Accurate, multi-kb reads resolve complex populations and detect rare microorganisms

Metagenomic analysis of pristine oil sheds new light on the global distribution of microbial genetic repertoire in hydrocarbon-associated ecosystems

Oil reservoirs are society's primary source of hydrocarbons. While microbial communities in industrially exploited oil reservoirs have been investigated in the past, pristine microbial communities in untapped oil reservoirs are little explored, as are distribution patterns of respective genetic signatures. Here, we show that a pristine oil sample contains a complex community consisting of bacteria and fungi for the degradation of hydrocarbons. We identified microorganisms and their pathways for the degradation of methane, n-alkanes, mono-aromatic, and polycyclic aromatic compounds in a metagenome retrieved from biodegraded petroleum encountered in a subsurface reservoir in the Barents Sea. Capitalizing on marker genes from metagenomes and public data mining, we compared the prokaryotes, putative viruses, and putative plasmids of the sampled site to those from 10 other hydrocarbon-associated sites, revealing a shared network of species and genetic elements across the globe. To test for the potential dispersal of the microbes and predicted elements via seawater, we compared our findings to the Tara Ocean dataset, resulting in a broad distribution of prokaryotic and viral signatures. Although frequently shared between hydrocarbon-associated sites, putative plasmids, however, showed little coverage in the Tara Oceans dataset, suggesting an undiscovered mode of transfer between hydrocarbon-affected ecosystems. Based on our analyses, genetic information is globally shared between oil reservoirs and hydrocarbon-associated sites, and we propose that currents and other physical occurrences within the ocean along with deep aquifers are major distributors of prokaryotes and viruses into these subsurface ecosystems.

Acidic proteomes are linked to microbial alkaline preference in African lakes

Microbial amino acid composition (AA) reflects adaptive strategies of cellular and molecular regulations such as a high proportion of acidic AAs, including glutamic and aspartic acids in alkaliphiles. It remains understudied how microbial AA content is linked to their pH adaptation especially in natural environments. Here we examined prokaryotic communities and their AA composition of genes with metagenomics for 39 water and sediments of East African lakes along a gradient of pH spanning from 7.2 to 10.1. We found that Shannon diversity declined with the increasing pH and that species abundance were either positively or negatively associated with pH, indicating their distinct habitat preference in lakes. Microbial communities showed higher acidic proteomes in alkaline than neutral lakes. Species acidic proteomes were also positively correlated with their pH preference, which was consistent across major bacterial lineages. These results suggest selective pressure associated with high pH likely shape microbial amino acid composition both at the species and community levels. Comparative genome analyses further revealed that alkaliphilic microbes contained more functional genes with higher acidic AAs when compared to those in neutral conditions. These traits included genes encoding diverse classes of cation transmembrane transporters, antiporters, and compatible solute transporters, which are involved in cytoplasmic pH homeostasis and osmotic stress defense under high pH conditions. Our results provide the field evidence for the strong relationship between prokaryotic AA composition and their habitat preference and highlight amino acid optimization as strategies for environmental adaptation.

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances.

IMPORTANCE

Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Closing the genome of unculturable cable bacteria using a combined metagenomic assembly of long and short sequencing reads

Many environmentally relevant micro-organisms cannot be cultured, and even with the latest metagenomic approaches, achieving complete genomes for specific target organisms of interest remains a challenge. Cable bacteria provide a prominent example of a microbial ecosystem engineer that is currently unculturable. They occur in low abundance in natural sediments, but due to their capability for long-distance electron transport, they exert a disproportionately large impact on the biogeochemistry of their environment. Current available genomes of marine cable bacteria are highly fragmented and incomplete, hampering the elucidation of their unique electrogenic physiology. Here, we present a metagenomic pipeline that combines Nanopore long-read and Illumina short-read shotgun sequencing. Starting from a clonal enrichment of a cable bacterium, we recovered a circular metagenome-assembled genome (5.09 Mbp in size), which represents a novel cable bacterium species with the proposed name Candidatus Electrothrix scaldis. The closed genome contains 1109 novel identified genes, including key metabolic enzymes not previously described in incomplete genomes of cable bacteria. We examined in detail the factors leading to genome closure. Foremost, native, non-amplified long reads are crucial to resolve the many repetitive regions within the genome of cable bacteria, and by analysing the whole metagenomic assembly, we found that low strain diversity is key for achieving genome closure. The insights and approaches presented here could help achieve genome closure for other keystone micro-organisms present in complex environmental samples at low abundance.

Life strategies for Aminicenantia in subseafloor oceanic crust

After decades studying the microbial "deep biosphere" in subseafloor oceanic crust, the growth and life strategies in this anoxic, low energy habitat remain poorly described. Using both single cell genomics and metagenomics, we reveal the life strategies of two distinct lineages of uncultivated Aminicenantia bacteria from the basaltic subseafloor oceanic crust of the eastern flank of the Juan de Fuca Ridge. Both lineages appear adapted to scavenge organic carbon, as each have genetic potential to catabolize amino acids and fatty acids, aligning with previous Aminicenantia reports. Given the organic carbon limitation in this habitat, seawater recharge and necromass may be important carbon sources for heterotrophic microorganisms inhabiting the ocean crust. Both lineages generate ATP via several mechanisms including substrate-level phosphorylation, anaerobic respiration, and electron bifurcation driving an Rnf ion translocation membrane complex. Genomic comparisons suggest these Aminicenantia transfer electrons extracellularly, perhaps to iron or sulfur oxides consistent with mineralogy of this site. One lineage, called JdFR-78, has small genomes that are basal to the Aminicenantia class and potentially use "primordial" siroheme biosynthetic intermediates for heme synthesis, suggesting this lineage retain characteristics of early evolved life. Lineage JdFR-78 contains CRISPR-Cas defenses to evade viruses, while other lineages contain prophage that may help prevent super-infection or no detectable viral defenses. Overall, genomic evidence points to Aminicenantia being well adapted to oceanic crust environments by taking advantage of simple organic molecules and extracellular electron transport.

