PorinPredict:

Pseudomonas aeruginosa antimicrobial resistance carbapenem resistance genotype-phenotype predictions inactivating mutations meropenem resistance outer membrane porin outer membrane porin OprD surveillance whole-genome sequencing

Journal

Microbiology spectrum
ISSN: 2165-0497
Titre abrégé: Microbiol Spectr
Pays: United States
ID NLM: 101634614

Informations de publication

Date de publication:
30 Jan 2023
Historique:
entrez: 30 1 2023
pubmed: 31 1 2023
medline: 31 1 2023
Statut: aheadofprint

Résumé

The increasing integration of genomics into routine clinical diagnostics requires reliable computational tools to identify determinants of antimicrobial resistance (AMR) from whole-genome sequencing data. Here, we developed PorinPredict, a bioinformatic tool that predicts defects of the Pseudomonas aeruginosa outer membrane porin OprD, which are strongly associated with reduced carbapenem susceptibility. PorinPredict relies on a database of intact OprD variants and reports inactivating mutations in the coding or promoter region. PorinPredict was validated against 987 carbapenemase-negative P. aeruginosa genomes, of which OprD loss was predicted for 454 out of 522 (87.0%) meropenem-nonsusceptible and 46 out of 465 (9.9%) meropenem-susceptible isolates. OprD loss was also found to be common among carbapenemase-producing isolates, resulting in even further increased MICs. Chromosomal mutations in quinolone resistance-determining regions and OprD loss commonly co-occurred, likely reflecting the restricted use of carbapenems for multidrug-resistant infections as recommended in antimicrobial stewardship programs. In combination with available AMR gene detection tools, PorinPredict provides a robust and standardized approach to link P. aeruginosa phenotypes to genotypes.

Identifiants

pubmed: 36715510
doi: 10.1128/spectrum.03588-22
pmc: PMC10100854
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0358822

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Auteurs

Michael Biggel (M)

Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.

Sophia Johler (S)

Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.

Tim Roloff (T)

Division of Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland.
Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
Institute of Medical Microbiology, University of Zurich, Zurich.

Sarah Tschudin-Sutter (S)

Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland.

Stefano Bassetti (S)

Internal Medicine, University Hospital Basel, Basel, Switzerland.

Martin Siegemund (M)

Intensive Care Unit, University Hospital Basel, Basel, Switzerland.

Adrian Egli (A)

Division of Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland.
Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
Institute of Medical Microbiology, University of Zurich, Zurich.

Roger Stephan (R)

Institute for Food Safety and Hygiene, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.

Helena M B Seth-Smith (HMB)

Division of Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland.
Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
Institute of Medical Microbiology, University of Zurich, Zurich.

Classifications MeSH