Community-wide analysis of microbial genome sequence signatures

Insights into the metabolism, lifestyle and putative evolutionary history of the novel archaeal phylum 'Diapherotrites'

The archaeal phylum 'Diapherotrites' was recently proposed based on phylogenomic analysis of genomes recovered from an underground water seep in an abandoned gold mine (Homestake mine in Lead, SD, USA). Here we present a detailed analysis of the metabolic capabilities and genomic features of three single amplified genomes (SAGs) belonging to the 'Diapherotrites'. The most complete of the SAGs, Candidatus 'Iainarchaeum andersonii' (Cand. IA), had a small genome (∼1.24 Mb), short average gene length (822 bp), one ribosomal RNA operon, high coding density (∼90.4%), high percentage of overlapping genes (27.6%) and low incidence of gene duplication (2.16%). Cand. IA genome possesses limited catabolic capacities that, nevertheless, could theoretically support a free-living lifestyle by channeling a narrow range of substrates such as ribose, polyhydroxybutyrate and several amino acids to acetyl-coenzyme A. On the other hand, Cand. IA possesses relatively well-developed anabolic capabilities, although it remains auxotrophic for several amino acids and cofactors. Phylogenetic analysis suggests that the majority of Cand. IA anabolic genes were acquired from bacterial donors via horizontal gene transfer. We thus propose that members of the 'Diapherotrites' have evolved from an obligate symbiotic ancestor by acquiring anabolic genes from bacteria that enabled independent biosynthesis of biological molecules previously acquired from symbiotic hosts. 'Diapherotrites' 16S rRNA genes exhibit multiple mismatches with the majority of archaeal 16S rRNA primers, a fact that could be responsible for their observed rarity in amplicon-generated data sets. The limited substrate range, complex growth requirements and slow growth rate predicted could be responsible for its refraction to isolation.

Species-level deconvolution of metagenome assemblies with Hi-C-based contact probability maps

Microbial communities consist of mixed populations of organisms, including unknown species in unknown abundances. These communities are often studied through metagenomic shotgun sequencing, but standard library construction methods remove long-range contiguity information; thus, shotgun sequencing and de novo assembly of a metagenome typically yield a collection of contigs that cannot readily be grouped by species. Methods for generating chromatin-level contact probability maps, e.g., as generated by the Hi-C method, provide a signal of contiguity that is completely intracellular and contains both intrachromosomal and interchromosomal information. Here, we demonstrate how this signal can be exploited to reconstruct the individual genomes of microbial species present within a mixed sample. We apply this approach to two synthetic metagenome samples, successfully clustering the genome content of fungal, bacterial, and archaeal species with more than 99% agreement with published reference genomes. We also show that the Hi-C signal can secondarily be used to create scaffolded genome assemblies of individual eukaryotic species present within the microbial community, with higher levels of contiguity than some of the species’ published reference genomes.

(15)N- and (2)H proteomic stable isotope probing links nitrogen flow to archaeal heterotrophic activity

Understanding how individual species contribute to nutrient transformations in a microbial community is critical to prediction of overall ecosystem function. We conducted microcosm experiments in which floating acid mine drainage (AMD) microbial biofilms were submerged - recapitulating the final stage in a natural biofilm life cycle. Biofilms were amended with either (15)NH4(+) or deuterium oxide ((2)H2O) and proteomic stable isotope probing (SIP) was used to track the extent to which different members of the community used these molecules in protein synthesis across anaerobic iron-reducing, aerobic iron-reducing and aerobic iron-oxidizing environments. Sulfobacillus spp. synthesized (15)N-enriched protein almost exclusively under iron-reducing conditions whereas the Leptospirillum spp. synthesized (15)N-enriched protein in all conditions. There were relatively few (15)N-enriched archaeal proteins, and all showed low atom% enrichment, consistent with Archaea synthesizing protein using the predominantly (14)N biomass derived from recycled biomolecules. In parallel experiments using (2)H2O, extensive archaeal protein synthesis was detected in all conditions. In contrast, the bacterial species showed little protein synthesis using (2)H2O. The nearly exclusive ability of Archaea to synthesize proteins using (2)H2O may be due to archaeal heterotrophy, whereby Archaea offset deleterious effects of (2)H by accessing (1)H generated by respiration of organic compounds.

Sulfur oxidation genes in diverse deep-sea viruses

Viruses are the most abundant biological entities in the oceans and a pervasive cause of mortality of microorganisms that drive biogeochemical cycles. Although the ecological and evolutionary effects of viruses on marine phototrophs are well recognized, little is known about their impact on ubiquitous marine lithotrophs. Here, we report 18 genome sequences of double-stranded DNA viruses that putatively infect widespread sulfur-oxidizing bacteria. Fifteen of these viral genomes contain auxiliary metabolic genes for the α and γ subunits of reverse dissimilatory sulfite reductase (rdsr). This enzyme oxidizes elemental sulfur, which is abundant in the hydrothermal plumes studied here. Our findings implicate viruses as a key agent in the sulfur cycle and as a reservoir of genetic diversity for bacterial enzymes that underpin chemosynthesis in the deep oceans.

Metagenomic analysis of the medicinal leech gut microbiota

There are trillions of microbes found throughout the human body and they exceed the number of eukaryotic cells by 10-fold. Metagenomic studies have revealed that the majority of these microbes are found within the gut, playing an important role in the host's digestion and nutrition. The complexity of the animal digestive tract, unculturable microbes, and the lack of genetic tools for most culturable microbes make it challenging to explore the nature of these microbial interactions within this niche. The medicinal leech, Hirudo verbana, has been shown to be a useful tool in overcoming these challenges, due to the simplicity of the microbiome and the availability of genetic tools for one of the two dominant gut symbionts, Aeromonas veronii. In this study, we utilize 16S rRNA gene pyrosequencing to further explore the microbial composition of the leech digestive tract, confirming the dominance of two taxa, the Rikenella-like bacterium and A. veronii. The deep sequencing approach revealed the presence of additional members of the microbial community that suggests the presence of a moderately complex microbial community with a richness of 36 taxa. The presence of a Proteus strain as a newly identified resident in the leech crop was confirmed using fluorescence in situ hybridization (FISH). The metagenome of this community was also pyrosequenced and the contigs were binned into the following taxonomic groups: Rikenella-like (3.1 MB), Aeromonas (4.5 MB), Proteus (2.9 MB), Clostridium (1.8 MB), Eryspelothrix (0.96 MB), Desulfovibrio (0.14 MB), and Fusobacterium (0.27 MB). Functional analyses on the leech gut symbionts were explored using the metagenomic data and MG-RAST. A comparison of the COG and KEGG categories of the leech gut metagenome to that of other animal digestive-tract microbiomes revealed that the leech digestive tract had a similar metabolic potential to the human digestive tract, supporting the usefulness of this system as a model for studying digestive-tract microbiomes. This study lays the foundation for more detailed metatranscriptomic studies and the investigation of symbiont population dynamics.