StrainSelect: A novel microbiome reference database that disambiguates all bacterial strains, genome assemblies and extant cultures worldwide

Motivation: Microbial metagenomic profiling software and databases are advancing rapidly for development of novel disease biomarkers and therapeutics yet three problems impede analyses: 1) the conflation of "genome assembly" and "strain" in reference databases; 2) difficulty connecting DNA biomarkers to a procurable strain for laboratory experimentation; and 3) absence of a comprehensive and unified strain-resolved reference database for integrating both shotgun metagenomics and 16S rRNA gene data. Results: We demarcated 681,087 strains, the largest collection of its kind, by filtering public data into a knowledge graph of vertices representing contiguous DNA sequences, genome assemblies, strain monikers and bio-resource center (BRC) catalog numbers then adding inter-vertex edges only for synonyms or direct derivatives. Surprisingly, for 10,043 important strains, we found replicate RefSeq genome assemblies obstructing interpretation of database searches. We organized each strain into eight taxonomic ranks with bootstrap confidence inversely correlated with genome assembly contamination. The StrainSelect database is suited for applications where a taxonomic, functional or procurement reference is needed for shotgun or amplicon metagenomics since 636,568 strains have at least one 16S rRNA gene, 245,005 have at least one annotated genome assembly, and 36,671 are procurable from at least one BRC. The database overcomes all three aforementioned problems since it disambiguates strains from assemblies, locates strains at BRCs, and unifies a taxonomic reference for both 16S rRNA and shotgun metagenomics. Availability: The StrainSelect database is available in igraph and tabular vertex-edge formats compatible with Neo4J. Dereplicated MinHash and fasta databases are distributed for sourmash and usearch pipelines at http://strainselect.secondgenome.com. Contact:todd.desantis@gmail.com. Supplementary information: Supplementary data are available online.

Impacts of Binary Oxide Nanoparticles on the Soybean Plant and Its Rhizosphere, Associated Phytohormones, and Enzymes

The utilization of binary oxide nanoparticles is geometrically increasing due to their numerous applications. Their intentional or accidental release after usage has led to their omnipresence in the environment. The usage of sludge or fertilizer containing binary oxide nanoparticles is likely to increase the chance of the plants being exposed to these binary oxide nanoparticles. The aim of the present review is to assess the detailed positive and negative impacts of these oxide nanoparticles on the soybean plants and its rhizosphere. In this study, methods of synthesizing binary oxide nanoparticles, as well as the merits and demerits of these methods, are discussed. Furthermore, various methods of characterizing the binary oxide nanoparticles in the tissues of soybean are highlighted. These characterization techniques help to track the nanoparticles inside the soybean plant. In addition, the assessment of rhizosphere microbial communities of soybean that have been exposed to these binary oxide nanoparticles is discussed. The impacts of binary oxide nanoparticles on the leaf, stem, root, seeds, and rhizosphere of soybean plant are comprehensively discussed. The impacts of binary oxides on the bioactive compounds such as phytohormones are also highlighted. Overall, it was observed that the impacts of the oxide nanoparticles on the soybean, rhizosphere, and bioactive compounds were dose-dependent. Lastly, the way forward on research involving the interactions of binary oxide nanoparticles and soybean plants is suggested.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Oxford Nanopore R10.4 long-read sequencing enables the generation of near-finished bacterial genomes from pure cultures and metagenomes without short-read or reference polishing

Long-read Oxford Nanopore sequencing has democratized microbial genome sequencing and enables the recovery of highly contiguous microbial genomes from isolates or metagenomes. However, to obtain near-finished genomes it has been necessary to include short-read polishing to correct insertions and deletions derived from homopolymer regions. Here, we show that Oxford Nanopore R10.4 can be used to generate near-finished microbial genomes from isolates or metagenomes without short-read or reference polishing.

Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade

Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data.

Hybrid, ultra-deep metagenomic sequencing enables genomic and functional characterization of low-abundance species in the human gut microbiome

A large number of microbial genomes have already been identified from the human gut microbiome, but the understanding of the role of the low-abundance species at the individual level remains challenging, largely due to the relatively shallow sequencing depth used in most studies. To improve genome assembling performance, a HiSeq-PacBio hybrid, ultra-deep metagenomic sequencing approach was used to reconstruct metagenomic-assembled genomes (MAGs) from 12 fecal samples. Such approach combined third-generation sequencing with ultra-deep second-generation sequencing to improve the sequencing coverage of the low-abundance subpopulation in the gut microbiome. Our study generated a total of 44 megabase-scale scaffolds, achieving four single-scaffolds of complete (circularized, no gaps) MAGs (CMAGs) that were the first circular genomes of their species. Moreover, 475 high-quality MAGs were assembled across all samples. Among them, 234 MAGs were currently uncultured, including 24 MAGs that were not found in any public genome database. Additionally, 287 and 77 MAGs were classified as low-abundance (0.1-1%) and extra-low-abundance (<0.1%) gut species in each individual, respectively. Our results also revealed individual-specific genomic features in the MAG profiles, including microbial genome growth rate, selective pressure, and frequency of chromosomal mobile genetic elements. Finally, thousands of extrachromosomal mobile genetic elements were identified from the metagenomic data, including 5097 bacteriophages and 79 novel plasmid genomes. Overall, our strategy represents an important step toward comprehensive genomic and functional characterization of the human gut microbiome at an individual level.

Metagenomic sequencing-driven multidisciplinary approaches to shed light on the untapped microbial natural products

The advantage of metagenomics over the culture-based natural product (NP) discovery pipeline is the ability to access the biosynthetic potential of uncultivable microbes. Advances in DNA sequencing are revolutionizing conventional metagenomics approaches for microbial NP discovery. The genomes of (in)cultivable bugs can be resolved straightforwardly from environmental samples, enabling in situ prediction of biosynthetic gene clusters (BGCs). The predicted chemical diversities could be realized not only by heterologous expression of gene clusters originating from DNA synthesis or direct cloning, but also potentially by bioinformatic-directed organic synthesis or chemoenzymatic total synthesis. In this review, we suggest that metagenomic sequencing in tandem with multidisciplinary approaches will form a versatile platform to shed light on a plethora of microbial 'dark matter'.

