Improved assemblies using a source-agnostic pipeline for MetaGenomic Assembly by Merging (MeGAMerge) of contigs

Enhanced mercury phytoremediation by Pseudomonodictys pantanalensis sp. nov. A73 and Westerdykella aquatica P71

Mercury is a non-essential and toxic metal that induces toxicity in most organisms, but endophytic fungi can develop survival strategies to tolerate and respond to metal contaminants and other environmental stressors. The present study demonstrated the potential of mercury-resistant endophytic fungi in phytoremediation. We examined the functional traits involved in plant growth promotion, phytotoxicity mitigation, and mercury phytoremediation in seven fungi strains. The endophytic isolates synthesized the phytohormone indole-3-acetic acid, secreted siderophores, and solubilized phosphate in vitro. Inoculation of maize (Zea mays) plants with endophytes increased plant growth attributes by up to 76.25%. The endophytic fungi stimulated mercury uptake from the substrate and promoted its accumulation in plant tissues (t test, p < 0.05), preferentially in the roots, which thereby mitigated the impacts of metal phytotoxicity. Westerdykella aquatica P71 and the newly identified species Pseudomonodictys pantanalensis nov. A73 were the isolates that presented the best phytoremediation potential. Assembling and annotation of P. pantanalensis A73 and W. aquatica P71 genomes resulted in genome sizes of 45.7 and 31.8 Mb that encoded 17,774 and 11,240 protein-coding genes, respectively. Some clusters of genes detected were involved in the synthesis of secondary metabolites such as dimethylcoprogen (NRPS) and melanin (T1PKS), which are metal chelators with antioxidant activity; mercury resistance (merA and merR1); oxidative stress (PRX1 and TRX1); and plant growth promotion (trpS and iscU). Therefore, both fungi species are potential tools for the bioremediation of mercury-contaminated soils due to their ability to reduce phytotoxicity and assist phytoremediation.

High-resolution shotgun metagenomics: the more data, the better?

In shotgun metagenomics (SM), the state-of-the-art bioinformatic workflows are referred to as high-resolution shotgun metagenomics (HRSM) and require intensive computing and disk storage resources. While the increase in data output of the latest iteration of high-throughput DNA sequencing systems can allow for unprecedented sequencing depth at a minimal cost, adjustments in HRSM workflows will be needed to properly process these ever-increasing sequence datasets. One potential adaptation is to generate so-called shallow SM datasets that contain fewer sequencing data per sample as compared with the more classic high coverage sequencing. While shallow sequencing is a promising avenue for SM data analysis, detailed benchmarks using real-data are lacking. In this case study, we took four public SM datasets, one massive and the others moderate in size and subsampled each dataset at various levels to mimic shallow sequencing datasets of various sequencing depths. Our results suggest that shallow SM sequencing is a viable avenue to obtain sound results regarding microbial community structures and that high-depth sequencing does not bring additional elements for ecological interpretation. More specifically, results obtained by subsampling as little as 0.5 M sequencing clusters per sample were similar to the results obtained with the largest subsampled dataset for human gut and agricultural soil datasets. For an Antarctic dataset, which contained only a few samples, 4 M sequencing clusters per sample was found to generate comparable results to the full dataset. One area where ultra-deep sequencing and maximizing the usage of all data was undeniably beneficial was in the generation of metagenome-assembled genomes.

