2025-03-03 ワシントン大学セントルイス校
<関連情報>
- https://source.washu.edu/2025/03/new-biosensor-can-detect-airborne-bird-flu-in-under-five-minutes/
- https://pubs.acs.org/doi/10.1021/acssensors.4c03087
エアロゾル中の鳥インフルエンザ(H5N1)と大腸菌を迅速に検出する静電容量型バイオセンサー Capacitive Biosensor for Rapid Detection of Avian (H5N1) Influenza and E. coli in Aerosols
Joshin Kumar,Meng Xu,Yuezhi August Li,Shu-Wen You,Brookelyn M. Doherty,Woodrow D. Gardiner,John R. Cirrito,Carla M. Yuede,Ananya Benegal,Michael D. Vahey,Astha Joshi,Kuljeet Seehra,Adrianus C.M. Boon,Yin-Yuan Huang,Joseph V. Puthussery,and Rajan K. Chakrabarty
ACS Sensors Published: February 21, 2025
DOI:https://doi.org/10.1021/acssensors.4c03087
Abstract
Airborne transmission via aerosols is a dominant route for the transmission of respiratory pathogens, including avian H5N1 influenza A virus and E. coli bacteria. Rapid and direct detection of respiratory pathogen aerosols has been a long-standing technical challenge. Herein, we develop a novel label-free capacitive biosensor using an interlocked Prussian blue (PB)/graphene oxide (GO) network on a screen-printed carbon electrode (SPCE) for direct detection of avian H5N1 and E. coli. A single-step electro-co-deposition process grows GO branches on the SPCE surface, while the PB nanocrystals simultaneously decorate around the GO branches, resulting in an ultrasensitive capacitive response at nanofarad levels. We tested the biosensor for H5N1 concentrations from 2.0 viral RNA copies/mL to 1.6 × 105 viral RNA copies/mL, with a limit of detection (LoD) of 56 viral RNA copies/mL. We tested it on E. coli for concentrations ranging from 2.0 bacterial cells/mL to 1.8 × 104 bacterial cells/mL, with a LoD of 5 bacterial cells/mL. The detection times for both pathogens were under 5 min. When integrated with a custom-built wet cyclone bioaerosol sampler, our biosensor could detect and quasi-quantitatively estimate H5N1 and E. coli concentrations in air with spatial resolutions of 93 viral RNA copies/m3 and 8 bacterial cells/m3, respectively. The quasi-quantification method, based on dilution and binary detection (positive/negative), achieved an overall accuracy of >90% for pathogen-laden aerosol samples. This biosensor is adaptable for multiplexed detection of other respiratory pathogens, making it a versatile tool for real-time airborne pathogen monitoring and risk assessment.