Hydrogel-Coated Nanonet-Based Field-Effect Transistors for SARS-CoV-2 Spike Protein Detection in High Ionic Strength Samples

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

The SARS-CoV-2 pandemic has triggered many studies worldwide in the area of biosensors, leading to innovative approaches for the quantitative assessment of COVID-19. A nanostructured field-effect transistor (FET) is one type of device shown to be ultrasensitive for virus determination. FETs can be used as transducers to analyze changes in electrical current caused by the bonding of viral molecules to the surface of the semiconducting nanomaterial layer of the FETs. Although nano-transistors require simple setups amenable to be miniaturized for point-of-care diagnostic of COVID-19, this type of sensor usually has limited sensitivity in biological fluids. The reason behind this is the shortened screening length in the presence of high ionic strength solutions. In the frame of this study, we propose a methodology consisting of the FET surface modification with a hydrogel based on the star-shaped polyethylene glycol (starPEG), which hosts specific antibodies against SARS-CoV-2 spike protein in its porous structure. The deposition of the hydrogel increases the effective Debye length, preserving the biosensor’s sensitivity. We demonstrate the capability of silicon nanonet-based FETs to detect viral antigens and cultured viral particles in phosphate-buffered saline (PBS) as well as in human-purified saliva. Finally, we discriminated between positive and negative patients’ nasopharyngeal swab samples.

Details

Original languageEnglish
Title of host publicationHydrogel-Coated Nanonet-Based Field-Effect Transistors for SARS-CoV-2 Spike Protein Detection in High Ionic Strength Samples
Volume35
Edition1
Publication statusPublished - 8 May 2023
Peer-reviewedYes

External IDs

unpaywall 10.3390/iecb2023-14566
ORCID /0000-0002-9899-1409/work/142249233
Scopus 85172771982

Keywords

Keywords

  • COVID-9 diagnostics, Debye screening length, field-effect transistor, hydrogel biosensor, SARS-CoV-2 detection, starPEG