Discovery of an Antarctic Ascidian-Associated Uncultivated Verrucomicrobia with Antimelanoma Palmerolide Biosynthetic Potential

The Antarctic marine ecosystem harbors a wealth of biological and chemical innovation that has risen in concert over millennia since the isolation of the continent and formation of the Antarctic circumpolar current. Scientific inquiry into the novelty of marine natural products produced by Antarctic benthic invertebrates led to the discovery of a bioactive macrolide, palmerolide A, that has specific activity against melanoma and holds considerable promise as an anticancer therapeutic. While this compound was isolated from the Antarctic ascidian Synoicum adareanum, its biosynthesis has since been hypothesized to be microbially mediated, given structural similarities to microbially produced hybrid nonribosomal peptide-polyketide macrolides. Here, we describe a metagenome-enabled investigation aimed at identifying the biosynthetic gene cluster (BGC) and palmerolide A-producing organism. A 74-kbp candidate BGC encoding the multimodular enzymatic machinery (hybrid type I-trans-AT polyketide synthase-nonribosomal peptide synthetase and tailoring functional domains) was identified and found to harbor key features predicted as necessary for palmerolide A biosynthesis. Surveys of ascidian microbiome samples targeting the candidate BGC revealed a high correlation between palmerolide gene targets and a single 16S rRNA gene variant (R = 0.83 to 0.99). Through repeated rounds of metagenome sequencing followed by binning contigs into metagenome-assembled genomes, we were able to retrieve a nearly complete genome (10 contigs) of the BGC-producing organism, a novel verrucomicrobium within the Opitutaceae family that we propose here as “Candidatus Synoicihabitans palmerolidicus.” The refined genome assembly harbors five highly similar BGC copies, along with structural and functional features that shed light on the host-associated nature of this unique bacterium.

IMPORTANCE Palmerolide A has potential as a chemotherapeutic agent to target melanoma. We interrogated the microbiome of the Antarctic ascidian, Synoicum adareanum, using a cultivation-independent high-throughput sequencing and bioinformatic strategy. The metagenome-encoded biosynthetic machinery predicted to produce palmerolide A was found to be associated with the genome of a member of the S. adareanum core microbiome. Phylogenomic analysis suggests the organism represents a new deeply branching genus, “Candidatus Synoicihabitans palmerolidicus,” in the Opitutaceae family of the Verrucomicrobia phylum. The Ca. Synoicihabitans palmerolidicus 4.29-Mb genome encodes a repertoire of carbohydrate-utilizing and transport pathways, a chemotaxis system, flagellar biosynthetic capacity, and other regulatory elements enabling its ascidian-associated lifestyle. The palmerolide producer’s genome also contains five distinct copies of the large palmerolide biosynthetic gene cluster that may provide structural complexity of palmerolide variants.

Metatranscriptomic Analysis of Bacterial Communities on Laundered Textiles: A Pilot Case Study

Microbially contaminated washing machines and mild laundering conditions facilitate the survival and growth of microorganisms on laundry, promoting undesired side effects such as malodor formation. Clearly, a deeper understanding of the functionality and hygienic relevance of the laundry microbiota necessitates the analysis of the microbial gene expression on textiles after washing, which—to the best of our knowledge—has not been performed before. In this pilot case study, we used single-end RNA sequencing to generate de novo transcriptomes of the bacterial communities remaining on polyester and cotton fabrics washed in a domestic washing machine in mild conditions and subsequently incubated under moist conditions for 72 h. Two common de novo transcriptome assemblers were used. The final assemblies included 22,321 Trinity isoforms and 12,600 Spades isoforms. A large part of these isoforms could be assigned to the SwissProt database, and was further categorized into “molecular function”, “biological process” and “cellular component” using Gene Ontology (GO) terms. In addition, differential gene expression was used to show the difference in the pairwise comparison of the two tissue types. When comparing the assemblies generated with the two assemblers, the annotation results were relatively similar. However, there were clear differences between the de novo assemblies regarding differential gene expression.

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing ¹³C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most ¹³C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed ¹³C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and ¹³C labeling (i.e., partial labeling or labeling at later stages). Major ¹³C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.

Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses

Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field.

