Team:HK SKHLPSS/Description
Background
According to the Hong Kong Department of Health, the H3N2 flu outbreak in Hong Kong has been a cause for concern. 307 people died from this disease, which is even more than that in the SARS outbreak in 2003.[1] This influenza can also be a serious illness to the weak and frail or elderly, and may be complicated by bronchitis, chest infection or even death.
According to Professor Yuen Kwok-yung, the chair professor of the microbiology department in University of Hong Kong (HKU), the dominant strain influenza A H3N2 was mutated this year, rendering made vaccines in the past two years ineffective.[2] And this may be the reason behind the surge in flu cases this year in Hong Kong.
Currently, there are a few conventional methods to detect influenza virus. One of them is to use real-time reverse transcription polymerase chain reaction (RT-PCR).[3] It is a reliable method with a high accuracy rate. However, the detection process takes around 2-6 hours, which may not be suitable for emergency cases which requires a short lead time for detection.
Another method is rapid influenza antigen test.[4] This method can detect influenza virus shortly from 15 to 20 minutes.[5] Nevertheless, using rapid influenza antigen test has its drawbacks. False negative result may be given due to the difference in viral activity and the amount of virus. Hence, the accuracy for this test lies between 50-80%, showing that the result may not fully reflect the situation of the patients.
Another drawback is that the antibody used in rapid influenza antigen test is quite expensive. The cost of diagnosis of H3N2 virus would be very high. Plus, the storage of antibody is less stable than that of chemicals, which also affects sensitivity of the diagnosis.
On the other hand, detecting virus using DNA nanostructure as a diagnostic device may be a possible way out. DNA nanostructure is formed from several DNA strands. They have the ability to detect RNA of specific virus. Compared to current methods, this diagnostic method is more stable and cheaper because it does not involve any antibody. Chemicals used for detection is cheap and easy to store, which makes our diagnosis more feasible for public use.
Inspired by this technology, we brainstormed a lot trying to modify our previous works so as to detect H3N2 virus effectively. In this project, we want to make a 3-dimensional nanostructure to detect H3N2 virus. Hence, we want to use this as an example to demonstrate the possibility of using DNA nanotechnology for diagnosis.
Our aim for this project is to provide a faster, cheaper yet a more specific and precise detection method to check for H3N2 virus.
Hypothesis
The nano-cube we designed is responsible to the presence of H3N2 mRNA biomarker, leading to the formation of complete G-quadruplex and gives a colorimetric signal.
Objectives
- DNA nano cube is designed corresponding to the target mRNA of the disease/virus.
- The eight oligos can be self-assembled to form a nano-cube.
- Concentration of the target DNA is proportional to the intensity of the ABTS colour change.
references
- ↑ Cheung, E., (2017, July 24). How worried should you be about Hong Kong’s unusual flu outbreak? South China Morning Post, Retrieved from [http://www.scmp.com/news/hong-kong/health-environment/article/2103878/how-worried-should-you-be-about-hong-kongs-unusual here]
- ↑ Cheung, E., (2017, July 21). Mutation may be behind surge in flu cases this summer, Hong Kong experts say. South China Morning Post, Retrieved from [http://www.scmp.com/news/hong-kong/health-environment/article/2103673/mutation-may-be-behind-surge-flu-cases-summer-hong here]
- ↑ J.Y. Yang (2014, November), Detection Efficiency of Rapid Influenza Antigen Test for Influenza, Taiwan Epidemiology Bulletin, 30(22) 443-450
- ↑ J.Y. Yang (2014, November), Detection Efficiency of Rapid Influenza Antigen Test for Influenza, Taiwan Epidemiology Bulletin, 30(22) 443-450
- ↑ J.Y. Yang (2017, May),Detection Efficiency of Alere i Influenza A & B for Influenza 2016, Taiwan Epidemiology Bulletin, 33(17) 324-333
