The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using 14C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of 14C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)'s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.
DWH oil spill; hydrocarbons; iTag/Metagenomics; microbial community structure; sediments
Eukaryotic microbes (protists) residing in the vertebrate gut influence host health and disease, but their diversity and distribution in healthy hosts is poorly understood. Protists found in the gut are typically considered parasites, but many are commensal and some are beneficial. Further, the hygiene hypothesis predicts that association with our co-evolved microbial symbionts may be important to overall health. It is therefore imperative that we understand the normal diversity of our eukaryotic gut microbiota to test for such effects and avoid eliminating commensal organisms. We assembled a dataset of healthy individuals from two populations, one with traditional, agrarian lifestyles and a second with modern, westernized lifestyles, and characterized the human eukaryotic microbiota via high-throughput sequencing. To place the human gut microbiota within a broader context our dataset also includes gut samples from diverse mammals and samples from other aquatic and terrestrial environments. We curated the SILVA ribosomal database to reflect current knowledge of eukaryotic taxonomy and employ it as a phylogenetic framework to compare eukaryotic diversity across environment. We show that adults from the non-western population harbor a diverse community of protists, and diversity in the human gut is comparable to that in other mammals. However, the eukaryotic microbiota of the western population appears depauperate. The distribution of symbionts found in mammals reflects both host phylogeny and diet. Eukaryotic microbiota in the gut are less diverse and more patchily distributed than bacteria. More broadly, we show that eukaryotic communities in the gut are less diverse than in aquatic and terrestrial habitats, and few taxa are shared across habitat types, and diversity patterns of eukaryotes are correlated with those observed for bacteria. These results outline the distribution and diversity of microbial eukaryotic communities in the mammalian gut and across environments.
protist; microbial ecology; microbial diversity; salinity; host-associated eukaryotes; parasites; intestinal protozoa; human microbiome
Understanding microbial partnerships with the medicinally and economically important crop Cannabis has the potential to affect agricultural practice by improving plant fitness and production yield. Furthermore, Cannabis presents an interesting model to explore plant-microbiome interactions as it produces numerous secondary metabolic compounds. Here we present the first description of the endorhiza-, rhizosphere-, and bulk soil-associated microbiome of five distinct Cannabis cultivars. Bacterial communities of the endorhiza showed significant cultivar-specificity. When controlling cultivar and soil type the microbial community structure was significantly different between plant cultivars, soil types, and between the endorhiza, rhizosphere and soil. The influence of soil type, plant cultivar and sample type differentiation on the microbial community structure provides support for a previously published two-tier selection model, whereby community composition across sample types is determined mainly by soil type, while community structure within endorhiza samples is determined mainly by host cultivar.
Sediment microbial communities are responsible for a majority of the metabolic activity in river and stream ecosystems. Understanding the dynamics in community structure and function across freshwater environments will help us to predict how these ecosystems will change in response to human land-use practices. Here we present a spatiotemporal study of sediments in the Tongue River (Montana, USA), comprising six sites along 134 km of river sampled in both spring and fall for two years. Sequencing of 16S rRNA amplicons and shotgun metagenomes revealed that these sediments are the richest (∼65,000 microbial ‘species’ identified) and most novel (93% of OTUs do not match known microbial diversity) ecosystems analyzed by the Earth Microbiome Project to date, and display more functional diversity than was detected in a recent review of global soil metagenomes. Community structure and functional potential have been significantly altered by anthropogenic drivers, including increased pathogenicity and antibiotic metabolism markers near towns and metabolic signatures of coal and coalbed methane extraction byproducts. The core (OTUs shared across all samples) and the overall microbial community exhibited highly similar structure, and phylogeny was weakly coupled with functional potential. Together, these results suggest that microbial community structure is shaped by environmental drivers and niche filtering, though stochastic assembly processes likely play a role as well. These results indicate that sediment microbial communities are highly complex and sensitive to changes in land use practices.
The human and earth microbiome are emerging as among the most important biological agents in understanding and preventing disease. Technology is advancing at a fast pace and allowing for high resolution analysis of the composition and function of our microbial partners across regions, space, and time. Bioinformaticists and biostatisticians are developing ever more elegant displays to understand the generated mega-datasets. A virtual cyberinfrastruture of search engines to cross reference the rapidly developing data is emerging in line with technologic advances. Nutritional science will reap the benefits of this new field and its role in preserving the earth and the humans that inhabit it will become evidently clear. In this report we highlight some of the topics of an ASPEN sponsored symposium that took place at the Clinical Nutrition Week in 2013 that address the importance of the human microbiome to human health and disease.