Distinct methane-dependent biogeochemical states in Arctic seafloor gas hydrate mounds

Archaea mediating anaerobic methane oxidation are key in preventing methane produced in marine sediments from reaching the hydrosphere; however, a complete understanding of how microbial communities in natural settings respond to changes in the flux of methane remains largely uncharacterized. We investigate microbial communities in gas hydrate-bearing seafloor mounds at Storfjordrenna, offshore Svalbard in the high Arctic, where we identify distinct methane concentration profiles that include steady-state, recently-increasing subsurface diffusive flux, and active gas seepage. Populations of anaerobic methanotrophs and sulfate-reducing bacteria were highest at the seep site, while decreased community diversity was associated with a recent increase in methane influx. Despite high methane fluxes and methanotroph doubling times estimated at 5-9 months, microbial community responses were largely synchronous with the advancement of methane into shallower sediment horizons. Together, these provide a framework for interpreting subseafloor microbial responses to methane escape in a warming Arctic Ocean.

Stable-Isotope-Informed, Genome-Resolved Metagenomics Uncovers Potential Cross-Kingdom Interactions in Rhizosphere Soil

The functioning, health, and productivity of soil are intimately tied to a complex network of interactions, particularly in plant root-associated rhizosphere soil. We conducted a stable-isotope-informed, genome-resolved metagenomic study to trace carbon from Avena fatua grown in a ¹³CO₂ atmosphere into soil. We collected paired rhizosphere and nonrhizosphere soil at 6 and 9 weeks of plant growth and extracted DNA that was then separated by density using ultracentrifugation. Thirty-two fractions from each of five samples were grouped by density, sequenced, assembled, and binned to generate 55 unique bacterial genomes that were ≥70% complete. We also identified complete 18S rRNA sequences of several ¹³C-enriched microeukaryotic bacterivores and fungi. We generated 10 circularized bacteriophage (phage) genomes, some of which were the most labeled entities in the rhizosphere, suggesting that phage may be important agents of turnover of plant-derived C in soil. CRISPR locus targeting connected one of these phage to a Burkholderiales host predicted to be a plant pathogen. Another highly labeled phage is predicted to replicate in a Catenulispora sp., a possible plant growth-promoting bacterium. We searched the genome bins for traits known to be used in interactions involving bacteria, microeukaryotes, and plant roots and found DNA from heavily ¹³C-labeled bacterial genes thought to be involved in modulating plant signaling hormones, plant pathogenicity, and defense against microeukaryote grazing. Stable-isotope-informed, genome-resolved metagenomics indicated that phage can be important agents of turnover of plant-derived carbon in soil.

IMPORTANCE Plants grow in intimate association with soil microbial communities; these microbes can facilitate the availability of essential resources to plants. Thus, plant productivity commonly depends on interactions with rhizosphere bacteria, viruses, and eukaryotes. Our work is significant because we identified the organisms that took up plant-derived organic C in rhizosphere soil and determined that many of the active bacteria are plant pathogens or can impact plant growth via hormone modulation. Further, by showing that bacteriophage accumulate CO₂-derived carbon, we demonstrated their vital roles in redistribution of plant-derived C into the soil environment through bacterial cell lysis. The use of stable-isotope probing (SIP) to identify consumption (or lack thereof) of root-derived C by key microbial community members within highly complex microbial communities opens the way for assessing manipulations of bacteria and phage with potentially beneficial and detrimental traits, ultimately providing a path to improved plant health and soil carbon storage.

Diverse sediment microbiota shape methane emission temperature sensitivity in Arctic lakes

Northern post-glacial lakes are significant, increasing sources of atmospheric carbon through ebullition (bubbling) of microbially-produced methane (CH₄) from sediments. Ebullitive CH₄ flux correlates strongly with temperature, reflecting that solar radiation drives emissions. However, here we show that the slope of the temperature-CH₄ flux relationship differs spatially across two post-glacial lakes in Sweden. We compared these CH₄ emission patterns with sediment microbial (metagenomic and amplicon), isotopic, and geochemical data. The temperature-associated increase in CH₄ emissions was greater in lake middles—where methanogens were more abundant—than edges, and sediment communities were distinct between edges and middles. Microbial abundances, including those of CH₄-cycling microorganisms and syntrophs, were predictive of porewater CH₄ concentrations. Results suggest that deeper lake regions, which currently emit less CH₄ than shallower edges, could add substantially to CH₄ emissions in a warmer Arctic and that CH₄ emission predictions may be improved by accounting for spatial variations in sediment microbiota.

Arctic lakes are strong and increasing sources of atmospheric methane, but extreme conditions and limited observations hinder robust understanding. Here the authors show that microbes in the middle of Arctic lakes have elevated methane producing potential, and are poised to release even more in the future.

Enhanced Recovery of Microbial Genes and Genomes From a Marine Water Column Using Long-Read Metagenomics

Third-generation sequencing has penetrated little in metagenomics due to the high error rate and dependence for assembly on short-read designed bioinformatics. However, second-generation sequencing metagenomics (mostly Illumina) suffers from limitations, particularly in the assembly of microbes with high microdiversity and retrieval of the flexible (adaptive) fraction of prokaryotic genomes. Here, we have used a third-generation technique to study the metagenome of a well-known marine sample from the mixed epipelagic water column of the winter Mediterranean. We have compared PacBio Sequel II with the classical approach using Illumina Nextseq short reads followed by assembly to study the metagenome. Long reads allow for efficient direct retrieval of complete genes avoiding the bias of the assembly step. Besides, the application of long reads on metagenomic assembly allows for the reconstruction of much more complete metagenome-assembled genomes (MAGs), particularly from microbes with high microdiversity such as Pelagibacterales. The flexible genome of reconstructed MAGs was much more complete containing many adaptive genes (some with biotechnological potential). PacBio Sequel II CCS appears particularly suitable for cellular metagenomics due to its low error rate. For most applications of metagenomics, from community structure analysis to ecosystem functioning, long reads should be applied whenever possible. Specifically, for in silico screening of biotechnologically useful genes, or population genomics, long-read metagenomics appears presently as a very fruitful approach and can be analyzed from raw reads before a computationally demanding (and potentially artifactual) assembly step.

Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology

Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples.

Metagenomic Data Assembly - The Way of Decoding Unknown Microorganisms

Metagenomics is a segment of conventional microbial genomics dedicated to the sequencing and analysis of combined genomic DNA of entire environmental samples. The most critical step of the metagenomic data analysis is the reconstruction of individual genes and genomes of the microorganisms in the communities using metagenomic assemblers - computational programs that put together small fragments of sequenced DNA generated by sequencing instruments. Here, we describe the challenges of metagenomic assembly, a wide spectrum of applications in which metagenomic assemblies were used to better understand the ecology and evolution of microbial ecosystems, and present one of the most efficient microbial assemblers, SPAdes that was upgraded to become applicable for metagenomics.

SPAligner: alignment of long diverged molecular sequences to assembly graphs

BACKGROUND

Graph-based representation of genome assemblies has been recently used in different contexts - from improved reconstruction of plasmid sequences and refined analysis of metagenomic data to read error correction and reference-free haplotype reconstruction. While many of these applications heavily utilize the alignment of long nucleotide sequences to assembly graphs, first general-purpose software tools for finding such alignments have been released only recently and their deficiencies and limitations are yet to be discovered. Moreover, existing tools can not perform alignment of amino acid sequences, which could prove useful in various contexts - in particular the analysis of metagenomic sequencing data.

RESULTS

In this work we present a novel SPAligner (Saint-Petersburg Aligner) tool for aligning long diverged nucleotide and amino acid sequences to assembly graphs. We demonstrate that SPAligner is an efficient solution for mapping third generation sequencing reads onto assembly graphs of various complexity and also show how it can facilitate the identification of known genes in complex metagenomic datasets.

CONCLUSIONS

Our work will facilitate accelerating the development of graph-based approaches in solving sequence to genome assembly alignment problem. SPAligner is implemented as a part of SPAdes tools library and is available on Github.

Exploring neighborhoods in large metagenome assembly graphs using spacegraphcats reveals hidden sequence diversity

Genomes computationally inferred from large metagenomic data sets are often incomplete and may be missing functionally important content and strain variation. We introduce an information retrieval system for large metagenomic data sets that exploits the sparsity of DNA assembly graphs to efficiently extract subgraphs surrounding an inferred genome. We apply this system to recover missing content from genome bins and show that substantial genomic sequence variation is present in a real metagenome. Our software implementation is available at https://github.com/spacegraphcats/spacegraphcats under the 3-Clause BSD License.

cloudSPAdes: assembly of synthetic long reads using de Bruijn graphs

Motivation

The recently developed barcoding-based synthetic long read (SLR) technologies have already found many applications in genome assembly and analysis. However, although some new barcoding protocols are emerging and the range of SLR applications is being expanded, the existing SLR assemblers are optimized for a narrow range of parameters and are not easily extendable to new barcoding technologies and new applications such as metagenomics or hybrid assembly.

Results

We describe the algorithmic challenge of the SLR assembly and present a cloudSPAdes algorithm for SLR assembly that is based on analyzing the de Bruijn graph of SLRs. We benchmarked cloudSPAdes across various barcoding technologies/applications and demonstrated that it improves on the state-of-the-art SLR assemblers in accuracy and speed.

Availability and implementation

Source code and installation manual for cloudSPAdes are available at https://github.com/ablab/spades/releases/tag/cloudspades-paper.

Supplementary Information

Supplementary data are available at Bioinformatics online.

Lipid analysis of CO2-rich subsurface aquifers suggests an autotrophy-based deep biosphere with lysolipids enriched in CPR bacteria

Sediment-hosted CO₂-rich aquifers deep below the Colorado Plateau (USA) contain a remarkable diversity of uncultivated microorganisms, including Candidate Phyla Radiation (CPR) bacteria that are putative symbionts unable to synthesize membrane lipids. The origin of organic carbon in these ecosystems is unknown and the source of CPR membrane lipids remains elusive. We collected cells from deep groundwater brought to the surface by eruptions of Crystal Geyser, sequenced the community, and analyzed the whole community lipidome over time. Characteristic stable carbon isotopic compositions of microbial lipids suggest that bacterial and archaeal CO₂ fixation ongoing in the deep subsurface provides organic carbon for the complex communities that reside there. Coupled lipidomic-metagenomic analysis indicates that CPR bacteria lack complete lipid biosynthesis pathways but still possess regular lipid membranes. These lipids may therefore originate from other community members, which also adapt to high in situ pressure by increasing fatty acid unsaturation. An unusually high abundance of lysolipids attributed to CPR bacteria may represent an adaptation to membrane curvature stress induced by their small cell sizes. Our findings provide new insights into the carbon cycle in the deep subsurface and suggest the redistribution of lipids into putative symbionts within this community.

Metatranscriptomic reconstruction reveals RNA viruses with the potential to shape carbon cycling in soil

Viruses impact nearly all organisms on Earth, with ripples of influence in agriculture, health, and biogeochemical processes. However, very little is known about RNA viruses in an environmental context, and even less is known about their diversity and ecology in soil, 1 of the most complex microbial systems. Here, we assembled 48 individual metatranscriptomes from 4 habitats within a planted soil sampled over a 22-d time series: Rhizosphere alone, detritosphere alone, rhizosphere with added root detritus, and unamended soil (4 time points and 3 biological replicates). We resolved the RNA viral community, uncovering a high diversity of viral sequences. We also investigated possible host organisms by analyzing metatranscriptome marker genes. Based on viral phylogeny, much of the diversity was Narnaviridae that may parasitize fungi or Leviviridae, which may infect Proteobacteria. Both host and viral communities appear to be highly dynamic, and rapidly diverged depending on experimental conditions. The viral and host communities were structured based on the presence of root litter. Clear temporal dynamics by Leviviridae and their hosts indicated that viruses were replicating. With this time-resolved analysis, we show that RNA viruses are diverse, abundant, and active in soil. When viral infection causes host cell death, it may mobilize cell carbon in a process that may represent an overlooked component of soil carbon cycling.

