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.

Differential laboratory passaging of SARS-CoV-2 viral stocks impacts the in vitro assessment of neutralizing antibodies.

Viral populations in natural infections can have a high degree of sequence diversity, which can directly impact immune escape. However, antibody potency is often tested in vitro with a relatively clonal viral populations, such as laboratory virus or pseudotyped virus stocks, which may not accurately represent the genetic diversity of circulating viral genotypes. This can affect the validity of viral phenotype assays, such as antibody neutralization assays. To address this issue, we tested whether recombinant virus carrying SARS-CoV-2 spike (VSV-SARS-CoV-2-S) stocks could be made more genetically diverse by passage, and if a stock passaged under selective pressure was more capable of escaping monoclonal antibody (mAb) neutralization than unpassaged stock or than viral stock passaged without selective pressures. We passaged VSV-SARS-CoV-2-S four times concurrently in three cell lines and then six times with or without polyclonal antiserum selection pressure. All three of the monoclonal antibodies tested neutralized the viral population present in the unpassaged stock. The viral inoculum derived from serial passage without antiserum selection pressure was neutralized by two of the three mAbs. However, the viral inoculum derived from serial passage under antiserum selection pressure escaped neutralization by all three mAbs. Deep sequencing revealed the rapid acquisition of multiple mutations associated with antibody escape in the VSV-SARS-CoV-2-S that had been passaged in the presence of antiserum, including key mutations present in currently circulating Omicron subvariants. These data indicate that viral stock that was generated under polyclonal antiserum selection pressure better reflects the natural environment of the circulating virus and may yield more biologically relevant outcomes in phenotypic assays. Thus, mAb assessment assays that utilize a more genetically diverse, biologically relevant, virus stock may yield data that are relevant for prediction of mAb efficacy and for enhancing biosurveillance.

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.

Evaluation of co-circulating pathogens and microbiome from COVID-19 infections.

Co-infections or secondary infections with SARS-CoV-2 have the potential to affect disease severity and morbidity. Additionally, the potential influence of the nasal microbiome on COVID-19 illness is not well understood. In this study, we analyzed 203 residual samples, originally submitted for SARS-CoV-2 testing, for the presence of viral, bacterial, and fungal pathogens and non-pathogens using a comprehensive microarray technology, the Lawrence Livermore Microbial Detection Array (LLMDA). Eighty-seven percent of the samples were nasopharyngeal samples, and 23% of the samples were oral, nasal and oral pharyngeal swabs. We conducted bioinformatics analyses to examine differences in microbial populations of these samples, as a proxy for the nasal and oral microbiome, from SARS-CoV-2 positive and negative specimens. We found 91% concordance with the LLMDA relative to a diagnostic RT-qPCR assay for detection of SARS-CoV-2. Sixteen percent of all the samples (32/203) revealed the presence of an opportunistic bacterial or frank viral pathogen with the potential to cause co-infections. The two most detected bacteria, Streptococcus pyogenes and Streptococcus pneumoniae, were present in both SARS-CoV-2 positive and negative samples. Human metapneumovirus was the most prevalent viral pathogen in the SARS-CoV-2 negative samples. Sequence analysis of 16S rRNA was also conducted to evaluate bacterial diversity and confirm LLMDA results.

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples.

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection.

Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae. Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.

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.

Microbial Tracking-2, a metagenomics analysis of bacteria and fungi onboard the International Space Station.

