Big data driven design for highly sensitive and selective virus-based electronic nose
발표자
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초록
내용
Genetically engineering of a bacteriophage is a promising way to develop a highly functional biosensor. In this paper, we demonstrate rapidly responding optical biosensor with high selectivity toward gaseous explosives with genetically engineered phages. To overcome the conventional issues, we use extensive utilization of empirical calculations to construct a large database of 8,000 tripeptides and screen the best for electronic nose sensing performance toward nine VOCs. DFT calculations unveil underlying correlations between the chemical affinity and optical property change on an electronic band structure level. The computational outcomes are validated by in vitro experimental design and testing of multiarray sensors using genetically modified phage implemented with five selected tripeptide sequences and wild-type phages. Our optical biosensor demonstrates a 1 ppb level of sensing resolution for explosive VOCs, which is a substantial improvement over conventional biosensor.