Ecological and functional capabilities of an uncultured Kordia sp

Cultivable bacteria represent only a fraction of the diversity in microbial communities. However, the official procedures for classification and characterization of a novel prokaryotic species still rely on isolates. Nevertheless, due to single cell genomics, it is possible to retrieve genomes from environmental samples by sequencing them individually, and to assign specific genes to a specific taxon, regardless of their ability to grow in culture. In this study, a complete description was performed for uncultured Kordia sp. TARA_039_SRF, a proposed novel species within the genus Kordia, using culture-independent techniques. The type material was a high-quality draft genome (94.97% complete, 4.65% gene redundancy) co-assembled using ten nearly identical single amplified genomes (SAGs) from surface seawater in the North Indian Ocean during the Tara Oceans Expedition. The assembly process was optimized to obtain the best possible assembly metrics and a less fragmented genome. The closest relative of the species was Kordia periserrulae, which shared 97.56% similarity of the 16S rRNA gene, 75% orthologs and 89.13% average nucleotide identity. The functional potential of the proposed novel species included proteorhodopsin, the ability to incorporate nitrate, cytochrome oxidases with high affinity for oxygen, and CAZymes that were unique features within the genus. Its abundance at different depths and size fractions was also evaluated together with its functional annotation, revealing that its putative ecological niche could be particles of phytoplanktonic origin. It could putatively attach to these particles and consume them while sinking to the deeper and oxygen depleted layers of the North Indian Ocean.

Unlinked rRNA genes are widespread among bacteria and archaea

Ribosomes are essential to cellular life and the genes for their RNA components are the most conserved and transcribed genes in bacteria and archaea. Ribosomal RNA genes are typically organized into a single operon, an arrangement thought to facilitate gene regulation. In reality, some bacteria and archaea do not share this canonical rRNA arrangement-their 16S and 23S rRNA genes are separated across the genome and referred to as "unlinked". This rearrangement has previously been treated as an anomaly or a byproduct of genome degradation in intracellular bacteria. Here, we leverage complete genome and long-read metagenomic data to show that unlinked 16S and 23S rRNA genes are more common than previously thought. Unlinked rRNA genes occur in many phyla, most significantly within Deinococcus-Thermus, Chloroflexi, and Planctomycetes, and occur in differential frequencies across natural environments. We found that up to 41% of rRNA genes in soil were unlinked, in contrast to the human gut, where all sequenced rRNA genes were linked. The frequency of unlinked rRNA genes may reflect meaningful life history traits, as they tend to be associated with a mix of slow-growing free-living species and intracellular species. We speculate that unlinked rRNA genes may confer selective advantages in some environments, though the specific nature of these advantages remains undetermined and worthy of further investigation. More generally, the prevalence of unlinked rRNA genes in poorly-studied taxa serves as a reminder that paradigms derived from model organisms do not necessarily extend to the broader diversity of bacteria and archaea.

Ecology of Subseafloor Crustal Biofilms

The crustal subseafloor is the least explored and largest biome on Earth. Interrogating crustal life is difficult due to habitat inaccessibility, low-biomass and contamination challenges. Subseafloor observatories have facilitated the study of planktonic life in crustal aquifers, however, studies of life in crust-attached biofilms are rare. Here, we investigate biofilms grown on various minerals at different temperatures over 1-6 years at subseafloor observatories in the Eastern Pacific. To mitigate potential sequence contamination, we developed a new bioinformatics tool - TaxonSluice. We explore ecological factors driving community structure and potential function of biofilms by comparing our sequence data to previous amplicon and metagenomic surveys of this habitat. We reveal that biofilm community structure is driven by temperature rather than minerology, and that rare planktonic lineages colonize the crustal biofilms. Based on 16S rRNA gene overlap, we partition metagenome assembled genomes into planktonic and biofilm fractions and suggest that there are functional differences between these community types, emphasizing the need to separately examine each to accurately describe subseafloor microbe-rock-fluid processes. Lastly, we report that some rare lineages present in our warm and anoxic study site are also found in cold and oxic crustal fluids in the Mid-Atlantic Ridge, suggesting global crustal biogeography patterns.

Long-read metagenomic exploration of extrachromosomal mobile genetic elements in the human gut

BACKGROUND

Elucidating the ecological and biological identity of extrachromosomal mobile genetic elements (eMGEs), such as plasmids and bacteriophages, in the human gut remains challenging due to their high complexity and diversity.

RESULTS

Here, we show efficient identification of eMGEs as complete circular or linear contigs from PacBio long-read metagenomic data. De novo assembly of PacBio long reads from 12 faecal samples generated 82 eMGE contigs (2.5~666.7-kb), which were classified as 71 plasmids and 11 bacteriophages, including 58 novel plasmids and six bacteriophages, and complete genomes of five diverse crAssphages with terminal direct repeats. In a dataset of 413 gut metagenomes from five countries, many of the identified plasmids were highly abundant and prevalent. The ratio of gut plasmids by our plasmid data is more than twice that in the public database. Plasmids outnumbered bacterial chromosomes three to one on average in this metagenomic dataset. Host prediction suggested that Bacteroidetes-associated plasmids predominated, regardless of microbial abundance. The analysis found several plasmid-enriched functions, such as inorganic ion transport, while antibiotic resistance genes were harboured mostly in low-abundance Proteobacteria-associated plasmids.

CONCLUSIONS

Overall, long-read metagenomics provided an efficient approach for unravelling the complete structure of human gut eMGEs, particularly plasmids.