It is now widely understood that all animals engage in complex interactions with bacteria (or microbes) throughout their various life stages. This ancient exchange can involve cooperation and has resulted in a wide range of evolved host-microbial interdependencies, including those observed in the gut. Ciona intestinalis, a filter-feeding basal chordate and classic developmental model that can be experimentally manipulated, is being employed to help define these relationships. Ciona larvae are first exposed internally to microbes upon the initiation of feeding in metamorphosed individuals; however, whether or not these microbes subsequently colonize the gut and whether or not Ciona forms relationships with specific bacteria in the gut remains unknown. In this report, we show that the Ciona gut not only is colonized by a complex community of bacteria, but also that samples from three geographically isolated populations reveal striking similarity in abundant operational taxonomic units (OTUs) consistent with the selection of a core community by the gut ecosystem.
During hydrocarbon exposure, the composition and functional dynamics of marine microbial communities are altered, favoring bacteria that can utilize this rich carbon source. Initial exposure of high levels of hydrocarbons in aerobic surface sediments can enrich growth of heterotrophic microorganisms having hydrocarbon degradation capacity. As a result, there can be a localized reduction in oxygen potential within the surface layer of marine sediments causing anaerobic zones. We hypothesized that increasing exposure to elevated hydrocarbon concentrations would positively correlate with an increase in denitrification processes and the net accumulation of dinitrogen. This hypothesis was tested by comparing the relative abundance of genes associated with nitrogen metabolism and nitrogen cycling identified in 6 metagenomes from sediments contaminated by polyaromatic hydrocarbons from the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico, and 3 metagenomes from sediments associated with natural oil seeps in the Santa Barbara Channel. An additional 8 metagenomes from uncontaminated sediments from the Gulf of Mexico were analyzed for comparison. We predicted relative changes in metabolite turnover as a function of the differential microbial gene abundances, which showed predicted accumulation of metabolites associated with denitrification processes, including anammox, in the contaminated samples compared to uncontaminated sediments, with the magnitude of this change being positively correlated to the hydrocarbon concentration and exposure duration. These data highlight the potential impact of hydrocarbon inputs on N cycling processes in marine sediments and provide information relevant for system scale models of nitrogen metabolism in affected ecosystems.
nitrogen cycling; marine sediments; denitrification; microbial ecology; metagenomics; deepwater horizon oil spill; oil contamination; oil seeps
The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.
An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.
Biodiversity; Genomics; Biocode; Earth observations
The majority of people in the developed world spend more than 90% of their lives indoors. Here, we examine our understanding of the bacteria that co-inhabit our artificial world and how they might influence human health.
Over the last 60 years, the use of hexachlorocyclohexane (HCH) as a pesticide has resulted in the production of >4 million tons of HCH waste, which has been dumped in open sinks across the globe. Here, the combination of the genomes of two genetic subspecies (Sphingobium japonicum UT26 and Sphingobium indicum B90A; isolated from two discrete geographical locations, Japan and India, respectively) capable of degrading HCH, with metagenomic data from an HCH dumpsite (∼450 mg HCH per g soil), enabled the reconstruction and validation of the last-common ancestor (LCA) genotype. Mapping the LCA genotype (3128 genes) to the subspecies genomes demonstrated that >20% of the genes in each subspecies were absent in the LCA. This includes two enzymes from the ‘upper' HCH degradation pathway, suggesting that the ancestor was unable to degrade HCH isomers, but descendants acquired lin genes by transposon-mediated lateral gene transfer. In addition, anthranilate and homogentisate degradation traits were found to be strain (selectively retained only by UT26) and environment (absent in the LCA and subspecies, but prevalent in the metagenome) specific, respectively. One draft secondary chromosome, two near complete plasmids and eight complete lin transposons were assembled from the metagenomic DNA. Collectively, these results reinforce the elastic nature of the genus Sphingobium, and describe the evolutionary acquisition mechanism of a xenobiotic degradation phenotype in response to environmental pollution. This also demonstrates for the first time the use of metagenomic data in ancestral genotype reconstruction, highlighting its potential to provide significant insight into the development of such phenotypes.
hexachlorocyclohexane; metagenome; pan-genome; last-common ancestor
Recent evidence suggests that a lower extent of the retronasal aroma release correspond to a higher amount of ad libitum food intake. This has been regarded as one of the bases of behavioral choices towards food consumption in obese people. In this pilot study we investigated the hypothesis that saliva from obese individuals could be responsible for an alteration of the retro-nasal aroma release. We tested this hypothesis in vitro, by comparing the release of volatiles from a liquid food matrix (wine) after its interaction with saliva from 28 obese (O) and 28 normal-weight (N) individuals.
