Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence...

Area of Science:

• Microfluidics
• Bacteriology
• Diagnostic Technology

Background:

• Conventional methods for bacterial trapping and identification are often time-consuming and technically demanding.
• Rapid detection of bacterial pathogens is crucial for timely clinical intervention and disease control.

Purpose of the Study:

• To demonstrate a novel microfluidic device, Adaptive Channel Bacterial Capture (ACBC), for rapid bacterial pathogen capture, enrichment, and identification.
• To evaluate the efficiency of ACBC in trapping low-density bacterial samples and its integration with species identification and antimicrobial susceptibility testing.

Main Methods:

• Utilized polydimethylsiloxane (PDMS) microfluidic devices with controlled backpressure to form bacterial capture regions.
• Employed multiplexed 16S rRNA-Fluorescence In Situ Hybridization (FISH) for species identification.
• Integrated ACBC with an ultra-rapid antimicrobial susceptibility testing (AST) method using fluorescence imaging and convolutional neural network (CNN) classification.

Main Results:

• Achieved near 100% capture efficiency for bacteria from samples with concentrations below 1000 cells/mL.
• Successfully identified seven bacterial species, including *Escherichia coli* and *Staphylococcus aureus*, with 70-98% accuracy within one hour.
• Demonstrated the ACBC chip's capability as an imaging flow cytometer for predicting antibiotic susceptibility in *E. coli*.

Conclusions:

• ACBC devices offer a rapid, efficient, and low-cost alternative for bacterial pathogen detection and characterization.
• The integrated system allows for rapid species identification and antibiotic susceptibility prediction, paving the way for faster clinical diagnostics.
• This technology has the potential to significantly improve the speed and accuracy of diagnosing bacterial infections.