Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis.

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

Cystic Fibrosis Rapid Response: Translating Multi-omics Data into Clinically Relevant Information.

Pulmonary exacerbations are the leading cause of death in cystic fibrosis (CF) patients. To track microbial dynamics during acute exacerbations, a CF rapid response (CFRR) strategy was developed. The CFRR relies on viromics, metagenomics, metatranscriptomics, and metabolomics data to rapidly monitor active members of the viral and microbial community during acute CF exacerbations. To highlight CFRR, a case study of a CF patient is presented, in which an abrupt decline in lung function characterized a fatal exacerbation. The microbial community in the patient's lungs was closely monitored through the multi-omics strategy, which led to the identification of pathogenic shigatoxigenic Escherichia coli (STEC) expressing Shiga toxin. This case study illustrates the potential for the CFRR to deconstruct complicated disease dynamics and provide clinicians with alternative treatments to improve the outcomes of pulmonary exacerbations and expand the life spans of individuals with CF.IMPORTANCE Proper management of polymicrobial infections in patients with cystic fibrosis (CF) has extended their life span. Information about the composition and dynamics of each patient's microbial community aids in the selection of appropriate treatment of pulmonary exacerbations. We propose the cystic fibrosis rapid response (CFRR) as a fast approach to determine viral and microbial community composition and activity during CF pulmonary exacerbations. The CFRR potential is illustrated with a case study in which a cystic fibrosis fatal exacerbation was characterized by the presence of shigatoxigenic Escherichia coli The incorporation of the CFRR within the CF clinic could increase the life span and quality of life of CF patients.

Three-Dimensional Microbiome and Metabolome Cartography of a Diseased Human Lung.

Our understanding of the spatial variation in the chemical and microbial makeup of an entire human organ remains limited, in part due to the size and heterogeneity of human organs and the complexity of the associated metabolome and microbiome. To address this challenge, we developed a workflow to enable the cartography of metabolomic and microbiome data onto a three-dimensional (3D) organ reconstruction built off radiological images. This enabled the direct visualization of the microbial and chemical makeup of a human lung from a cystic fibrosis patient. We detected host-derived molecules, microbial metabolites, medications, and region-specific metabolism of medications and placed it in the context of microbial distributions in the lung. Our tool further created browsable maps of a 3D microbiome/metabolome reconstruction map on a radiological image of a human lung and forms an interactive resource for the scientific community.

Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease.

Background. Cystic fibrosis (CF) is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE) that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples) to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable). Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF) and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events) as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

Ecological networking of cystic fibrosis lung infections.

In the context of a polymicrobial infection, treating a specific pathogen poses challenges because of unknown consequences on other members of the community. The presence of ecological interactions between microbes can change their physiology and response to treatment. For example, in the cystic fibrosis lung polymicrobial infection, antimicrobial susceptibility testing on clinical isolates is often not predictive of antibiotic efficacy. Novel approaches are needed to identify the interrelationships within the microbial community to better predict treatment outcomes. Here we used an ecological networking approach on the cystic fibrosis lung microbiome characterized using 16S rRNA gene sequencing and metagenomics. This analysis showed that the community is separated into three interaction groups: Gram-positive anaerobes, Pseudomonas aeruginosa, and Staphylococcus aureus. The P. aeruginosa and S. aureus groups both anti-correlate with the anaerobic group, indicating a functional antagonism. When patients are clinically stable, these major groupings were also stable, however, during exacerbation, these communities fragment. Co-occurrence networking of functional modules annotated from metagenomics data supports that the underlying taxonomic structure is driven by differences in the core metabolism of the groups. Topological analysis of the functional network identified the non-mevalonate pathway of isoprenoid biosynthesis as a keystone for the microbial community, which can be targeted with the antibiotic fosmidomycin. This study uses ecological theory to identify novel treatment approaches against a polymicrobial disease with more predictable outcomes.

Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

Cystic fibrosis (CF) lungs are filled with thick mucus that obstructs airways and facilitates chronic infections. Pseudomonas aeruginosa is a significant pathogen of this disease that produces a variety of toxic small molecules. We used molecular networking-based metabolomics to investigate the chemistry of CF sputa and assess how the microbial molecules detected reflect the microbiome and clinical culture history of the patients. Metabolites detected included xenobiotics, P. aeruginosa specialized metabolites and host sphingolipids. The clinical culture and microbiome profiles did not correspond to the detection of P. aeruginosa metabolites in the same samples. The P. aeruginosa molecules that were detected in sputum did not match those from laboratory cultures. The pseudomonas quinolone signal (PQS) was readily detectable from cultured strains, but absent from sputum, even when its precursor molecules were present. The lack of PQS production in vivo is potentially due to the chemical nature of the CF lung environment, indicating that culture-based studies of this pathogen may not explain its behavior in the lung. The most differentially abundant molecules between CF and non-CF sputum were sphingolipids, including sphingomyelins, ceramides and lactosylceramide. As these highly abundant molecules contain the inflammatory mediator ceramide, they may have a significant role in CF hyperinflammation. This study demonstrates that the chemical makeup of CF sputum is a complex milieu of microbial, host and xenobiotic molecules. Detection of a bacterium by clinical culturing and 16S rRNA gene profiling do not necessarily reflect the active production of metabolites from that bacterium in a sputum sample.

Mass spectral similarity for untargeted metabolomics data analysis of complex mixtures.

While in nucleotide sequencing, the analysis of DNA from complex mixtures of organisms is common, this is not yet true for mass spectrometric data analysis of complex mixtures. The comparative analyses of mass spectrometry data of microbial communities at the molecular level is difficult to perform, especially in the context of a host. The challenge does not lie in generating the mass spectrometry data, rather much of the difficulty falls in the realm of how to derive relevant information from this data. The informatics based techniques to visualize and organize datasets are well established for metagenome sequencing; however, due to the scarcity of informatics strategies in mass spectrometry, it is currently difficult to cross correlate two very different mass spectrometry data sets from microbial communities and their hosts. We highlight that molecular networking can be used as an organizational tool of tandem mass spectrometry data, automated database search for rapid identification of metabolites, and as a workflow to manage and compare mass spectrometry data from complex mixtures of organisms. To demonstrate this platform, we show data analysis from hard corals and a human lung associated with cystic fibrosis.

A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation.

There is a poor understanding of how the physiology of polymicrobial communities in cystic fibrosis (CF) lungs contributes to pulmonary exacerbations and lung function decline. In this study, a microbial culture system based on the principles of the Winogradsky column (WinCF system) was developed to study the physiology of CF microbes. The system used glass capillary tubes filled with artificial sputum medium to mimic a clogged airway bronchiole. Chemical indicators were added to observe microbial physiology within the tubes. Characterization of sputum samples from seven patients showed variation in pH, respiration, biofilm formation and gas production, indicating that the physiology of CF microbial communities varied among patients. Incubation of homogenized tissues from an explant CF lung mirrored responses of a Pseudomonas aeruginosa pure culture, supporting evidence that end-stage lungs are dominated by this pathogen. Longitudinal sputum samples taken through two exacerbation events in a single patient showed that a two-unit drop in pH and a 30% increase in gas production occurred in the tubes prior to exacerbation, which was reversed with antibiotic treatment. Microbial community profiles obtained through amplification and sequencing of the 16S rRNA gene showed that fermentative anaerobes became more abundant during exacerbation and were then reduced during treatment where P. aeruginosa became the dominant bacterium. Results from the WinCF experiments support the model where two functionally different CF microbial communities exist, the persistent Climax Community and the acute Attack Community. Fermentative anaerobes are hypothesized to be the core members of the Attack Community and production of acidic and gaseous products from fermentation may drive developing exacerbations. Treatment targeting the Attack Community may better resolve exacerbations and resulting lung damage.

Purifying the impure: sequencing metagenomes and metatranscriptomes from complex animal-associated samples.

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.

The upper respiratory tract as a microbial source for pulmonary infections in cystic fibrosis. Parallels from island biogeography.