Genome signature-based dissection of human gut metagenomes to extract subliminal viral sequences

Bacterial viruses (bacteriophages) have a key role in shaping the development and functional outputs of host microbiomes. Although metagenomic approaches have greatly expanded our understanding of the prokaryotic virosphere, additional tools are required for the phage-oriented dissection of metagenomic data sets, and host-range affiliation of recovered sequences. Here we demonstrate the application of a genome signature-based approach to interrogate conventional whole-community metagenomes and access subliminal, phylogenetically targeted, phage sequences present within. We describe a portion of the biological dark matter extant in the human gut virome, and bring to light a population of potentially gut-specific Bacteroidales-like phage, poorly represented in existing virus like particle-derived viral metagenomes. These predominantly temperate phage were shown to encode functions of direct relevance to human health in the form of antibiotic resistance genes, and provided evidence for the existence of putative ‘viral-enterotypes’ among this fraction of the human gut virome.

Bacteriophages have a significant impact on microbial ecosystems, but additional tools are needed to assess viral communities. Ogilvie et al. present a new strategy to extract viral sequences from metagenomic data sets, and present new insights on their function in the gut ecosystem.

Alignment-free visualization of metagenomic data by nonlinear dimension reduction

The visualization of metagenomic data, especially without prior taxonomic identification of reconstructed genomic fragments, is a challenging problem in computational biology. An ideal visualization method should, among others, enable clear distinction of congruent groups of sequences of closely related taxa, be applicable to fragments of lengths typically achievable following assembly, and allow the efficient analysis of the growing amounts of community genomic sequence data. Here, we report a scalable approach for the visualization of metagenomic data that is based on nonlinear dimension reduction via Barnes-Hut Stochastic Neighbor Embedding of centered log-ratio transformed oligonucleotide signatures extracted from assembled genomic sequence fragments. The approach allows for alignment-free assessment of the data-inherent taxonomic structure, and it can potentially facilitate the downstream binning of genomic fragments into uniform clusters reflecting organismal origin. We demonstrate the performance of our approach by visualizing community genomic sequence data from simulated as well as groundwater, human-derived and marine microbial communities.

Metabolic interdependencies between phylogenetically novel fermenters and respiratory organisms in an unconfined aquifer

Fermentation-based metabolism is an important ecosystem function often associated with environments rich in organic carbon, such as wetlands, sewage sludge and the mammalian gut. The diversity of microorganisms and pathways involved in carbon and hydrogen cycling in sediments and aquifers and the impacts of these processes on other biogeochemical cycles remain poorly understood. Here we used metagenomics and proteomics to characterize microbial communities sampled from an aquifer adjacent to the Colorado River at Rifle, CO, USA, and document interlinked microbial roles in geochemical cycling. The organic carbon content in the aquifer was elevated via acetate amendment of the groundwater occurring over 2 successive years. Samples were collected at three time points, with the objective of extensive genome recovery to enable metabolic reconstruction of the community. Fermentative community members include organisms from a new phylum, Melainabacteria, most closely related to Cyanobacteria, phylogenetically novel members of the Chloroflexi and Bacteroidales, as well as candidate phyla genomes (OD1, BD1-5, SR1, WWE3, ACD58, TM6, PER and OP11). These organisms have the capacity to produce hydrogen, acetate, formate, ethanol, butyrate and lactate, activities supported by proteomic data. The diversity and expression of hydrogenases suggests the importance of hydrogen metabolism in the subsurface. Our proteogenomic data further indicate the consumption of fermentation intermediates by Proteobacteria can be coupled to nitrate, sulfate and iron reduction. Thus, fermentation carried out by previously unknown members of sediment microbial communities may be an important driver of nitrogen, hydrogen, sulfur, carbon and iron cycling.

MetaCluster-TA: taxonomic annotation for metagenomic data based on assembly-assisted binning

BACKGROUND

Taxonomic annotation of reads is an important problem in metagenomic analysis. Existing annotation tools, which rely on the approach of aligning each read to the taxonomic structure, are unable to annotate many reads efficiently and accurately as reads (~100 bp) are short and most of them come from unknown genomes. Previous work has suggested assembling the reads to make longer contigs before annotation. More reads/contigs can be annotated as a longer contig (in Kbp) can be aligned to a taxon even if it is from an unknown species as long as it contains a conserved region of that taxon. Unfortunately existing metagenomic assembly tools are not mature enough to produce long enough contigs. Binning tries to group reads/contigs of similar species together. Intuitively, reads in the same group (cluster) should be annotated to the same taxon and these reads altogether should cover a significant portion of the genome alleviating the problem of short contigs if the quality of binning is high. However, no existing work has tried to use binning results to help solve the annotation problem. This work explores this direction.

RESULTS

In this paper, we describe MetaCluster-TA, an assembly-assisted binning-based annotation tool which relies on an innovative idea of annotating binned reads instead of aligning each read or contig to the taxonomic structure separately. We propose the novel concept of the 'virtual contig' (which can be up to 10 Kb in length) to represent a set of reads and then represent each cluster as a set of 'virtual contigs' (which together can be total up to 1 Mb in length) for annotation. MetaCluster-TA can outperform widely-used MEGAN4 and can annotate (1) more reads since the virtual contigs are much longer; (2) more accurately since each cluster of long virtual contigs contains global information of the sampled genome which tends to be more accurate than short reads or assembled contigs which contain only local information of the genome; and (3) more efficiently since there are much fewer long virtual contigs to align than short reads. MetaCluster-TA outperforms MetaCluster 5.0 as a binning tool since binning itself can be more sensitive and precise given long virtual contigs and the binning results can be improved using the reference taxonomic database.

CONCLUSIONS

MetaCluster-TA can outperform widely-used MEGAN4 and can annotate more reads with higher accuracy and higher efficiency. It also outperforms MetaCluster 5.0 as a binning tool.

PhyloSift: phylogenetic analysis of genomes and metagenomes

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection.

In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata.

These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).

Comparison of metatranscriptomic samples based on k-tuple frequencies

Background

The comparison of samples, or beta diversity, is one of the essential problems in ecological studies. Next generation sequencing (NGS) technologies make it possible to obtain large amounts of metagenomic and metatranscriptomic short read sequences across many microbial communities. De novo assembly of the short reads can be especially challenging because the number of genomes and their sequences are generally unknown and the coverage of each genome can be very low, where the traditional alignment-based sequence comparison methods cannot be used. Alignment-free approaches based on k-tuple frequencies, on the other hand, have yielded promising results for the comparison of metagenomic samples. However, it is not known if these approaches can be used for the comparison of metatranscriptome datasets and which dissimilarity measures perform the best.

Results

We applied several beta diversity measures based on k-tuple frequencies to real metatranscriptomic datasets from pyrosequencing 454 and Illumina sequencing platforms to evaluate their effectiveness for the clustering of metatranscriptomic samples, including three dissimilarity measures, one dissimilarity measure in CVTree, one relative entropy based measure S2 and three classical distances. Results showed that the measure can achieve superior performance on clustering metatranscriptomic samples into different groups under different sequencing depths for both 454 and Illumina datasets, recovering environmental gradients affecting microbial samples, classifying coexisting metagenomic and metatranscriptomic datasets, and being robust to sequencing errors. We also investigated the effects of tuple size and order of the background Markov model. A software pipeline to implement all the steps of analysis is built and is available at http://code.google.com/p/d2-tools/.

Conclusions

The k-tuple based sequence signature measures can effectively reveal major groups and gradient variation among metatranscriptomic samples from NGS reads. The dissimilarity measure performs well in all application scenarios and its performance is robust with respect to tuple size and order of the Markov model.

