CoVSense: Ultrasensitive Nucleocapsid Antigen Immunosensor for Rapid Clinical Detection of Wildtype and Variant SARS-CoV-2.
Adv Sci (Weinh)
; 10(15): e2206615, 2023 05.
Article
in English
| MEDLINE | ID: covidwho-2279406
ABSTRACT
The widespread accessibility of commercial/clinically-viable electrochemical diagnostic systems for rapid quantification of viral proteins demands translational/preclinical investigations. Here, Covid-Sense (CoVSense) antigen testing platform; an all-in-one electrochemical nano-immunosensor for sample-to-result, self-validated, and accurate quantification of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N)-proteins in clinical examinations is developed. The platform's sensing strips benefit from a highly-sensitive, nanostructured surface, created through the incorporation of carboxyl-functionalized graphene nanosheets, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOTPSS) conductive polymers, enhancing the overall conductivity of the system. The nanoengineered surface chemistry allows for compatible direct assembly of bioreceptor molecules. CoVSense offers an inexpensive (<$2 kit) and fast/digital response (<10 min), measured using a customized hand-held reader (<$25), enabling data-driven outbreak management. The sensor shows 95% clinical sensitivity and 100% specificity (Ct<25), and overall sensitivity of 91% for combined symptomatic/asymptomatic cohort with wildtype SARS-CoV-2 or B.1.1.7 variant (N = 105, nasal/throat samples). The sensor correlates the N-protein levels to viral load, detecting high Ct values of ≈35, with no sample preparation steps, while outperforming the commercial rapid antigen tests. The current translational technology fills the gap in the workflow of rapid, point-of-care, and accurate diagnosis of COVID-19.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
SARS-CoV-2
/
COVID-19
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Topics:
Variants
Limits:
Humans
Language:
English
Journal:
Adv Sci (Weinh)
Year:
2023
Document Type:
Article
Affiliation country:
Advs.202206615
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