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    Hyperspectral Mapping for the Detection of SARS-CoV-2 Using Nanomolecular Probes with Yoctomole Sensitivity

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    Author
    Alafeef, Maha
    Moitra, Parikshit
    Dighe, Ketan
    Pan, Dipanjan
    Date
    2021-07-19
    Journal
    ACS Nano
    Publisher
    American Chemical Society
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1021/acsnano.1c05226
    Abstract
    Efficient monitoring of SARS-CoV-2 outbreak requires the use of a sensitive and rapid diagnostic test. Although SARS-CoV-2 RNA can be detected by RT-qPCR, the molecular-level quantification of the viral load is still challenging, time-consuming, and labor-intensive. Here, we report an ultrasensitive hyperspectral sensor (HyperSENSE) based on hafnium nanoparticles (HfNPs) for specific detection of COVID-19 causative virus, SARS-CoV-2. Density functional theoretical calculations reveal that HfNPs exhibit higher changes in their absorption wavelength and light scattering when bound to their target SARS-CoV-2 RNA sequence relative to the gold nanoparticles. The assay has a turnaround time of a few seconds and has a limit of detection in the yoctomolar range, which is 1 000 000-fold times higher than the currently available COVID-19 tests. We demonstrated in ∼100 COVID-19 clinical samples that the assay is highly sensitive and has a specificity of 100%. We also show that HyperSENSE can rapidly detect other viruses such as influenza A H1N1. The outstanding sensitivity indicates the potential of the current biosensor in detecting the prevailing presymptomatic and asymptomatic COVID-19 cases. Thus, integrating hyperspectral imaging with nanomaterials establishes a diagnostic platform for ultrasensitive detection of COVID-19 that can potentially be applied to any emerging infectious pathogen.
    Keyword
    SARS-CoV-2
    antisense oligonucleotides
    dark-field microscopy
    hafnium
    hyperspectral imaging
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/16270
    ae974a485f413a2113503eed53cd6c53
    10.1021/acsnano.1c05226
    Scopus Count
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    UMB Coronavirus Publications
    UMB Open Access Articles

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