An introduction to the analysis of shotgun metagenomic data

Environmental DNA sequencing has revealed the expansive biodiversity of microorganisms and clarified the relationship between host-associated microbial communities and host phenotype. Shotgun metagenomic DNA sequencing is a relatively new and powerful environmental sequencing approach that provides insight into community biodiversity and function. But, the analysis of metagenomic sequences is complicated due to the complex structure of the data. Fortunately, new tools and data resources have been developed to circumvent these complexities and allow researchers to determine which microbes are present in the community and what they might be doing. This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use. Specifically, it documents how metagenomes can be analyzed to quantify community structure and diversity, assemble novel genomes, identify new taxa and genes, and determine which metabolic pathways are encoded in the community. It also discusses several methods that can be used compare metagenomes to identify taxa and functions that differentiate communities.

MaxBin: an automated binning method to recover individual genomes from metagenomes using an expectation-maximization algorithm

BACKGROUND

Recovering individual genomes from metagenomic datasets allows access to uncultivated microbial populations that may have important roles in natural and engineered ecosystems. Understanding the roles of these uncultivated populations has broad application in ecology, evolution, biotechnology and medicine. Accurate binning of assembled metagenomic sequences is an essential step in recovering the genomes and understanding microbial functions.

RESULTS

We have developed a binning algorithm, MaxBin, which automates the binning of assembled metagenomic scaffolds using an expectation-maximization algorithm after the assembly of metagenomic sequencing reads. Binning of simulated metagenomic datasets demonstrated that MaxBin had high levels of accuracy in binning microbial genomes. MaxBin was used to recover genomes from metagenomic data obtained through the Human Microbiome Project, which demonstrated its ability to recover genomes from real metagenomic datasets with variable sequencing coverages. Application of MaxBin to metagenomes obtained from microbial consortia adapted to grow on cellulose allowed genomic analysis of new, uncultivated, cellulolytic bacterial populations, including an abundant myxobacterial population distantly related to Sorangium cellulosum that possessed a much smaller genome (5 MB versus 13 to 14 MB) but has a more extensive set of genes for biomass deconstruction. For the cellulolytic consortia, the MaxBin results were compared to binning using emergent self-organizing maps (ESOMs) and differential coverage binning, demonstrating that it performed comparably to these methods but had distinct advantages in automation, resolution of related genomes and sensitivity.

CONCLUSIONS

The automatic binning software that we developed successfully classifies assembled sequences in metagenomic datasets into recovered individual genomes. The isolation of dozens of species in cellulolytic microbial consortia, including a novel species of myxobacteria that has the smallest genome among all sequenced aerobic myxobacteria, was easily achieved using the binning software. This work demonstrates that the processes required for recovering genomes from assembled metagenomic datasets can be readily automated, an important advance in understanding the metabolic potential of microbes in natural environments. MaxBin is available at https://sourceforge.net/projects/maxbin/.

Blobology: exploring raw genome data for contaminants, symbionts and parasites using taxon-annotated GC-coverage plots

Generating the raw data for a de novo genome assembly project for a target eukaryotic species is relatively easy. This democratization of access to large-scale data has allowed many research teams to plan to assemble the genomes of non-model organisms. These new genome targets are very different from the traditional, inbred, laboratory-reared model organisms. They are often small, and cannot be isolated free of their environment – whether ingested food, the surrounding host organism of parasites, or commensal and symbiotic organisms attached to or within the individuals sampled. Preparation of pure DNA originating from a single species can be technically impossible, but assembly of mixed-organism DNA can be difficult, as most genome assemblers perform poorly when faced with multiple genomes in different stoichiometries. This class of problem is common in metagenomic datasets that deliberately try to capture all the genomes present in an environment, but replicon assembly is not often the goal of such programs. Here we present an approach to extracting, from mixed DNA sequence data, subsets that correspond to single species’ genomes and thus improving genome assembly. We use both numerical (proportion of GC bases and read coverage) and biological (best-matching sequence in annotated databases) indicators to aid partitioning of draft assembly contigs, and the reads that contribute to those contigs, into distinct bins that can then be subjected to rigorous, optimized assembly, through the use of taxon-annotated GC-coverage plots (TAGC plots). We also present Blobsplorer, a tool that aids exploration and selection of subsets from TAGC-annotated data. Partitioning the data in this way can rescue poorly assembled genomes, and reveal unexpected symbionts and commensals in eukaryotic genome projects. The TAGC plot pipeline script is available from https://github.com/blaxterlab/blobology, and the Blobsplorer tool from https://github.com/mojones/Blobsplorer.

A Novel Bioinformatics Strategy to Analyze Microbial Big Sequence Data for Efficient Knowledge Discovery: Batch-Learning Self-Organizing Map (BLSOM)

With the remarkable increase of genomic sequence data of microorganisms, novel tools are needed for comprehensive analyses of the big sequence data available. The self-organizing map (SOM) is an effective tool for clustering and visualizing high-dimensional data, such as oligonucleotide composition on one map. By modifying the conventional SOM, we developed batch-learning SOM (BLSOM), which allowed classification of sequence fragments (e.g., 1 kb) according to phylotypes, solely depending on oligonucleotide composition. Metagenomics studies of uncultivable microorganisms in clinical and environmental samples should allow extensive surveys of genes important in life sciences. BLSOM is most suitable for phylogenetic assignment of metagenomic sequences, because fragmental sequences can be clustered according to phylotypes, solely depending on oligonucleotide composition. We first constructed oligonucleotide BLSOMs for all available sequences from genomes of known species, and by mapping metagenomic sequences on these large-scale BLSOMs, we can predict phylotypes of individual metagenomic sequences, revealing a microbial community structure of uncultured microorganisms, including viruses. BLSOM has shown that influenza viruses isolated from humans and birds clearly differ in oligonucleotide composition. Based on this host-dependent oligonucleotide composition, we have proposed strategies for predicting directional changes of virus sequences and for surveilling potentially hazardous strains when introduced into humans from non-human sources.

Single-cell genome and metatranscriptome sequencing reveal metabolic interactions of an alkane-degrading methanogenic community

Microbial interactions have a key role in global geochemical cycles. Although we possess significant knowledge about the general biochemical processes occurring in microbial communities, we are often unable to decipher key functions of individual microorganisms within the environment in part owing to the inability to cultivate or study them in isolation. Here, we circumvent this shortcoming through the use of single-cell genome sequencing and a novel low-input metatranscriptomics protocol to reveal the intricate metabolic capabilities and microbial interactions of an alkane-degrading methanogenic community. This methanogenic consortium oxidizes saturated hydrocarbons under anoxic conditions through a thus-far-uncharacterized biochemical process. The genome sequence of a dominant bacterial member of this community, belonging to the genus Smithella, was sequenced and served as the basis for subsequent analysis through metabolic reconstruction. Metatranscriptomic data generated from less than 500 pg of mRNA highlighted metabolically active genes during anaerobic alkane oxidation in comparison with growth on fatty acids. These data sets suggest that Smithella is not activating hexadecane by fumarate addition. Differential expression assisted in the identification of hypothetical proteins with no known homology that may be involved in hexadecane activation. Additionally, the combination of 16S rDNA sequence and metatranscriptomic data enabled the study of other prevalent organisms within the consortium and their interactions with Smithella, thus yielding a comprehensive characterization of individual constituents at the genome scale during methanogenic alkane oxidation.

