Fluorescent Sensor Array for Highly Efficient Microbial Lysate Identification through Competitive Interactions.

Area of Science:

• Biochemistry
• Materials Science
• Analytical Chemistry

Background:

• Optical cross-reactive sensor arrays are effective for high-throughput bioanalyte identification.
• Microbial identification and classification, especially from complex lysates, remain challenging.
• Existing methods often lack the required specificity and simplicity for complex samples.

Purpose of the Study:

• To develop a novel fluorescent sensor array for the identification and classification of microbial lysates.
• To overcome the limitations of current methods in analyzing complex biological samples.
• To enhance the discrimination ability of sensor arrays for microbial analytes.

Main Methods:

• Construction of a microbial lysate-responsive fluorescent sensor array using aggregation-induced emission luminogens (AIEgens) and graphene oxide (GO).
• Utilizing the synergistic effects of AIEgens and GO to reduce background noise and enhance signal interactions.
• Employing competition interactions between AIEgens, microbial lysates, and GO to improve analyte discrimination.

Main Results:

• Precisely identified six different microbes, including fungi, Gram-positive bacteria, and Gram-negative bacteria.
• Demonstrated significantly improved discrimination ability compared to conventional sensor arrays.
• Showcased the reduction of background signal through the combined use of AIEgens and GO.

Conclusions:

• The developed sensor array provides a new, safer, and simpler method for discriminating complex microbial analytes.
• The combination of AIEgens and GO offers a promising strategy for designing advanced biosensors.
• This approach holds potential for high-throughput screening and identification in various biological applications.