The design of a point of care FET biosensor to detect and screen COVID-19

Advancing transistor-based point-of-care (POC) biosensors: additive manufacturing technologies and device integration strategies for real-life sensing

Infectious pathogens pose a significant threat to public health and healthcare systems, making the development of a point-of-care (POC) detection platform for their early identification a key focus in recent decades. Among the numerous biosensors developed over the years, transistor-based biosensors, particularly those incorporating nanomaterials, have emerged as promising candidates for POC detection, given their unique electronic characteristics, compact size, broad dynamic range, and real-time biological detection capabilities with limits of detection (LODs) down to zeptomolar levels. However, the translation of laboratory-based biosensors into practical applications faces two primary challenges: the cost-effective and scalable fabrication of high-quality transistor sensors and functional device integration. This review is structured into two main parts. The first part examines recent advancements in additive manufacturing technologies-namely in screen printing, inkjet printing, aerosol jet printing, and digital light processing-and evaluates their applications in the mass production of transistor-based biosensors. While additive manufacturing offers significant advantages, such as high quality, cost-effectiveness, rapid prototyping, less instrument reliance, less material waste, and adaptability to diverse surfaces, challenges related to uniformity and yield remain to be addressed before these technologies can be widely adopted for large-scale production. The second part focuses on various functional integration strategies to enhance the practical applicability of these biosensors, which is essential for their successful translation from laboratory research to commercialization. Specifically, it provides a comprehensive review of current miniaturized lab-on-a-chip systems, microfluidic manipulation, simultaneous sampling and detection, wearable implementation, and integration with the Internet of Things (IoT).

The Versatility of Biological Field-Effect Transistor-Based Biosensors (BioFETs) in Point-of-Care Diagnostics: Applications and Future Directions for Peritoneal Dialysis Monitoring

Peritoneal dialysis (PD) is a vital treatment for end-stage renal disease patients, but its efficacy is often compromised by complications such as infections and peritoneal fibrosis. Biological field-effect transistors (BioFETs) present a promising solution for rapid, sensitive, and non-invasive detection of indicators and biomarkers associated with these complications, potentially enabling early intervention. However, BioFETs are yet to be adopted for PD monitoring. This review presents a forward-looking analysis of the capacity and potential integration of BioFETs into PD management systems, highlighting their capacity to monitor both routine indicators of dialysis efficiency and metabolic status, as well as specific biomarkers for complications such as inflammation and fibrosis. We examine the challenges in adapting BioFETs for PD applications, focusing on key areas for improvement, including sensitivity, specificity, stability, reusability, and clinical integration. Furthermore, we discuss various approaches to address these challenges, which are crucial for developing point-of-care (PoC) and multiplexed wearable devices. These advancements could facilitate continuous, precise, and user-friendly monitoring, potentially revolutionizing PD complication management and enhancing patient care.

Modeling Carbon-Based Nanomaterials (CNMs) and Derived Composites and Devices

A review of different modeling techniques, specifically in the framework of carbon-based nanomaterials (CNMs, including nanoparticles such as graphene and carbon nanotubes-CNTs) and the composites and devices that can be derived from them, is presented. The article emphasizes that the overall performance of these materials depends on mechanisms that operate across different time and spatial scales, requiring tailored approaches based on the material type, size, internal structure/configuration, and the specific properties of interest. Far from attempting to cover the entire spectrum of models, this review examines a wide range of analysis and simulation techniques, highlighting their potential use, some of their weaknesses and strengths, and presenting the latest developments and some application examples. In this way, it is shown how modeling can provide key information for tailoring or designing new materials for specific components or systems or to obtain certain functionalities. At the same time, it is revealed to be an area constantly undergoing development and improvement, as evidenced by the progress made by various of these techniques and the new modeling approaches that have emerged in recent years.