Small genomes and sparse metabolisms of sediment-associated bacteria from four candidate phyla

Cultivation-independent surveys of microbial diversity have revealed many bacterial phyla that lack cultured representatives. These lineages, referred to as candidate phyla, have been detected across many environments. Here, we deeply sequenced microbial communities from acetate-stimulated aquifer sediment to recover the complete and essentially complete genomes of single representatives of the candidate phyla SR1, WWE3, TM7, and OD1. All four of these genomes are very small, 0.7 to 1.2 Mbp, and have large inventories of novel proteins. Additionally, all lack identifiable biosynthetic pathways for several key metabolites. The SR1 genome uses the UGA codon to encode glycine, and the same codon is very rare in the OD1 genome, suggesting that the OD1 organism could also transition to alternate coding. Interestingly, the relative abundance of the members of SR1 increased with the appearance of sulfide in groundwater, a pattern mirrored by a member of the phylum Tenericutes. All four genomes encode type IV pili, which may be involved in interorganism interaction. On the basis of these results and other recently published research, metabolic dependence on other organisms may be widely distributed across multiple bacterial candidate phyla.

Few or no genomic sequences exist for members of the numerous bacterial phyla lacking cultivated representatives, making it difficult to assess their roles in the environment. This paper presents three complete and one essentially complete genomes of members of four candidate phyla, documents consistently small genome size, and predicts metabolic capabilities on the basis of gene content. These metagenomic analyses expand our view of a lifestyle apparently common across these candidate phyla.

Reconstructing the genomic content of microbiome taxa through shotgun metagenomic deconvolution

Metagenomics has transformed our understanding of the microbial world, allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples. However, associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge. Existing binning methods, based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa. Here, we introduce a novel computational framework, integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members. This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction. An implementation of this framework is available at http://elbo.gs.washington.edu/software.html. We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components. We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples. We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes. We finally apply metagenomic deconvolution to samples from the Human Microbiome Project, successfully reconstructing genus-level genomic content of various microbial genera, based solely on variation in gene count. These reconstructed genera are shown to correctly capture genus-specific properties. With the accumulation of metagenomic data, this deconvolution framework provides an essential tool for characterizing microbial taxa never before seen, laying the foundation for addressing fundamental questions concerning the taxa comprising diverse microbial communities.

The human gut and groundwater harbor non-photosynthetic bacteria belonging to a new candidate phylum sibling to Cyanobacteria

Cyanobacteria were responsible for the oxygenation of the ancient atmosphere; however, the evolution of this phylum is enigmatic, as relatives have not been characterized. Here we use whole genome reconstruction of human fecal and subsurface aquifer metagenomic samples to obtain complete genomes for members of a new candidate phylum sibling to Cyanobacteria, for which we propose the designation 'Melainabacteria'. Metabolic analysis suggests that the ancestors to both lineages were non-photosynthetic, anaerobic, motile, and obligately fermentative. Cyanobacterial light sensing may have been facilitated by regulators present in the ancestor of these lineages. The subsurface organism has the capacity for nitrogen fixation using a nitrogenase distinct from that in Cyanobacteria, suggesting nitrogen fixation evolved separately in the two lineages. We hypothesize that Cyanobacteria split from Melainabacteria prior or due to the acquisition of oxygenic photosynthesis. Melainabacteria remained in anoxic zones and differentiated by niche adaptation, including for symbiosis in the mammalian gut. DOI:http://dx.doi.org/10.7554/eLife.01102.001.

Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries

Recent advances in sequencing technologies generate new predictions and hypotheses about the functional roles of environmental microorganisms. Yet, until we can test these predictions at a scale that matches our ability to generate them, most of them will remain as hypotheses. Function-based mining of metagenomic libraries can provide direct linkages between genes, metabolic traits and microbial taxa and thus bridge this gap between sequence data generation and functional predictions. Here we developed high-throughput screening assays for function-based characterization of activities involved in plant polymer decomposition from environmental metagenomic libraries. The multiplexed assays use fluorogenic and chromogenic substrates, combine automated liquid handling and use a genetically modified expression host to enable simultaneous screening of 12,160 clones for 14 activities in a total of 170,240 reactions. Using this platform we identified 374 (0.26%) cellulose, hemicellulose, chitin, starch, phosphate and protein hydrolyzing clones from fosmid libraries prepared from decomposing leaf litter. Sequencing on the Illumina MiSeq platform, followed by assembly and gene prediction of a subset of 95 fosmid clones, identified a broad range of bacterial phyla, including Actinobacteria, Bacteroidetes, multiple Proteobacteria sub-phyla in addition to some Fungi. Carbohydrate-active enzyme genes from 20 different glycoside hydrolase (GH) families were detected. Using tetranucleotide frequency (TNF) binning of fosmid sequences, multiple enzyme activities from distinct fosmids were linked, demonstrating how biochemically-confirmed functional traits in environmental metagenomes may be attributed to groups of specific organisms. Overall, our results demonstrate how functional screening of metagenomic libraries can be used to connect microbial functionality to community composition and, as a result, complement large-scale metagenomic sequencing efforts.

Alignment-free supervised classification of metagenomes by recursive SVM

BACKGROUND

Comparison and classification of metagenome samples is one of the major tasks in the study of microbial communities of natural environments or niches on human bodies. Bioinformatics methods play important roles on this task, including 16S rRNA gene analysis and some alignment-based or alignment-free methods on metagenomic data. Alignment-free methods have the advantage of not depending on known genome annotations and therefore have high potential in studying complicated microbiomes. However, the existing alignment-free methods are all based on unsupervised learning strategy (e.g., PCA or hierarchical clustering). These types of methods are powerful in revealing major similarities and grouping relations between microbiome samples, but cannot be applied for discriminating predefined classes of interest which might not be the dominating assortment in the data. Supervised classification is needed in the latter scenario, with the goal of classifying samples into predefined classes and finding the features that can discriminate the classes. The effectiveness of supervised classification with alignment-based features on metagenomic data have been shown in some recent studies. The application of alignment-free supervised classification methods on metagenome data has not been well explored yet.

RESULTS

We developed a method for this task using k-tuple frequencies as features counted directly from metagenome short reads and the R-SVM (Recursive SVM) for feature selection and classification. We tested our method on a simulation dataset, a real dataset composed of several known genomes, and a real metagenome NGS short reads dataset. Experiments on simulated data showed that the method can classify the classes almost perfectly and can recover major sequence signatures that distinguish the two classes. On the real human gut metagenome data, the method can discriminate samples of inflammatory bowel disease (IBD) patients from control samples with high accuracy, which cannot be separated when comparing the samples with unsupervised clustering approaches.

CONCLUSIONS

The proposed alignment-free supervised classification method can perform well in discriminating of metagenomic samples of predefined classes and in selecting characteristic sequence features for the discrimination. This study shows as an example on the feasibility of using metagenome sequence features of microbiomes on human bodies to study specific human health conditions using supervised machine learning methods.

Draft Genome Sequence of Thermotoga maritima A7A Reconstructed from Metagenomic Sequencing Analysis of a Hydrocarbon Reservoir in the Bass Strait, Australia

The draft genome sequence of Thermotoga maritima A7A was obtained from a metagenomic assembly obtained from a high-temperature hydrocarbon reservoir in the Gippsland Basin, Australia. The organism is predicted to be a motile anaerobe with an array of catabolic enzymes for the degradation of numerous carbohydrates.

