AsianScientist (Oct. 4, 2018) – A research group at the National University of Singapore (NUS) has developed a portable device for quick and accurate screening of diseases. Their work is published in Nature Communications.
The ability to detect diseases in the field can be a boon for healthcare. However, most diagnostic devices and kits are meant for lab-based operation.
In the present study, scientists led by Assistant Professor Shao Huilin of NUS developed a technology platform called enVision (enzyme-assisted nanocomplexes for visual identification of nucleic acids) that can be used to detect a wide range of diseases. The research team used the human papillomavirus (HPV), the key cause of cervical cancer, as a clinical model to validate the performance of enVision.
“The enVision platform has three key steps—target recognition, target-independent signal enhancement and visual detection. It employs a unique set of molecular switches, composed of enzyme-DNA nanostructures, to accurately detect, as well as convert and amplify molecular information into visible signals for disease diagnosis,” said Dr. Lim Geok Soon of NUS who co-authored the study.
The enVision assay turns from colorless to brown if a disease-causing agent is detected, giving a clear readout. The platform takes between 30 minutes to one hour to give a result, which is two to four times faster than existing infection diagnostics methods, said the researchers. In addition, each test kit costs under S$1 to manufacture—100 times lower than the current cost of conducting similar tests.
“enVision is not only able to accurately detect different subtypes of [HPV], it is also able to spot differences within a specific subtype of a given disease to identify previously undetectable infections,” said Shao.
Going forward, the research team is developing a sample preparation module for extraction and treatment of DNA material. In addition, the research team foresees that smartphone apps with more advanced image correction and analysis algorithms will further improve the enVision’s performance for real-world application.
The article can be found at: Ho et al. (2018) Visual and Modular Detection of Pathogen Nucleic Acids With Enzyme–DNA Molecular Complexes.
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Source: National University of Singapore.
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