Terabase-scale metagenome coassembly with MetaHipMer

Metagenome sequence datasets can contain terabytes of reads, too many to be coassembled together on a single shared-memory computer; consequently, they have only been assembled sample by sample (multiassembly) and combining the results is challenging. We can now perform coassembly of the largest datasets using MetaHipMer, a metagenome assembler designed to run on supercomputers and large clusters of compute nodes. We have reported on the implementation of MetaHipMer previously; in this paper we focus on analyzing the impact of very large coassembly. In particular, we show that coassembly recovers a larger genome fraction than multiassembly and enables the discovery of more complete genomes, with lower error rates, whereas multiassembly recovers more dominant strain variation. Being able to coassemble a large dataset does not preclude one from multiassembly; rather, having a fast, scalable metagenome assembler enables a user to more easily perform coassembly and multiassembly, and assemble both abundant, high strain variation genomes, and low-abundance, rare genomes. We present several assemblies of terabyte datasets that could never be coassembled before, demonstrating MetaHipMer’s scaling power. MetaHipMer is available for public use under an open source license and all datasets used in the paper are available for public download.

Assessment of metagenomic assemblers based on hybrid reads of real and simulated metagenomic sequences

In metagenomic studies of microbial communities, the short reads come from mixtures of genomes. Read assembly is usually an essential first step for the follow-up studies in metagenomic research. Understanding the power and limitations of various read assembly programs in practice is important for researchers to choose which programs to use in their investigations. Many studies evaluating different assembly programs used either simulated metagenomes or real metagenomes with unknown genome compositions. However, the simulated datasets may not reflect the real complexities of metagenomic samples and the estimated assembly accuracy could be misleading due to the unknown genomes in real metagenomes. Therefore, hybrid strategies are required to evaluate the various read assemblers for metagenomic studies. In this paper, we benchmark the metagenomic read assemblers by mixing reads from real metagenomic datasets with reads from known genomes and evaluating the integrity, contiguity and accuracy of the assembly using the reads from the known genomes. We selected four advanced metagenome assemblers, MEGAHIT, MetaSPAdes, IDBA-UD and Faucet, for evaluation. We showed the strengths and weaknesses of these assemblers in terms of integrity, contiguity and accuracy for different variables, including the genetic difference of the real genomes with the genome sequences in the real metagenomic datasets and the sequencing depth of the simulated datasets. Overall, MetaSPAdes performs best in terms of integrity and continuity at the species-level, followed by MEGAHIT. Faucet performs best in terms of accuracy at the cost of worst integrity and continuity, especially at low sequencing depth. MEGAHIT has the highest genome fractions at the strain-level and MetaSPAdes has the overall best performance at the strain-level. MEGAHIT is the most efficient in our experiments. Availability: The source code is available at https://github.com/ziyewang/MetaAssemblyEval.

Enteric Virome and Carcinogenesis in the Gut

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in both the USA and the world. Recent research has demonstrated the involvement of the gut microbiota in CRC development and progression. Microbial biomarkers of disease have focused primarily on the bacterial component of the microbiome; however, the viral portion of the microbiome, consisting of both bacteriophages and eukaryotic viruses, together known as the virome, has been lesser studied. Here we review the recent advancements in high-throughput sequencing (HTS) technologies and bioinformatics, which have enabled scientists to better understand how viruses might influence the development of colorectal cancer. We discuss the contemporary findings revealing modulations in the virome and their correlation with CRC development and progression. While a variety of challenges still face viral HTS detection in clinical specimens, we consider herein numerous next steps for future basic and clinical research. Clinicians need to move away from a single infectious agent model for disease etiology by grasping new, more encompassing etiological paradigms, in which communities of various microbial components interact with each other and the host. The reporting and indexing of patient health information, socioeconomic data, and other relevant metadata will enable identification of predictive variables and covariates of viral presence and CRC development. Altogether, the virome has a more profound role in carcinogenesis and cancer progression than once thought, and viruses, specific for either human cells or bacteria, are clinically relevant in understanding CRC pathology, patient prognosis, and treatment development.

