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Nanorod Array Rapidly Detects Respiratory Viruses

By HospiMedica staff writers
Posted on 05 Dec 2006
A diagnostic test based on nanotechnology can detect viruses as diverse as influenza, human immunodeficiency virus (HIV), and respiratory syncytial virus (RSV) in 60 seconds or less. More...


The spectroscopic assay is based on surface-enhanced Raman scattering (SERS) using silver nano-rod array substrates. It works by measuring the change in frequency of a near-infrared laser as it scatters off viral DNA or RNA. Trace levels of viruses can be detected with a high degree of specificity and sensitivity. The assay detects spectral differences between viruses, viral strains, and viruses with gene deletions in biologic media. The method provides rapid diagnostics for the detection and characterization of viruses.

The technique, described in the November 2006 issue of NanoLetters (an American Chemical Society Publication), was developed by scientists at the University of Georgia (Athens, USA). Lead author of the study, Professor Ralph Tripp, said "It saves days to weeks. You could actually apply it to a person walking off a plane and know if they [are] infected.” He said the technique is so powerful that it has the potential to detect a single virus particle and can also discern virus subtypes and those with mutations such as gene insertions and deletions. This specificity makes it valuable as a diagnostic tool, but also as a means for epidemiologists to track where viruses originate from and how they change as they move through populations. In addition the technique could save lives by rapidly detecting a naturally occurring disease outbreak or bioterrorism attack.

The scientists have shown that the technique works with viruses isolated from infected cells grown in a lab, and their next step is to study its use in biologic samples such as blood, feces, or nasal swabs. Prof. Tripp said preliminary results are so promising that they are currently working to create an online encyclopedia of Raman shift values. With that information, a technician could readily reference a Raman shift for a particular virus to identify an unknown virus.



Related Links:
University of Georgia

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