Ultrasensitive, Real-Time Detection of Viral Antigens and RNA Enabled by Scalable Graphene-Based FET Sensors for Pathogen Detection: A Case Study on COVID-19
Herein, a novel and simple electrospray (ES) printing technique was developed for the fabrication of ultrathin graphene layers with precisely controlled nanometer-scale thickness, where graphene oxide (GO) was electrosprayed on wafers and subsequently chemically reduced into reduced GO (rGO). Utilizing that technique, we prepared ultrathin rGO in-plane graphene field-effect transistor (GFET)-based biosensors coupled with a portable prototype measuring system for point-of-care detection of pathogens. We illustrate the use of such prepared GFETs to detect COVID-19, using the SARS-CoV-2 nucleocapsid protein antigen (N-protein) and genomic viral RNA as detection targets. The electrosprayed and chemically reduced rGO films enhance the molecular detection in GFET sensors through significant local gating effects. The device detects the N-protein from the SARS-CoV-2 Omicron variant in a culture medium with an LOD of 1.44 PFU/mL and in clinical oropharyngeal samples with an LOD of 45 genome copies/mL in 5 min. It also successfully detects viral RNA in oropharyngeal swabs within 10 min. The GFET sensor responses were further analyzed using our proprietary wireless, miniaturized, and portable FET analyzer, coupled with a smartphone detecting app. Altogether, we present low-cost and mass-producible GFETs with high-quality graphene channels, enabling a portable, efficient, and accurate solution for point-of-care pathogen detection and in clinical testing. This technology has the potential to become a crucial tool in preventing future global epidemic outbreaks.
Authors
- Congcong Zhu (ORCID: https://orcid.org/0000-0002-0143-7453)
- John J. Taylor (ORCID: https://orcid.org/0000-0002-0766-186X)
- Jadranka Travaš‐Sejdić (ORCID: https://orcid.org/0000-0002-1205-3770)
- Yu Luo (ORCID: https://orcid.org/0000-0002-2333-1457)
- Bicheng Zhu (ORCID: https://orcid.org/0000-0003-1230-0863)
- Ashley Nutsford (ORCID: https://orcid.org/0009-0004-4184-0660)
- Claire Honney
- Erasmus Smit (ORCID: https://orcid.org/0000-0003-3286-798X)
- Kean Chin Aw (ORCID: https://orcid.org/0000-0001-9308-508X)
- Chaofeng Ma (ORCID: https://orcid.org/0000-0001-9834-8766)
- Peikai Zhang (ORCID: https://orcid.org/0000-0002-7190-7270)
- Rui Wu (ORCID: https://orcid.org/0009-0009-5352-4506)
- Hailong Chen (ORCID: https://orcid.org/0000-0003-3310-6330)
- Penghui Lai (ORCID: https://orcid.org/0009-0004-7163-4040)
Institutions
- Agency for Science, Technology and Research (SG)
- University of Auckland (NZ)
- Auckland City Hospital (NZ)
- Victoria University of Wellington (NZ)
- Xian Center for Disease Control and Prevention (CN)
- Maurice Wilkins Centre (NZ)
- New Zealand Institute for Public Health and Forensic Science (NZ)
- Xi'an Jiaotong University (CN)
- MacDiarmid Institute for Advanced Materials and Nanotechnology (NZ)
Publication Details
- Journal
- ACS Sensors
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1021/acssensors.4c03049
- Citations
- 5
- Primary Topic
- SARS-CoV-2 detection and testing
- Type
- article
- Field-Weighted Citation Impact
- 6.98
Funders
- National Natural Science Foundation of China
- Health Research Council of New Zealand