BACKGROUND: The International Space Station (ISS) is a unique and complex built environment with the ISS surface microbiome originating from crew and cargo or from life support recirculation in an almost entirely closed system. The Microbial Tracking 1 (MT-1) project was the first ISS environmental surface study to report on the metagenome profiles without using whole-genome amplification. The study surveyed the microbial communities from eight surfaces over a 14-month period. The Microbial Tracking 2 (MT-2) project aimed to continue the work of MT-1, sampling an additional four flights from the same locations, over another 14 months. METHODS: Eight surfaces across the ISS were sampled with sterile wipes and processed upon return to Earth. DNA extracted from the processed samples (and controls) were treated with propidium monoazide (PMA) to detect intact/viable cells or left untreated and to detect the total DNA population (free DNA/compromised cells/intact cells/viable cells). DNA extracted from PMA-treated and untreated samples were analyzed using shotgun metagenomics. Samples were cultured for bacteria and fungi to supplement the above results. RESULTS: Staphylococcus sp. and Malassezia sp. were the most represented bacterial and fungal species, respectively, on the ISS. Overall, the ISS surface microbiome was dominated by organisms associated with the human skin. Multi-dimensional scaling and differential abundance analysis showed significant temporal changes in the microbial population but no spatial differences. The ISS antimicrobial resistance gene profiles were however more stable over time, with no differences over the 5-year span of the MT-1 and MT-2 studies. Twenty-nine antimicrobial resistance genes were detected across all samples, with macrolide/lincosamide/streptogramin resistance being the most widespread. Metagenomic assembled genomes were reconstructed from the dataset, resulting in 82 MAGs. Functional assessment of the collective MAGs showed a propensity for amino acid utilization over carbohydrate metabolism. Co-occurrence analyses showed strong associations between bacterial and fungal genera. Culture analysis showed the microbial load to be on average 3.0 × 105 cfu/m2 CONCLUSIONS: Utilizing various metagenomics analyses and culture methods, we provided a comprehensive analysis of the ISS surface microbiome, showing microbial burden, bacterial and fungal species prevalence, changes in the microbiome, and resistome over time and space, as well as the functional capabilities and microbial interactions of this unique built microbiome. Data from this study may help to inform policies for future space missions to ensure an ISS surface microbiome that promotes astronaut health and spacecraft integrity. Video Abstract.

Investigation of Spaceflight Induced Changes to Astronaut Microbiomes.

The International Space Station (ISS) is a uniquely enclosed environment that has been continuously occupied for the last two decades. Throughout its operation, protecting the health of the astronauts on-board has been a high priority. The human microbiome plays a significant role in maintaining human health, and disruptions in the microbiome have been linked to various diseases. To evaluate the effects of spaceflight on the human microbiome, body swabs and saliva samples were collected from four ISS astronauts on consecutive expeditions. Astronaut samples were analyzed using shotgun metagenomic sequencing and microarrays to characterize the microbial biodiversity before, during, and after the astronauts' time onboard the ISS. Samples were evaluated at an individual and population level to identify changes in microbial diversity and abundance. No significant changes in the number or relative abundance of taxa were observed between collection time points when samples from all four astronauts were analyzed together. When the astronauts' saliva samples were analyzed individually, the saliva samples of some astronauts showed significant changes in the relative abundance of taxa during and after spaceflight. The relative abundance of Prevotella in saliva samples increased during two astronauts' time onboard the ISS while the relative abundance of other commensal taxa such as Neisseria, Rothia, and Haemophilus decreased. The abundance of some antimicrobial resistance genes within the saliva samples also showed significant changes. Most notably, elfamycin resistance gene significantly increased in all four astronauts post-flight and a CfxA6 beta-lactam marker significantly increased during spaceflight but returned to normal levels post-flight. The combination of both shotgun metagenomic sequencing and microarrays showed the benefit of both technologies in monitoring microbes on board the ISS. There were some changes in each astronaut's microbiome during spaceflight, but these changes were not universal for all four astronauts. Two antimicrobial resistance gene markers did show a significant change in abundance in the saliva samples of all four astronauts across their collection times. These results provide insight for future ISS microbial monitoring studies and targets for antimicrobial resistance screenings.

Gut microbiome associations with outcome following co-infection with porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) in pigs immunized with a PRRS modified live virus vaccine.

Porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) are two of the most significant pathogens affecting swine. Co-infections are common and result in respiratory disease and reduced weight gain in growing pigs. Although PRRS modified live virus (MLV) vaccines are widely used to decrease PRRS-associated losses, they are generally considered inadequate for disease control. The gut microbiome provides an alternative strategy to enhance vaccine efficacy and improve PRRS control. The objective of this study was to identify gut microbiome characteristics associated with improved outcome in pigs immunized with a PRRS MLV and co-challenged with PRRSV and PCV2b. Twenty-eight days after vaccination and prior to co-challenge, fecal samples were collected from an experimental population of 50 nursery pigs. At 42 days post-challenge, 20 pigs were retrospectively identified as having high or low growth outcomes during the post-challenge period. Gut microbiomes of the two outcome groups were compared using the Lawrence Livermore Microbial Detection Array (LLMDA) and 16S rDNA sequencing. High growth outcomes were associated with several gut microbiome characteristics, such as increased bacterial diversity, increased Bacteroides pectinophilus, decreased Mycoplasmataceae species diversity, higher Firmicutes:Bacteroidetes ratios, increased relative abundance of the phylum Spirochaetes, reduced relative abundance of the family Lachnospiraceae, and increased Lachnospiraceae species C6A11 and P6B14. Overall, this study identifies gut microbiomes associated with improved outcomes in PRRS vaccinated pigs following a polymicrobial respiratory challenge and provides evidence towards the gut microbiome playing a role in PRRS vaccine efficacy.

