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

Genome-Centric Analysis of a Thermophilic and Cellulolytic Bacterial Consortium Derived from Composting

Microbial consortia selected from complex lignocellulolytic microbial communities are promising alternatives to deconstruct plant waste, since synergistic action of different enzymes is required for full degradation of plant biomass in biorefining applications. Culture enrichment also facilitates the study of interactions among consortium members, and can be a good source of novel microbial species. Here, we used a sample from a plant waste composting operation in the São Paulo Zoo (Brazil) as inoculum to obtain a thermophilic aerobic consortium enriched through multiple passages at 60°C in carboxymethylcellulose as sole carbon source. The microbial community composition of this consortium was investigated by shotgun metagenomics and genome-centric analysis. Six near-complete (over 90%) genomes were reconstructed. Similarity and phylogenetic analyses show that four of these six genomes are novel, with the following hypothesized identifications: a new Thermobacillus species; the first Bacillus thermozeamaize genome (for which currently only 16S sequences are available) or else the first representative of a new family in the Bacillales order; the first representative of a new genus in the Paenibacillaceae family; and the first representative of a new deep-branching family in the Clostridia class. The reconstructed genomes from known species were identified as Geobacillus thermoglucosidasius and Caldibacillus debilis. The metabolic potential of these recovered genomes based on COG and CAZy analyses show that these genomes encode several glycoside hydrolases (GHs) as well as other genes related to lignocellulose breakdown. The new Thermobacillus species stands out for being the richest in diversity and abundance of GHs, possessing the greatest potential for biomass degradation among the six recovered genomes. We also investigated the presence and activity of the organisms corresponding to these genomes in the composting operation from which the consortium was built, using compost metagenome and metatranscriptome datasets generated in a previous study. We obtained strong evidence that five of the six recovered genomes are indeed present and active in that composting process. We have thus discovered three (perhaps four) new thermophillic bacterial species that add to the increasing repertoire of known lignocellulose degraders, whose biotechnological potential can now be investigated in further studies.

Utilization of defined microbial communities enables effective evaluation of meta-genomic assemblies

BACKGROUND

Metagenomics is the study of the microbial genomes isolated from communities found on our bodies or in our environment. By correctly determining the relation between human health and the human associated microbial communities, novel mechanisms of health and disease can be found, thus enabling the development of novel diagnostics and therapeutics. Due to the diversity of the microbial communities, strategies developed for aligning human genomes cannot be utilized, and genomes of the microbial species in the community must be assembled de novo. However, in order to obtain the best metagenomic assemblies, it is important to choose the proper assembler. Due to the rapidly evolving nature of metagenomics, new assemblers are constantly created, and the field has not yet agreed on a standardized process. Furthermore, the truth sets used to compare these methods are either too simple (computationally derived diverse communities) or complex (microbial communities of unknown composition), yielding results that are hard to interpret. In this analysis, we interrogate the strengths and weaknesses of five popular assemblers through the use of defined biological samples of known genomic composition and abundance. We assessed the performance of each assembler on their ability to reassemble genomes, call taxonomic abundances, and recreate open reading frames (ORFs).

RESULTS

We tested five metagenomic assemblers: Omega, metaSPAdes, IDBA-UD, metaVelvet and MEGAHIT on known and synthetic metagenomic data sets. MetaSPAdes excelled in diverse sets, IDBA-UD performed well all around, metaVelvet had high accuracy in high abundance organisms, and MEGAHIT was able to accurately differentiate similar organisms within a community. At the ORF level, metaSPAdes and MEGAHIT had the least number of missing ORFs within diverse and similar communities respectively.

CONCLUSIONS

Depending on the metagenomics question asked, the correct assembler for the task at hand will differ. It is important to choose the appropriate assembler, and thus clearly define the biological problem of an experiment, as different assemblers will give different answers to the same question.

metaSPAdes: a new versatile metagenomic assembler

While metagenomics has emerged as a technology of choice for analyzing bacterial populations, the assembly of metagenomic data remains challenging, thus stifling biological discoveries. Moreover, recent studies revealed that complex bacterial populations may be composed from dozens of related strains, thus further amplifying the challenge of metagenomic assembly. metaSPAdes addresses various challenges of metagenomic assembly by capitalizing on computational ideas that proved to be useful in assemblies of single cells and highly polymorphic diploid genomes. We benchmark metaSPAdes against other state-of-the-art metagenome assemblers and demonstrate that it results in high-quality assemblies across diverse data sets.

