The military gear microbiome: risk factors surrounding the warfighter.

Combat extremity wounds are highly susceptible to contamination from surrounding environmental material. This bioburden could be partially transferred from materials in immediate proximity to the wound, including fragments of the uniform and gear. However, the assessment of the microbial bioburden present on military gear during operational conditions of deployment or training is relatively unexplored. Opportunistic pathogens that can survive on gear represent risk factors for infection following injury, especially following combat blasts, where fibers and other materials are embedded in wounded tissue. We utilized 16S rRNA sequencing to assess the microbiome composition of different military gear types (boot, trouser, coat, and canteen) from two operational environments (training in Hawai'i and deployed in Indonesia) across time (days 0 and 14). We found that microbiome diversity, stability, and composition were dependent on gear type, training location, and sampling timepoint. At day 14, species diversity was significantly higher in Hawai'i samples compared to Indonesia samples for boot, coat, and trouser swabs. In addition, we observed the presence of potential microbial risk factors, as opportunistic pathogenic species, such as Acinetobacter, Pseudomonas, and Staphylococcus, were found to be present in all sample types and in both study sites. These study outcomes will be used to guide the design of antimicrobial materials and uniforms and for infection control efforts following combat blasts and other injuries, thereby improving treatment guidance during military training and deployment.IMPORTANCECombat extremity wounds are vulnerable to contamination from environments of proximity to the warfighter, leading to potential detrimental outcomes such as infection and delayed wound healing. Therefore, microbial surveillance of such environments is necessary to aid the advancement of military safety and preparedness through clinical diagnostics, treatment protocols, and uniform material design.

Targeted metagenomic assessment reflects critical colonization in battlefield injuries.

IMPORTANCE: Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

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.

Sendai virus intra-host population dynamics and host immunocompetence influence viral virulence during in vivo passage.

In vivo serial passage of non-pathogenic viruses has been shown to lead to increased viral virulence, and although the precise mechanism(s) are not clear, it is known that both host and viral factors are associated with increased pathogenicity. Under- or overnutrition leads to a decreased or dysregulated immune response and can increase viral mutant spectrum diversity and virulence. The objective of this study was to identify the role of viral mutant spectra dynamics and host immunocompetence in the development of pathogenicity during in vivo passage. Because the nutritional status of the host has been shown to affect the development of viral virulence, the diet of animal model reflected two extremes of diets which exist in the global population, malnutrition and obesity. Sendai virus was serially passaged in groups of mice with differing nutritional status followed by transmission of the passaged virus to a second host species, guinea pigs. Viral population dynamics were characterized using deep sequence analysis and computational modeling. Histopathology, viral titer and cytokine assays were used to characterize viral virulence. Viral virulence increased with passage and the virulent phenotype persisted upon passage to a second host species. Additionally, nutritional status of mice during passage influenced the phenotype. Sequencing revealed the presence of several non-synonymous changes in the consensus sequence associated with passage, a majority of which occurred in the hemagglutinin-neuraminidase and polymerase genes, as well as the presence of persistent high frequency variants in the viral population. In particular, an N1124D change in the consensus sequences of the polymerase gene was detected by passage 10 in a majority of the animals. In vivo comparison of an 1124D plaque isolate to a clone with 1124N genotype indicated that 1124D was associated with increased virulence.

Identification of Genome-Wide Mutations in Ciprofloxacin-Resistant F. tularensis LVS Using Whole Genome Tiling Arrays and Next Generation Sequencing.

Francisella tularensis is classified as a Class A bioterrorism agent by the U.S. government due to its high virulence and the ease with which it can be spread as an aerosol. It is a facultative intracellular pathogen and the causative agent of tularemia. Ciprofloxacin (Cipro) is a broad spectrum antibiotic effective against Gram-positive and Gram-negative bacteria. Increased Cipro resistance in pathogenic microbes is of serious concern when considering options for medical treatment of bacterial infections. Identification of genes and loci that are associated with Ciprofloxacin resistance will help advance the understanding of resistance mechanisms and may, in the future, provide better treatment options for patients. It may also provide information for development of assays that can rapidly identify Cipro-resistant isolates of this pathogen. In this study, we selected a large number of F. tularensis live vaccine strain (LVS) isolates that survived in progressively higher Ciprofloxacin concentrations, screened the isolates using a whole genome F. tularensis LVS tiling microarray and Illumina sequencing, and identified both known and novel mutations associated with resistance. Genes containing mutations encode DNA gyrase subunit A, a hypothetical protein, an asparagine synthase, a sugar transamine/perosamine synthetase and others. Structural modeling performed on these proteins provides insights into the potential function of these proteins and how they might contribute to Cipro resistance mechanisms.

Temporal succession in carbon incorporation from macromolecules by particle-attached bacteria in marine microcosms.

We investigated bacterial carbon assimilation from stable isotope-labelled macromolecular substrates (proteins; lipids; and two types of polysaccharides, starch and cellobiose) while attached to killed diatom detrital particles during laboratory microcosms incubated for 17 days. Using Chip-SIP (secondary ion mass spectrometry analysis of RNA microarrays), we identified generalist operational taxonomic units (OTUs) from the Gammaproteobacteria, belonging to the genera Colwellia, Glaciecola, Pseudoalteromonas and Rheinheimera, and from the Bacteroidetes, genera Owenweeksia and Maribacter, that incorporated the four tested substrates throughout the incubation period. Many of these OTUs exhibited the highest isotope incorporation relative to the others, indicating that they were likely the most active. Additional OTUs from the Gammaproteobacteria, Bacteroidetes and Alphaproteobacteria exhibited generally (but not always) lower activity and did not incorporate all tested substrates at all times, showing species succession in organic carbon incorporation. We also found evidence to suggest that both generalist and specialist OTUs changed their relative substrate incorporation over time, presumably in response to changing substrate availability as the particles aged. This pattern was demonstrated by temporal succession from relatively higher starch incorporation early in the incubations, eventually switching to higher cellobiose incorporation after 2 weeks.