Functional screening of a soil metagenome for DNA endonucleases by acquired resistance to bacteriophage infection

Endonucleases play a crucial role as reagents in laboratory research and diagnostics. Here, metagenomics was used to functionally screen a fosmid library for endonucleases. A fosmid library was constructed using metagenomic DNA isolated from soil sampled from the unique environment of the Kogelberg Nature Reserve in the Western Cape of South Africa. The principle of acquired immunity against phage infection was used to develop a plate-based screening technique for the isolation of restriction endonucleases from the library. Using next-generation sequencing and bioinformatics tools, sequence data were generated and analysed, revealing 113 novel open reading frames (ORFs) encoding putative endonuclease genes and ORFs of unknown identity and function. One endonuclease designated Endo52 was selected from the putative endonuclease ORFs and was recombinantly produced in Escherichia coli Rosetta™ (DE3) pLysS. Endo52 was purified by immobilised metal affinity chromatography and yielded 0.437 g per litre of cultivation volume. Its enzyme activity was monitored by cleaving lambda DNA and pUC19 plasmid as substrates, and it demonstrated non-specific endonuclease activity. In addition to endonuclease-like genes, the screen identified several unknown genes. These could present new phage resistance mechanisms and are an opportunity for future investigations.

Wetland Sediments Host Diverse Microbial Taxa Capable of Cycling Alcohols

Understanding patterns of organic matter degradation in wetlands is essential for identifying the substrates and mechanisms supporting greenhouse gas production and emissions from wetlands, the main natural source of methane in the atmosphere. Alcohols are common fermentation products but are poorly studied as key intermediates in organic matter degradation in wetlands. By investigating genes, pathways, and microorganisms potentially accounting for the high concentrations of ethanol and isopropanol measured in Prairie Pothole wetland sediments, this work advanced our understanding of alcohol fermentations in wetlands linked to extremely high greenhouse gas emissions. Moreover, the novel alcohol dehydrogenases and microbial taxa potentially involved in alcohol metabolism may serve biotechnological efforts in bioengineering commercially valuable alcohol production and in the discovery of novel isopropanol producers or isopropanol fermentation pathways.

Alcohols are commonly derived from the degradation of organic matter and yet are rarely measured in environmental samples. Wetlands in the Prairie Pothole Region (PPR) support extremely high methane emissions and the highest sulfate reduction rates reported to date, likely contributing to a significant proportion of organic matter mineralization in this system. While ethanol and isopropanol concentrations up to 4 to 5 mM in PPR wetland pore fluids have been implicated in sustaining these high rates of microbial activity, the mechanisms that support alcohol cycling in this ecosystem are poorly understood. We leveraged metagenomic and transcriptomic tools to identify genes, pathways, and microorganisms potentially accounting for alcohol cycling in PPR wetlands. Phylogenetic analyses revealed diverse alcohol dehydrogenases and putative substrates. Alcohol dehydrogenase and aldehyde dehydrogenase genes were included in 62 metagenome-assembled genomes (MAGs) affiliated with 16 phyla. The most frequently encoded pathway (in 30 MAGs) potentially accounting for alcohol production was a Pyrococcus furiosus-like fermentation which can involve pyruvate:ferredoxin oxidoreductase (PFOR). Transcripts for 93 of 137 PFOR genes in these MAGs were detected, as well as for 158 of 243 alcohol dehydrogenase genes retrieved from these same MAGs. Mixed acid fermentation and heterofermentative lactate fermentation were also frequently encoded. Finally, we identified 19 novel putative isopropanol dehydrogenases in 15 MAGs affiliated with Proteobacteria, Acidobacteria, Chloroflexi, Planctomycetes, Ignavibacteriae, Thaumarchaeota, and the candidate divisions KSB1 and Rokubacteria. We conclude that diverse microorganisms may use uncommon and potentially novel pathways to produce ethanol and isopropanol in PPR wetland sediments.