Functional Metagenomics as a Tool for Identification of New Antibiotic Resistance Genes from Natural Environments

Antibiotic resistance has become a major concern for human and animal health, as therapeutic alternatives to treat multidrug-resistant microorganisms are rapidly dwindling. The problem is compounded by low investment in antibiotic research and lack of new effective antimicrobial drugs on the market. Exploring environmental antibiotic resistance genes (ARGs) will help us to better understand bacterial resistance mechanisms, which may be the key to identifying new drug targets. Because most environment-associated microorganisms are not yet cultivable, culture-independent techniques are essential to determine which organisms are present in a given environmental sample and allow the assessment and utilization of the genetic wealth they represent. Metagenomics represents a powerful tool to achieve these goals using sequence-based and functional-based approaches. Functional metagenomic approaches are particularly well suited to the identification new ARGs from natural environments because, unlike sequence-based approaches, they do not require previous knowledge of these genes. This review discusses functional metagenomics-based ARG research and describes new possibilities for surveying the resistome in environmental samples.

MetaSort untangles metagenome assembly by reducing microbial community complexity

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.

High-resolution characterization of the human microbiome

The human microbiome plays an important and increasingly recognized role in human health. Studies of the microbiome typically use targeted sequencing of the 16S rRNA gene, whole metagenome shotgun sequencing, or other meta-omic technologies to characterize the microbiome's composition, activity, and dynamics. Processing, analyzing, and interpreting these data involve numerous computational tools that aim to filter, cluster, annotate, and quantify the obtained data and ultimately provide an accurate and interpretable profile of the microbiome's taxonomy, functional capacity, and behavior. These tools, however, are often limited in resolution and accuracy and may fail to capture many biologically and clinically relevant microbiome features, such as strain-level variation or nuanced functional response to perturbation. Over the past few years, extensive efforts have been invested toward addressing these challenges and developing novel computational methods for accurate and high-resolution characterization of microbiome data. These methods aim to quantify strain-level composition and variation, detect and characterize rare microbiome species, link specific genes to individual taxa, and more accurately characterize the functional capacity and dynamics of the microbiome. These methods and the ability to produce detailed and precise microbiome information are clearly essential for informing microbiome-based personalized therapies. In this review, we survey these methods, highlighting the challenges each method sets out to address and briefly describing methodological approaches.

Measurement of bacterial replication rates in microbial communities

Culture-independent microbiome studies have increased our understanding of the complexity and metabolic potential of microbial communities. However, to understand the contribution of individual microbiome members to community functions, it is important to determine which bacteria are actively replicating. We developed an algorithm, iRep, that uses draft-quality genome sequences and single time-point metagenome sequencing to infer microbial population replication rates. The algorithm calculates an index of replication (iRep) based on the sequencing coverage trend that results from bi-directional genome replication from a single origin of replication. We apply this method to show that microbial replication rates increase after antibiotic administration in human infants. We also show that uncultivated, groundwater-associated, Candidate Phyla Radiation bacteria only rarely replicate quickly in subsurface communities undergoing substantial changes in geochemistry. Our method can be applied to any genome-resolved microbiome study to track organism responses to varying conditions, identify actively growing populations and measure replication rates for use in modeling studies.

