Drosophila eiger Mutants Are Sensitive to Extracellular Pathogens

We showed previously that eiger, the Drosophila tumor necrosis factor homolog, contributes to the pathology induced by infection with Salmonella typhimurium. We were curious whether eiger is always detrimental in the context of infection or if it plays a role in fighting some types of microbes. We challenged wild-type and eiger mutant flies with a collection of facultative intracellular and extracellular pathogens, including a fungus and Gram-positive and Gram-negative bacteria. The response of eiger mutants divided these microbes into two groups: eiger mutants are immunocompromised with respect to extracellular pathogens but show no change or reduced sensitivity to facultative intracellular pathogens. Hence, eiger helps fight infections but also can cause pathology. We propose that eiger activates the cellular immune response of the fly to aid clearance of extracellular pathogens. Intracellular pathogens, which can already defeat professional phagocytes, are unaffected by eiger

Metagenomic features of bioburden serve as outcome indicators in combat extremity wounds.

Battlefield injury management requires specialized care, and wound infection is a frequent complication. Challenges related to characterizing relevant pathogens further complicates treatment. Applying metagenomics to wounds offers a comprehensive path toward assessing microbial genomic fingerprints and could indicate prognostic variables for future decision support tools. Wound specimens from combat-injured U.S. service members, obtained during surgical debridements before delayed wound closure, were subjected to whole metagenome analysis and targeted enrichment of antimicrobial resistance genes. Results did not indicate a singular, common microbial metagenomic profile for wound failure, instead reflecting a complex microenvironment with varying bioburden diversity across outcomes. Genus-level Pseudomonas detection was associated with wound failure at all surgeries. A logistic regression model was fit to the presence and absence of antimicrobial resistance classes to assess associations with nosocomial pathogens. A. baumannii detection was associated with detection of genomic signatures for resistance to trimethoprim, aminoglycosides, bacitracin, and polymyxin. Machine learning classifiers were applied to identify wound and microbial variables associated with outcome. Feature importance rankings averaged across models indicated the variables with the largest effects on predicting wound outcome, including an increase in P. putida sequence reads. These results describe the microbial genomic determinants in combat wound bioburden and demonstrate metagenomic investigation as a comprehensive tool for providing information toward aiding treatment of combat-related injuries