Two Sides of a Coin: a Zika Virus Mutation Selected in Pregnant Rhesus Macaques Promotes Fetal Infection in Mice but at a Cost of Reduced Fitness in Nonpregnant Macaques and Diminished Transmissibility by Vectors.

Although fetal death is now understood to be a severe outcome of congenital Zika syndrome, the role of viral genetics is still unclear. We sequenced Zika virus (ZIKV) from a rhesus macaque fetus that died after inoculation and identified a single intrahost substitution, M1404I, in the ZIKV polyprotein, located in nonstructural protein 2B (NS2B). Targeted sequencing flanking position 1404 in 9 additional macaque mothers and their fetuses identified M1404I at a subconsensus frequency in the majority (5 of 9, 56%) of animals and some of their fetuses. Despite its repeated presence in pregnant macaques, M1404I has occurred rarely in humans since 2015. Since the primary ZIKV transmission cycle is human-mosquito-human, mutations in one host must be retained in the alternate host to be perpetuated. We hypothesized that ZIKV I1404 increases viral fitness in nonpregnant macaques and pregnant mice but is less efficiently transmitted by vectors, explaining its low frequency in humans during outbreaks. By examining competitive fitness relative to that of ZIKV M1404, we observed that ZIKV I1404 produced lower viremias in nonpregnant macaques and was a weaker competitor in tissues. In pregnant wild-type mice, ZIKV I1404 increased the magnitude and rate of placental infection and conferred fetal infection, in contrast to ZIKV M1404, which was not detected in fetuses. Although infection and dissemination rates were not different, Aedes aegypti mosquitoes transmitted ZIKV I1404 more poorly than ZIKV M1404. Our data highlight the complexity of arbovirus mutation-fitness dynamics and suggest that intrahost ZIKV mutations capable of augmenting fitness in pregnant vertebrates may not necessarily spread efficiently via mosquitoes during epidemics.IMPORTANCE Although Zika virus infection of pregnant women can result in congenital Zika syndrome, the factors that cause the syndrome in some but not all infected mothers are still unclear. We identified a mutation that was present in some ZIKV genomes in experimentally inoculated pregnant rhesus macaques and their fetuses. Although we did not find an association between the presence of the mutation and fetal death, we performed additional studies with ZIKV with the mutation in nonpregnant macaques, pregnant mice, and mosquitoes. We observed that the mutation increased the ability of the virus to infect mouse fetuses but decreased its capacity to produce high levels of virus in the blood of nonpregnant macaques and to be transmitted by mosquitoes. This study shows that mutations in mosquito-borne viruses like ZIKV that increase fitness in pregnant vertebrates may not spread in outbreaks when they compromise transmission via mosquitoes and fitness in nonpregnant hosts.

Sierra Nevada sweep: metagenomic measurements of bioaerosols vertically distributed across the troposphere.

To explore how airborne microbial patterns change with height above the Earth's surface, we flew NASA's C-20A aircraft on two consecutive days in June 2018 along identical flight paths over the US Sierra Nevada mountain range at four different altitudes ranging from 10,000 ft to 40,000 ft. Bioaerosols were analyzed by metagenomic DNA sequencing and traditional culturing methods to characterize the composition and diversity of atmospheric samples compared to experimental controls. The relative abundance of taxa changed significantly at each altitude sampled, and the diversity profile shifted across the two sampling days, revealing a regional atmospheric microbiome that is dynamically changing. The most proportionally abundant microbial genera were Mycobacterium and Achromobacter at 10,000 ft; Stenotrophomonas and Achromobacter at 20,000 ft; Delftia and Pseudoperonospora at 30,000 ft; and Alcaligenes and Penicillium at 40,000 ft. Culture-based detections also identified viable Bacillus zhangzhouensis, Bacillus pumilus, and Bacillus spp. in the upper troposphere. To estimate bioaerosol dispersal, we developed a human exposure likelihood model (7-day forecast) using general aerosol characteristics and measured meteorological conditions. By coupling metagenomics to a predictive atmospheric model, we aim to set the stage for field campaigns that monitor global bioaerosol emissions and impacts.