New group in the Leptospirillum clade: cultivation-independent community genomics, proteomics, and transcriptomics of the new species "Leptospirillum group IV UBA BS"

Leptospirillum spp. are widespread members of acidophilic microbial communities that catalyze ferrous iron oxidation, thereby increasing sulfide mineral dissolution rates. These bacteria play important roles in environmental acidification and are harnessed for bioleaching-based metal recovery. Known members of the Leptospirillum clade of the Nitrospira phylum are Leptospirillum ferrooxidans (group I), Leptospirillum ferriphilum and "Leptospirillum rubarum" (group II), and Leptospirillum ferrodiazotrophum (group III). In the Richmond Mine acid mine drainage (AMD) system, biofilm formation is initiated by L. rubarum; L. ferrodiazotrophum appears in later developmental stages. Here we used community metagenomic data from unusual, thick floating biofilms to identify distinguishing metabolic traits in a rare and uncultivated community member, the new species "Leptospirillum group IV UBA BS." These biofilms typically also contain a variety of Archaea, Actinobacteria, and a few other Leptospirillum spp. The Leptospirillum group IV UBA BS species shares 98% 16S rRNA sequence identity and 70% average amino acid identity between orthologs with its closest relative, L. ferrodiazotrophum. The presence of nitrogen fixation and reverse tricarboxylic acid (TCA) cycle proteins suggest an autotrophic metabolism similar to that of L. ferrodiazotrophum, while hydrogenase proteins suggest anaerobic metabolism. Community transcriptomic and proteomic analyses demonstrate expression of a multicopper oxidase unique to this species, as well as hydrogenases and core metabolic genes. Results suggest that the Leptospirillum group IV UBA BS species might play important roles in carbon fixation, nitrogen fixation, hydrogen metabolism, and iron oxidation in some acidic environments.

Community genomic analyses constrain the distribution of metabolic traits across the Chloroflexi phylum and indicate roles in sediment carbon cycling

BACKGROUND

Sediments are massive reservoirs of carbon compounds and host a large fraction of microbial life. Microorganisms within terrestrial aquifer sediments control buried organic carbon turnover, degrade organic contaminants, and impact drinking water quality. Recent 16S rRNA gene profiling indicates that members of the bacterial phylum Chloroflexi are common in sediment. Only the role of the class Dehalococcoidia, which degrade halogenated solvents, is well understood. Genomic sampling is available for only six of the approximate 30 Chloroflexi classes, so little is known about the phylogenetic distribution of reductive dehalogenation or about the broader metabolic characteristics of Chloroflexi in sediment.

RESULTS

We used metagenomics to directly evaluate the metabolic potential and diversity of Chloroflexi in aquifer sediments. We sampled genomic sequence from 86 Chloroflexi representing 15 distinct lineages, including members of eight classes previously characterized only by 16S rRNA sequences. Unlike in the Dehalococcoidia, genes for organohalide respiration are rare within the Chloroflexi genomes sampled here. Near-complete genomes were reconstructed for three Chloroflexi. One, a member of an unsequenced lineage in the Anaerolinea, is an aerobe with the potential for respiring diverse carbon compounds. The others represent two genomically unsampled classes sibling to the Dehalococcoidia, and are anaerobes likely involved in sugar and plant-derived-compound degradation to acetate. Both fix CO2 via the Wood-Ljungdahl pathway, a pathway not previously documented in Chloroflexi. The genomes each encode unique traits apparently acquired from Archaea, including mechanisms of motility and ATP synthesis.

CONCLUSIONS

Chloroflexi in the aquifer sediments are abundant and highly diverse. Genomic analyses provide new evolutionary boundaries for obligate organohalide respiration. We expand the potential roles of Chloroflexi in sediment carbon cycling beyond organohalide respiration to include respiration of sugars, fermentation, CO2 fixation, and acetogenesis with ATP formation by substrate-level phosphorylation.

A new omics data resource of Pleurocybella porrigens for gene discovery

Background

Pleurocybellaporrigens is a mushroom-forming fungus, which has been consumed as a traditional food in Japan. In 2004, 55 people were poisoned by eating the mushroom and 17 people among them died of acute encephalopathy. Since then, the Japanese government has been alerting Japanese people to take precautions against eating the P. porrigens mushroom. Unfortunately, despite efforts, the molecular mechanism of the encephalopathy remains elusive. The genome and transcriptome sequence data of P. porrigens and the related species, however, are not stored in the public database. To gain the omics data in P. porrigens, we sequenced genome and transcriptome of its fruiting bodies and mycelia by next generation sequencing.

Methodology/Principal Findings

Short read sequences of genomic DNAs and mRNAs in P. porrigens were generated by Illumina Genome Analyzer. Genome short reads were de novo assembled into scaffolds using Velvet. Comparisons of genome signatures among Agaricales showed that P. porrigens has a unique genome signature. Transcriptome sequences were assembled into contigs (unigenes). Biological functions of unigenes were predicted by Gene Ontology and KEGG pathway analyses. The majority of unigenes would be novel genes without significant counterparts in the public omics databases.

Conclusions

Functional analyses of unigenes present the existence of numerous novel genes in the basidiomycetes division. The results mean that the omics information such as genome, transcriptome and metabolome in basidiomycetes is short in the current databases. The large-scale omics information on P. porrigens, provided from this research, will give a new data resource for gene discovery in basidiomycetes.

Comparative genomics in acid mine drainage biofilm communities reveals metabolic and structural differentiation of co-occurring archaea

Background

Metal sulfide mineral dissolution during bioleaching and acid mine drainage (AMD) formation creates an environment that is inhospitable to most life. Despite dominance by a small number of bacteria, AMD microbial biofilm communities contain a notable variety of coexisting and closely related Euryarchaea, most of which have defied cultivation efforts. For this reason, we used metagenomics to analyze variation in gene content that may contribute to niche differentiation among co-occurring AMD archaea. Our analyses targeted members of the Thermoplasmatales and related archaea. These results greatly expand genomic information available for this archaeal order.

Results

We reconstructed near-complete genomes for uncultivated, relatively low abundance organisms A-, E-, and Gplasma, members of Thermoplasmatales order, and for a novel organism, Iplasma. Genomic analyses of these organisms, as well as Ferroplasma type I and II, reveal that all are facultative aerobic heterotrophs with the ability to use many of the same carbon substrates, including methanol. Most of the genomes share genes for toxic metal resistance and surface-layer production. Only Aplasma and Eplasma have a full suite of flagellar genes whereas all but the Ferroplasma spp. have genes for pili production. Cryogenic-electron microscopy (cryo-EM) and tomography (cryo-ET) strengthen these metagenomics-based ultrastructural predictions. Notably, only Aplasma, Gplasma and the Ferroplasma spp. have predicted iron oxidation genes and Eplasma and Iplasma lack most genes for cobalamin, valine, (iso)leucine and histidine synthesis.

Conclusion

The Thermoplasmatales AMD archaea share a large number of metabolic capabilities. All of the uncultivated organisms studied here (A-, E-, G-, and Iplasma) are metabolically very similar to characterized Ferroplasma spp., differentiating themselves mainly in their genetic capabilities for biosynthesis, motility, and possibly iron oxidation. These results indicate that subtle, but important genomic differences, coupled with unknown differences in gene expression, distinguish these organisms enough to allow for co-existence. Overall this study reveals shared features of organisms from the Thermoplasmatales lineage and provides new insights into the functioning of AMD communities.

