Local genomic adaptation of coral reef-associated microbiomes to gradients of natural variability and anthropogenic stressors.

Holobionts are species-specific associations between macro- and microorganisms. On coral reefs, the benthic coverage of coral and algal holobionts varies due to natural and anthropogenic forcings. Different benthic macroorganisms are predicted to have specific microbiomes. In contrast, local environmental factors are predicted to select for specific metabolic pathways in microbes. To reconcile these two predictions, we hypothesized that adaptation of microbiomes to local conditions is facilitated by the horizontal transfer of genes responsible for specific metabolic capabilities. To test this hypothesis, microbial metagenomes were sequenced from 22 coral reefs at 11 Line Islands in the central Pacific that together span a wide range of biogeochemical and anthropogenic influences. Consistent with our hypothesis, the percent cover of major benthic functional groups significantly correlated with particular microbial taxa. Reefs with higher coral cover had a coral microbiome with higher abundances of Alphaproteobacteria (such as Rhodobacterales and Sphingomonadales), whereas microbiomes of algae-dominated reefs had higher abundances of Gammaproteobacteria (such as Alteromonadales, Pseudomonadales, and Vibrionales), Betaproteobacteria, and Bacteriodetes. In contrast to taxa, geography was the strongest predictor of microbial community metabolism. Microbial communities on reefs with higher nutrient availability (e.g., equatorial upwelling zones) were enriched in genes involved in nutrient-related metabolisms (e.g., nitrate and nitrite ammonification, Ton/Tol transport, etc.). On reefs further from the equator, microbes had more genes encoding chlorophyll biosynthesis and photosystems I/II. These results support the hypothesis that core microbiomes are determined by holobiont macroorganisms, and that those core taxa adapt to local conditions by selecting for advantageous metabolic genes.

Using viromes to predict novel immune proteins in non-model organisms.

Immunity is mostly studied in a few model organisms, leaving the majority of immune systems on the planet unexplored. To characterize the immune systems of non-model organisms alternative approaches are required. Viruses manipulate host cell biology through the expression of proteins that modulate the immune response. We hypothesized that metagenomic sequencing of viral communities would be useful to identify both known and unknown host immune proteins. To test this hypothesis, a mock human virome was generated and compared to the human proteome using tBLASTn, resulting in 36 proteins known to be involved in immunity. This same pipeline was then applied to reef-building coral, a non-model organism that currently lacks traditional molecular tools like transgenic animals, gene-editing capabilities, and in vitro cell cultures. Viromes isolated from corals and compared with the predicted coral proteome resulted in 2503 coral proteins, including many proteins involved with pathogen sensing and apoptosis. There were also 159 coral proteins predicted to be involved with coral immunity but currently lacking any functional annotation. The pipeline described here provides a novel method to rapidly predict host immune components that can be applied to virtually any system with the potential to discover novel immune proteins.

Metabolomics of reef benthic interactions reveals a bioactive lipid involved in coral defence.

Holobionts are assemblages of microbial symbionts and their macrobial host. As extant representatives of some of the oldest macro-organisms, corals and algae are important for understanding how holobionts develop and interact with one another. Using untargeted metabolomics, we show that non-self interactions altered the coral metabolome more than self-interactions (i.e. different or same genus, respectively). Platelet activating factor (PAF) and Lyso-PAF, central inflammatory modulators in mammals, were major lipid components of the coral holobionts. When corals were damaged during competitive interactions with algae, PAF increased along with expression of the gene encoding Lyso-PAF acetyltransferase; the protein responsible for converting Lyso-PAF to PAF. This shows that self and non-self recognition among some of the oldest extant holobionts involve bioactive lipids identical to those in highly derived taxa like humans. This further strengthens the hypothesis that major players of the immune response evolved during the pre-Cambrian.

Diversity, Productivity, and Stability of an Industrial Microbial Ecosystem.

Managing ecosystems to maintain biodiversity may be one approach to ensuring their dynamic stability, productivity, and delivery of vital services. The applicability of this approach to industrial ecosystems that harness the metabolic activities of microbes has been proposed but has never been tested at relevant scales. We used a tag-sequencing approach with bacterial small subunit rRNA (16S) genes and eukaryotic internal transcribed spacer 2 (ITS2) to measuring the taxonomic composition and diversity of bacteria and eukaryotes in an open pond managed for bioenergy production by microalgae over a year. Periods of high eukaryotic diversity were associated with high and more-stable biomass productivity. In addition, bacterial diversity and eukaryotic diversity were inversely correlated over time, possibly due to their opposite responses to temperature. The results indicate that maintaining diverse communities may be essential to engineering stable and productive bioenergy ecosystems using microorganisms.

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.

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.

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.

Identification and removal of ribosomal RNA sequences from metatranscriptomes.

SUMMARY: Here, we present riboPicker, a robust framework for the rapid, automated identification and removal of ribosomal RNA sequences from metatranscriptomic datasets. The results can be exported for subsequent analysis, and the databases used for the web-based version are updated on a regular basis. riboPicker categorizes rRNA-like sequences and provides graphical visualizations and tabular outputs of ribosomal coverage, alignment results and taxonomic classifications. AVAILABILITY AND IMPLEMENTATION: This open-source application was implemented in Perl and can be used as stand-alone version or accessed online through a user-friendly web interface. The source code, user help and additional information is available at http://ribopicker.sourceforge.net/. CONTACT: rschmied@sciences.sdsu.edu; rschmied@sciences.sdsu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.

TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets.

BACKGROUND: Sequencing metagenomes that were pre-amplified with primer-based methods requires the removal of the additional tag sequences from the datasets. The sequenced reads can contain deletions or insertions due to sequencing limitations, and the primer sequence may contain ambiguous bases. Furthermore, the tag sequence may be unavailable or incorrectly reported. Because of the potential for downstream inaccuracies introduced by unwanted sequence contaminations, it is important to use reliable tools for pre-processing sequence data. RESULTS: TagCleaner is a web application developed to automatically identify and remove known or unknown tag sequences allowing insertions and deletions in the dataset. TagCleaner is designed to filter the trimmed reads for duplicates, short reads, and reads with high rates of ambiguous sequences. An additional screening for and splitting of fragment-to-fragment concatenations that gave rise to artificial concatenated sequences can increase the quality of the dataset. Users may modify the different filter parameters according to their own preferences. CONCLUSIONS: TagCleaner is a publicly available web application that is able to automatically detect and efficiently remove tag sequences from metagenomic datasets. It is easily configurable and provides a user-friendly interface. The interactive web interface facilitates export functionality for subsequent data processing, and is available at http://edwards.sdsu.edu/tagcleaner.

Decoding diversity in a coral reef fish species complex with restricted range using metagenomic sequencing of gut contents.

AIM: Identification of the processes that generate and maintain species diversity within the same region can provide insight into biogeographic patterns at broader spatiotemporal scales. Hawkfishes in the genus Paracirrhites are a unique taxon to explore with respect to niche differentiation, exhibiting diagnostic differences in coloration, and an apparent center of distribution outside of the Indo-Malay-Philippine (IMP) biodiversity hotspot for coral reef fishes. Our aim is to use next-generation sequencing methods to leverage samples of a taxon at their center of maximum diversity to explore phylogenetic relationships and a possible mechanism of coexistence. LOCATION: Flint Island, Southern Line Islands, Republic of Kiribati. METHODS: A comprehensive review of museum records, the primary literature, and unpublished field survey records was undertaken to determine ranges for four "arc-eye" hawkfish species in the Paracirrhites species complex and a potential hybrid. Fish from four Paracirrhites species were collected from Flint Island in the Southern Line Islands, Republic of Kiribati. Hindgut contents were sequenced, and subsequent metagenomic analyses were used to assess the phylogenetic relatedness of the host fish, the microbiome community structure, and prey remains for each species. RESULTS: Phylogenetic analyses conducted with recovered mitochondrial genomes revealed clustering of P. bicolor with P. arcatus and P. xanthus with P. nisus, which were unexpected on the basis of previous morphological work in this species complex. Differences in taxonomic composition of gut microbial communities and presumed prey remains indicate likely separation of foraging niches. MAIN CONCLUSIONS: Our findings point toward previously unidentified relationships in this cryptic species complex at its proposed center of distribution. The three species endemic to the Polynesian province (P. nisus, P. xanthus, and P. bicolor) cluster separately from the more broadly distributed P. arcatus on the basis of relative abundance of metazoan sequences in the gut (presumed prey remains). Discordance between gut microbial communities and phylogeny of the host fish further reinforce the hypothesis of niche separation.

Metagenomic analysis of viruses in reclaimed water.

Reclaimed water use is an important component of sustainable water resource management. However, there are concerns regarding pathogen transport through this alternative water supply. This study characterized the viral community found in reclaimed water and compared it with viruses in potable water. Reclaimed water contained 1000-fold more virus-like particles than potable water, having approximately 10(8) VLPs per millilitre. Metagenomic analyses revealed that most of the viruses in both reclaimed and potable water were novel. Bacteriophages dominated the DNA viral community in both reclaimed and potable water, but reclaimed water had a distinct phage community based on phage family distributions and host representation within each family. Eukaryotic viruses similar to plant pathogens and invertebrate picornaviruses dominated RNA metagenomic libraries. Established human pathogens were not detected in reclaimed water viral metagenomes, which contained a wealth of novel single-stranded DNA and RNA viruses related to plant, animal and insect viruses. Therefore, reclaimed water may play a role in the dissemination of highly stable viruses. Information regarding viruses present in reclaimed water but not in potable water can be used to identify new bioindicators of water quality. Future studies will need to investigate the infectivity and host range of these viruses to evaluate the impacts of reclaimed water use on human and ecosystem health.

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.

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.

Diel population and functional synchrony of microbial communities on coral reefs.

On coral reefs, microorganisms are essential for recycling nutrients to primary producers through the remineralization of benthic-derived organic matter. Diel investigations of reef processes are required to holistically understand the functional roles of microbial players in these ecosystems. Here we report a metagenomic analysis characterizing microbial communities in the water column overlying 16 remote forereef sites over a diel cycle. Our results show that microbial community composition is more dissimilar between day and night samples collected from the same site than between day or night samples collected across geographically distant reefs. Diel community differentiation is largely driven by the flux of Psychrobacter sp., which is two-orders of magnitude more abundant during the day. Nighttime communities are enriched with species of Roseobacter, Halomonas, and Alteromonas encoding a greater variety of pathways for carbohydrate catabolism, further illustrating temporal patterns of energetic provisioning between different marine microbes. Dynamic diel fluctuations of microbial populations could also support the efficient trophic transfer of energy posited in coral reef food webs.

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.

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.

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.