Optical biosensing of monkeypox virus using novel recombinant silica-binding proteins for site-directed antibody immobilizationOA
Optical biosensing of monkeypox virus using novel recombinant silica-binding proteins for site-directed antibody immobilization
The efficient immobilization of capture antibodies is crucial for timely pathogen detection during global pandemic outbreaks.Therefore,we proposed a silica-binding protein featuring core functional domains(cSP).It comprises a peptide with a silica-binding tag designed to adhere to silica surfaces and tandem protein G fragments(2C2)for effective antibody capture.This innovation facilitates precise site-directed immobilization of antibodies onto silica surfaces.We applied cSP to silica-coated optical fibers,creating a fiber-optic biolayer interferometer(FO-BLI)biosensor capable of monitoring the monkeypox virus(MPXV)protein A29L in spiked clinical samples to rapidly detect the MPXV.The cSP-based FO-BLI biosensor for MPXV demonstrated a limit of detection(LOD)of 0.62 ng/mL in buffer,comparable to the 0.52 ng/mL LOD achieved using a conventional streptavidin(SA)-based FO-BLI biosensor.Furthermore,it achieved LODs of 0.77 ng/mL in spiked serum and 0.80 ng/mL in spiked saliva,exhibiting no cross-reactivity with other viral antigens.The MPXV detection process was completed within 14 min.We further proposed a cSP-based multi-virus biosensor strategy capable of detecting various pandemic strains,such as MPXV,the latest coronavirus disease(COVID)variants,and influenza A protein,to extend its versatility.The proposed cSP-modified FO-BLI biosensor has a high potential for rapidly and accurately detecting MPXV antigens,making valuable contributions to epidemiological studies.
Xixi Song;Ying Tao;Sumin Bian;Mohamad Sawan
CenBRAIN Neurotech,School of Engineering,Westlake University,Hangzhou,310030,China
Site-directed immobilizationSilica-binding proteinsOptical biosensingMonkeypox virusSpiked clinical samplesMulti-virus biosensor
《药物分析学报(英文)》 2024 (010)
1496-1504 / 9
This research was supported by Westlake University,China(Startup funds),the Research Center for Industries of the Future of Westlake University,China(Grant No.:WU2022C040),and the National Natural Science Foundation of China(Grant No.:82104122).
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