Genomic and metagenomic technologies to explore the antibiotic resistance mobilome

Antibiotic resistance is a relevant problem for human health that requires global approaches to establish a deep understanding of the processes of acquisition, stabilization, and spread of resistance among human bacterial pathogens. Since natural (nonclinical) ecosystems are reservoirs of resistance genes, a health-integrated study of the epidemiology of antibiotic resistance requires the exploration of such ecosystems with the aim of determining the role they may play in the selection, evolution, and spread of antibiotic resistance genes, involving the so-called resistance mobilome. High-throughput sequencing techniques allow an unprecedented opportunity to describe the genetic composition of a given microbiome without the need to subculture the organisms present inside. However, bioinformatic methods for analyzing this bulk of data, mainly with respect to binning each resistance gene with the organism hosting it, are still in their infancy. Here, we discuss how current genomic methodologies can serve to analyze the resistance mobilome and its linkage with different bacterial genomes and metagenomes. In addition, we describe the drawbacks of current methodologies for analyzing the resistance mobilome, mainly in cases of complex microbiotas, and discuss the possibility of implementing novel tools to improve our current metagenomic toolbox.

Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone

Annually, half of all plant-derived carbon is added to soil where it is microbially respired to CO₂. However, understanding of the microbiology of this process is limited because most culture-independent methods cannot link metabolic processes to the organisms present, and this link to causative agents is necessary to predict the results of perturbations on the system. We collected soil samples at two sub-root depths (10–20 cm and 30–40 cm) before and after a rainfall-driven nutrient perturbation event in a Northern California grassland that experiences a Mediterranean climate. From ten samples, we reconstructed 198 metagenome-assembled genomes that represent all major phylotypes. We also quantified 6,835 proteins and 175 metabolites and showed that after the rain event the concentrations of many sugars and amino acids approach zero at the base of the soil profile. Unexpectedly, the genomes of novel members of the Gemmatimonadetes and Candidate Phylum Rokubacteria phyla encode pathways for methylotrophy. We infer that these abundant organisms contribute substantially to carbon turnover in the soil, given that methylotrophy proteins were among the most abundant proteins in the proteome. Previously undescribed Bathyarchaeota and Thermoplasmatales archaea are abundant in deeper soil horizons and are inferred to contribute appreciably to aromatic amino acid degradation. Many of the other bacteria appear to breakdown other components of plant biomass, as evidenced by the prevalence of various sugar and amino acid transporters and corresponding hydrolyzing machinery in the proteome. Overall, our work provides organism-resolved insight into the spatial distribution of bacteria and archaea whose activities combine to degrade plant-derived organics, limiting the transport of methanol, amino acids and sugars into underlying weathered rock. The new insights into the soil carbon cycle during an intense period of carbon turnover, including biogeochemical roles to previously little known soil microbes, were made possible via the combination of metagenomics, proteomics, and metabolomics.

Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system

The subterranean world hosts up to one-fifth of all biomass, including microbial communities that drive transformations central to Earth's biogeochemical cycles. However, little is known about how complex microbial communities in such environments are structured, and how inter-organism interactions shape ecosystem function. Here we apply terabase-scale cultivation-independent metagenomics to aquifer sediments and groundwater, and reconstruct 2,540 draft-quality, near-complete and complete strain-resolved genomes that represent the majority of known bacterial phyla as well as 47 newly discovered phylum-level lineages. Metabolic analyses spanning this vast phylogenetic diversity and representing up to 36% of organisms detected in the system are used to document the distribution of pathways in coexisting organisms. Consistent with prior findings indicating metabolic handoffs in simple consortia, we find that few organisms within the community can conduct multiple sequential redox transformations. As environmental conditions change, different assemblages of organisms are selected for, altering linkages among the major biogeochemical cycles.

Beyond 16S rRNA Community Profiling: Intra-Species Diversity in the Gut Microbiota

