Research validates biosensor's AI detection capabilities
In the Fall 2008, the Georgia Tech Research Institute (GTRI) publication PoultryTech reported on the potential of using an optical biosensor developed by GTRI for the detection of the avian influenza (AI) virus*. The optical sensor is low-cost, easy to use, field-deployable, and provides rapid results less than 30 minutes. Recently, GTRI researchers teamed with colleagues at the U.S. Department of Agriculture’s Southeast Poultry Research Laboratory to validate the sensor’s detection capabilities with experimentally infected live chickens.
The optical biosensor uses a concept known as waveguide interferometry to precisely determine how many virus particles attach to the receptors on the biosensor’s surface. For the validation tests, sensing assays were tested against low-pathogenic H5 and H7 avian influenza strains in a “field use” manner. Split samples (oropharyngeal swabs) were collected each day for seven days post inoculation from 100 experimentally infected four-week-old broiler chickens. These samples were tested using the optical biosensor and two other diagnostic methods: real-time reverse transcriptase polymerase chain reaction (RRT-PCR) and the Synbiotics dipstick immunoassay.
Sample results from each of the three methods were then evaluated and compared for detection sensitivity and specificity as well as other performance factors. Results of the evaluation are summarized in Table 1. The RRT-PCR method was used as the standard for the comparison.
Researchers believe that considering the optical biosensor’s performance (detection sensitivity and specificity), cost, portability, field-usability and ease of use, it can be an excellent tool for AI surveillance and outbreak control.
“How fast we can identify the circulating viruses is critical to the implementation of timely and adequate prevention and control strategies,” says Dr. Jie Xu, GTRI senior research engineer and project director. “The development of the waveguide sensor-based technology as an AI diagnostic tool is a promising technology that could meet this goal.”
According to Xu, the optical biosensor technology also has the capability of simultaneous detection of a variety of different viral strains through multiple channels on the same waveguide chip. This capability provides several benefits: parallel processing of samples, rapid subtyping when strain is unknown, simplified sample preparation (separate samples for each test are not required), and increases in testing throughput.
The team plans to focus on improving overall sample throughput. The number of samples that need to be tested could be high when there is an influenza outbreak, explains Xu. In addition, fecal samples could be tested as well since the sensor-based technology is contaminant-proof and fecal samples are easier to obtain.
The research is being conducted in collaboration with Dr. David Suarez, the research leader of the Exotic and Emerging Avian Viral Diseases Unit at the Southeast Poultry Research Laboratory. Funding is being provided by the Georgia Tech Research Institute’s Agricultural Technology Research Program, the Georgia Research Alliance, and the U.S. Department of Agriculture.
*PoultryTech, Vol. 20, No. 3, Fall 2008: http://www.atrp.gatech.edu/pt20v3fl08/20-3_p1.html