Litcius/Paper detail

PorinPredict: <i>In Silico</i> Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance

Michael Biggel, Sophia Johler, Tim Roloff, Sarah Tschudin‐Sutter, Stefano Bassetti, Martin Siegemund, Adrian Egli, Roger Stephan, Helena M. B. Seth-Smith

2023Microbiology Spectrum19 citationsDOIOpen Access PDF

Abstract

population and developed PorinPredict, a bioinformatic tool that enables the prediction of OprD loss from whole-genome sequencing data. We show a high correlation between predicted OprD loss and meropenem nonsusceptibility irrespective of the presence of carbapenemases, which are a second widespread determinant of carbapenem resistance. Isolates with resistance determinants to other antibiotics were disproportionally affected by OprD loss, possibly due to an increased exposure to carbapenems. Integration of PorinPredict into genomic surveillance platforms will facilitate a better understanding of the clinical impact of OprD modifications and transmission dynamics of resistant clones.

Topics & Concepts

Pseudomonas aeruginosaBiologyMeropenemCarbapenemGeneticsAntibiotic resistanceIn silicoWhole genome sequencingGenomeGenotypeComputational biologyGeneMicrobiologyAntibioticsBacteriaAntibiotic Resistance in BacteriaGenomics and Phylogenetic StudiesBacterial Genetics and Biotechnology