Interactions with microbes affect many aspects of animal biology, including immune system development, nutrition and health. In vertebrates, the gut microbiota is dominated by a small subset of phyla, but the species composition within these phyla is typically not conserved. Moreover, several recent studies have shown that bacterial species in the gut are composed of a multitude of strains, which frequently co-exist in their host, and may be host-specific. However, since the study of intra-species diversity is challenging, particularly in the setting of complex, host-associated microbial communities, our current understanding of the distribution, evolution and functional relevance of intra-species diversity in the gut is scarce. In order to unravel how genomic diversity translates into phenotypic diversity, community analyses going beyond 16S rRNA profiling, in combination with experimental approaches, are needed. Recently, the honeybee has emerged as a promising model for studying gut bacterial communities, particularly in terms of strain-level diversity. Unlike most other invertebrates, the honeybee gut is colonized by a remarkably consistent and specific core microbiota, which is dominated by only eight bacterial species. As for the vertebrate gut microbiota, these species are composed of highly diverse strains suggesting that similar evolutionary forces shape gut community structures in vertebrates and social insects. In this review, we outline current knowledge on the evolution and functional relevance of strain diversity within the gut microbiota, including recent insights gained from mammals and other animals such as the honeybee. We discuss methodological approaches and propose possible future avenues for studying strain diversity in complex bacterial communities.

Moleculo Long-Read Sequencing Facilitates Assembly and Genomic Binning from Complex Soil Metagenomes

Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes.

Soil metagenomics has been touted as the “grand challenge” for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600 reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of “Candidatus Pseudomonas sp. strain JKJ-1” from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundance Acidobacteria were highly transcriptionally active, whereas bins corresponding to high-relative-abundance Verrucomicrobia were not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities.

IMPORTANCE Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes.

Author Video: An author video summary of this article is available.

Genome-Centric Analysis of Microbial Populations Enriched by Hydraulic Fracture Fluid Additives in a Coal Bed Methane Production Well

Coal bed methane (CBM) is generated primarily through the microbial degradation of coal. Despite a limited understanding of the microorganisms responsible for this process, there is significant interest in developing methods to stimulate additional methane production from CBM wells. Physical techniques including hydraulic fracture stimulation are commonly applied to CBM wells, however the effects of specific additives contained in hydraulic fracture fluids on native CBM microbial communities are poorly understood. Here, metagenomic sequencing was applied to the formation waters of a hydraulically fractured and several non-fractured CBM production wells to determine the effect of this stimulation technique on the in-situ microbial community. The hydraulically fractured well was dominated by two microbial populations belonging to the class Phycisphaerae (within phylum Planctomycetes) and candidate phylum Aminicenantes. Populations from these phyla were absent or present at extremely low abundance in non-fractured CBM wells. Detailed metabolic reconstruction of near-complete genomes from these populations showed that their high relative abundance in the hydraulically fractured CBM well could be explained by the introduction of additional carbon sources, electron acceptors, and biocides contained in the hydraulic fracture fluid.

Capturing One of the Human Gut Microbiome's Most Wanted: Reconstructing the Genome of a Novel Butyrate-Producing, Clostridial Scavenger from Metagenomic Sequence Data

The role of the microbiome in health and disease is attracting great attention, yet we still know little about some of the most prevalent microorganisms inside our bodies. Several years ago, Human Microbiome Project (HMP) researchers generated a list of "most wanted" taxa: bacteria both prevalent among healthy volunteers and distantly related to any sequenced organisms. Unfortunately, the challenge of assembling high-quality genomes from a tangle of metagenomic reads has slowed progress in learning about these uncultured bacteria. Here, we describe how recent advances in sequencing and analysis allowed us to assemble "most wanted" genomes from metagenomic data collected from four stool samples. Using a combination of both de novo and guided assembly methods, we assembled and binned over 100 genomes from an initial data set of over 1,300 Gbp. One of these genome bins, which met HMP's criteria for a "most wanted" taxa, contained three essentially complete genomes belonging to a previously uncultivated species. This species is most closely related to Eubacterium desmolans and the clostridial cluster IV/Clostridium leptum subgroup species Butyricicoccus pullicaecorum (71-76% average nucleotide identity). Gene function analysis indicates that the species is an obligate anaerobe, forms spores, and produces the anti-inflammatory short-chain fatty acids acetate and butyrate. It also appears to take up metabolically costly molecules such as cobalamin, methionine, and branch-chained amino acids from the environment, and to lack virulence genes. Thus, the evidence is consistent with a secondary degrader that occupies a host-dependent, nutrient-scavenging niche within the gut; its ability to produce butyrate, which is thought to play an anti-inflammatory role, makes it intriguing for the study of diseases such as colon cancer and inflammatory bowel disease. In conclusion, we have assembled essentially complete genomes from stool metagenomic data, yielding valuable information about uncultured organisms' metabolic and ecologic niches, factors that may be required to successfully culture these bacteria, and their role in maintaining health and causing disease.

