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Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage

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AMER CHEMICAL SOC
DOI: 10.1021/jasms.3c00066

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Concerns about the use of polymers in mass spectrometry (MS)-based metabolomics have led to their avoidance. However, experiments using adhesive bandages have shown that they can still provide biologically informative MS data. This method has been successfully applied to study the metabolome of murine surgical wound infections, revealing significant differences in metabolites between different infection conditions.
Concerns about ionsuppression, spectral contamination, or interferencehave led to avoidance of polymers in mass spectrometry (MS)-basedmetabolomics. This avoidance, however, has left many biochemical fieldsunderexplored, including wounds, which are often treated with adhesivebandages. Here, we found that despite previous concerns, the additionof an adhesive bandage can still result in biologically informativeMS data. Initially, a test LC-MS analysis was performed on a mixtureof known chemical standards and a polymer bandage extract. Resultsdemonstrated successful removal of many polymer-associated featuresthrough a data processing step. Furthermore, the bandage presencedid not interfere with metabolite annotation. This method was thenimplemented in the context of murine surgical wound infections coveredwith an adhesive bandage and inoculated with Staphylococcusaureus, Pseudomonas aeruginosa, or a 1:1 mix of these pathogens. Metabolites were extracted andanalyzed by LC-MS. On the bandage side, we observed a greater impactof infection on the metabolome. Distance analysis showed significantdifferences between all conditions and demonstrated that coinfectedsamples were more similar to S. aureus-infectedsamples compared to P. aeruginosa-infected samples.We also found that coinfection was not merely a summative effect ofeach monoinfection. Overall, these results represent an expansionof LC-MS-based metabolomics to a novel, previously under-investigatedclass of samples, leading to actionable biological information.

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