Cargando…

Label-free SRM-based relative quantification of antibiotic resistance mechanisms in Pseudomonas aeruginosa clinical isolates

Both acquired and intrinsic mechanisms play a crucial role in Pseudomonas aeruginosa antibiotic resistance. Many clinically relevant resistance mechanisms result from changes in gene expression, namely multidrug efflux pump overproduction, AmpC β-lactamase induction or derepression, and inactivation...

Descripción completa

Detalles Bibliográficos
Autores principales: Charretier, Yannick, Köhler, Thilo, Cecchini, Tiphaine, Bardet, Chloé, Cherkaoui, Abdessalam, Llanes, Catherine, Bogaerts, Pierre, Chatellier, Sonia, Charrier, Jean-Philippe, Schrenzel, Jacques
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4322712/
https://www.ncbi.nlm.nih.gov/pubmed/25713571
http://dx.doi.org/10.3389/fmicb.2015.00081
Descripción
Sumario:Both acquired and intrinsic mechanisms play a crucial role in Pseudomonas aeruginosa antibiotic resistance. Many clinically relevant resistance mechanisms result from changes in gene expression, namely multidrug efflux pump overproduction, AmpC β-lactamase induction or derepression, and inactivation or repression of the carbapenem-specific porin OprD. Changes in gene expression are usually assessed using reverse-transcription quantitative real-time PCR (RT-qPCR) assays. Here, we evaluated label-free Selected Reaction Monitoring (SRM)-based mass spectrometry to directly quantify proteins involved in antibiotic resistance. We evaluated the label-free SRM using a defined set of P. aeruginosa isolates with known resistance mechanisms and compared it with RT-qPCR. Referring to efflux systems, we found a more robust relative quantification of antibiotic resistance mechanisms by SRM than RT-qPCR. The SRM-based approach was applied to a set of clinical P. aeruginosa isolates to detect antibiotic resistance proteins. This multiplexed SRM-based approach is a rapid and reliable method for the simultaneous detection and quantification of resistance mechanisms and we demonstrate its relevance for antibiotic resistance prediction.