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Microfluidic One-Pot Digital Droplet FISH Using LNA/DNA Molecular Beacons for Bacteria Detection and Absolute
Yu-Ting Kao1,2, Silvia Calabrese3, Nadine Borst1,3
1Laboratory for MEMS Applications, IMTEK-Department of Microsystems Engineering, University of Freiburg, Georges-Koehler-Allee 103, 79110 Freiburg, Germany.
Biosensors
|April 21, 2022
Summary
This study presents a novel microfluidic assay for rapid bacterial detection and quantification. The wash-free fluorescence in situ hybridization (FISH) method offers high sensitivity and a wide dynamic range, reducing hands-on time for accurate results.
Area of Science:
- Microfluidics
- Molecular Diagnostics
- Bacteriology
Background:
- Accurate bacterial quantification is crucial for clinical diagnostics and research.
- Traditional methods often involve multiple steps, increasing workload and time-to-results.
- Novel approaches are needed to streamline bacterial detection and enumeration.
Purpose of the Study:
- To develop and validate a novel microfluidic one-pot, wash-free fluorescence in situ hybridization (FISH) assay for bacterial load detection and quantification.
- To assess the assay's performance in terms of sensitivity, dynamic range, linearity, and turnaround time.
Main Methods:
- Utilized centrifugal microfluidics for droplet-based sample partitioning (210 pL droplets).
- Integrated bacterial encapsulation, in situ permeabilization, and hybridization within microfluidic cartridges.
- Employed locked nucleic acid (LNA)/DNA molecular beacons (LNA/DNA MBs) and a specialized hybridization buffer.
Main Results:
- Achieved single-cell sensitivity for bacterial detection.
- Demonstrated a 4-log dynamic range, from ~3 × 10^3 to ~3 × 10^7 bacteria/mL.
- Reported high linearity (R^2 = 0.976) with a total time-to-results of approximately 1.5 hours.
Conclusions:
- The developed microfluidic FISH assay provides a rapid, sensitive, and efficient method for bacterial quantification.
- The wash-free, one-pot design significantly minimizes manual workload.
- This technology holds potential for streamlined diagnostic applications requiring bacterial enumeration.