Tracking Strains in the Microbiome: Insights from Metagenomics and Models

Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single person's microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.

Understanding Haemonchus contortus Better Through Genomics and Transcriptomics

Parasitic roundworms (nematodes) cause substantial mortality and morbidity in animals globally. The barber's pole worm, Haemonchus contortus, is one of the most economically significant parasitic nematodes of small ruminants worldwide. Although this and related nematodes can be controlled relatively well using anthelmintics, resistance against most drugs in common use has become a major problem. Until recently, almost nothing was known about the molecular biology of H. contortus on a global scale. This chapter gives a brief background on H. contortus and haemonchosis, immune responses, vaccine research, chemotherapeutics and current problems associated with drug resistance. It also describes progress in transcriptomics before the availability of H. contortus genomes and the challenges associated with such work. It then reviews major progress on the two draft genomes and developmental transcriptomes of H. contortus, and summarizes their implications for the molecular biology of this worm in both the free-living and the parasitic stages of its life cycle. The chapter concludes by considering how genomics and transcriptomics can accelerate research on Haemonchus and related parasites, and can enable the development of new interventions against haemonchosis.

Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

High-throughput sequencing provides a fast and cost-effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigrade Hypsibius dujardini, and created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes from the raw assembly, and curate a 182 Mbp draft genome for H. dujardini supported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

Resolving the Complexity of Human Skin Metagenomes Using Single-Molecule Sequencing

Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communities. However, the resultant "genomes" are typically fragmented and incomplete due to the limited ability of short-read sequence data to assemble complex or low-coverage regions. Here, we use single-molecule, real-time (SMRT) sequencing to reconstruct a high-quality, closed genome of a previously uncharacterized Corynebacterium simulans and its companion bacteriophage from a skin metagenomic sample. Considerable improvement in assembly quality occurs in hybrid approaches incorporating short-read data, with even relatively small amounts of long-read data being sufficient to improve metagenome reconstruction. Using short-read data to evaluate strain variation of this C. simulans in its skin community at single-nucleotide resolution, we observed a dominant C. simulans strain with moderate allelic heterozygosity throughout the population. We demonstrate the utility of SMRT sequencing and hybrid approaches in metagenome quantitation, reconstruction, and annotation.

IMPORTANCE

The species comprising a microbial community are often difficult to deconvolute due to technical limitations inherent to most short-read sequencing technologies. Here, we leverage new advances in sequencing technology, single-molecule sequencing, to significantly improve reconstruction of a complex human skin microbial community. With this long-read technology, we were able to reconstruct and annotate a closed, high-quality genome of a previously uncharacterized skin species. We demonstrate that hybrid approaches with short-read technology are sufficiently powerful to reconstruct even single-nucleotide polymorphism level variation of species in this a community.

TruSPAdes: barcode assembly of TruSeq synthetic long reads

The recently introduced TruSeq synthetic long read (TSLR) technology generates long and accurate virtual reads from an assembly of barcoded pools of short reads. The TSLR method provides an attractive alternative to existing sequencing platforms that generate long but inaccurate reads. We describe the truSPAdes algorithm (http://bioinf.spbau.ru/spades) for TSLR assembly and show that it results in a dramatic improvement in the quality of metagenomics assemblies.

Haplotype-Phased Synthetic Long Reads from Short-Read Sequencing

Next-generation DNA sequencing has revolutionized the study of biology. However, the short read lengths of the dominant instruments complicate assembly of complex genomes and haplotype phasing of mixtures of similar sequences. Here we demonstrate a method to reconstruct the sequences of individual nucleic acid molecules up to 11.6 kilobases in length from short (150-bp) reads. We show that our method can construct 99.97%-accurate synthetic reads from bacterial, plant, and animal genomic samples, full-length mRNA sequences from human cancer cell lines, and individual HIV env gene variants from a mixture. The preparation of multiple samples can be multiplexed into a single tube, further reducing effort and cost relative to competing approaches. Our approach generates sequencing libraries in three days from less than one microgram of DNA in a single-tube format without custom equipment or specialized expertise.