IMPORTANCE Understanding patterns of organic matter degradation in wetlands is essential for identifying the substrates and mechanisms supporting greenhouse gas production and emissions from wetlands, the main natural source of methane in the atmosphere. Alcohols are common fermentation products but are poorly studied as key intermediates in organic matter degradation in wetlands. By investigating genes, pathways, and microorganisms potentially accounting for the high concentrations of ethanol and isopropanol measured in Prairie Pothole wetland sediments, this work advanced our understanding of alcohol fermentations in wetlands linked to extremely high greenhouse gas emissions. Moreover, the novel alcohol dehydrogenases and microbial taxa potentially involved in alcohol metabolism may serve biotechnological efforts in bioengineering commercially valuable alcohol production and in the discovery of novel isopropanol producers or isopropanol fermentation pathways.

Viral and metabolic controls on high rates of microbial sulfur and carbon cycling in wetland ecosystems

BACKGROUND

Microorganisms drive high rates of methanogenesis and carbon mineralization in wetland ecosystems. These signals are especially pronounced in the Prairie Pothole Region of North America, the tenth largest wetland ecosystem in the world. Sulfate reduction rates up to 22 μmol cm-3 day-1 have been measured in these wetland sediments, as well as methane fluxes up to 160 mg m-2 h-1-some of the highest emissions ever measured in North American wetlands. While pore waters from PPR wetlands are characterized by high concentrations of sulfur species and dissolved organic carbon, the constraints on microbial activity are poorly understood. Here, we utilized metagenomics to investigate candidate sulfate reducers and methanogens in this ecosystem and identify metabolic and viral controls on microbial activity.

RESULTS

We recovered 162 dsrA and 206 dsrD sequences from 18 sediment metagenomes and reconstructed 24 candidate sulfate reducer genomes assigned to seven phyla. These genomes encoded the potential for utilizing a wide variety of electron donors, such as methanol and other alcohols, methylamines, and glycine betaine. We also identified 37 mcrA sequences spanning five orders and recovered two putative methanogen genomes representing the most abundant taxa-Methanosaeta and Methanoregulaceae. However, given the abundance of Methanofollis-affiliated mcrA sequences, the detection of F420-dependent alcohol dehydrogenases, and millimolar concentrations of ethanol and 2-propanol in sediment pore fluids, we hypothesize that these alcohols may drive a significant fraction of methanogenesis in this ecosystem. Finally, extensive viral novelty was detected, with approximately 80% of viral populations being unclassified at any known taxonomic levels and absent from publicly available databases. Many of these viral populations were predicted to target dominant sulfate reducers and methanogens.

CONCLUSIONS

Our results indicate that diversity is likely key to extremely high rates of methanogenesis and sulfate reduction observed in these wetlands. The inferred genomic diversity and metabolic versatility could result from dynamic environmental conditions, viral infections, and niche differentiation in the heterogeneous sediment matrix. These processes likely play an important role in modulating carbon and sulfur cycling in this ecosystem.

Using metagenomics to investigate human and environmental resistomes

Antibiotic resistance is a global health concern declared by the WHO as one of the largest threats to modern healthcare. In recent years, metagenomic DNA sequencing has started to be applied as a tool to study antibiotic resistance in different environments, including the human microbiota. However, a multitude of methods exist for metagenomic data analysis, and not all methods are suitable for the investigation of resistance genes, particularly if the desired outcome is an assessment of risks to human health. In this review, we outline the current state of methods for sequence handling, mapping to databases of resistance genes, statistical analysis and metagenomic assembly. In addition, we provide an overview of important considerations related to the analysis of resistance genes, and recommend some of the currently used tools and methods that are best equipped to inform research and clinical practice related to antibiotic resistance.

