Disposable all-printed electronic biosensor for instantaneous detection and classification of pathogens

Area of Science:

• Biomedical Engineering
• Materials Science
• Microbiology

Background:

• Rapid and accurate detection of bacterial pathogens is crucial for public health and food safety.
• Existing methods for bacterial identification can be time-consuming and require specialized laboratory equipment.
• There is a need for portable, cost-effective, and user-friendly biosensing platforms for on-site pathogen analysis.

Purpose of the Study:

• To develop and validate a novel disposable all-printed electronic biosensor for the rapid detection and classification of bacteria.
• To assess the performance of the biosensor in distinguishing between common bacterial pathogens, including Salmonella typhimurium and Escherichia coli strains (JM109, DH5-α).
• To explore the application of pattern recognition techniques for analyzing biosensor data and achieving accurate bacterial classification.

Main Methods:

• Fabrication of inter-digital silver electrodes using an inkjet material printer on a polyethylene terephthalate substrate.
• Decoration of electrodes with silver nanowires via electrohydrodynamic technique to enhance sensor sensitivity.
• Optimization of electrode design (200 µm spacing) and silver nanowire density (30 × 10^3/mm^2) for maximal performance.
• Measurement of impedance values for different bacteria types using an impedance analyzer at ±2.5 V.
• Analysis of impedance data using pattern recognition methods (LDA, Maximum Likelihood, BP-ANN) for bacterial classification.

Main Results:

• The optimized printed electronic biosensor demonstrated high sensitivity and selectivity for differentiating between Salmonella typhimurium and Escherichia coli strains.
• The biosensor achieved accurate impedance measurements within 8 minutes of sample injection.
• Pattern recognition methods, including linear discriminate analysis, maximum likelihood, and back propagation artificial neural network, successfully classified each bacterium type.
• Perfect classification and cross-validation were achieved, highlighting the reliability of the biosensor's unique impedance fingerprints.

Conclusions:

• The proposed disposable all-printed electronic biosensor is a viable tool for the rapid and accurate detection and classification of bacterial pathogens.
• The sensor's design, utilizing inkjet-printed electrodes and silver nanowires, offers a cost-effective and scalable solution for pathogen detection.
• The integration of pattern recognition algorithms enhances the biosensor's classification capabilities, paving the way for practical applications in diagnostics and food safety monitoring.