A continuously mixed series of microbial communities inhabits various points of the respiratory tract, with community composition determined by distance from colonization sources, colonization rates, and extinction rates. Ecology and evolution theory developed in the context of biogeography is relevant to clinical microbiology and could reframe the interpretation of recent studies comparing communities from lung explant samples, sputum samples, and oropharyngeal swabs. We propose an island biogeography model of the microbial communities inhabiting different niches in human airways. Island biogeography as applied to communities separated by time and space is a useful parallel for exploring microbial colonization of healthy and diseased lungs, with the potential to inform our understanding of microbial community dynamics and the relevance of microbes detected in different sample types. In this perspective, we focus on the intermixed microbial communities inhabiting different regions of the airways of patients with cystic fibrosis.

Biogeochemical forces shape the composition and physiology of polymicrobial communities in the cystic fibrosis lung.

The cystic fibrosis (CF) lung contains thick mucus colonized by opportunistic pathogens which adapt to the CF lung environment over decades. The difficulty associated with sampling airways has impeded a thorough examination of the biochemical microhabitats these pathogens are exposed to. An indirect approach is to study the responses of microbial communities to these microhabitats, facilitated by high-throughput sequencing of microbial DNA and RNA from sputum samples. Microbial metagenomes and metatranscriptomes were sequenced from multiple CF patients, and the reads were assigned taxonomy and function through sequence homology to NCBI and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database hierarchies. For a comparison, saliva microbial metagenomes from the Human Microbiome Project (HMP) were also analyzed. These analyses identified that functions encoded and expressed by CF microbes were significantly enriched for amino acid catabolism, folate biosynthesis, and lipoic acid biosynthesis. The data indicate that the community uses oxidative phosphorylation as a major energy source but that terminal electron acceptors were diverse. Nitrate reduction was the most abundant anaerobic respiratory pathway, and genes for nitrate reductase were largely assigned to Pseudomonas and Rothia. Although many reductive pathways of the nitrogen cycle were present, the cycle was incomplete, because the oxidative pathways were absent. Due to the abundant amino acid catabolism and incomplete nitrogen cycle, the CF microbial community appears to accumulate ammonia. This finding was verified experimentally using a CF bronchiole culture model system. The data also revealed abundant sensing and transport of iron, ammonium, zinc, and other metals along with a low-oxygen environment. This study reveals the core biochemistry and physiology of the CF microbiome. IMPORTANCE The cystic fibrosis (CF) microbial community is complex and adapts to the environmental conditions of the lung over the lifetime of a CF patient. This analysis illustrates the core functions of the CF microbial community in the context of CF lung biochemistry. There are many studies of the metabolism and physiology of individual microbes within the CF lung, but none that collectively analyze data from the whole microbiome. Understanding the core metabolism of microbes that inhabit the CF lung can provide new targets for novel therapies. The fundamental processes that CF pathogens rely on for survival may represent an Achilles heel for this pathogenic community. Novel therapies that are designed to disrupt understudied survival strategies of the CF microbial community may succeed against otherwise untreatable or antibiotic-resistant microbes.

Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis.

As DNA sequencing becomes faster and cheaper, genomics-based approaches are being explored for their use in personalized diagnoses and treatments. Here, we provide a proof of principle for disease monitoring using personal metagenomic sequencing and traditional clinical microbiology by focusing on three adults with cystic fibrosis (CF). The CF lung is a dynamic environment that hosts a complex ecosystem composed of bacteria, viruses, and fungi that can vary in space and time. Not surprisingly, the microbiome data from the induced sputum samples we collected revealed a significant amount of species diversity not seen in routine clinical laboratory cultures. The relative abundances of several species changed as clinical treatment was altered, enabling the identification of the climax and attack communities that were proposed in an earlier work. All patient microbiomes encoded a diversity of mechanisms to resist antibiotics, consistent with the characteristics of multidrug-resistant microbial communities that are commonly observed in CF patients. The metabolic potentials of these communities differed by the health status and recovery route of each patient. Thus, this pilot study provides an example of how metagenomic data might be used with clinical assessments for the development of treatments tailored to individual patients.

Breath gas metabolites and bacterial metagenomes from cystic fibrosis airways indicate active pH neutral 2,3-butanedione fermentation.