A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation

Matching metagenomic and/or metatranscriptomic data, currently often under-used, can be useful reference for metaproteomic tandem mass spectra (MS/MS) data analysis. Here we developed a software pipeline for identification of peptides and proteins from metaproteomic MS/MS data using proteins derived from matching metagenomic (and metatranscriptomic) data as the search database, based on two novel approaches Graph2Pro (published) and Var2Pep (new). Graph2Pro retains and uses uncertainties of metagenome assembly for reference-based MS/MS data analysis. Var2Pep considers the variations found in metagenomic/metatranscriptomic sequencing reads that are not retained in the assemblies (contigs). The new software pipeline provides one stop application of both tools, and it supports the use of metagenome assembly from commonly used assemblers including MegaHit and metaSPAdes. When tested on two collections of multi-omic microbiome data sets, our pipeline significantly improved the identification rate of the metaproteomic MS/MS spectra by about two folds, comparing to conventional contig- or read-based approaches (the Var2Pep alone identified 5.6% to 24.1% more unique peptides, depending on the data set). We also showed that identified variant peptides are important for functional profiling of microbiomes. All results suggested that it is important to take into consideration of the assembly uncertainties and genomic variants to facilitate metaproteomic MS/MS data interpretation.

Mediterranean grassland soil C-N compound turnover is dependent on rainfall and depth, and is mediated by genomically divergent microorganisms

Soil microbial activity drives the carbon and nitrogen cycles and is an important determinant of atmospheric trace gas turnover, yet most soils are dominated by microorganisms with unknown metabolic capacities. Even Acidobacteria, among the most abundant bacteria in soil, remain poorly characterized, and functions across groups such as Verrucomicrobia, Gemmatimonadetes, Chloroflexi and Rokubacteria are understudied. Here, we have resolved 60 metagenomic and 20 proteomic data sets from a Mediterranean grassland soil ecosystem and recovered 793 near-complete microbial genomes from 18 phyla, representing around one-third of all microorganisms detected. Importantly, this enabled extensive genomics-based metabolic predictions for these communities. Acidobacteria from multiple previously unstudied classes have genomes that encode large enzyme complements for complex carbohydrate degradation. Alternatively, most microorganisms encode carbohydrate esterases that strip readily accessible methyl and acetyl groups from polymers like pectin and xylan, forming methanol and acetate, the availability of which could explain the high prevalence of C1 metabolism and acetate utilization in genomes. Microorganism abundances among samples collected at three soil depths and under natural and amended rainfall regimes indicate statistically higher associations of inorganic nitrogen metabolism and carbon degradation in deep and shallow soils, respectively. This partitioning decreased in samples under extended spring rainfall, indicating that long-term climate alteration can affect both carbon and nitrogen cycling. Overall, by leveraging natural and experimental gradients with genome-resolved metabolic profiles, we link microorganisms lacking prior genomic characterization to specific roles in complex carbon, C1, nitrate and ammonia transformations, and constrain factors that impact their distributions in soil.

Subsampled Assemblies and Hybrid Nucleotide Composition/Differential Coverage Binning for Genome-Resolved Metagenomics

Metagenomic analyses for reconstruction of genomes from mixed microbial community datasets now routinely allow rapid, accurate genome recovery for tens to hundreds of organisms from environmental samples. This chapter provides a step-by-step protocol for reconstructing genomes from metagenomic datasets, with a focus on the most abundant community members. Subsampling assembly approaches are implemented to improve assembly of abundant genome sequences, an iterative process that targets progressively less abundant populations and improves total community representation in the final merged assembly. A hybrid approach to genome binning is described, combining differential coverage information from a series of metagenomic samples with nucleotide composition information. This approach strengthens binning through application of multiple independent variables for contig clustering. Genome curation through error correction and gap closure leads to high-quality draft genomes, and, for some community members, closed and complete genome sequences reconstructed directly from environmental samples.

Long-read based de novo assembly of low-complexity metagenome samples results in finished genomes and reveals insights into strain diversity and an active phage system

BACKGROUND

Complete and contiguous genome assemblies greatly improve the quality of subsequent systems-wide functional profiling studies and the ability to gain novel biological insights. While a de novo genome assembly of an isolated bacterial strain is in most cases straightforward, more informative data about co-existing bacteria as well as synergistic and antagonistic effects can be obtained from a direct analysis of microbial communities. However, the complexity of metagenomic samples represents a major challenge. While third generation sequencing technologies have been suggested to enable finished metagenome-assembled genomes, to our knowledge, the complete genome assembly of all dominant strains in a microbiome sample has not been demonstrated. Natural whey starter cultures (NWCs) are used in cheese production and represent low-complexity microbiomes. Previous studies of Swiss Gruyère and selected Italian hard cheeses, mostly based on amplicon metagenomics, concurred that three species generally pre-dominate: Streptococcus thermophilus, Lactobacillus helveticus and Lactobacillus delbrueckii.

RESULTS

Two NWCs from Swiss Gruyère producers were subjected to whole metagenome shotgun sequencing using the Pacific Biosciences Sequel and Illumina MiSeq platforms. In addition, longer Oxford Nanopore Technologies MinION reads had to be generated for one to resolve repeat regions. Thereby, we achieved the complete assembly of all dominant bacterial genomes from these low-complexity NWCs, which was corroborated by a 16S rRNA amplicon survey. Moreover, two distinct L. helveticus strains were successfully co-assembled from the same sample. Besides bacterial chromosomes, we could also assemble several bacterial plasmids and phages and a corresponding prophage. Biologically relevant insights were uncovered by linking the plasmids and phages to their respective host genomes using DNA methylation motifs on the plasmids and by matching prokaryotic CRISPR spacers with the corresponding protospacers on the phages. These results could only be achieved by employing long-read sequencing data able to span intragenomic as well as intergenomic repeats.

CONCLUSIONS

Here, we demonstrate the feasibility of complete de novo genome assembly of all dominant strains from low-complexity NWCs based on whole metagenomics shotgun sequencing data. This allowed to gain novel biological insights and is a fundamental basis for subsequent systems-wide omics analyses, functional profiling and phenotype to genotype analysis of specific microbial communities.

