Biosensor-based diagnosis for infectious diseases: Nano-enabled revolution

Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multidrug-resistant (MDR) and antimicrobial-resistant (AMR) pathogens. The conventional diagnostic methods, such as culture characteristics, microscopical examinations, and polymerase chain reaction (PCR), are reliable but often face challenges like long turnaround times, high costs, and demanding infrastructure and trained personnel. Alternatively, biosensor-based diagnostics have emerged as rapid, cost-effective, and sensitive options for detection of different pathogens. This review delves into the principles, structural components, and classifications of biosensors, emphasizing nano-enabled platforms tailored for diagnosis of IDs. Biosensors are typically comprising a biorecognition element, signal transducer, and data processor. These tools able to convert the molecular interactions into measurable signals through various modalities, including optical (fluorescence, surface plasmon resonance (SPR), chemiluminescence, colorimetric), electrochemical (amperometric, potentiometric, impedimetric), and mass-sensitive formats. The review systematically classifies biosensors based on transduction mechanisms (optical, electrochemical, mass-sensitive, and magnetic) and biorecognition factors, focusing on their advantages and disadvantages. Biosensors are further categorized by bioreceptor type, including aptamers, antibodies, enzymes, peptides, and whole cells, each offering distinct recognition mechanisms. The integration of nanomaterials (NMs), such as gold, silver, magnesium oxide, quantum dots (QDs), and carbon nanotubes (CNTs), enhances the nano-biosensors' sensitivity, miniaturization, and applicability. The review also highlights nano-biosensors that specifically detect the pathogens like Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), Klebsiella pneumoniae (K. pneumoniae), and Pseudomonas aeruginosa (P. aeruginosa), underscoring their clinical relevance and low detection limits. Ultimately, the review discusses current limitations and future pathways for innovation, including multiplexed detection, artificial intelligence (AI) integration, and improved biosensor portability. By enabling early and precise identification of resistant pathogens, nano-biosensors represent a transformative advancement in diagnostic microbiology, particularly in resource-limited settings. Overall, this review demonstrates that nano-enabled biosensors provide rapid and cost-effective options to traditional diagnostic techniques, providing crucial insights for early detection of MDR pathogens and outbreak manipulation.