Synthetic long-read sequencing reveals intraspecies diversity in the human microbiome

Identifying bacterial strains in metagenome and microbiome samples using computational analyses of short-read sequence remains a difficult problem. Here, we present an analysis of a human gut microbiome using on Tru-seq synthetic long reads combined with new computational tools for metagenomic long-read assembly, variant-calling and haplotyping (Nanoscope and Lens). Our analysis identifies 178 bacterial species of which 51 were not found using short sequence reads alone. We recover bacterial contigs that comprise multiple operons, including 22 contigs of >1Mbp. Extensive intraspecies variation among microbial strains in the form of haplotypes that span up to hundreds of Kbp can be observed using our approach. Our method incorporates synthetic long-read sequencing technology with standard shotgun approaches to move towards rapid, precise and comprehensive analyses of metagenome and microbiome samples.

A viability-linked metagenomic analysis of cleanroom environments: eukarya, prokaryotes, and viruses

BACKGROUND

Recent studies posit a reciprocal dependency between the microbiomes associated with humans and indoor environments. However, none of these metagenome surveys has considered the viability of constituent microorganisms when inferring impact on human health.

RESULTS

Reported here are the results of a viability-linked metagenomics assay, which (1) unveil a remarkably complex community profile for bacteria, fungi, and viruses and (2) bolster the detection of underrepresented taxa by eliminating biases resulting from extraneous DNA. This approach enabled, for the first time ever, the elucidation of viral genomes from a cleanroom environment. Upon comparing the viable biomes and distribution of phylotypes within a cleanroom and adjoining (uncontrolled) gowning enclosure, the rigorous cleaning and stringent control countermeasures of the former were observed to select for a greater presence of anaerobes and spore-forming microflora. Sequence abundance and correlation analyses suggest that the viable indoor microbiome is influenced by both the human microbiome and the surrounding ecosystem(s).

CONCLUSIONS

The findings of this investigation constitute the literature's first ever account of the indoor metagenome derived from DNA originating solely from the potential viable microbial population. Results presented in this study should prove valuable to the conceptualization and experimental design of future studies on indoor microbiomes aimed at inferring impact on human health.

Anvi'o: an advanced analysis and visualization platform for 'omics data

Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations through de novo characterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.

Emerging spatial patterns in Antarctic prokaryotes

Recent advances in knowledge of patterns of biogeography in terrestrial eukaryotic organisms have led to a fundamental paradigm shift in understanding of the controls and history of life on land in Antarctica, and its interactions over the long term with the glaciological and geological processes that have shaped the continent. However, while it has long been recognized that the terrestrial ecosystems of Antarctica are dominated by microbes and their processes, knowledge of microbial diversity and distributions has lagged far behind that of the macroscopic eukaryote organisms. Increasing human contact with and activity in the continent is leading to risks of biological contamination and change in a region whose isolation has protected it for millions of years at least; these risks may be particularly acute for microbial communities which have, as yet, received scant recognition and attention. Even a matter apparently as straightforward as Protected Area designation in Antarctica requires robust biodiversity data which, in most parts of the continent, remain almost completely unavailable. A range of important contributing factors mean that it is now timely to reconsider the state of knowledge of Antarctic terrestrial prokaryotes. Rapid advances in molecular biological approaches are increasingly demonstrating that bacterial diversity in Antarctica may be far greater than previously thought, and that there is overlap in the environmental controls affecting both Antarctic prokaryotic and eukaryotic communities. Bacterial dispersal mechanisms and colonization patterns remain largely unaddressed, although evidence for regional evolutionary differentiation is rapidly accruing and, with this, there is increasing appreciation of patterns in regional bacterial biogeography in this large part of the globe. In this review, we set out to describe the state of knowledge of Antarctic prokaryote diversity patterns, drawing analogy with those of eukaryote groups where appropriate. Based on our synthesis, it is clear that spatial patterns of Antarctic prokaryotes can be unique at local scales, while the limited evidence available to date supports the group exhibiting overall regional biogeographical patterns similar to the eukaryotes. We further consider the applicability of the concept of “functional redundancy” for the Antarctic microbial community and highlight the requirements for proper consideration of their important and distinctive roles in Antarctic terrestrial ecosystems.

