Bacterial autoinducer-2 detection via an engineered quorum sensing protein.

Area of Science:

• Microbiology
• Biotechnology
• Analytical Chemistry

Background:

• Autoinducer-2 (AI-2) is a key bacterial quorum sensing (QS) molecule involved in interspecies communication.
• AI-2 plays a critical role in regulating QS pathways in human and foodborne pathogens.
• Rapid and sensitive detection methods for AI-2 are crucial for early bacterial infection diagnosis.

Purpose of the Study:

• To develop a rapid, selective, and highly sensitive protein-based biosensing system for AI-2 detection.
• To establish a method for quantifying AI-2 at subnanomolar concentrations.
• To validate the biosensing system's efficacy in clinical samples.

Main Methods:

• Utilized Fluorescence Resonance Energy Transfer (FRET) between a LuxP-EGFP protein fusion and MDCC.
• Engineered a protein-based biosensor for AI-2 recognition.
• Applied the biosensor to analyze clinical samples like saliva and blood serum.

Main Results:

• Achieved subnanomolar detection limits for AI-2.
• Demonstrated high sensitivity and selectivity of the developed biosensing system.
• Successfully detected AI-2 in clinical samples, including saliva and blood serum.

Conclusions:

• The developed FRET-based protein biosensor offers a rapid, selective, and highly sensitive method for AI-2 detection.
• This biosensing system has significant potential for the early detection of bacterial infections in clinical settings.
• The technology enables AI-2 quantification in complex biological matrices.