The airways of cystic fibrosis (CF) patients are chronically colonized by patient-specific polymicrobial communities. The conditions and nutrients available in CF lungs affect the physiology and composition of the colonizing microbes. Recent work in bioreactors has shown that the fermentation product 2,3-butanediol mediates cross-feeding between some fermenting bacteria and Pseudomonas aeruginosa, and that this mechanism increases bacterial current production. To examine bacterial fermentation in the respiratory tract, breath gas metabolites were measured and several metagenomes were sequenced from CF and non-CF volunteers. 2,3-butanedione was produced in nearly all respiratory tracts. Elevated levels in one patient decreased during antibiotic treatment, and breath concentrations varied between CF patients at the same time point. Some patients had high enough levels of 2,3-butanedione to irreversibly damage lung tissue. Antibiotic therapy likely dictates the activities of 2,3-butanedione-producing microbes, which suggests a need for further study with larger sample size. Sputum microbiomes were dominated by P. aeruginosa, Streptococcus spp. and Rothia mucilaginosa, and revealed the potential for 2,3-butanedione biosynthesis. Genes encoding 2,3-butanedione biosynthesis were disproportionately abundant in Streptococcus spp, whereas genes for consumption of butanedione pathway products were encoded by P. aeruginosa and R. mucilaginosa. We propose a model where low oxygen conditions in CF lung lead to fermentation and a decrease in pH, triggering 2,3-butanedione fermentation to avoid lethal acidification. We hypothesize that this may also increase phenazine production by P. aeruginosa, increasing reactive oxygen species and providing additional electron acceptors to CF microbes.

Mechanistic model of Rothia mucilaginosa adaptation toward persistence in the CF lung, based on a genome reconstructed from metagenomic data.

The impaired mucociliary clearance in individuals with Cystic Fibrosis (CF) enables opportunistic pathogens to colonize CF lungs. Here we show that Rothia mucilaginosa is a common CF opportunist that was present in 83% of our patient cohort, almost as prevalent as Pseudomonas aeruginosa (89%). Sequencing of lung microbial metagenomes identified unique R. mucilaginosa strains in each patient, presumably due to evolution within the lung. The de novo assembly of a near-complete R. mucilaginosa (CF1E) genome illuminated a number of potential physiological adaptations to the CF lung, including antibiotic resistance, utilization of extracellular lactate, and modification of the type I restriction-modification system. Metabolic characteristics predicted from the metagenomes suggested R. mucilaginosa have adapted to live within the microaerophilic surface of the mucus layer in CF lungs. The results also highlight the remarkable evolutionary and ecological similarities of many CF pathogens; further examination of these similarities has the potential to guide patient care and treatment.

Identification of a novel human papillomavirus by metagenomic analysis of samples from patients with febrile respiratory illness.

As part of a virus discovery investigation using a metagenomic approach, a highly divergent novel Human papillomavirus type was identified in pooled convenience nasal/oropharyngeal swab samples collected from patients with febrile respiratory illness. Phylogenetic analysis of the whole genome and the L1 gene reveals that the new HPV identified in this study clusters with previously described gamma papillomaviruses, sharing only 61.1% (whole genome) and 63.1% (L1) sequence identity with its closest relative in the Papillomavirus episteme (PAVE) database. This new virus was named HPV_SD2 pending official classification. The complete genome of HPV-SD2 is 7,299 bp long (36.3% G/C) and contains 7 open reading frames (L2, L1, E6, E7, E1, E2 and E4) and a non-coding long control region (LCR) between L1 and E6. The metagenomic procedures, coupled with the bioinformatic methods described herein are well suited to detect small circular genomes such as those of human papillomaviruses.

Metagenomics and metatranscriptomics: windows on CF-associated viral and microbial communities.

