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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.

The gut microbiota is a vast and diverse microbial community that has co-evolved with its host to perform a variety of essential functions involved in the utilization of nutrients and the processing of xenobiotics. Shifts in the composition of gut microbiota can disturb the balance of organisms which can influence the biodisposition of orally administered drugs. To determine how changes in the gut microbiome can alter drug disposition, the pharmacokinetics (PK), and biodistribution of acetaminophen were assessed in C57Bl/6 mice after treatment with the antibiotics ciprofloxacin, amoxicillin, or a cocktail of ampicillin/neomycin. Altered PK, and excretion profiles of acetaminophen were observed in antibiotic exposed animals. Plasma Cmax was significantly decreased in antibiotic treated animals suggesting decreased bioavailability. Urinary metabolite profiles revealed decreases in acetaminophen-sulfate metabolite levels in both the amoxicillin and ampicillin/neomycin treated animals. The ratio between urinary and fecal excretion was also altered in antibiotic treated animals. Analysis of gut microbe composition revealed that changes in microbe content in antibiotic treated animals was associated with changes in acetaminophen biodisposition. These results suggest that exposure to amoxicillin or ampicillin/neomycin can alter the biodisposition of acetaminophen and that these alterations could be due to changes in gut microbiome composition.

Bacillus anthracis is the potentially lethal etiologic agent of anthrax disease, and is a significant concern in the realm of biodefense. One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the B. anthracis genome, however, renders specific detection difficult, due to close homology with B. cereus and B. thuringiensis. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of B. anthracis in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of B. anthracis in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of B. anthracis DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from B. anthracis could be reliably distinguished from sequence data mapping to either B. cereus or B. thuringiensis. We also demonstrated the efficacy of a microbial census microarray in detecting B. anthracis in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. Our results, in combination with the capacity of sequencing for providing insights into the genomic characteristics of complex and novel organisms, suggest that these platforms should be considered important components of a biosurveillance strategy. [ABSTRACT FROM AUTHOR]

The number and prevalence of diseases is rapidly increasing in the marine ecosystem. Although there is an increase in the number of marine diseases observed world-wide, current understanding of the pathogens associated with marine mammals is limited. An important need exists to develop and apply platforms for rapid detection and characterization of pathogenic agents to assess, prevent and respond to disease outbreaks. In this study, a broad-spectrum molecular detection technology capable of detecting all sequenced microbial organisms, the Lawrence Livermore Microbial Detection Array, was used to assess the microbial agents that could be associated with wild Atlantic dolphins. Blowhole, gastric, and fecal samples from 8 bottlenose dolphins were collected in Charleston, SC, as part of the dolphin assessment effort. The array detected various microbial agents from the dolphin samples. Clostridium perfringens was most prevalent in the samples surveyed using the microarray. This pathogen was also detected using microbiological culture techniques. Additionally, Campylobacter sp., Staphylococcus sp., Erwinia amylovora, Helicobacter pylori, and Frankia sp. were also detected in more than one dolphin using the microarray, but not in culture. This study provides the first survey of pathogens associated with 3 tissue types in dolphins using a broad-spectrum microbial detection microarray and expands insight on the microbial community profile in dolphins.

Advances in viral detection technologies have the potential to increase the safety assurance of medicines produced in biological production systems. However, taking full advantage of these technological advances in the regulated testing environment will require protocols for standardization and performance testing. The most essential performance characteristics of detection methods for these applications include sensitivity, breadth of detection, and consistency. We have evaluated an approach to establishing the suitability of advanced nucleic-acid-based detection systems for characterization of cell substrates and production cultures. This approach is based on selecting relevant challenge viruses, their preparation and characterization, their application to a sample preparation workflow, and quantitation of their recovery by an independent means as well as the advanced detection readout. This approach helps us evaluate the suitability of the workflow for handling diverse sample matrices across manufacturing platforms for vaccines and other biological products, and also suggests a means by which technology users, developers, and regulators may consider the critical performance attributes of novel detection technologies. We have applied this workflow to a novel microarray-based viral detection system in collaboration with Lawrence Livermore National Laboratory. This system is appealing because of the rapid turnaround of results compared to some other advanced detection technologies., (© PDA, Inc. 2014.)

CONFERENCE PROCEEDING Proceedings of the PDA/FDA Adventitious Viruses in Biologics: Detection and Mitigation Strategies Workshop in Bethesda, MD, USA; December 1-3, 2010 Guest Editors: Arifa Khan (Bethesda, MD), Patricia Hughes (Bethesda, MD) and Michael Wiebe (San Francisco, CA) We designed the Lawrence Livermore Microbial Detection Array (LLMDA), which contains 388,000 DNA probes. This array can detect any sequenced viruses or bacteria within 24 h. In addition, the oligonucleotide probes were selected to enable detection of novel, divergent species with homology to sequenced organisms. We recently used this array to identify an adventitious virus from a vaccine product. We have also used this array to detect viral and bacterial infections from various human clinical samples. Broad-spectrum microbial detection microarrays are efficient and cost-effective tools to rapidly screen cell bank samples, raw materials, vaccine samples, and clinical samples to ensure drug, food, and health safety in the United States and worldwide.