Show simple item record

dc.contributor.authorDepke, Tobias
dc.contributor.authorThöming, Janne Gesine
dc.contributor.authorKordes, Adrian
dc.contributor.authorHäussler, Susanne
dc.contributor.authorBrönstrup, Mark
dc.date.accessioned2020-08-31T13:00:52Z
dc.date.available2020-08-31T13:00:52Z
dc.date.issued2020-07-13
dc.identifier.citationBiomolecules. 2020;10(7):1041. Published 2020 Jul 13. doi:10.3390/biom10071041.en_US
dc.identifier.pmid32668735
dc.identifier.doi10.3390/biom10071041
dc.identifier.urihttp://hdl.handle.net/10033/622420
dc.description.abstractPseudomonas aeruginosa is a facultative pathogen that can cause, inter alia, acute or chronic pneumonia in predisposed individuals. The gram-negative bacterium displays considerable genomic and phenotypic diversity that is also shaped by small molecule secondary metabolites. The discrimination of virulence phenotypes is highly relevant to the diagnosis and prognosis of P. aeruginosa infections. In order to discover small molecule metabolites that distinguish different virulence phenotypes of P. aeruginosa, 35 clinical strains were cultivated under standard conditions, characterized in terms of virulence and biofilm phenotype, and their metabolomes were investigated by untargeted liquid chromatography-mass spectrometry. The data was both mined for individual candidate markers as well as used to construct statistical models to infer the virulence phenotype from metabolomics data. We found that clinical strains that differed in their virulence and biofilm phenotype also had pronounced divergence in their metabolomes, as underlined by 332 features that were significantly differentially abundant with fold changes greater than 1.5 in both directions. Important virulence-associated secondary metabolites like rhamnolipids, alkyl quinolones or phenazines were found to be strongly upregulated in virulent strains. In contrast, we observed little change in primary metabolism. A hitherto novel cationic metabolite with a sum formula of C12H15N2 could be identified as a candidate biomarker. A random forest model was able to classify strains according to their virulence and biofilm phenotype with an area under the Receiver Operation Characteristics curve of 0.84. These findings demonstrate that untargeted metabolomics is a valuable tool to characterize P. aeruginosa virulence, and to explore interrelations between clinically important phenotypic traits and the bacterial metabolome.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relationnfo:eu-repo/grantAgreement/EC/H2020/ 654008en_US
dc.rightsopenAccessen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectLC-MSen_US
dc.subjectPseudomonas aeruginosaen_US
dc.subjectbiomarkeren_US
dc.subjectphenotypingen_US
dc.subjectrandom forest classificationen_US
dc.subjectuntargeted metabolomicsen_US
dc.subjectvirulenceen_US
dc.titleUntargeted LC-MS Metabolomics Differentiates Between Virulent and Avirulent Clinical Strains of Pseudomonas aeruginosaen_US
dc.typeArticleen_US
dc.identifier.eissn2218-273X
dc.contributor.departmentHZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.en_US
dc.identifier.journalBiomoleculesen_US
dc.source.volume10
dc.source.issue7
refterms.dateFOA2020-08-31T13:00:54Z
dc.source.journaltitleBiomolecules
dc.source.countrySwitzerland


Files in this item

Thumbnail
Name:
Depke et al.pdf
Size:
427.2Kb
Format:
PDF
Description:
Open Access publication

This item appears in the following Collection(s)

Show simple item record

openAccess
Except where otherwise noted, this item's license is described as openAccess