Overview of Virus Metagenomic Classification Methods and Their Biological Applications

Metagenomics poses opportunities for clinical and public health virology applications by offering a way to assess complete taxonomic composition of a clinical sample in an unbiased way. However, the techniques required are complicated and analysis standards have yet to develop. This, together with the wealth of different tools and workflows that have been proposed, poses a barrier for new users. We evaluated 49 published computational classification workflows for virus metagenomics in a literature review. To this end, we described the methods of existing workflows by breaking them up into five general steps and assessed their ease-of-use and validation experiments. Performance scores of previous benchmarks were summarized and correlations between methods and performance were investigated. We indicate the potential suitability of the different workflows for (1) time-constrained diagnostics, (2) surveillance and outbreak source tracing, (3) detection of remote homologies (discovery), and (4) biodiversity studies. We provide two decision trees for virologists to help select a workflow for medical or biodiversity studies, as well as directions for future developments in clinical viral metagenomics.

Analysis of Vibrio seventh pandemic island II and novel genomic islands in relation to attachment sequences among a wide variety of Vibrio cholerae strains

Vibrio cholerae O1 El Tor, the pathogen responsible for the current cholera pandemic, became pathogenic by acquiring virulent factors including Vibrio seventh pandemic islands (VSP)‐I and −II. Diversity of VSP‐II is well recognized; however, studies addressing attachment sequence left (attL) sequences of VSP‐II are few. In this report, a wide variety of V. cholerae strains were analyzed for the structure and distribution of VSP‐II in relation to their attachment sequences. Of 188 V. cholerae strains analyzed, 81% (153/188) strains carried VSP‐II; of these, typical VSP‐II, and a short variant was found in 36% (55/153), and 63% (96/153), respectively. A novel VSP‐II was found in two V. cholerae non‐O1/non‐O139 strains. In addition to the typical 14‐bp attL, six new attL‐like sequences were identified. The 14‐bp attL was associated with VSP‐II in 91% (139/153), whereas the remaining six types were found in 9.2% (14/153) of V. cholerae strains. Of note, six distinct types of the attL‐like sequence were found in the seventh pandemic wave 1 strains; however, only one or two types were found in the wave 2 or 3 strains. Interestingly, 86% (24/28) of V. cholerae seventh pandemic strains harboring a 13‐bp attL‐like sequence were devoid of VSP‐II. Six novel genomic islands using two unique insertion sites to those of VSP‐II were identified in 11 V. cholerae strains in this study. Four of those shared similar gene clusters with VSP‐II, except integrase gene.

ICoVeR - an interactive visualization tool for verification and refinement of metagenomic bins

Background

Recent advances in high-throughput sequencing allow for much deeper exploitation of natural and engineered microbial communities, and to unravel so-called “microbial dark matter” (microbes that until now have evaded cultivation). Metagenomic analyses result in a large number of genomic fragments (contigs) that need to be grouped (binned) in order to reconstruct draft microbial genomes. While several contig binning algorithms have been developed in the past 2 years, they often lack consensus. Furthermore, these software tools typically lack a provision for the visualization of data and bin characteristics.

Results

We present ICoVeR, the Interactive Contig-bin Verification and Refinement tool, which allows the visualization of genome bins. More specifically, ICoVeR allows curation of bin assignments based on multiple binning algorithms. Its visualization window is composed of two connected and interactive main views, including a parallel coordinates view and a dimensionality reduction plot. To demonstrate ICoVeR’s utility, we used it to refine disparate genome bins automatically generated using MetaBAT, CONCOCT and MyCC for an anaerobic digestion metagenomic (AD microbiome) dataset. Out of 31 refined genome bins, 23 were characterized with higher completeness and lower contamination in comparison to their respective, automatically generated, genome bins. Additionally, to benchmark ICoVeR against a previously validated dataset, we used Sharon’s dataset representing an infant gut metagenome.

Conclusions

ICoVeR is an open source software package that allows curation of disparate genome bins generated with automatic binning algorithms. It is freely available under the GPLv3 license at https://git.list.lu/eScience/ICoVeR. The data management and analytical functions of ICoVeR are implemented in R, therefore the software can be easily installed on any system for which R is available. Installation and usage guide together with the example files ready to be visualized are also provided via the project wiki. ICoVeR running instance preloaded with AD microbiome and Sharon’s datasets can be accessed via the website.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1653-5) contains supplementary material, which is available to authorized users.

