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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. [ABSTRACT FROM AUTHOR]

The human spaceflight environment is notable for the unique factor of microgravity, which exerts numerous physiologic effects on macroscopic organisms, but how this environment may affect single-celled microbes is less clear. In an effort to understand how the microbial transcriptome responds to the unique environment of spaceflight, the model Gram-positive bacterium Bacillus subtilis was flown on two separate missions to the International Space Station in experiments dubbed BRIC-21 and BRIC-23. Cells were grown to late-exponential/early stationary phase, frozen, then returned to Earth for RNA-seq analysis in parallel with matched ground control samples. A total of 91 genes were significantly differentially expressed in both experiments; 55 exhibiting higher transcript levels in flight samples and 36 showing higher transcript levels in ground control samples. Genes upregulated in flight samples notably included those involved in biofilm formation, biotin and arginine biosynthesis, siderophores, manganese transport, toxin production and resistance, and sporulation inhibition. Genes preferentially upregulated in ground control samples notably included those responding to oxygen limitation, e.g., fermentation, anaerobic respiration, subtilosin biosynthesis, and anaerobic regulatory genes. The results indicated differences in oxygen availability between flight and ground control samples, likely due to differences in cell sedimentation and the toroidal shape assumed by the liquid cultures in microgravity. [ABSTRACT FROM AUTHOR]

Results from previous experiments indicated that the Gram-negative α-proteobacterium Serratia liquefaciens strain ATCC 27592 was capable of growth under low temperature (0 °C), low pressure (0.7 kPa), and anoxic, CO2-dominated atmosphere-conditions intended to simulate the near-subsurface environment of Mars. To probe the response of its transcriptome to this extreme environment, S. liquefaciens ATCC 27592 was cultivated under 4 different environmental simulations: 0 °C, 0.7 kPa, CO2 atmosphere (Condition A); 0 °C, ~101.3 kPa, CO2 atmosphere (Condition B); 0 °C, ~101.3 kPa, ambient N2/O2 atmosphere (Condition C); and 30 °C, ~101.3 kPa, N2/O2 atmosphere (Condition D; ambient laboratory conditions). RNA-seq was performed on ribosomal RNA-depleted total RNA isolated from triplicate cultures grown under Conditions A-D and the datasets generated were subjected to transcriptome analyses. The data from Conditions A, B, or C were compared to laboratory Condition D. Significantly differentially expressed transcripts were identified belonging to a number of KEGG pathway categories. Up-regulated genes under all Conditions A, B, and C included those encoding transporters (ABC and PTS transporters); genes involved in translation (ribosomes and their biogenesis, biosynthesis of both tRNAs and aminoacyl-tRNAs); DNA repair and recombination; and non-coding RNAs. Genes down-regulated under all Conditions A, B, and C included: transporters (mostly ABC transporters); flagellar and motility proteins; genes involved in phenylalanine metabolism; transcription factors; and two-component systems. The results are discussed in the context of Mars astrobiology and planetary protection. [ABSTRACT FROM AUTHOR]