FEM simulation of SARS-CoV-2 sensing in single-layer graphene-based bionanosensors

CONTEXT

Airborne pathogens, defined as microscopic organisms, pose significant health risks and can potentially cause a variety of diseases. Given their ability to spread through diverse transmission routes from infected hosts, there is a critical need for accurate monitoring of these pathogens. This study aims to develop a sensor by investigating the vibrational responses of cantilever and bridged boundary-conditioned single-layer graphene (SLG) sheets with microorganisms, specifically SARS-CoV-2, attached at various positions on the sheet. The dynamic analysis of SLG with different boundary conditions and lengths was conducted using the atomistic finite element method (AFEM). Simulations were performed to evaluate SLG's performance as a sensor for biological entities. Altering the sheet's length and the mass of the attached biological object revealed observable frequency differences. This sensor design shows promise for enhancing the detection capabilities of graphene-based technologies for viruses.

METHODS

Finite element method (FEM) analysis is employed to model the sensor's performance and optimize its design parameters. The simulation results highlight the sensor's potential for achieving high sensitivity and rapid detection of SARS-CoV-2. Bridged and cantilever boundary conditions are applied at the ends of the SLG structure by using ANSYS software. Simulations have been conducted to observe how SLG behaves when used as sensors. In armchair graphene, under both boundary conditions, an SLG (5, 5) structure with a length of 50 nm displayed the highest frequency when a SARS-CoV-2 molecule with a mass of 2.6594 × 10-18 g was attached. Conversely, the chiral SLG (17, 1) structure exhibited its lowest frequency at a length of 10 nm. This insight is crucial for grasping detection limits and how factors such as size and boundary conditions influence sensor efficacy. These biosensors hold immense promise in biological sciences and medical applications, revolutionizing patient care by enabling early detection and accurate pathogen identification in clinical settings.

Bionanosensor utilizing single-layer graphene for the detection of iridovirus

CONTEXT

Iridoviruses, a group of double-stranded DNA viruses, pose a significant threat to various aquatic animals, causing substantial economic losses in aquaculture and impacting ecosystem health. Early and accurate detection of these viruses is crucial for effective disease management and control. Conventional diagnostic methods, including polymerase chain reaction (PCR) and virus isolation, often require specialized laboratories, skilled personnel, and considerable time. This highlights the need for rapid, sensitive, and cost-effective diagnostic tools for iridovirus detection. Single-layer graphene, a two-dimensional material with unique properties like high surface area, excellent electrical conductivity, and chemical stability, has emerged as a versatile platform for biosensing applications. This paper explores the potential of employing single-layer graphene in the development of a bionanosensor for the sensitive and rapid detection of iridoviruses. The aim of the present investigation is to develop a sensor by analyzing the vibrational responses of single-layer graphene sheets (SLGS) with attached microorganisms. Graphene-based virus sensors typically rely on the interaction between the virus and the graphene surface, which lead to changes in the frequency response of graphene. This change is measured and used to detect the presence of the virus. Its high surface-to-volume ratio and sensitivity to changes in its frequency make it a highly sensitive platform for virus detection.

METHODS

We employ finite element method (FEM) analysis to model the sensor's performance and optimize its design parameters. The simulation results highlight the sensor's potential for achieving high sensitivity and rapid detection of iridovirus. Bridged and simply supported with roller support boundary conditions applied at the ends of SLG structure. Simulations have been performed to see how SLG behaves when used as sensors. A single-layer graphene armchair SLG (5,5) with 50-nm length exhibits its highest frequency vibration at 8.66 × 106 Hz, with a mass of 1.2786 Zg. In contrast, a zigzag-SLG with a (18,0) configuration has its lowest frequency vibration at 2.82 × 105 Hz. This aids in comprehending the thresholds of detection and the influence of factors such as size, and boundary conditions on sensor effectiveness. These biosensors can be especially helpful in biological sciences and the medical field since they can considerably improve the treatment of patients, cancer early diagnosis, and pathogen identification when used in clinical environments.

Label-Free Field Effect Transistors (FETs) for Fabrication of Point-of-Care (POC) Biomedical Detection Probes

Field effect transistors (FETs)-based detection probes are powerful platforms for quantification in biological media due to their sensitivity, ease of miniaturization, and ability to function in biological media. Especially, FET-based platforms have been utilized as promising probes for label-free detections with the potential for use in real-time monitoring. The integration of new materials in the FET-based probe enhances the analytical performance of the developed probes by increasing the active surface area, rejecting interfering agents, and providing the possibility for surface modification. Furthermore, the use of new materials eliminates the need for traditional labeling techniques, providing rapid and cost-effective detection of biological analytes. This review discusses the application of materials in the development of FET-based label-free systems for point-of-care (POC) analysis of different biomedical analytes from 2018 to 2024. The mechanism of action of the reported probes is discussed, as well as their pros and cons were also investigated. Also, the possible challenges and potential for the fabrication of commercial devices or methods for use in clinics were discussed.

High enhancement of sensitivity and reproducibility in label-free SARS-CoV-2 detection with graphene field-effect transistor sensors through precise surface biofunctionalization control

The COVID-19 pandemic has taught us valuable lessons, especially the urgent need for a widespread, rapid and sensitive diagnostic tool. To this, the integration of bidimensional nanomaterials, particularly graphene, into point-of-care biomedical devices is a groundbreaking strategy able to potentially revolutionize the diagnostic landscape. Despite advancements in the fabrication of these biosensors, the relationship between their surface biofunctionalization and sensing performance remains unclear. Here, we demonstrate that the combination of careful sensor fabrication and its precise surface biofunctionalization is crucial for exalting the sensing performances of 2D biosensors. Specifically, we have biofunctionalized Graphene Field-Effect Transistor (GFET) sensors surface through different biochemical reactions to promote either random/heterogeneous or oriented/homogeneous immobilization of the Anti-SARS-CoV-2 spike protein antibody. Each strategy was thoroughly characterized by in-silico simulations, physicochemical and biochemical techniques and electrical characterization. Subsequently, both biosensors were tested in the label-free direct titration of SARS-CoV-2 virus in simulated clinical samples, avoiding sample preprocessing and within short timeframes. Remarkably, the oriented GFET biosensor exhibited significantly enhanced reproducibility and responsiveness, surpassing the detection sensitivity of conventional non-oriented GFET by more than twofold. This breakthrough not only involves direct implications for COVID-19 surveillance and next pandemic preparedness but also clarify an unexplored mechanistic dimension of biosensor research utilizing 2D-nanomaterials.

Graphene transistor-based biosensors for rapid detection of SARS-CoV-2

Field-effect transistor (FET) biosensors use FETs to detect changes in the amount of electrical charge caused by biomolecules like antigens and antibodies. COVID-19 can be detected by employing these biosensors by immobilising bio-receptor molecules that bind to the SARS-CoV-2 virus on the FET channel surface and subsequent monitoring of the changes in the current triggered by the virus. Graphene Field-effect Transistor (GFET)-based biosensors utilise graphene, a two-dimensional material with high electrical conductivity, as the sensing element. These biosensors can rapidly detect several biomolecules including the SARS-CoV-2 virus, which is responsible for COVID-19. GFETs are ideal for real-time infectious illness diagnosis due to their great sensitivity and specificity. These graphene transistor-based biosensors could revolutionise clinical diagnostics by generating fast, accurate data that could aid pandemic management. GFETs can also be integrated into point-of-care (POC) diagnostic equipment. Recent advances in GFET-type biosensors for SARS-CoV-2 detection are discussed here, along with their associated challenges and future scope.

Machine Learning for COVID-19 Determination Using Surface-Enhanced Raman Spectroscopy

The rapid, low cost, and efficient detection of SARS-CoV-2 virus infection, especially in clinical samples, remains a major challenge. A promising solution to this problem is the combination of a spectroscopic technique: surface-enhanced Raman spectroscopy (SERS) with advanced chemometrics based on machine learning (ML) algorithms. In the present study, we conducted SERS investigations of saliva and nasopharyngeal swabs taken from a cohort of patients (saliva: 175; nasopharyngeal swabs: 114). Obtained SERS spectra were analyzed using a range of classifiers in which random forest (RF) achieved the best results, e.g., for saliva, the precision and recall equals 94.0% and 88.9%, respectively. The results demonstrate that even with a relatively small number of clinical samples, the combination of SERS and shallow machine learning can be used to identify SARS-CoV-2 virus in clinical practice.

