Detection of the influenza virus - more widely known as the flu - has been a slow and laborious process to date. But biomedical engineers at Brown recently developed a prototype for a biochip that can rapidly and reliably detect influenza in patients. This chip would allow scientists to track the spread of the flu, ideally preventing outbreaks through early diagnosis, the researchers reported in the June issue of the Journal of Molecular Diagnostics.
The chip, the size of a credit card, quickly isolates and amplifies viral RNA - the blueprint for constructing proteins. Anubhav Tripathi, associate professor of engineering and corresponding author of the study, named the technique SMART, an acronym for a "simple method of amplifying RNA targets." The prototype chip can detect very small quantities of virus in patient samples, making it a great alternative to conventional methods that require higher viral loads for strain detection. Currently, the chip can be used to detect the H3, H1 seasonal and H1 swine strains of the virus, according to the article.
The biochip would allow physicians to overcome many of the obstacles associated with traditional genetic amplification methods such as polymerase chain reaction, which is less efficient and more costly.
On the chips, viral RNA is mixed with probes, which bind to known target sequences on the RNA. The probes contain magnetic beads that pull target sequences through a channel on the chip upon application of a magnet, thereby causing separation from unprobed strands. After the sorting, only the target strands are amplified, rather than the entire sample. This accelerates the process and allows it to occur in a handheld device, making it possible to use this approach in a remote clinic.
Tripathi said the probe is "very accurate and highly sensitive" with approximately 90 percent accuracy. While the accuracy already exceeds that of conventional methods, the ultimate goal is to achieve greater than 99 percent accuracy. The chip has been successful with patient samples collected from Memorial Hospital of Rhode Island, but Tripathi said the next step will be to test the chip with actual patients.
"We need to prove that it performs better than what already exists," said Andrew Artenstein, professor of medicine.
The prototype chip could also be used to detect diseases, such as HIV and tuberculosis. Tripathi hopes to apply the SMART technique to HIV patient samples collected from Kenya. Artenstein said the "same concept could be applied to anything, even non-infectious diseases like cancer."
Victor Ugaz, associate professor of chemical engineering at Texas A&M University, who was not involved in the study, said the test "has a lot of potential to improve the current state of surveillance and diagnostics."
"Being able to make these kinds of low-cost diagnostic tools more widely available will have (a) large impact on how medicine is practiced," Ugaz added.
Though the biochip is still in the prototype phase, researchers are already improving the current model. Maswazi Sihlabela GS is tweaking the prototype so that it can be used in resource-limited settings, such as small clinics and is compatible with devices such as laptops or iPhones for data analysis.