Resolving prokaryotic taxonomy without rRNA: longer oligonucleotide word lengths improve genome and metagenome taxonomic classification

Oligonucleotide signatures, especially tetranucleotide signatures, have been used as method for homology binning by exploiting an organism’s inherent biases towards the use of specific oligonucleotide words. Tetranucleotide signatures have been especially useful in environmental metagenomics samples as many of these samples contain organisms from poorly classified phyla which cannot be easily identified using traditional homology methods, including NCBI BLAST. This study examines oligonucleotide signatures across 1,424 completed genomes from across the tree of life, substantially expanding upon previous work. A comprehensive analysis of mononucleotide through nonanucleotide word lengths suggests that longer word lengths substantially improve the classification of DNA fragments across a range of sizes of relevance to high throughput sequencing. We find that, at present, heptanucleotide signatures represent an optimal balance between prediction accuracy and computational time for resolving taxonomy using both genomic and metagenomic fragments. We directly compare the ability of tetranucleotide and heptanucleotide world lengths (tetranucleotide signatures are the current standard for oligonucleotide word usage analyses) for taxonomic binning of metagenome reads. We present evidence that heptanucleotide word lengths consistently provide more taxonomic resolving power, particularly in distinguishing between closely related organisms that are often present in metagenomic samples. This implies that longer oligonucleotide word lengths should replace tetranucleotide signatures for most analyses. Finally, we show that the application of longer word lengths to metagenomic datasets leads to more accurate taxonomic binning of DNA scaffolds and have the potential to substantially improve taxonomic assignment and assembly of metagenomic data.

Metabolic flexibility of enigmatic SAR324 revealed through metagenomics and metatranscriptomics

Chemolithotrophy is a pervasive metabolic lifestyle for microorganisms in the dark ocean. The SAR324 group of Deltaproteobacteria is ubiquitous in the ocean and has been implicated in sulfur oxidation and carbon fixation, but also contains genomic signatures of C1 utilization and heterotrophy. Here, we reconstructed the metagenome and metatranscriptome of a population of SAR324 from a hydrothermal plume and surrounding waters in the deep Gulf of California to gain insight into the genetic capability and transcriptional dynamics of this enigmatic group. SAR324's metabolism is signified by genes that encode a novel particulate hydrocarbon monooxygenase (pHMO), degradation pathways for corresponding alcohols and short-chain fatty acids, dissimilatory sulfur oxidation, formate dehydrogenase (FDH) and a nitrite reductase (NirK). Transcripts of the pHMO, NirK, FDH and transporters for exogenous carbon and amino acid uptake were highly abundant in plume waters. Sulfur oxidation genes were also abundant in the plume metatranscriptome, indicating SAR324 may also utilize reduced sulfur species in hydrothermal fluids. These results suggest that aspects of SAR324's versatile metabolism (lithotrophy, heterotrophy and alkane oxidation) operate simultaneously, and may explain SAR324's ubiquity in the deep Gulf of California and in the global marine biosphere.

Condensing the omics fog of microbial communities

Natural microbial communities are ubiquitous, complex, heterogeneous, and dynamic. Here, we argue that the future standard for their study will require systematic omic measurements of spatially and temporally resolved unique samples in line with a discovery-driven planning approach. Resulting datasets will allow the generation of solid hypotheses about causal relationships and, thereby, will facilitate the discovery of previously unknown traits of specific microbial community members. However, to achieve this, solid wet lab, bioinformatic and statistical methodologies are required to have the promises of the emerging field of Eco-Systems Biology come to fruition.

Metagenomic de novo assembly of an aquatic representative of the verrucomicrobial class Spartobacteria

The verrucomicrobial subdivision 2 class Spartobacteria is one of the most abundant bacterial lineages in soil and has recently also been found to be ubiquitous in aquatic environments. A 16S rRNA gene study from samples spanning the entire salinity range of the Baltic Sea indicated that, in the pelagic brackish water, a phylotype of the Spartobacteria is one of the dominating bacteria during summer. Phylogenetic analyses of related 16S rRNA genes indicate that a purely aquatic lineage within the Spartobacteria exists. Since no aquatic representative from the Spartobacteria has been cultured or sequenced, the metabolic capacity and ecological role of this lineage are yet unknown. In this study, we reconstructed the genome and metabolic potential of the abundant Baltic Sea Spartobacteria phylotype by metagenomics. Binning of genome fragments by nucleotide composition and a self-organizing map recovered the near-complete genome of the organism, the gene content of which suggests an aerobic heterotrophic metabolism. Notably, we found 23 glycoside hydrolases that likely allow the use of a variety of carbohydrates, like cellulose, mannan, xylan, chitin, and starch, as carbon sources. In addition, a complete pathway for sulfate utilization was found, indicating catabolic processing of sulfated polysaccharides, commonly found in aquatic phytoplankton. The high frequency of glycoside hydrolase genes implies an important role of this organism in the aquatic carbon cycle. Spatiotemporal data of the phylotype’s distribution within the Baltic Sea indicate a connection to Cyanobacteria that may be the main source of the polysaccharide substrates.

The ecosystem roles of many phylogenetic lineages are not yet well understood. One such lineage is the class Spartobacteria within the Verrucomicrobia that, despite being abundant in soil and aquatic systems, is relatively poorly studied. Here we circumvented the difficulties of growing aquatic Verrucomicrobia by applying shotgun metagenomic sequencing on a water sample from the Baltic Sea. By using a method based on sequence signatures, we were able to in silico isolate genome fragments belonging to a phylotype of the Spartobacteria. The genome, which represents the first aquatic representative of this clade, encodes a diversity of glycoside hydrolases that likely allow degradation of various complex carbohydrates. Since the phylotype cooccurs with Cyanobacteria, these may be the primary producers of the carbohydrate substrates. The phylotype, which is highly abundant in the Baltic Sea during summer, may thus play an important role in the carbon cycle of this ecosystem.

The YNP Metagenome Project: Environmental Parameters Responsible for Microbial Distribution in the Yellowstone Geothermal Ecosystem

The Yellowstone geothermal complex contains over 10,000 diverse geothermal features that host numerous phylogenetically deeply rooted and poorly understood archaea, bacteria, and viruses. Microbial communities in high-temperature environments are generally less diverse than soil, marine, sediment, or lake habitats and therefore offer a tremendous opportunity for studying the structure and function of different model microbial communities using environmental metagenomics. One of the broader goals of this study was to establish linkages among microbial distribution, metabolic potential, and environmental variables. Twenty geochemically distinct geothermal ecosystems representing a broad spectrum of Yellowstone hot-spring environments were used for metagenomic and geochemical analysis and included approximately equal numbers of: (1) phototrophic mats, (2) "filamentous streamer" communities, and (3) archaeal-dominated sediments. The metagenomes were analyzed using a suite of complementary and integrative bioinformatic tools, including phylogenetic and functional analysis of both individual sequence reads and assemblies of predominant phylotypes. This volume identifies major environmental determinants of a large number of thermophilic microbial lineages, many of which have not been fully described in the literature nor previously cultivated to enable functional and genomic analyses. Moreover, protein family abundance comparisons and in-depth analyses of specific genes and metabolic pathways relevant to these hot-spring environments reveal hallmark signatures of metabolic capabilities that parallel the distribution of phylotypes across specific types of geochemical environments.