Crewmember microbiome may influence microbial composition of ISS habitable surfaces.

The International Space Station (ISS) is a complex built environment physically isolated from Earth. Assessing the interplay between the microbial community of the ISS and its crew is important for preventing biomedical and structural complications for long term human spaceflight missions. In this study, we describe one crewmember's microbial profile from body swabs of mouth, nose, ear, skin and saliva that were collected at eight different time points pre-, during and post-flight. Additionally, environmental surface samples from eight different habitable locations in the ISS were collected from two flights. Environmental samples from one flight were collected by the crewmember and samples from the next flight were collected after the crewmember departed. The microbial composition in both environment and crewmember samples was measured using shotgun metagenomic sequencing and processed using the Livermore Metagenomics Analysis Toolkit. Ordination of sample to sample distances showed that of the eight crew body sites analyzed, skin, nostril, and ear samples are more similar in microbial composition to the ISS surfaces than mouth and saliva samples; and that the microbial composition of the crewmember's skin samples are more closely related to the ISS surface samples collected by the crewmember on the same flight than ISS surface samples collected by other crewmembers on different flights. In these collections, species alpha diversity in saliva samples appears to decrease during flight and rebound after returning to Earth. This is the first study to compare the ISS microbiome to a crewmember's microbiome via shotgun metagenomic sequencing. We observed that the microbiome of the surfaces inside the ISS resemble those of the crew's skin. These data support future crew and ISS microbial surveillance efforts and the design of preventive measures to maintain crew habitat onboard spacecraft destined for long term space travel.

The influence of spaceflight on the astronaut salivary microbiome and the search for a microbiome biomarker for viral reactivation.

BACKGROUND: Spaceflight impacts astronauts in many ways but little is known on how spaceflight affects the salivary microbiome and the consequences of these changes on astronaut health, such as viral reactivation. In order to understand this, the salivary microbiome was analyzed with 16S rRNA gene amplicon sequencing, and saliva viral titers were analyzed with quantitative polymerase chain reaction (qPCR) with primers specific for Epstein-Barr virus (EBV), herpes simplex virus (HSV), and varicella zoster virus (VZV) from 10 astronauts pre-flight, in-flight, and post-flight. RESULTS: Streptococcus was the most abundant organism in the saliva, making up 8% of the total organisms detected, and their diversity decreased during spaceflight. Other organisms that had statistically significant changes were Proteobacteria and Fusobacteria which increased during flight and Actinobacteria which decreased during flight. At the genus level, Catonella, Megasphera, and Actinobacillus were absent in more than half of saliva samples collected pre-flight but were then detected during flight. In those subjects that already had these genera pre-flight, their relative abundances increased during flight. Correlation analyses between the microbiome and viral titers revealed a positive correlation with Gracilibacteria, Absconditabacteria, and Abiotrophia and a negative correlation between Oribacterium, Veillonella, and Haemophilus. There was also a significant positive correlation between microbiome richness and EBV viral titers. CONCLUSIONS: This is the first study to look at how the salivary microbiome changes as a result of spaceflight and the search for bacterial biomarkers for viral reactivation. Further studies examining the role of specific organisms that were shown to be correlative and predictive in viral reactivation, a serious problem in astronauts during spaceflight, could lead to mitigation strategies to help prevent disease during both short and long duration space missions. Video abstract.

Manipulation of the Gut Microbiome Alters Acetaminophen Biodisposition in Mice.

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.

Multiscale analysis for patterns of Zika virus genotype emergence, spread, and consequence.

