Details

Autor(en) / Beteiligte

• Delgado-Cano, David
• Clemente, Antonio
• Adrover-Jaume, Cristina
• Vaquer, Andreu
• López, Meritxell
• Martíne z, Rocío
• R oig, Isabel M
• Iglesias, Amanda
• Cosío, Borja G
• de la Rica, Roberto

Titel

Facemask analyses for the non-invasive detection of chronic and acute lung infections using nanoparticle-based immunoassays

Ist Teil von

• Analyst (London), 2023-09, Vol.148 (19), p.4837-4843

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Pseudomonas aeruginosa ( P. aeruginosa ) is a pathogen that persistently colonizes the respiratory tract of patients with chronic lung diseases. The risk of acquiring a chronic P. aeruginosa infection can be minimized by rapidly detecting the pathogen in the patient's airways and promptly administrating adequate antibiotics. However, the rapid detection of P. aeruginosa in the lungs involves the analysis of sputum, which is a highly complex matrix that is not always available. Here, we propose an alternative diagnosis based on analyzing breath aerosols. In this approach, nanoparticle immunosensors identify bacteria adhered to the polypropylene layer of a surgical facemask that was previously worn by the patient. A polypropylene processing protocol was optimized to ensure the efficient capture and analysis of the target pathogen. The proposed analytical platform has a theoretical limit of detection of 10 5 CFU mL −1 in aerosolized mock samples, and a dynamic range between 10 5 and 10 8 CFU mL −1 . When tested with facemasks worn by patients, the biosensors were able to detect chronic and acute P. aeruginosa lung infections, and to differentiate them from respiratory infections caused by other pathogens. The results shown here pave the way to diagnose Pseudomonas infections at the bedside, as well as to identify the progress from chronic to acute infection. We present a method for detecting respiratory infections caused by P. aeruginosa that involves analyzing facemasks worn by patients with a nanoparticle-based biosensor. The obtained colorimetric signals are related to the bacterial load in lungs.