Genome of a giant bacteriophage from a decaying Trichodesmium bloom

De-novo assembly of a metagenomic dataset obtained from a decaying cyanobacterial Trichodesmium bloom from the New Caledonian lagoon resulted in a complete giant phage genome of 257,908bp, obtained independently with multiple assembly tools. Noteworthy, gammaproteobacteria were an abundant fraction in the sequenced samples. Mapping of the raw reads with 99% accuracy to the giant phage genome resulted in an average coverage of 262X. The closest sequenced relatives, albeit still distant, are the Pseudomonas phages PaBG from Lake Baikal and Lu11 isolated from a soil sample from the Philippines. The phage reported here might belong to the same family within the Myoviridae as PaBG and Lu11 and would thus be its first marine member, indicating a more widespread occurrence of this group. We named this phage NCTB (New Caledonia Trichodesmium Bloom) after its origin.

Metagenomics and CAZyme Discovery

Microorganisms play a primary role in regulating biogeochemical cycles and are a valuable source of enzymes that have biotechnological applications, such as carbohydrate-active enzymes (CAZymes). However, the inability to culture the majority of microorganisms that exist in natural ecosystems using common culture-dependent techniques restricts access to potentially novel cellulolytic bacteria and beneficial enzymes. The development of molecular-based culture-independent methods such as metagenomics enables researchers to study microbial communities directly from environmental samples, and presents a platform from which enzymes of interest can be sourced. We outline key methodological stages that are required as well as describe specific protocols that are currently used for metagenomic projects dedicated to CAZyme discovery.

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

The gastrointestinal microbiome is a complex ecosystem with functions that shape human health. Studying the relationship between taxonomic alterations and functional repercussions linked to disease remains challenging. Here, we present an integrative approach to resolve the taxonomic and functional attributes of gastrointestinal microbiota at the metagenomic, metatranscriptomic and metaproteomic levels. We apply our methods to samples from four families with multiple cases of type 1 diabetes mellitus (T1DM). Analysis of intra- and inter-individual variation demonstrates that family membership has a pronounced effect on the structural and functional composition of the gastrointestinal microbiome. In the context of T1DM, consistent taxonomic differences were absent across families, but certain human exocrine pancreatic proteins were found at lower levels. The associated microbial functional signatures were linked to metabolic traits in distinct taxa. The methodologies and results provide a foundation for future large-scale integrated multi-omic analyses of the gastrointestinal microbiome in the context of host-microbe interactions in human health and disease.

Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data

DNA assembly is a core methodological step in metagenomic pipelines used to study the structure and function within microbial communities. Here we investigate the utility of Pacific Biosciences long and high accuracy circular consensus sequencing (CCS) reads for metagenomic projects. We compared the application and performance of both PacBio CCS and Illumina HiSeq data with assembly and taxonomic binning algorithms using metagenomic samples representing a complex microbial community. Eight SMRT cells produced approximately 94 Mb of CCS reads from a biogas reactor microbiome sample that averaged 1319 nt in length and 99.7% accuracy. CCS data assembly generated a comparative number of large contigs greater than 1 kb, to those assembled from a ~190x larger HiSeq dataset (~18 Gb) produced from the same sample (i.e approximately 62% of total contigs). Hybrid assemblies using PacBio CCS and HiSeq contigs produced improvements in assembly statistics, including an increase in the average contig length and number of large contigs. The incorporation of CCS data produced significant enhancements in taxonomic binning and genome reconstruction of two dominant phylotypes, which assembled and binned poorly using HiSeq data alone. Collectively these results illustrate the value of PacBio CCS reads in certain metagenomics applications.

Recovering complete and draft population genomes from metagenome datasets

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem of chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.