The question of how Zika virus (ZIKV) changed from a seemingly mild virus to a human pathogen capable of microcephaly and sexual transmission remains unanswered. The unexpected emergence of ZIKV's pathogenicity and capacity for sexual transmission may be due to genetic changes, and future changes in phenotype may continue to occur as the virus expands its geographic range. Alternatively, the sheer size of the 2015-16 epidemic may have brought attention to a pre-existing virulent ZIKV phenotype in a highly susceptible population. Thus, it is important to identify patterns of genetic change that may yield a better understanding of ZIKV emergence and evolution. However, because ZIKV has an RNA genome and a polymerase incapable of proofreading, it undergoes rapid mutation which makes it difficult to identify combinations of mutations associated with viral emergence. As next generation sequencing technology has allowed whole genome consensus and variant sequence data to be generated for numerous virus samples, the task of analyzing these genomes for patterns of mutation has become more complex. However, understanding which combinations of mutations spread widely and become established in new geographic regions versus those that disappear relatively quickly is essential for defining the trajectory of an ongoing epidemic. In this study, multiscale analysis of the wealth of genomic data generated over the course of the epidemic combined with in vivo laboratory data allowed trends in mutations and outbreak trajectory to be assessed. Mutations were detected throughout the genome via deep sequencing, and many variants appeared in multiple samples and in some cases become consensus. Similarly, amino acids that were previously consensus in pre-outbreak samples were detected as low frequency variants in epidemic strains. Protein structural models indicate that most of the mutations associated with the epidemic transmission occur on the exposed surface of viral proteins. At the macroscale level, consensus data was organized into large and interactive databases to allow the spread of individual mutations and combinations of mutations to be visualized and assessed for temporal and geographical patterns. Thus, the use of multiscale modeling for identifying mutations or combinations of mutations that impact epidemic transmission and phenotypic impact can aid the formation of hypotheses which can then be tested using reverse genetics.

Mosquito-Borne Viruses and Insect-Specific Viruses Revealed in Field-Collected Mosquitoes by a Monitoring Tool Adapted from a Microbial Detection Array.

Several mosquito-borne diseases affecting humans are emerging or reemerging in the United States. The early detection of pathogens in mosquito populations is essential to prevent and control the spread of these diseases. In this study, we tested the potential applicability of the Lawrence Livermore Microbial Detection Array (LLMDA) to enhance biosurveillance by detecting microbes present in Aedes aegypti, Aedes albopictus, and Culex mosquitoes, which are major vector species globally, including in Texas. The sensitivity and reproducibility of the LLMDA were tested in mosquito samples spiked with different concentrations of dengue virus (DENV), revealing a detection limit of >100 but <1,000 PFU/ml. Additionally, field-collected mosquitoes from Chicago, IL, and College Station, TX, of known infection status (West Nile virus [WNV] and Culex flavivirus [CxFLAV] positive) were tested on the LLMDA to confirm its efficiency. Mosquito field samples of unknown infection status, collected in San Antonio, TX, and the Lower Rio Grande Valley (LRGV), TX, were run on the LLMDA and further confirmed by PCR or quantitative PCR (qPCR). The analysis of the field samples with the LLMDA revealed the presence of cell-fusing agent virus (CFAV) in A. aegypti populations. Wolbachia was also detected in several of the field samples (A. albopictus and Culex spp.) by the LLMDA. Our findings demonstrated that the LLMDA can be used to detect multiple arboviruses of public health importance, including viruses that belong to the Flavivirus, Alphavirus, and Orthobunyavirus genera. Additionally, insect-specific viruses and bacteria were also detected in field-collected mosquitoes. Another strength of this array is its ability to detect multiple viruses in the same mosquito pool, allowing for the detection of cocirculating pathogens in an area and the identification of potential ecological associations between different viruses. This array can aid in the biosurveillance of mosquito-borne viruses circulating in specific geographical areas.IMPORTANCE Viruses associated with mosquitoes have made a large impact on public and veterinary health. In the United States, several viruses, including WNV, DENV, and chikungunya virus (CHIKV), are responsible for human disease. From 2015 to 2018, imported Zika cases were reported in the United States, and in 2016 to 2017, local Zika transmission occurred in the states of Texas and Florida. With globalization and a changing climate, the frequency of outbreaks linked to arboviruses will increase, revealing a need to better detect viruses in vector populations. With the capacity of the LLMDA to detect viruses, bacteria, and fungi, this study highlights its ability to broadly screen field-collected mosquitoes and contribute to the surveillance and management of arboviral diseases.

