Acyclic cucurbit[n]uril-based sensor array for identification and discrimination of antimicrobial agents

Area of Science:

• Analytical Chemistry
• Environmental Science
• Biotechnology

Background:

• Antimicrobial resistance is a growing global health threat due to antimicrobial overuse.
• Antimicrobial residues in the environment are complex mixtures of similar compounds, difficult to detect with conventional methods.

Purpose of the Study:

• To develop a sensor array for accurate identification and quantification of multiple antimicrobial agents.
• To address the challenge of detecting structurally similar antimicrobial compounds in environmental samples.

Main Methods:

• Development of a sensor array using two acyclic phosphonate hosts and three fluorescent indicators.
• Utilizing host-guest complexation and competitive displacement for signal generation.
• Testing the array's accuracy, sensitivity, and robustness with known antimicrobial agents and real water samples.

Main Results:

• The sensor array achieved 100% accuracy in discriminating all 10 tested antimicrobial agents.
• Detection limits were below regulatory levels, enabling quantitative concentration determination.
• The array successfully analyzed binary mixtures of antimicrobials in real water samples, demonstrating robustness.

Conclusions:

• Sensor arrays show significant potential for identifying and discriminating complex antimicrobial mixtures with similar structures.
• The developed sensor array provides a rapid, sensitive, affordable, and portable method for environmental monitoring of antimicrobial contamination.