Identifying Pathoadaptation in Pseudomonas aeruginosa Using Glycopolymer Sensor Arrays

Area of Science:

• Microbiology and Infectious Diseases
• Biotechnology and Sensor Development
• Evolutionary Biology

Background:

• In-host bacterial evolution, including antibiotic resistance and virulence changes, complicates infection management.
• Pseudomonas aeruginosa rapidly evolves during chronic lung infections, posing diagnostic and therapeutic challenges.
• Current methods for bacterial strain typing are time-consuming and expensive, hindering the identification of clinically relevant pathotypes.

Purpose of the Study:

• To develop a rapid, direct method for identifying phenotypic changes in P. aeruginosa associated with in-host evolution.
• To create a sensor array capable of distinguishing between different evolutionary trajectories and pathoadaptive states of P. aeruginosa.
• To assess the sensor array's ability to differentiate P. aeruginosa from other bacteria in polymicrobial infections.

Main Methods:

• Development of a cross-reactive, glycopolymer-based fluorescent sensor array.
• Direct detection of phenotypic variations in P. aeruginosa isolates.
• Discrimination of clinical isolates based on evolutionary and pathoadaptive differences.
• Testing the sensor array's specificity against other common lung pathogens.

Main Results:

• The sensor array accurately identified phenotypic changes linked to in-host evolution in P. aeruginosa.
• The system successfully distinguished variations from single-gene defects and differentiated clinical isolates with distinct evolutionary histories.
• The sensor array could differentiate P. aeruginosa from other bacterial species in polymicrobial samples.
• The platform demonstrated modularity for targeting carbohydrate recognition in diverse pathogens.

Conclusions:

• A glycopolymer-based fluorescent sensor array offers a rapid method for classifying P. aeruginosa phenotypic profiles.
• This technology can directly assess in-host bacterial evolution, bypassing genetic analysis.
• The sensor array platform has potential as a rapid diagnostic tool to guide clinical treatment decisions for P. aeruginosa infections.