Putative parapoxvirus-associated foot disease in the endangered huemul deer (Hippocamelus bisulcus) in Bernardo O'Higgins National Park, Chile.

The huemul (Hippocamelus bisulcus) is an endangered cervid endemic to southern Argentina and Chile. Here we report foot lesions in 24 huemul from Bernardo O'Higgins National Park, Chile, between 2005 and 2010. Affected deer displayed variably severe clinical signs, including lameness and soft tissue swelling of the limbs proximal to the hoof or in the interdigital space, ulceration of the swollen tissues, and some developed severe proliferative tissue changes that caused various types of abnormal wear, entrapment, and/or displacement of the hooves and/or dewclaws. Animals showed signs of intense pain and reduced mobility followed by loss of body condition and recumbency, which often preceded death. The disease affected both genders and all age categories. Morbidity and mortality reached 80% and 40%, respectively. Diagnostics were restricted to a limited number of cases from which samples were available. Histology revealed severe papillomatous epidermal hyperplasia and superficial dermatitis. Electron microscopy identified viral particles consistent with viruses in the Chordopoxvirinae subfamily. The presence of parapoxvirus DNA was confirmed by a pan-poxvirus PCR assay, showing high identity (98%) with bovine papular stomatitis virus and pseudocowpoxvirus. This is the first report of foot disease in huemul deer in Chile, putatively attributed to poxvirus. Given the high morbidity and mortality observed, this virus might pose a considerable conservation threat to huemul deer in Chilean Patagonia. Moreover, this report highlights a need for improved monitoring of huemul populations and synergistic, rapid response efforts to adequately address disease events that threaten the species.

Axiom Microbiome Array, the next generation microarray for high-throughput pathogen and microbiome analysis.

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. In this study, the Axiom Microbiome Array was evaluated to determine its sensitivity, specificity and utility in microbiome analysis of veterinary clinical samples. The array contains probes designed to detect more than 12,000 species of viruses, bacteria, fungi, protozoa and archaea, yielding the most comprehensive microbial detection platform built to date. The array was able to detect Shigella and Aspergillus at 100 genome copies, and vaccinia virus DNA at 1,000 genome copies. The Axiom Microbiome Array made correct species-level calls in mock microbial community samples. When tested against serum, tissue, and fecal samples from pigs experimentally co-infected with porcine reproductive and respiratory syndrome virus and porcine circovirus type 2, the microarray correctly detected these two viruses and other common viral and bacterial microbiome species. This cost-effective and high-throughput microarray is an efficient tool to rapidly analyze large numbers of clinical and environmental samples for the presence of multiple viral and bacterial pathogens.

A novel variant of torque teno virus 7 identified in patients with Kawasaki disease.

Kawasaki disease (KD), first identified in 1967, is a pediatric vasculitis of unknown etiology that has an increasing incidence in Japan and many other countries. KD can cause coronary artery aneurysms. Its epidemiological characteristics, such as seasonality and clinical picture of acute systemic inflammation with prodromal intestinal/respiratory symptoms, suggest an infectious etiology for KD. Interestingly, multiple host genotypes have been identified as predisposing factors for KD. To explore experimental methodology for identifying etiological agent(s) for KD and to optimize epidemiological study design (particularly the sample size) for future studies, we conducted a pilot study. For a 1-year period, we prospectively enrolled 11 patients with KD. To each KD patient, we assigned two control individuals (one with diarrhea and the other with respiratory infections), matched for age, sex, and season of diagnosis. During the acute phase of disease, we collected peripheral blood, nasopharyngeal aspirate, and feces. We also determined genotypes, to identify those that confer susceptibility to KD. There was no statistically significant difference in the frequency of the risk genotypes between KD patients and control subjects. We also used unbiased metagenomic sequencing to analyze these samples. Metagenomic sequencing and PCR detected torque teno virus 7 (TTV7) in two patients with KD (18%), but not in control subjects (P = 0.111). Sanger sequencing revealed that the TTV7 found in the two KD patients contained almost identical variants in nucleotide and identical changes in resulting amino acid, relative to the reference sequence. Additionally, we estimated the sample size that would be required to demonstrate a statistical correlation between TTV7 and KD. Future larger scale studies with carefully optimized metagenomic sequencing experiments and adequate sample size are warranted to further examine the association between KD and potential pathogens, including TTV7.