Bacteriophage-Activated DNAzyme Hydrogels Combined with Machine Learning Enable Point-of-Use Colorimetric Detection...

Area of Science:

• Biotechnology
• Environmental Science
• Clinical Diagnostics

Background:

• Current pathogen detection methods rely on time-consuming culturing.
• There is a need for accessible, ultrasensitive, and rapid point-of-use testing platforms.
• Escherichia coli (E. coli) is a significant pathogen in both environmental and clinical settings.

Purpose of the Study:

• To develop a cost-effective, consumer-accessible platform for point-of-use environmental and clinical pathogen testing.
• To create a sensor capable of ultrasensitive detection with minimal equipment and training.
• To specifically detect Escherichia coli (E. coli) in various sample types.

Main Methods:

• A colorimetric DNAzyme-crosslinked hydrogel sensor was developed.
• Hydrogel dissolution upon target pathogen presence releases entrapped gold nanoparticles for visual detection.
• E. coli-responsive DNAzyme and bacteriophage-induced signal amplification were utilized.
• An artificial intelligence model was integrated for sensor readout analysis.

Main Results:

• The sensor detected 10^1 CFU mL^-1 E. coli in lake water samples.
• The AI model achieved 96% true positive and 100% true negative accuracy.
• The platform demonstrated high specificity and stability.
• 100% accuracy was achieved in identifying E. coli in patient urine samples with no false positives in healthy samples.

Conclusions:

• The DNAzyme-crosslinked hydrogel sensor offers a sensitive, specific, and stable method for E. coli detection.
• The platform is suitable for both environmental monitoring and clinical diagnostics.
• This technology significantly enhances pathogen testing accessibility, potentially improving population health.