Read clouds uncover variation in complex regions of the human genome

Although an increasing amount of human genetic variation is being identified and recorded, determining variants within repeated sequences of the human genome remains a challenge. Most population and genome-wide association studies have therefore been unable to consider variation in these regions. Core to the problem is the lack of a sequencing technology that produces reads with sufficient length and accuracy to enable unique mapping. Here, we present a novel methodology of using read clouds, obtained by accurate short-read sequencing of DNA derived from long fragment libraries, to confidently align short reads within repeat regions and enable accurate variant discovery. Our novel algorithm, Random Field Aligner (RFA), captures the relationships among the short reads governed by the long read process via a Markov Random Field. We utilized a modified version of the Illumina TruSeq synthetic long-read protocol, which yielded shallow-sequenced read clouds. We test RFA through extensive simulations and apply it to discover variants on the NA12878 human sample, for which shallow TruSeq read cloud sequencing data are available, and on an invasive breast carcinoma genome that we sequenced using the same method. We demonstrate that RFA facilitates accurate recovery of variation in 155 Mb of the human genome, including 94% of 67 Mb of segmental duplication sequence and 96% of 11 Mb of transcribed sequence, that are currently hidden from short-read technologies.

"Altiarchaeales": uncultivated archaea from the subsurface

Due to the limited cultivability of the vast majority of microorganisms, researchers have applied environmental genomics and other state-of-the-art technologies to gain insights into the biology of uncultivated Archaea and bacteria in their natural biotope. In this review, we summarize the scientific findings on a recently proposed order-level lineage of uncultivated Archaea called Altiarchaeales, which includes “Candidatus Altiarchaeum hamiconexum” as the most well-described representative. Ca. A. hamiconexum possesses a complex biology: thriving strictly anaerobically, this microorganism is capable of forming highly-pure biofilms, connecting the cells by extraordinary cell surface appendages (the “hami”) and has other highly unusual traits, such as a double-membrane-based cell wall. Indicated by genomic information from different biotopes, the Altiarchaeales seem to proliferate in deep, anoxic groundwater of Earth’s crust bearing a potentially very important function: carbon fixation. Although their net carbon fixation rate has not yet been determined, they appear as highly abundant organisms in their biotopes and may thus represent an important primary producer in the subsurface. In sum, the research over more than a decade on Ca. A. hamiconexum has revealed many interesting features of its lifestyle, its genomic information, metabolism and ultrastructure, making this archaeon one of the best-studied uncultivated Archaea in the literature.

Aquifer environment selects for microbial species cohorts in sediment and groundwater

Little is known about the biogeography or stability of sediment-associated microbial community membership because these environments are biologically complex and generally difficult to sample. High-throughput-sequencing methods provide new opportunities to simultaneously genomically sample and track microbial community members across a large number of sampling sites or times, with higher taxonomic resolution than is associated with 16 S ribosomal RNA gene surveys, and without the disadvantages of primer bias and gene copy number uncertainty. We characterized a sediment community at 5 m depth in an aquifer adjacent to the Colorado River and tracked its most abundant 133 organisms across 36 different sediment and groundwater samples. We sampled sites separated by centimeters, meters and tens of meters, collected on seven occasions over 6 years. Analysis of 1.4 terabase pairs of DNA sequence showed that these 133 organisms were more consistently detected in saturated sediments than in samples from the vadose zone, from distant locations or from groundwater filtrates. Abundance profiles across aquifer locations and from different sampling times identified organism cohorts that comprised subsets of the 133 organisms that were consistently associated. The data suggest that cohorts are partly selected for by shared environmental adaptation.