticles for rapid visual and SERS-based antigen tests . |
| Lysis & Extraction Kits | Breaks open the virus and purifies its RNA for analysis. | Essential for preparing RNA samples for the FTIR spectroscopy experiment 3 . |
Spectroscopic analysis represents a paradigm shift in viral detection. Its advantages are clear: speed, minimal reagent use, non-invasiveness, and the potential for low-cost, point-of-care devices 7 . As machine learning algorithms become more sophisticated and portable spectrometers like MEMS-based FTIR systems evolve, these techniques are poised to move from the research lab to the clinic 2 .
While regulatory hurdles and the need for extensive clinical validation remain, the progress so far is undeniable. The ability to not just detect but also structurally understand viruses through light promises to be an invaluable tool not only for managing the ongoing COVID-19 pandemic but also for preparing for future viral threats. The fight against invisible pathogens is being illuminated by the power of light.