Probing Interkingdom Signaling Molecules via Liquid Extraction Surface Analysis-Mass Spectrometry

Previously, metabolites diffused or secreted from microbial samples have been analyzed via liquid chromatography-mass spectrometry (LC-MS) approaches following lengthy extraction protocols. Here, we present a model system for growing biofilms on discs before utilizing rapid and direct surface sampling MS, namely, liquid extraction surface analysis, to study the microbial exometabolome. One of the benefits of this approach is its surface-specific nature, enabling mimicking biofilm formation in a way that the study of planktonic liquid cultures cannot imitate. Even though Pseudomonas aeruginosa (P. aeruginosa), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans) have been studied previously in isolation, very few studies consider the complexity of the interplay between these pathogens, which are commonly combined causative agents of infection. Our model system provides a route to investigate changes in the exometabolome, such as metabolites that become circulatory in the presence of multiple pathogens. Our results agree with previous reports showing that 2-alkyl-4(1H)-quinolone signal molecules produced by P. aeruginosa are important markers of infection and suggest that methods for monitoring levels of 2-heptyl-4-hydroxyquinoline and 2,4-dihydroxyquinoline, as well as pyocyanin, could be beneficial in the determination of causative agents in interkingdom infection including P. aeruginosa. Furthermore, studying changes in exometabolome metabolites between pqs quorum sensing antagonists in treated and nontreated samples suggests suppression of phenazine production by P. aeruginosa. Hence, our model provides a rapid analytical approach to gaining a mechanistic understanding of bacterial signaling.

Automated summary

Previously, metabolites from microbial samples were analyzed using liquid chromatography-mass spectrometry. This study presents a model system for studying the microbial exometabolome by growing biofilms on discs and using liquid extraction surface analysis. The specific surface nature of this approach allows for mimicking biofilm formation and studying the interplay between commonly combined causative agents of infection. The results suggest that certain signal molecules are important markers of infection, and monitoring their levels can aid in determining causative agents in interkingdom infection.