Chemical Cartography Approaches to Study Trypanosomatid Infection

The intersection of host in vivo metabolism and immune responses to infection with kinetoplastid and apicomplexan parasites

SUMMARYProtozoan parasite infection dramatically alters host metabolism, driven by immunological demand and parasite manipulation strategies. Immunometabolic checkpoints are often exploited by kinetoplastid and protozoan parasites to establish chronic infection, which can significantly impair host metabolic homeostasis. The recent growth of tools to analyze metabolism is expanding our understanding of these questions. Here, we review and contrast host metabolic alterations that occur in vivo during infection with Leishmania, trypanosomes, Toxoplasma, Plasmodium, and Cryptosporidium. Although genetically divergent, there are commonalities among these pathogens in terms of metabolic needs, induction of the type I immune responses required for clearance, and the potential for sustained host metabolic dysbiosis. Comparing these pathogens provides an opportunity to explore how transmission strategy, nutritional demand, and host cell and tissue tropism drive similarities and unique aspects in host response and infection outcome and to design new strategies to treat disease.

Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage

Concerns about ion suppression, spectral contamination, or interference have led to avoidance of polymers in mass spectrometry (MS)-based metabolomics. This avoidance, however, has left many biochemical fields underexplored, including wounds, which are often treated with adhesive bandages. Here, we found that despite previous concerns, the addition of an adhesive bandage can still result in biologically informative MS data. Initially, a test LC-MS analysis was performed on a mixture of known chemical standards and a polymer bandage extract. Results demonstrated successful removal of many polymer-associated features through a data processing step. Furthermore, the bandage presence did not interfere with metabolite annotation. This method was then implemented in the context of murine surgical wound infections covered with an adhesive bandage and inoculated with Staphylococcus aureus, Pseudomonas aeruginosa, or a 1:1 mix of these pathogens. Metabolites were extracted and analyzed by LC-MS. On the bandage side, we observed a greater impact of infection on the metabolome. Distance analysis showed significant differences between all conditions and demonstrated that coinfected samples were more similar to S. aureus-infected samples compared to P. aeruginosa-infected samples. We also found that coinfection was not merely a summative effect of each monoinfection. Overall, these results represent an expansion of LC-MS-based metabolomics to a novel, previously under-investigated class of samples, leading to actionable biological information.