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Moreira G, Qian H, Datta SPA, Bliznyuk N, Carpenter J, Dean D, McLamore E, Vanegas D. A capacitive laser-induced graphene based aptasensor for SARS-CoV-2 detection in human saliva. PLoS One 2023; 18:e0290256. [PMID: 37590297 PMCID: PMC10434860 DOI: 10.1371/journal.pone.0290256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 08/03/2023] [Indexed: 08/19/2023] Open
Abstract
SARS-CoV-2 virus induced CoVID-19 pandemic has accelerated the development of diagnostic tools. Devices integrated with electrochemical biosensors may be an interesting alternative to respond to the high demand for testing, particularly in contexts where access to standard detection technologies is lacking. Aptamers as recognition elements are useful due to their stability, specificity, and sensitivity to binding target molecules. We have developed a non-invasive electrochemical aptamer-based biosensor targeting SARS-CoV-2 in human saliva. The aptamer is expected to detect the Spike protein of SARS-CoV-2 wildtype and its variants. Laser-induced graphene (LIG) electrodes coated with platinum nanoparticles were biofunctionalized with a biotin-tagged aptamer. Electrochemical Impedance Spectroscopy (EIS) for BA.1 sensing was conducted in sodium chloride/sodium bicarbonate solution supplemented with pooled saliva. To estimate sensing performance, the aptasensor was tested with contrived samples of UV-attenuated virions from 10 to 10,000 copies/ml. Selectivity was assessed by exposing the aptasensor to non-targeted viruses (hCoV-OC43, Influenza A, and RSV-A). EIS data outputs were further used to select a suitable response variable and cutoff frequency. Capacitance increases in response to the gradual loading of the attenuated BA.1. The aptasensor was sensitive and specific for BA.1 at a lower viral load (10-100 copies/ml) and was capable of discriminating between negative and positive contrived samples (with strain specificity against other viruses: OC43, Influenza A, and RSV-A). The aptasensor detected SARS-CoV-2 with an estimated LOD of 1790 copies/ml in contrived samples. In human clinical samples, the aptasensor presents an accuracy of 72%, with 75% of positive percent of agreement and 67% of negative percent of agreement. Our results show that the aptasensor is a promising candidate to detect SARS-CoV-2 during early stages of infection when virion concentrations are low, which may be useful for preventing the asymptomatic spread of CoVID-19.
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Affiliation(s)
- Geisianny Moreira
- Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, United States of America
- Department of Agricultural Sciences, Clemson University, Clemson, South Carolina, United States of America
- Global Alliance for Rapid Diagnostics, Michigan State University, East Lancing, Michigan, United States of America
| | - Hanyu Qian
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Shoumen Palit Austin Datta
- Department of Mechanical Engineering, MIT Auto-ID Labs, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Anesthesiology, Medical Device (MDPnP) Interoperability and Cybersecurity Labs, Biomedical Engineering Program, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Nikolay Bliznyuk
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Jeremiah Carpenter
- Center for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, South Carolina, United States of America
- Department of Bioengineering, Clemson University, Clemson, South Carolina, United States of America
| | - Delphine Dean
- Center for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, South Carolina, United States of America
- Department of Bioengineering, Clemson University, Clemson, South Carolina, United States of America
| | - Eric McLamore
- Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, United States of America
- Department of Agricultural Sciences, Clemson University, Clemson, South Carolina, United States of America
- Global Alliance for Rapid Diagnostics, Michigan State University, East Lancing, Michigan, United States of America
| | - Diana Vanegas
- Environmental Engineering and Earth Sciences, Clemson University, Clemson, South Carolina, United States of America
- Global Alliance for Rapid Diagnostics, Michigan State University, East Lancing, Michigan, United States of America
- Interdisciplinary Group for Biotechnology Innovation and Ecosocial Change -BioNovo, Universidad del Valle, Cali, Colombia
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