The future is now: single-cell genomics of bacteria and archaea

Interest in the expanding catalog of uncultivated microorganisms, increasing recognition of heterogeneity among seemingly similar cells, and technological advances in whole-genome amplification and single-cell manipulation are driving considerable progress in single-cell genomics. Here, the spectrum of applications for single-cell genomics, key advances in the development of the field, and emerging methodology for single-cell genome sequencing are reviewed by example with attention to the diversity of approaches and their unique characteristics. Experimental strategies transcending specific methodologies are identified and organized as a road map for future studies in single-cell genomics of environmental microorganisms. Over the next decade, increasingly powerful tools for single-cell genome sequencing and analysis will play key roles in accessing the genomes of uncultivated organisms, determining the basis of microbial community functions, and fundamental aspects of microbial population biology.

Biostimulation induces syntrophic interactions that impact C, S and N cycling in a sediment microbial community

Stimulation of subsurface microorganisms to induce reductive immobilization of metals is a promising approach for bioremediation, yet the overall microbial community response is typically poorly understood. Here we used proteogenomics to test the hypothesis that excess input of acetate activates complex community functioning and syntrophic interactions among autotrophs and heterotrophs. A flow-through sediment column was incubated in a groundwater well of an acetate-amended aquifer and recovered during microbial sulfate reduction. De novo reconstruction of community sequences yielded near-complete genomes of Desulfobacter (Deltaproteobacteria), Sulfurovum- and Sulfurimonas-like Epsilonproteobacteria and Bacteroidetes. Partial genomes were obtained for Clostridiales (Firmicutes) and Desulfuromonadales-like Deltaproteobacteria. The majority of proteins identified by mass spectrometry corresponded to Desulfobacter-like species, and demonstrate the role of this organism in sulfate reduction (Dsr and APS), nitrogen fixation and acetate oxidation to CO2 during amendment. Results indicate less abundant Desulfuromonadales, and possibly Bacteroidetes, also actively contributed to CO2 production via the tricarboxylic acid (TCA) cycle. Proteomic data indicate that sulfide was partially re-oxidized by Epsilonproteobacteria through nitrate-dependent sulfide oxidation (using Nap, Nir, Nos, SQR and Sox), with CO2 fixed using the reverse TCA cycle. We infer that high acetate concentrations, aimed at stimulating anaerobic heterotrophy, led to the co-enrichment of, and carbon fixation in Epsilonproteobacteria. Results give an insight into ecosystem behavior following addition of simple organic carbon to the subsurface, and demonstrate a range of biological processes and community interactions were stimulated.

Exploration of noncoding sequences in metagenomes

Environment-dependent genomic features have been defined for different metagenomes, whose genes and their associated processes are related to specific environments. Identification of ORFs and their functional categories are the most common methods for association between functional and environmental features. However, this analysis based on finding ORFs misses noncoding sequences and, therefore, some metagenome regulatory or structural information could be discarded. In this work we analyzed 23 whole metagenomes, including coding and noncoding sequences using the following sequence patterns: (G+C) content, Codon Usage (Cd), Trinucleotide Usage (Tn), and functional assignments for ORF prediction. Herein, we present evidence of a high proportion of noncoding sequences discarded in common similarity-based methods in metagenomics, and the kind of relevant information present in those. We found a high density of trinucleotide repeat sequences (TRS) in noncoding sequences, with a regulatory and adaptive function for metagenome communities. We present associations between trinucleotide values and gene function, where metagenome clustering correlate with microorganism adaptations and kinds of metagenomes. We propose here that noncoding sequences have relevant information to describe metagenomes that could be considered in a whole metagenome analysis in order to improve their organization, classification protocols, and their relation with the environment.

Metabolites associated with adaptation of microorganisms to an acidophilic, metal-rich environment identified by stable-isotope-enabled metabolomics

Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities.

IMPORTANCE

Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.

A novel approach, based on BLSOMs (Batch Learning Self-Organizing Maps), to the microbiome analysis of ticks

Ticks transmit a variety of viral, bacterial and protozoal pathogens, which are often zoonotic. The aim of this study was to identify diverse tick microbiomes, which may contain as-yet unidentified pathogens, using a metagenomic approach. DNA prepared from bacteria/archaea-enriched fractions obtained from seven tick species, namely Amblyomma testudinarium, Amblyomma variegatum, Haemaphysalis formosensis, Haemaphysalis longicornis, Ixodes ovatus, Ixodes persulcatus and Ixodes ricinus, was subjected to pyrosequencing after whole-genome amplification. The resulting sequence reads were phylotyped using a Batch Learning Self-Organizing Map (BLSOM) program, which allowed phylogenetic estimation based on similarity of oligonucleotide frequencies, and functional annotation by BLASTX similarity searches. In addition to bacteria previously associated with human/animal diseases, such as Anaplasma, Bartonella, Borrelia, Ehrlichia, Francisella and Rickettsia, BLSOM analysis detected microorganisms belonging to the phylum Chlamydiae in some tick species. This was confirmed by pan-Chlamydia PCR and sequencing analysis. Gene sequences associated with bacterial pathogenesis were also identified, some of which were suspected to originate from horizontal gene transfer. These efforts to construct a database of tick microbes may lead to the ability to predict emerging tick-borne diseases. Furthermore, a comprehensive understanding of tick microbiomes will be useful for understanding tick biology, including vector competency and interactions with pathogens and symbionts.

Comparison of metagenomic samples using sequence signatures

BACKGROUND

Sequence signatures, as defined by the frequencies of k-tuples (or k-mers, k-grams), have been used extensively to compare genomic sequences of individual organisms, to identify cis-regulatory modules, and to study the evolution of regulatory sequences. Recently many next-generation sequencing (NGS) read data sets of metagenomic samples from a variety of different environments have been generated. The assembly of these reads can be difficult and analysis methods based on mapping reads to genes or pathways are also restricted by the availability and completeness of existing databases. Sequence-signature-based methods, however, do not need the complete genomes or existing databases and thus, can potentially be very useful for the comparison of metagenomic samples using NGS read data. Still, the applications of sequence signature methods for the comparison of metagenomic samples have not been well studied.

RESULTS

We studied several dissimilarity measures, including d2, d2* and d2S recently developed from our group, a measure (hereinafter noted as Hao) used in CVTree developed from Hao's group (Qi et al., 2004), measures based on relative di-, tri-, and tetra-nucleotide frequencies as in Willner et al. (2009), as well as standard lp measures between the frequency vectors, for the comparison of metagenomic samples using sequence signatures. We compared their performance using a series of extensive simulations and three real next-generation sequencing (NGS) metagenomic datasets: 39 fecal samples from 33 mammalian host species, 56 marine samples across the world, and 13 fecal samples from human individuals. Results showed that the dissimilarity measure d2S can achieve superior performance when comparing metagenomic samples by clustering them into different groups as well as recovering environmental gradients affecting microbial samples. New insights into the environmental factors affecting microbial compositions in metagenomic samples are obtained through the analyses. Our results show that sequence signatures of the mammalian gut are closely associated with diet and gut physiology of the mammals, and that sequence signatures of marine communities are closely related to location and temperature.

CONCLUSIONS

Sequence signatures can successfully reveal major group and gradient relationships among metagenomic samples from NGS reads without alignment to reference databases. The d2S dissimilarity measure is a good choice in all application scenarios. The optimal choice of tuple size depends on sequencing depth, but it is quite robust within a range of choices for moderate sequencing depths.

