Pseudomonas 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.
Summary
Compound identification is one of the most eminent challenges in the untargeted analysis of complex mixtures of small molecules by mass spectrometry. Similarity of tandem mass spectra can provide valuable information on putative structural similarities between known and unknown analytes and hence aids feature identification in the bioanalytical sciences. We have developed CluMSID (Clustering of MS2 spectra for metabolite identification), an R package that enables researchers to make use of tandem mass spectra and neutral loss pattern similarities as a part of their metabolite annotation workflow. CluMSID offers functions for all analysis steps from import of raw data to data mining by unsupervised multivariate methods along with respective (interactive) visualizations. A detailed tutorial with example data is provided as supplementary information.
Availability and implementation
CluMSID is available as R package from https://github.com/tdepke/CluMSID/and from https://bioconductor.org/packages/CluMSID/.
Supplementary information
Supplementary data are available at Bioinformatics online.
Pseudomonas aeruginosa is a bacterial pathogen that causes life-threatening infections in immunocompromised patients. It produces a large armory of saturated and mono-unsaturated 2-alkyl-4(1H)-quinolones (AQs) and AQ N-oxides (AQNOs) that serve as signaling molecules to control the production of virulence factors and that are involved in membrane vesicle formation and iron chelation; furthermore, they also have, for example, antibiotic properties. It has been shown that the β-ketoacyl-acyl-carrier protein synthase III (FabH)-like heterodimeric enzyme PqsBC catalyzes the last step in the biosynthesis of the most abundant AQ congener, 2-heptyl-4(1H)-quinolone (HHQ), by condensing octanoyl-coenzyme A (CoA) with 2-aminobenzoylacetate (2-ABA), but the basis for the large number of other AQs/AQNOs produced by P. aeruginosa is not known. Here, we demonstrate that PqsBC uses different medium-chain acyl-CoAs to produce various saturated AQs/AQNOs and that it also biosynthesizes mono-unsaturated congeners. Further, we determined the structures of PqsBC in four different crystal forms at 1.5 to 2.7 Å resolution. Together with a previous report, the data reveal that PqsBC adopts open, intermediate, and closed conformations that alter the shape of the acyl-binding cavity and explain the promiscuity of PqsBC. The different conformations also allow us to propose a model for structural transitions that accompany the catalytic cycle of PqsBC that might have broader implications for other FabH-enzymes, for which such structural transitions have been postulated but have never been observed.
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