Plasmonic optical fiber biosensors for ultra-low detection of respiratory syncytial virus via point-of-care tests - Federica Passeggio; Luigi Zeni; Massimiliano Galdiero; Francesco Arcadio; Carla Zannella; Anna De Filippis; Chiara Marzano; Ines Tavoletta; Fabiana Napolitano; Rosalba Pitruzzella; Giuseppe Portella; Nunzio Cennamo (Scientific Reports)
Abstract Respiratory syncytial virus (RSV) is a major cause of bronchiolitis and pneumonia, particularly in children, the elderly, and immunocompromised individuals. Despite significant health impacts, annual RSV-related hospitalizations may be underreported due to undertesting and limited diagnostic sensitivity. Point-of-care tests (POCTs) could enhance the rapid and accurate detection of RSV, enabling timely treatment and reducing hospitalizations. In this frame, for the first time, a plasmonic RSV biosensor based on modified plastic optical fibers (POFs) has been developed and tested by functionalizing the plasmonic platform with a specific antibody targeting the RSV fusion (F) protein. This protein was selected because it is the most conserved surface protein between the two RSV subtypes, RSV A and RSV B. The main goal of the work is to develop a biosensor capable of detecting RSV regardless of the subtype (A or B), as subtype discrimination is not clinically relevant for therapeutic decision-making. The POF-based RSV biosensor performance was first obtained via standard solutions with different RSV concentrations to evaluate the binding sensitivity with the target analyte. In such a way, an ultra-low detection limit equal to about 0.88 PFU/mL was achieved. Furthermore, selectivity tests demonstrated the biosensor’s ability to distinguish RSV from other viruses. In addition, nasopharyngeal swab samples were tested. The POCT’s RSV measurement time is about ten minutes. A gold standard analysis confirmed the achieved results. Hence, the results establish the POF-based RSV biosensor as a sensitive, cost-effective, ultra-fast, capable of being connected to the Internet, and a scalable alternative to traditional RSV detection methods, offering a promising tool for improving diagnostic capabilities in clinical and resource-limited settings.