Phylogenetic patterns in the microbial response to resource availability: amino acid incorporation in San Francisco Bay.

Aquatic microorganisms are typically identified as either oligotrophic or copiotrophic, representing trophic strategies adapted to low or high nutrient concentrations, respectively. Here, we sought to take steps towards identifying these and additional adaptations to nutrient availability with a quantitative analysis of microbial resource use in mixed communities. We incubated an estuarine microbial community with stable isotope labeled amino acids (AAs) at concentrations spanning three orders of magnitude, followed by taxon-specific quantitation of isotopic incorporation using NanoSIMS analysis of high-density microarrays. The resulting data revealed that trophic response to AA availability falls along a continuum between copiotrophy and oligotrophy, and high and low activity. To illustrate strategies along this continuum more simply, we statistically categorized microbial taxa among three trophic types, based on their incorporation responses to increasing resource concentration. The data indicated that taxa with copiotrophic-like resource use were not necessarily the most active, and taxa with oligotrophic-like resource use were not always the least active. Two of the trophic strategies were not randomly distributed throughout a 16S rDNA phylogeny, suggesting they are under selective pressure in this ecosystem and that a link exists between evolutionary relatedness and substrate affinity. The diversity of strategies to adapt to differences in resource availability highlights the need to expand our understanding of microbial interactions with organic matter in order to better predict microbial responses to a changing environment.

Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray.

Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1h. The LLMDA was able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 µL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.

The role of viral population diversity in adaptation of bovine coronavirus to new host environments.

The high mutation rate of RNA viruses enables a diverse genetic population of viral genotypes to exist within a single infected host. In-host genetic diversity could better position the virus population to respond and adapt to a diverse array of selective pressures such as host-switching events. Multiple new coronaviruses, including SARS, have been identified in human samples just within the last ten years, demonstrating the potential of coronaviruses as emergent human pathogens. Deep sequencing was used to characterize genomic changes in coronavirus quasispecies during simulated host-switching. Three bovine nasal samples infected with bovine coronavirus were used to infect human and bovine macrophage and lung cell lines. The virus reproduced relatively well in macrophages, but the lung cell lines were not infected efficiently enough to allow passage of non lab-adapted samples. Approximately 12 kb of the genome was amplified before and after passage and sequenced at average coverages of nearly 950×(454 sequencing) and 38,000×(Illumina). The consensus sequence of many of the passaged samples had a 12 nucleotide insert in the consensus sequence of the spike gene, and multiple point mutations were associated with the presence of the insert. Deep sequencing revealed that the insert was present but very rare in the unpassaged samples and could quickly shift to dominate the population when placed in a different environment. The insert coded for three arginine residues, occurred in a region associated with fusion entry into host cells, and may allow infection of new cell types via heparin sulfate binding. Analysis of the deep sequencing data indicated that two distinct genotypes circulated at different frequency levels in each sample, and support the hypothesis that the mutations present in passaged strains were "selected" from a pre-existing pool rather than through de novo mutation and subsequent population fixation.

High-throughput isotopic analysis of RNA microarrays to quantify microbial resource use.

Most microorganisms remain uncultivated, and typically their ecological roles must be inferred from diversity and genomic studies. To directly measure functional roles of uncultivated microbes, we developed Chip-stable isotope probing (SIP), a high-sensitivity, high-throughput SIP method performed on a phylogenetic microarray (chip). This approach consists of microbial community incubations with isotopically labeled substrates, hybridization of the extracted community rRNA to a microarray and measurement of isotope incorporation--and therefore substrate use--by secondary ion mass spectrometer imaging (NanoSIMS). Laboratory experiments demonstrated that Chip-SIP can detect isotopic enrichment of 0.5 atom % (13)C and 0.1 atom % (15)N, thus permitting experiments with short incubation times and low substrate concentrations. We applied Chip-SIP analysis to a natural estuarine community and quantified amino acid, nucleic acid or fatty acid incorporation by 81 distinct microbial taxa, thus demonstrating that resource partitioning occurs with relatively simple organic substrates. The Chip-SIP approach expands the repertoire of stable isotope-enabled methods available to microbial ecologists and provides a means to test genomics-generated hypotheses about biogeochemical function in any natural environment.

Array2BIO: from microarray expression data to functional annotation of co-regulated genes.

BACKGROUND: There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. RESULTS: Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1) comparative analysis of signal versus control and (2) clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. CONCLUSION: We have developed Array2BIO - a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

Temporal global changes in gene expression during temperature transition in Yersinia pestis.

DNA microarrays encompassing the entire genome of Yersinia pestis were used to characterize global regulatory changes during steady-state vegetative growth occurring after shift from 26 to 37 degrees C in the presence and absence of Ca2+. Transcriptional profiles revealed that 51, 4, and 13 respective genes and open reading frames (ORFs) on pCD, pPCP, and pMT were thermoinduced and that the majority of these genes carried by pCD were downregulated by Ca2+. In contrast, Ca2+ had little effect on chromosomal genes and ORFs, of which 235 were thermally upregulated and 274 were thermally downregulated. The primary consequence of these regulatory events is profligate catabolism of numerous metabolites available in the mammalian host.