Abstract
Opportunistic infections by Burkholderia cenocepacia are life threatening for patients suffering from cystic fibrosis and chronic granulomatous disease. These infections are often associated with variable clinical outcomes, prompting an interest in molecular investigations of phenotypes associated with disease severity. The production of the pyomelanin pigment is one such phenotype, which was recently linked to the ability of clinical strains to carry out biotransformation of the antibiotic trimethoprim. However, this biotransformation product was not identified, and differences in metabolite production associated with pyomelanin pigmentation are poorly understood. Here, we identify several key metabolites produced exclusively by the pyomelanin-producing strains. To provide insight into the structures and biosynthetic origin of these metabolites, we developed a mass spectrometry-based strategy coupling unsupervised in silico substructure prediction with stable isotope labeling referred to as MAS-SILAC (Metabolite Annotation assisted by Substructure discovery and Stable Isotope Labeling by Amino acids in Cell culture). This approach led to discovery of homogentisic acid as a precursor for biosynthesis of several natural products and for biotransformation of trimethoprim, representing a previously unknown mechanism of antibiotic tolerance. This work presents application of computational methods for analysis of untargeted metabolomic data to link the chemotype of pathogenic microorganisms with a specific phenotype. The observations made in this study provide insights into the clinical significance of the melanated phenotype.
Submitted Version
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