Heterotrophic archaea contribute to carbon cycling in low-pH, suboxic biofilm communities

Archaea are widely distributed and yet are most often not the most abundant members of microbial communities. Here, we document a transition from Bacteria- to Archaea-dominated communities in microbial biofilms sampled from the Richmond Mine acid mine drainage (AMD) system (∼pH 1.0, ∼38°C) and in laboratory-cultivated biofilms. This transition occurs when chemoautotrophic microbial communities that develop at the air-solution interface sink to the sediment-solution interface and degrade under microaerobic and anaerobic conditions. The archaea identified in these sunken biofilms are from the class Thermoplasmata, and in some cases, the highly divergent ARMAN nanoarchaeal lineage. In several of the sunken biofilms, nanoarchaea comprise 10 to 25% of the community, based on fluorescent in situ hybridization and metagenomic analyses. Comparative community proteomic analyses show a persistence of bacterial proteins in sunken biofilms, but there is clear evidence for amino acid modifications due to acid hydrolysis. Given the low representation of bacterial cells in sunken biofilms based on microscopy, we infer that hydrolysis reflects proteins derived from lysed cells. For archaea, we detected ∼2,400 distinct proteins, including a subset involved in proteolysis and peptide uptake. Laboratory cultivation experiments using complex carbon substrates demonstrated anaerobic enrichment of Ferroplasma and Aplasma coupled to the reduction of ferric iron. These findings indicate dominance of acidophilic archaea in degrading biofilms and suggest that they play roles in anaerobic nutrient cycling at low pH.

Current opportunities and challenges in microbial metagenome analysis--a bioinformatic perspective

Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such 'ecosystems biology' approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.

Comparative metagenomic analysis of soil microbial communities across three hexachlorocyclohexane contamination levels

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.

Grappling with Proteus: population level approaches to understanding microbial diversity

The emerging fields of microbial population genetics and genomics provide an avenue to study the ecological rules that govern how communities form, function, and evolve. Our struggle to understand the causes and consequences of microbial diversity stems from our inability to define ecologically and evolutionarily meaningful units of diversity. The 16S rRNA-based tools that have been so useful in charting microbial diversity may lack sufficient sensitivity to answer many questions about the ecology and evolution of microbes. Examining genetic diversity with increased resolution is vital to understanding the forces shaping community structure. Population genetic analyses enabled by whole genome sequencing, multilocus sequence analyses, or single-nucleotide polymorphism analyses permit the testing of hypotheses pertaining to the geographic distribution, migration, and habitat preference of specific microbial lineages. Furthermore, these approaches can reveal patterns of gene exchange within and between populations and communities. Tools from microbial population genetics and population genomics can be used to increase the resolution with which we measure microbial diversity, enabling a focus on the scale of genetic diversity at which ecological processes impact evolutionary events. This tighter focus promises to improve our understanding of the causes and consequences of microbial community structure.

Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization

The gastrointestinal microbiome undergoes shifts in species and strain abundances, yet dynamics involving closely related microorganisms remain largely unknown because most methods cannot resolve them. We developed new metagenomic methods and utilized them to track species and strain level variations in microbial communities in 11 fecal samples collected from a premature infant during the first month of life. Ninety six percent of the sequencing reads were assembled into scaffolds of >500 bp in length that could be assigned to organisms at the strain level. Six essentially complete (∼99%) and two near-complete genomes were assembled for bacteria that comprised as little as 1% of the community, as well as nine partial genomes of bacteria representing as little as 0.05%. In addition, three viral genomes were assembled and assigned to their hosts. The relative abundance of three Staphylococcus epidermidis strains, as well as three phages that infect them, changed dramatically over time. Genes possibly related to these shifts include those for resistance to antibiotics, heavy metals, and phage. At the species level, we observed the decline of an early-colonizing Propionibacterium acnes strain similar to SK137 and the proliferation of novel Propionibacterium and Peptoniphilus species late in colonization. The Propionibacterium species differed in their ability to metabolize carbon compounds such as inositol and sialic acid, indicating that shifts in species composition likely impact the metabolic potential of the community. These results highlight the benefit of reconstructing complete genomes from metagenomic data and demonstrate methods for achieving this goal.

The metatranscriptome of a deep-sea hydrothermal plume is dominated by water column methanotrophs and lithotrophs

Microorganisms mediate geochemical processes in deep-sea hydrothermal vent plumes, which are a conduit for transfer of elements and energy from the subsurface to the oceans. Despite this important microbial influence on marine geochemistry, the ecology and activity of microbial communities in hydrothermal plumes is largely unexplored. Here, we use a coordinated metagenomic and metatranscriptomic approach to compare microbial communities in Guaymas Basin hydrothermal plumes to background waters above the plume and in the adjacent Carmen Basin. Despite marked increases in plume total RNA concentrations (3-4 times) and microbially mediated manganese oxidation rates (15-125 times), plume and background metatranscriptomes were dominated by the same groups of methanotrophs and chemolithoautotrophs. Abundant community members of Guaymas Basin seafloor environments (hydrothermal sediments and chimneys) were not prevalent in the plume metatranscriptome. De novo metagenomic assembly was used to reconstruct genomes of abundant populations, including Marine Group I archaea, Methylococcaceae, SAR324 Deltaproteobacteria and SUP05 Gammaproteobacteria. Mapping transcripts to these genomes revealed abundant expression of genes involved in the chemolithotrophic oxidation of ammonia (amo), methane (pmo) and sulfur (sox). Whereas amo and pmo gene transcripts were abundant in both plume and background, transcripts of sox genes for sulfur oxidation from SUP05 groups displayed a 10-20-fold increase in plumes. We conclude that the biogeochemistry of Guaymas Basin hydrothermal plumes is mediated by microorganisms that are derived from seawater rather than from seafloor hydrothermal environments such as chimneys or sediments, and that hydrothermal inputs serve as important electron donors for primary production in the deep Gulf of California.

Genome-enabled transcriptomics reveals archaeal populations that drive nitrification in a deep-sea hydrothermal plume

Ammonia-oxidizing Archaea (AOA) are among the most abundant microorganisms in the oceans and have crucial roles in biogeochemical cycling of nitrogen and carbon. To better understand AOA inhabiting the deep sea, we obtained community genomic and transcriptomic data from ammonium-rich hydrothermal plumes in the Guaymas Basin (GB) and from surrounding deep waters of the Gulf of California. Among the most abundant and active lineages in the sequence data were marine group I (MGI) Archaea related to the cultured autotrophic ammonia-oxidizer, Nitrosopumilus maritimus. Assembly of MGI genomic fragments yielded 2.9 Mb of sequence containing seven 16S rRNA genes (95.4-98.4% similar to N. maritimus), including two near-complete genomes and several lower-abundance variants. Equal copy numbers of MGI 16S rRNA genes and ammonia monooxygenase genes and transcription of ammonia oxidation genes indicates that all of these genotypes actively oxidize ammonia. De novo genomic assembly revealed the functional potential of MGI populations and enhanced interpretation of metatranscriptomic data. Physiological distinction from N. maritimus is evident in the transcription of novel genes, including genes for urea utilization, suggesting an alternative source of ammonia. We were also able to determine which genotypes are most active in the plume. Transcripts involved in nitrification were more prominent in the plume and were among the most abundant transcripts in the community. These unique data sets reveal populations of deep-sea AOA thriving in the ammonium-rich GB that are related to surface types, but with key genomic and physiological differences.