ABSTRACT
In food safety analysis, the detection and control of foodborne pathogens and their toxins are of great importance. Monitoring of virus transmission is equally important, especially in light of recent findings that coronaviruses have been detected in frozen foods and packages during the current global epidemic of coronavirus disease 2019. In recent years, field-effect transistor (FET) biosensors have attracted considerable scholarly attention for pathogenic microorganisms and toxins detection and sensing due to their rapid response time, high sensitivity, wide dynamic range, high specificity, label-free detection, portability, and cost-effectiveness. FET-based biosensors can be modified with specific recognition elements, thus providing real-time qualitative and semiquantitative analysis. Furthermore, with advances in nanotechnology and device design, various high-performance nanomaterials are gradually applied in the detection of FET-based biosensors. In this article, we review specific detection in different biological recognition elements are immobilized on FET biosensors for the detection of pathogenic microorganisms and toxins, and we also discuss nonspecific detection by FET biosensors. In addition, there are still unresolved challenges in the development and application of FET biosensors for achieving efficient, multiplexed, in situ detection of pathogenic microorganisms and toxins. Therefore, directions for future FET biosensor research and applications are discussed.
ABSTRACT
The rapid and sensitive detection of trace-level viruses in a simple and reliable way is of great importance for epidemic prevention and control. Here, a multi-functionalized floating gate carbon nanotube field effect transistor (FG-CNT FET) based biosensor is reported for the single virus level detection of SARS-CoV-2 virus antigen and RNA rapidly with a portable sensing platform. The aptamers functionalized sensors can detect SARS-CoV-2 antigens from unprocessed nasopharyngeal swab samples within 1 min. Meanwhile, enhanced by a multi-probe strategy, the FG-CNT FET-based biosensor can detect the long chain RNA directly without amplification down to single virus level within 1 min. The device, constructed with packaged sensor chips and a portable sensing terminal, can distinguish 10 COVID-19 patients from 10 healthy individuals in clinical tests both by the RNAs and antigens by a combination detection strategy with an combined overall percent agreement (OPA) close to 100%. The results provide a general and simple method to enhance the sensitivity of FET-based biochemical sensors for the detection of nucleic acid molecules and demonstrate that the CNT FG FET biosensor is a versatile and reliable integrated platform for ultrasensitive multibiomarker detection without amplification and has great potential for point-of-care (POC) clinical tests.
ABSTRACT
SARS-CoV-2 RNA is identified as a pivotal player to bolster energizing zones of COVID-19 detection. Herein, we develop a rapid and unamplified nanosensing platform for detection of SARS-CoV-2 RNA in human throat swab specimens. A gold nanoparticle (AuNP)-decorated graphene field-effect transistor (G-FET) sensor was fabricated, after which complementary phosphorodiamidate morpholino oligos (PMO) probe was immobilized on the AuNP surface. This sensor allowed for highly sensitive testing of SARS-CoV-2 RdRp as PMO does not have charges, leading to low background signal. Not only did the method present a low limit of detection in PBS (0.37 fM), throat swab (2.29 fM), and serum (3.99 fM), but also it achieved a rapid response to COVID-19 patients' samples within 2 min. The developed nanosensor was capable of analyzing RNA extracts from 30 real clinical samples. The results show that the sensor could differentiate the healthy people from infected people, which are in high agreement with RT-PCR results (Kappa index = 0.92). Furthermore, a well-defined distinction between SARS-CoV-2 RdRp and SARS-CoV RdRp was also made. Therefore, we believe that this work provides a satisfactory, attractive option for COVID-19 diagnosis.