BACKGROUND: Samples collected from CF patient airways often contain large amounts of host-derived nucleic acids that interfere with recovery and purification of microbial and viral nucleic acids. This study describes metagenomic and metatranscriptomic methods that address these issues. METHODS: Microbial and viral metagenomes, and microbial metatranscriptomes, were successfully prepared from sputum samples from five adult CF patients. RESULTS: Contaminating host DNA was dramatically reduced in the metagenomes. Each CF patient presented a unique microbiome; in some Pseudomonas aeruginosa was replaced by other opportunistic bacteria. Even though the taxonomic composition of the microbiomes is very different, the metabolic potentials encoded by the community are very similar. The viral communities were dominated by phages that infect major CF pathogens. The metatranscriptomes reveal differential expression of encoded metabolic potential with changing health status. CONCLUSIONS: Microbial and viral metagenomics combined with microbial transcriptomics characterize the dynamic polymicrobial communities found in CF airways, revealing both the taxa present and their current metabolic activities. These approaches can facilitate the development of individualized treatment plans and novel therapeutic approaches.

Spatial distribution of microbial communities in the cystic fibrosis lung.

Cystic fibrosis (CF) is a common fatal genetic disorder with mortality most often resulting from microbial infections of the lungs. Culture-independent studies of CF-associated microbial communities have indicated that microbial diversity in the CF airways is much higher than suggested by culturing alone. However, these studies have relied on indirect methods to sample the CF lung such as expectorated sputum and bronchoalveolar lavage (BAL). Here, we characterize the diversity of microbial communities in tissue sections from anatomically distinct regions of the CF lung using barcoded 16S amplicon pyrosequencing. Microbial communities differed significantly between different areas of the lungs, and few taxa were common to microbial communities in all anatomical regions surveyed. Our results indicate that CF lung infections are not only polymicrobial, but also spatially heterogeneous suggesting that treatment regimes tailored to dominant populations in sputum or BAL samples may be ineffective against infections in some areas of the lung.

Case studies of the spatial heterogeneity of DNA viruses in the cystic fibrosis lung.

Microbial communities in the lungs of patients with cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) have been shown to be spatially heterogeneous. Viral communities may also vary spatially, leading to localized viral populations and infections. Here, we characterized viral communities from multiple areas of the lungs of two patients with late-stage CF using metagenomics, that is, the explanted lungs from a transplant patient and lungs acquired postmortem. All regions harbored eukaryotic viruses that may infect the human host, notably herpesviruses, anelloviruses, and papillomaviruses. In the highly diseased apical lobes of explant lungs, viral diversity was extremely low, and only eukaryotic viruses were present. The absence of phage suggests that CF-associated microbial biofilms may escape top-down controls by phage predation. The phages present in other lobes of explant lungs and in all lobes of postmortem lungs comprised distinct communities, and encoded genes for clinically important microbial phenotypes, including small colony variants and antibiotic resistance. Based on the these observations, we postulate that viral communities in CF lungs are spatially distinct and contribute to CF pathology by augmenting the metabolic potential of resident microbes, as well as by directly damaging lung tissue via carcinomas and herpesviral outbreaks.

Broad surveys of DNA viral diversity obtained through viral metagenomics of mosquitoes.

Viruses are the most abundant and diverse genetic entities on Earth; however, broad surveys of viral diversity are hindered by the lack of a universal assay for viruses and the inability to sample a sufficient number of individual hosts. This study utilized vector-enabled metagenomics (VEM) to provide a snapshot of the diversity of DNA viruses present in three mosquito samples from San Diego, California. The majority of the sequences were novel, suggesting that the viral community in mosquitoes, as well as the animal and plant hosts they feed on, is highly diverse and largely uncharacterized. Each mosquito sample contained a distinct viral community. The mosquito viromes contained sequences related to a broad range of animal, plant, insect and bacterial viruses. Animal viruses identified included anelloviruses, circoviruses, herpesviruses, poxviruses, and papillomaviruses, which mosquitoes may have obtained from vertebrate hosts during blood feeding. Notably, sequences related to human papillomaviruses were identified in one of the mosquito samples. Sequences similar to plant viruses were identified in all mosquito viromes, which were potentially acquired through feeding on plant nectar. Numerous bacteriophages and insect viruses were also detected, including a novel densovirus likely infecting Culex erythrothorax. Through sampling insect vectors, VEM enables broad survey of viral diversity and has significantly increased our knowledge of the DNA viruses present in mosquitoes.