AI-driven colorimetric nucleic acid test for tilapia lake virus: A large-scale, point-of-care diagnostic model for future emerging diseases
Issued Date
2023-12-15
Resource Type
ISSN
00448486
Scopus ID
2-s2.0-85169562391
Journal Title
Aquaculture
Volume
577
Rights Holder(s)
SCOPUS
Bibliographic Citation
Aquaculture Vol.577 (2023)
Suggested Citation
Jaroenram W., Teerapittayanon S., Kampeera J., Suvannakad R., Senapin S., Prasertsincharoen N., Chatnuntawech I., Kiatpathomchai W. AI-driven colorimetric nucleic acid test for tilapia lake virus: A large-scale, point-of-care diagnostic model for future emerging diseases. Aquaculture Vol.577 (2023). doi:10.1016/j.aquaculture.2023.739983 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/89582
Title
AI-driven colorimetric nucleic acid test for tilapia lake virus: A large-scale, point-of-care diagnostic model for future emerging diseases
Other Contributor(s)
Abstract
It is indisputable that the world is currently facing several health challenges, which include outbreaks of diseases. One way to limit the spread of such diseases is to have simple yet efficient bioassays that work well in large-scale operation. To address this issue, a new artificial intelligence (AI) based colorimetric DNA/RNA detection platform was developed using tilapia lake virus as a model. The assay uses a newly formulated indicator dye and colorimetric nucleic acid amplification done in a thermos or a simple heating block to produce visible results that can be observed by the naked eye. To ensure high-throughput screening, an AI-based analysis web application was developed that can be used on computers, tablets, and smartphones to accurately and quickly determine the colorimetric results. With a genetic material extraction procedure that takes only 5 min and requires no equipment, our assay can be completed within an hour from sampling to readout, with 96% accuracy and a sensitivity approaching a single copy of the target virus. The entire assay incubation can be done in a simple thermos, as a substitute for thermal cyclers, rendering its potential use in remote areas where access to electricity is restricted. To demonstrate the versatility of our platform, we modified our testing solution by changing pathogen-specific primers and tested it on various target pathogens that infect humans, animals, and plants. The results were accurate, indicating that the platform has the potential to be used for point-of-care disease diagnosis in the future.