Methods and Findings
Amplicon sequencing of the 16S rRNA V4 region indicated that Firmicutes and Actinobacteria were more abundant in O, while Proteobacteria and Fusobacteria dominated in N. Streptococcaceae were significantly more abundant in the O subjects and constituted 34% and 19% on average of the saliva microbiota of O and N subjects, respectively. The Total Antioxidant Capacity was higher in O vs N saliva samples. A model mouth system was used to test whether the in-mouth wine aroma release differs after the interaction with O or N saliva. In O samples, a 18% to 60% significant decrease in the mean concentration of wine volatiles was detected as a result of interaction with saliva, compared with N. This suppression was linked to biochemical differences in O and N saliva composition, which include protein content.
Microbiological and biochemical differences were found in O vs N saliva samples. An impaired retronasal aroma release from white wine was detected in vitro and linked to compositional differences between saliva from obese and normal-weight subjects. Additional in vivo investigations on diverse food matrices could contribute to understanding whether a lower olfactory stimulation due to saliva composition can be a co-factor in the development/maintenance of obesity.
The soil ecosystem is critical for human health, affecting aspects of the environment from key agricultural and edaphic parameters to critical influence on climate change. Soil has more unknown biodiversity than any other ecosystem. We have applied diverse DNA extraction methods coupled with high throughput pyrosequencing to explore 4.88 × 109 bp of metagenomic sequence data from the longest continually studied soil environment (Park Grass experiment at Rothamsted Research in the UK). Results emphasize important DNA extraction biases and unexpectedly low seasonal and vertical soil metagenomic functional class variations. Clustering-based subsystems and carbohydrate metabolism had the largest quantity of annotated reads assigned although <50% of reads were assigned at an E value cutoff of 10−5. In addition, with the more detailed subsystems, cAMP signaling in bacteria (3.24±0.27% of the annotated reads) and the Ton and Tol transport systems (1.69±0.11%) were relatively highly represented. The most highly represented genome from the database was that for a Bradyrhizobium species. The metagenomic variance created by integrating natural and methodological fluctuations represents a global picture of the Rothamsted soil metagenome that can be used for specific questions and future inter-environmental metagenomic comparisons. However, only 1% of annotated sequences correspond to already sequenced genomes at 96% similarity and E values of <10−5, thus, considerable genomic reconstructions efforts still have to be performed.
soil metagenomics; phylogenetic; pyrosequencing; structural biodiversity; functional biodiversity
Recent advances in DNA sequencing technologies have allowed scientists to probe increasingly complex biological systems, including the diversity of bacteria in the environment. However, despite a multitude of recent studies incorporating these methods, many questions regarding how environmental samples should be collected and stored still persist. Here, we assess the impact of different soil storage conditions on microbial community composition using Illumina-based 16S rRNA V4 amplicon sequencing. Both storage time and temperature affected bacterial community composition and structure. Frozen samples maintained the highest alpha diversity and differed least in beta diversity, suggesting the utility of cold storage for maintaining consistent communities. Samples stored for intermediate times (three and seven days) had both the highest alpha diversity and the largest differences in overall beta diversity, showing the degree of community change after sample collection. These divergences notwithstanding, differences in neither storage time nor storage temperature substantially altered overall communities relative to more than 500 previously examined soil samples. These results systematically support previous studies and stress the importance of methodological consistency for accurate characterization and comparison of soil microbiological assemblages.
Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways.
Agrobacterium albertimagni strain AOL15 is an alphaproteobacterium isolated from arsenite-oxidizing biofilms whose draft genome contains 5.1 Mb in 55 contigs with 61.2% GC content and includes a 21-gene arsenic gene island. This is the first available genome for this species and the second Agrobacterium arsenic gene island.