Microbial community composition along a 50 000-year lacustrine sediment sequence

For decades, microbial community composition in subseafloor sediments has been the focus of extensive studies. In deep lacustrine sediments, however, the taxonomic composition of microbial communities remains undercharacterized. Greater knowledge on microbial diversity in lacustrine sediments would improve our understanding of how environmental factors, and resulting selective pressures, shape subsurface biospheres in marine and freshwater sediments. Using high-throughput sequencing of 16S rRNA genes across high-resolution climate intervals covering the last 50 000 years in Laguna Potrok Aike, Argentina, we identified changes in microbial populations in response to both past environmental conditions and geochemical changes of the sediment during burial. Microbial communities in Holocene sediments were most diverse, reflecting a layering of taxa linked to electron acceptors availability. In deeper intervals, the data show that salinity, organic matter and the depositional conditions over the Last Glacial-interglacial cycle were all selective pressures in the deep lacustrine assemblage resulting in a genetically distinct biosphere from the surface dominated primarily by Bathyarchaeota and Atribacteria groups. However, similar to marine sediments, some dominant taxa in the shallow subsurface persisted into the subsurface as minor fraction of the community. The subsequent establishment of a deep subsurface community likely results from a combination of paleoenvironmental factors that have shaped the pool of available substrates, together with substrate depletion and/or reworking of organic matter with depth.

High-quality genome sequences of uncultured microbes by assembly of read clouds

Although shotgun metagenomic sequencing of microbiome samples enables partial reconstruction of strain-level community structure, obtaining high-quality microbial genome drafts without isolation and culture remains difficult. Here, we present an application of read clouds, short-read sequences tagged with long-range information, to microbiome samples. We present Athena, a de novo assembler that uses read clouds to improve metagenomic assemblies. We applied this approach to sequence stool samples from two healthy individuals and compared it with existing short-read and synthetic long-read metagenomic sequencing techniques. Read-cloud metagenomic sequencing and Athena assembly produced the most comprehensive individual genome drafts with high contiguity (>200-kb N50, fewer than ten contigs), even for bacteria with relatively low (20×) raw short-read-sequence coverage. We also sequenced a complex marine-sediment sample and generated 24 intermediate-quality genome drafts (>70% complete, <10% contaminated), nine of which were complete (>90% complete, <5% contaminated). Our approach allows for culture-free generation of high-quality microbial genome drafts by using a single shotgun experiment.

Structure and function of the global topsoil microbiome

Soils harbour some of the most diverse microbiomes on Earth and are essential for both nutrient cycling and carbon storage. To understand soil functioning, it is necessary to model the global distribution patterns and functional gene repertoires of soil microorganisms, as well as the biotic and environmental associations between the diversity and structure of both bacterial and fungal soil communities^1-4. Here we show, by leveraging metagenomics and metabarcoding of global topsoil samples (189 sites, 7,560 subsamples), that bacterial, but not fungal, genetic diversity is highest in temperate habitats and that microbial gene composition varies more strongly with environmental variables than with geographic distance. We demonstrate that fungi and bacteria show global niche differentiation that is associated with contrasting diversity responses to precipitation and soil pH. Furthermore, we provide evidence for strong bacterial-fungal antagonism, inferred from antibiotic-resistance genes, in topsoil and ocean habitats, indicating the substantial role of biotic interactions in shaping microbial communities. Our results suggest that both competition and environmental filtering affect the abundance, composition and encoded gene functions of bacterial and fungal communities, indicating that the relative contributions of these microorganisms to global nutrient cycling varies spatially.

Joint Analysis of Long and Short Reads Enables Accurate Estimates of Microbiome Complexity

Reduced microbiome diversity has been linked to several diseases. However, estimating the diversity of bacterial communities-the number and the total length of distinct genomes within a metagenome-remains an open problem in microbial ecology. Here, we describe an algorithm for estimating the microbial diversity in a metagenomic sample based on a joint analysis of short and long reads. Unlike previous approaches, the algorithm does not make any assumptions on the distribution of the frequencies of genomes within a metagenome (as in parametric methods) and does not require a large database that covers the total diversity (as in non-parametric methods). We estimate that genomes comprising a human gut metagenome have total length varying from 1.3 to 3.5 billion nucleotides, with genomes responsible for 50% of total abundance having total length varying from only 25 to 61 million nucleotides. In contrast, genomes comprising an aquifer sediment metagenome have more than two orders of magnitude larger total length (≈840 billion nucleotides).

Opisthorchis viverrini Draft Genome - Biomedical Implications and Future Avenues

Opisthorchiasis is a neglected tropical disease of major proportion, caused by the carcinogenic, Asian liver fluke, Opisthorchis viverrini. This hepatobiliary disease is known to be associated with malignant cancer (cholangiocarcinoma, CCA) and affects millions of people in Southeast Asia. No vaccine is available, and only one drug (praziquantel) is routinely employed against the parasite. Despite technological advances, little is known about the molecular biology of the fluke itself and the disease complex that it causes in humans. The advent of high-throughput nucleic acid sequencing and bioinformatic technologies is enabling researchers to gain global insights into the molecular pathways and processes in parasites. The principal aims of this chapter are to (1) review molecular research of O. viverrini and opisthorchiasis; (2) provide an account of recent advances in the sequencing and characterization of the genome and transcriptomes of O. viverrini; (3) describe the complex life of this worm in the biliary system of the definitive (human) host and how the fluke interacts with this host and causes disease at the molecular level; (4) discuss the implications of systems biological research and (5) consider how progress in genomics and informatics might enable explorations of O. viverrini and related worms and the discovery of new interventions against opisthorchiasis and CCA.

Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach

The worldwide commercial cultivation of transgenic crops, including glyphosate-tolerant (GT) soybeans, has increased widely during the past 20 years. However, it is accompanied with a growing concern about potential effects of transgenic crops on the soil microbial communities, especially on rhizosphere bacterial communities. Our previous study found that the GT soybean line NZL06-698 (N698) significantly affected rhizosphere bacteria, including some unidentified taxa, through 16S rRNA gene (16S rDNA) V4 region amplicon deep sequencing via Illumina MiSeq. In this study, we performed 16S rDNA V5–V7 region amplicon deep sequencing via Illumina MiSeq and shotgun metagenomic approaches to identify those major taxa. Results of these processes revealed that the species richness and evenness increased in the rhizosphere bacterial communities of N698, the beta diversity of the rhizosphere bacterial communities of N698 was affected, and that certain dominant bacterial phyla and genera were related to N698 compared with its control cultivar Mengdou12. Consistent with our previous findings, this study showed that N698 affects the rhizosphere bacterial communities. In specific, N698 negatively affects Rahnella, Janthinobacterium, Stenotrophomonas, Sphingomonas and Luteibacter while positively affecting Arthrobacter, Bradyrhizobium, Ramlibacter and Nitrospira.

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putative species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.

Mining prokaryotes for antimicrobial compounds: from diversity to function

The bacterial kingdom provides a major source of antimicrobials that can either be directly applied or used as scaffolds to further improve their functionality in the host. The rapidly increasing amount of bacterial genomic, metabolomic and transcriptomic data offers unique opportunities to apply a variety of approaches to mine for existing and novel antimicrobials. Here, we discuss several powerful mining approaches to identify novel molecules with antimicrobial activity across structurally diverse natural products, including ribosomally synthesized and posttranslationally modified peptides, nonribosomal peptides and polyketides. We not only discuss the direct mining of genomes based on identification of biosynthetic gene clusters, but also describe more advanced and integrative approaches in ecology-based mining, functionality-based mining and mode-of-action-based mining. These efforts are likely to accelerate the discovery and development of novel antimicrobial drugs.

Linking soil biology and chemistry in biological soil crust using isolate exometabolomics

Metagenomic sequencing provides a window into microbial community structure and metabolic potential; however, linking these data to exogenous metabolites that microorganisms process and produce (the exometabolome) remains challenging. Previously, we observed strong exometabolite niche partitioning among bacterial isolates from biological soil crust (biocrust). Here we examine native biocrust to determine if these patterns are reproduced in the environment. Overall, most soil metabolites display the expected relationship (positive or negative correlation) with four dominant bacteria following a wetting event and across biocrust developmental stages. For metabolites that were previously found to be consumed by an isolate, 70% are negatively correlated with the abundance of the isolate’s closest matching environmental relative in situ, whereas for released metabolites, 67% were positively correlated. Our results demonstrate that metabolite profiling, shotgun sequencing and exometabolomics may be successfully integrated to functionally link microbial community structure with environmental chemistry in biocrust.

Metagenomic sequencing provides a window into microbial community structure and metabolic potential. Here, Swenson et al. integrate metabolomics and shotgun sequencing to functionally link microbial community structure with environmental chemistry in biological soil crust (biocrust).

Novel Microbial Diversity and Functional Potential in the Marine Mammal Oral Microbiome

The vast majority of bacterial diversity lies within phylum-level lineages called "candidate phyla," which lack isolated representatives and are poorly understood. These bacteria are surprisingly abundant in the oral cavity of marine mammals. We employed a genome-resolved metagenomic approach to recover and characterize genomes and functional potential from microbes in the oral gingival sulcus of two bottlenose dolphins (Tursiops truncatus). We detected organisms from 24 known bacterial phyla and one archaeal phylum. We also recovered genomes from two deep-branching, previously uncharacterized phylum-level lineages (here named "Candidatus Delphibacteria" and "Candidatus Fertabacteria"). The Delphibacteria lineage is found in both managed and wild dolphins; its metabolic profile suggests a capacity for denitrification and a possible role in dolphin health. We uncovered a rich diversity of predicted Cas9 proteins, including the two longest predicted Cas9 proteins to date. Notably, we identified the first type II CRISPR-Cas systems encoded by members of the Candidate Phyla Radiation. Using their spacer sequences, we subsequently identified and assembled a complete Saccharibacteria phage genome. These findings underscore the immense microbial diversity and functional potential that await discovery in previously unexplored environments.

Shotgun metagenomics, from sampling to analysis

Diverse microbial communities of bacteria, archaea, viruses and single-celled eukaryotes have crucial roles in the environment and in human health. However, microbes are frequently difficult to culture in the laboratory, which can confound cataloging of members and understanding of how communities function. High-throughput sequencing technologies and a suite of computational pipelines have been combined into shotgun metagenomics methods that have transformed microbiology. Still, computational approaches to overcome the challenges that affect both assembly-based and mapping-based metagenomic profiling, particularly of high-complexity samples or environments containing organisms with limited similarity to sequenced genomes, are needed. Understanding the functions and characterizing specific strains of these communities offers biotechnological promise in therapeutic discovery and innovative ways to synthesize products using microbial factories and can pinpoint the contributions of microorganisms to planetary, animal and human health.

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

Background

Viral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we used in silico mock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates.

Results

Tools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, and IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates.

Conclusions

These simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.

Genome assembly from synthetic long read clouds

MOTIVATION

Despite rapid progress in sequencing technology, assembling de novo the genomes of new species as well as reconstructing complex metagenomes remains major technological challenges. New synthetic long read (SLR) technologies promise significant advances towards these goals; however, their applicability is limited by high sequencing requirements and the inability of current assembly paradigms to cope with combinations of short and long reads.

RESULTS

Here, we introduce Architect, a new de novo scaffolder aimed at SLR technologies. Unlike previous assembly strategies, Architect does not require a costly subassembly step; instead it assembles genomes directly from the SLR's underlying short reads, which we refer to as read clouds This enables a 4- to 20-fold reduction in sequencing requirements and a 5-fold increase in assembly contiguity on both genomic and metagenomic datasets relative to state-of-the-art assembly strategies aimed directly at fully subassembled long reads.

AVAILABILITY AND IMPLEMENTATION

Our source code is freely available at https://github.com/kuleshov/architect

CONTACT

kuleshov@stanford.edu.

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC.