The contamination of food and the environment by pathogens poses a significant threat to global food safety and public health. While bacterial contamination is more frequently reported, viral contamination, with its high transmissibility, also presents a substantial risk. Recent outbreaks of hepatitis A and norovirus highlight this threat, with viruses being detected in various food sources and water. The COVID-19 pandemic, caused by SARS-CoV-2, further emphasizes this concern. Although direct evidence of foodborne transmission of SARS-CoV-2 is limited, its contamination of food, especially cold-chain foods, is a significant risk due to the virus's stability at low temperatures. The long survival time at below 0°C and the need for testing a large number of samples necessitate sensitive, rapid, and low-cost detection methods. Current methods, such as culture/counting and PCR-based techniques, have limitations in terms of speed and cost. Culture methods are time-consuming, while PCR-based methods, though more common, still require several hours for results. Antibody-based biosensors offer a promising alternative due to their specificity and versatility. The SARS-CoV-2 spike (S-) protein, specifically the S1 subunit, is an ideal biomarker for detection due to its abundance and exposure on the virion surface, making it a suitable target for antibody-based detection. This research introduces a novel method for the rapid and sensitive detection of the S1 subunit of the SARS-CoV-2 spike protein using an interdigitated microelectrode (IDME) chip, dieletrophoresis, and interfacial capacitance sensing. This method aims to address the need for real-time, selective, and cost-effective screening of SARS-CoV-2 contamination in cold-chain food.

Existing methods for virus detection in food primarily involve culture/counting and PCR-based approaches. While PCR is faster than culture, it remains time-consuming, typically taking several hours. The literature highlights numerous applications of PCR and RT-PCR for detecting various viruses in food, including hepatitis A, hepatitis E, and norovirus. However, the complexity and time constraints associated with PCR have spurred the development of bio-probe-based sensors as promising alternatives. Antibody-based detection methods are particularly attractive due to their high specificity, reproducibility, and stability, making them well-suited for food safety applications. Research on SARS-CoV-2 detection has focused on various biomarkers, with the S-protein, particularly the S1 subunit, gaining prominence due to its surface exposure and role in receptor binding. Various approaches, including near-infrared nanosensors and cell-based biosensors, have been explored for S-protein detection, but a need persists for a method that combines speed, sensitivity, selectivity, and low cost.

This study employs a novel immunosensor based on a low-cost interdigitated microelectrode (IDME) chip modified with an anti-SARS-CoV-2 S-protein antibody. The sensor's functionalization was verified using X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy. XPS analysis confirmed the presence of nitrogen (N1s), a characteristic element of the antibody, on the modified IDME surface. Electrochemical impedance spectroscopy showed an increase in impedance after antibody modification, indicating successful immobilization. Dielectrophoresis (DEP) was utilized to efficiently enrich the target S-protein particles toward the sensor surface. An alternating current (AC) signal was applied to the IDME chip to generate a DEP force, driving the S-proteins towards the antibody-coated surface for capture. The detection principle relies on measuring the change in interfacial capacitance at the IDME surface, with the decrease in capacitance directly correlating to the amount of captured S-protein. The limit of detection (LOD), linear range, and selectivity of the sensor were determined experimentally. The sensor's performance was evaluated using different concentrations of S-protein in phosphate-buffered saline (PBS) to establish a calibration curve. Specificity was assessed by testing the sensor's response to various interferents, including nucleocapsid (N-) protein, peptidoglycan (PGN), and lipopolysaccharide (LPS). Finally, the sensor was validated using real-world samples spiked with S-protein, including melted tap water, salmon extracts, scallop extracts, and extracts from a beef packing bag. These samples were pretreated using centrifugation to remove interfering substances. The capacitance changes were measured using an impedance analyzer, and the data were analyzed to determine the concentration of S-protein.

The developed immunosensor demonstrated a remarkable limit of detection (LOD) of 2.29 × 10⁻¹⁰ ng/mL for S-protein within 20 seconds. This ultra-low LOD significantly enhances the sensitivity for detecting trace levels of SARS-CoV-2 in cold-chain food. The sensor exhibited a wide linear range spanning from 10⁻⁵ to 10⁻¹ ng/mL, enabling the detection of S-protein across a broad concentration range. High selectivity of the sensor was demonstrated with a selectivity ratio of 234:1 for S-protein against the interfering substances tested (N-protein, PGN, and LPS). The sensor successfully detected S-protein spiked in various real-world samples, including tap water, salmon, scallop, and packing bag extracts, demonstrating its applicability to various matrices. Despite the complexity of the food matrices, especially the salmon samples rich in lipids, the sensor was able to detect the target protein effectively, demonstrating its robustness. The cost-effectiveness of the sensor, estimated at approximately $1 per test, makes it suitable for large-scale applications. The ease of operation and minimal sample pretreatment also contribute to the practicality of the method for on-site detection and screening.

This study successfully developed and validated a rapid, sensitive, and cost-effective method for detecting trace levels of SARS-CoV-2 S-protein in cold-chain food samples. The ultra-low LOD achieved is crucial for detecting low levels of viral contamination, as virus replication is unlikely to occur on food surfaces. The high selectivity of the sensor ensures reliable detection even in complex matrices containing various interferents. The method addresses the urgent need for rapid screening in cold-chain food quarantine, offering a practical solution to minimize the risk of SARS-CoV-2 transmission through food. The low cost and ease of use further contribute to the practicality of widespread implementation for food safety surveillance and monitoring. The findings have significant implications for public health, food safety, and the management of future pandemics.

This research presents a highly sensitive, selective, and cost-effective immunosensor for the rapid detection of SARS-CoV-2 S-protein in cold-chain food. The method's ultra-low LOD, wide linear range, high selectivity, and low cost make it a promising tool for large-scale applications in food quarantine and safety. Future research could explore the application of this technology for detecting other foodborne viruses and adapting the platform for diverse food matrices to improve sensitivity and broaden its utility in global food safety management. Further investigation could focus on miniaturization for point-of-care testing.

While the sensor demonstrated excellent performance in various matrices, it's important to acknowledge limitations. The study relied on spiked samples rather than naturally contaminated samples due to the difficulty in obtaining confirmed positive samples. Also, the sample pretreatment, specifically centrifugation, might potentially lead to loss of the target protein. The effectiveness of the dielectrophoresis enrichment might vary based on the composition of the food matrices.