Graphene-based biosensors for detecting coronavirus: a brief review

The coronavirus (SARS-CoV-2) disease has affected the globe with 770 437 327 confirmed cases, including about 6 956 900 deaths, according to the World Health Organization (WHO) as of September 2023. Hence, it is imperative to develop diagnostic technologies, such as a rapid cost-effective SARS-CoV-2 detection method. A typical biosensor enables biomolecule detection with an appropriate transducer by generating a measurable signal from the sample. Graphene can be employed as a component for ultrasensitive and selective biosensors based on its physical, optical, and electrochemical properties. Herein, we briefly review graphene-based electrochemical, field-effect transistor (FET), and surface plasmon biosensors for detecting the SARS-CoV-2 target. In addition, details on the surface modification, immobilization, sensitivity and limit of detection (LOD) of all three sensors with regard to SARS-CoV-2 were reported. Finally, the point-of-care (POC) detection of SARS-CoV-2 using a portable smartphone and a wearable watch is a current topic of interest.

Sybodies as Novel Bioreceptors toward Field-Effect Transistor-Based Detection of SARS-CoV-2 Antigens

The SARS-CoV-2 pandemic has increased the demand for low-cost, portable, and rapid biosensors, driving huge research efforts toward new nanomaterial-based approaches with high sensitivity. Many of them employ antibodies as bioreceptors, which have a costly development process that requires animal facilities. Recently, sybodies emerged as a new alternative class of synthetic binders and receptors with high antigen binding efficiency, improved chemical stability, and lower production costs via animal-free methods. Their smaller size is an important asset to consider in combination with ultrasensitive field-effect transistors (FETs) as transducers, which respond more intensely when biorecognition occurs near their surface. This work demonstrates the immobilization of sybodies against the spike protein of the virus on silicon surfaces, which are often integral parts of the semiconducting channel of FETs. Immobilized sybodies maintain the capability to capture antigens, even at low concentrations in the femtomolar range, as observed by fluorescence microscopy. Finally, the first proof of concept of sybody-modified FET sensing is provided using a nanoscopic silicon net as the sensitive area where the sybodies are immobilized. The future development of further sybodies against other biomarkers and their generalization in biosensors could be critical to decrease the cost of biodetection platforms in future pandemics.

Gold nanostructures modified carbon-based electrode enhanced with methylene blue for point-of-care COVID-19 tests using isothermal amplification

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) envelope (E) and RNA-dependent RNA polymerase (RdRP) genes were detected via electrochemical measurements using a screen-printed carbon electrode (SPCE) (3-electrode system) coupled with a battery-operated thin-film heater based on the loop-mediated isothermal amplification (LAMP) technique. The working electrodes of the SPCE sensor were decorated with synthesized gold nanostars (AuNSs) to obtain a large surface area and improve sensitivity. The LAMP assay was enhanced using a real-time amplification reaction system to detect the optimal target genes (E and RdRP) of SARS-CoV-2. The optimized LAMP assay was performed with diluted concentrations (from 0 to 10⁹ copies) of the target DNA using 30 μM of methylene blue as a redox indicator. Target DNA amplification was conducted for 30 min at a constant temperature using a thin-film heater, and the final amplicon electrical signals were detected based on cyclic voltammetry curves. Our electrochemical LAMP analysis of SARS-CoV-2 clinical samples showed an excellent correlation with the Ct value of real-time reverse transcriptase-polymerase chain reaction, indicating successful validation of results. A linear relationship between the peak current response and the amplified DNA was observed for both genes. The AuNS-decorated SPCE sensor with the optimized LAMP primer enabled accurate analysis of both SARS-CoV-2-positive and -negative clinical samples. Therefore, the developed device is suitable for use as a point-of-care test DNA-based sensor for the diagnosis of SARS-CoV-2.