Electrochemical sensors for detection of Pseudomonas aeruginosa virulence biomarkers: Principles of design and characterization - Olja Simoska; Keith J. Stevenson (Sensors and Actuators Reports, 2022)
Microbial infections remain an urgent threat to human health, specifically with the increasing antimicrobial resistance mechanisms. The opportunistic human pathogen Pseudomonas aeruginosa successfully establishes diseases in patients with compromised immune systems and those suffering from severe conditions. The development of diagnostic platforms for rapid detection, reliable confirmation of infection, and continuous monitoring of P. aeruginosa is a critical challenge of clinical importance, especially in terms of tailoring effective treatment strategies. During infection stages, this pathogen produces various virulence metabolites, which promote virulence by interfering with cellular functions in immune cells, allowing P. aeruginosa to successfully establish infectious colonies that proliferate. Due to the redox-active nature of these metabolites, several electrochemical sensing platforms have been proposed as diagnostic platforms for rapid and quantitative detection of P. aeruginosa biomarkers with high sensitivity. These sensors must be appropriately designed and modified to not only allow for the dynamic, real-time detection of metabolites, but also ensure adequate selectivity, sensitivity, and biocompatibility in complex biological environments. This minireview provides a critical overview of advances in the field of electrochemical sensors for the detection of P. aeruginosa biomarkers, with an emphasis on sensors developed to operate in challenging biological samples with specific physiological properties. Unique to this minireview, we highlight research efforts on the design of electrochemical sensors with adequate analytical figures of merit and meticulous characterization of the sensor performance in simulated and real samples. Finally, we conclude with perspectives on future sensor designs for P. aeruginosa biomarker detection and their applications in biomedical diagnostics.