Achromobacter piechaudii strain HLE is a betaproteobacterium (previously known as Alcaligenes faecalis) that was an early isolate with arsenite oxidase activity. This draft genome of 6.89 Mb is the second available genome for this species in the opportunistic pathogen Alcaligenaceae family.
This report details the outcome of the 1st Hospital Microbiome Project workshop held on June 7th-8th, 2012 at the University of Chicago, USA. The workshop was arranged to determine the most appropriate sampling strategy and approach to building science measurement to characterize the development of a microbial community within a new hospital pavilion being built at the University of Chicago Medical Center. The workshop made several recommendations and led to the development of a full proposal to the Alfred P. Sloan Foundation as well as to the creation of the Hospital Microbiome Consortium.
Cold environments, such as glaciers, are large reservoirs of microbial life. The present study employed 16S rRNA gene amplicon metagenomic sequencing to survey the prokaryotic microbiota on Alaskan glacial ice, revealing a rich and diverse microbial community of some 2,500 species of bacteria and archaea.
In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets.
Alcaligenes faecalis subsp. faecalis NCIB 8687, the betaproteobacterium from which arsenite oxidase had its structure solved and the first “arsenate gene island” identified, provided a draft genome of 3.9 Mb in 186 contigs (with the largest 15 comprising 90% of the total) for this opportunistic pathogen species.
The development of culture-independent strategies to study microbial diversity and function has led to a revolution in microbial ecology, enabling us to address fundamental questions about the distribution of microbes and their influence on Earth’s biogeochemical cycles. This article discusses some of the progress that scientists have made with the use of so-called “omic” techniques (metagenomics, metatranscriptomics, and metaproteomics) and the limitations and major challenges these approaches are currently facing. These ‘omic methods have been used to describe the taxonomic structure of microbial communities in different environments and to discover new genes and enzymes of industrial and medical interest. However, microbial community structure varies in different spatial and temporal scales and none of the ‘omic techniques are individually able to elucidate the complex aspects of microbial communities and ecosystems. In this article we highlight the importance of a spatiotemporal sampling design, together with a multilevel ‘omic approach and a community analysis strategy (association networks and modeling) to examine and predict interacting microbial communities and their impact on the environment.
Spatiotemporal sampling; Next generation sequencing; Metagenomics; ‘Omic approach; Community dynamics; Microbial community analysis
Halomonas strain GFAJ-1 was reported in Science magazine to be a remarkable microbe for which there was “arsenate in macromolecules that normally contain phosphate, most notably nucleic acids.” The draft genome of the bacterium was determined (NCBI accession numbers AHBC01000001 through AHBC01000103). It appears to be a typical gamma proteobacterium.
This paper presents the characterization of the microbial community responsible for the in-situ bioremediation of hexachlorocyclohexane (HCH). Microbial community structure and function was analyzed using 16S rRNA amplicon and shotgun metagenomic sequencing methods for three sets of soil samples. The three samples were collected from a HCH-dumpsite (450 mg HCH/g soil) and comprised of a HCH/soil ratio of 0.45, 0.0007, and 0.00003, respectively. Certain bacterial; (Chromohalobacter, Marinimicrobium, Idiomarina, Salinosphaera, Halomonas, Sphingopyxis, Novosphingobium, Sphingomonas and Pseudomonas), archaeal; (Halobacterium, Haloarcula and Halorhabdus) and fungal (Fusarium) genera were found to be more abundant in the soil sample from the HCH-dumpsite. Consistent with the phylogenetic shift, the dumpsite also exhibited a relatively higher abundance of genes coding for chemotaxis/motility, chloroaromatic and HCH degradation (lin genes). Reassembly of a draft pangenome of Chromohalobacter salaxigenes sp. (∼8X coverage) and 3 plasmids (pISP3, pISP4 and pLB1; 13X coverage) containing lin genes/clusters also provides an evidence for the horizontal transfer of HCH catabolism genes.
We present the genomic sequence of the human pathogen Legionella pneumophila serogroup 12 strain 570-CO-H (ATCC 43290), a clinical isolate from the Colorado Department of Health, Denver, CO. This is the first example of a genome sequence of L. pneumophila from a serogroup other than serogroup 1. We highlight the similarities and differences relative to six genome sequences that have been reported for serogroup 1 strains.