Metagenomic investigation of the geologically unique Hellenic Volcanic Arc reveals a distinctive ecosystem with unexpected physiology

Hydrothermal vents represent a deep, hot, aphotic biosphere where chemosynthetic primary producers, fuelled by chemicals from Earth's subsurface, form the basis of life. In this study, we examined microbial mats from two distinct volcanic sites within the Hellenic Volcanic Arc (HVA). The HVA is geologically and ecologically unique, with reported emissions of CO2 -saturated fluids at temperatures up to 220°C and a notable absence of macrofauna. Metagenomic data reveals highly complex prokaryotic communities composed of chemolithoautotrophs, some methanotrophs, and to our surprise, heterotrophs capable of anaerobic degradation of aromatic hydrocarbons. Our data suggest that aromatic hydrocarbons may indeed be a significant source of carbon in these sites, and instigate additional research into the nature and origin of these compounds in the HVA. Novel physiology was assigned to several uncultured prokaryotic lineages; most notably, a SAR406 representative is attributed with a role in anaerobic hydrocarbon degradation. This dataset, the largest to date from submarine volcanic ecosystems, constitutes a significant resource of novel genes and pathways with potential biotechnological applications.

First Complete Genome Sequence of Felis catus Gammaherpesvirus 1

We sequenced the complete genome of Felis catus gammaherpesvirus 1 (FcaGHV1) from lymph node DNA of an infected cat. The genome includes a 121,556-nucleotide unique region with 87 predicted open reading frames (61 gammaherpesvirus conserved and 26 unique) flanked by multiple copies of a 966-nucleotide terminal repeat.

Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community

BACKGROUND

The rapid development of sequencing technologies has provided access to environments that were either once thought inhospitable to life altogether or that contain too few cells to be analyzed using genomics approaches. While 16S rRNA gene microbial community sequencing has revolutionized our understanding of community composition and diversity over time and space, it only provides a crude estimate of microbial functional and metabolic potential. Alternatively, shotgun metagenomics allows comprehensive sampling of all genetic material in an environment, without any underlying primer biases. Until recently, one of the major bottlenecks of shotgun metagenomics has been the requirement for large initial DNA template quantities during library preparation.

RESULTS

Here, we investigate the effects of varying template concentrations across three low biomass library preparation protocols on their ability to accurately reconstruct a mock microbial community of known composition. We analyze the effects of input DNA quantity and library preparation method on library insert size, GC content, community composition, assembly quality and metagenomic binning. We found that library preparation method and the amount of starting material had significant impacts on the mock community metagenomes. In particular, GC content shifted towards more GC rich sequences at the lower input quantities regardless of library prep method, the number of low quality reads that could not be mapped to the reference genomes increased with decreasing input quantities, and the different library preparation methods had an impact on overall metagenomic community composition.

CONCLUSIONS

This benchmark study provides recommendations for library creation of representative and minimally biased metagenome shotgun sequencing, enabling insights into functional attributes of low biomass ecosystem microbial communities.

InteMAP: Integrated metagenomic assembly pipeline for NGS short reads

Background

Next-generation sequencing (NGS) has greatly facilitated metagenomic analysis but also raised new challenges for metagenomic DNA sequence assembly, owing to its high-throughput nature and extremely short reads generated by sequencers such as Illumina. To date, how to generate a high-quality draft assembly for metagenomic sequencing projects has not been fully addressed.

Results

We conducted a comprehensive assessment on state-of-the-art de novo assemblers and revealed that the performance of each assembler depends critically on the sequencing depth. To address this problem, we developed a pipeline named InteMAP to integrate three assemblers, ABySS, IDBA-UD and CABOG, which were found to complement each other in assembling metagenomic sequences. Making a decision of which assembling approaches to use according to the sequencing coverage estimation algorithm for each short read, the pipeline presents an automatic platform suitable to assemble real metagenomic NGS data with uneven coverage distribution of sequencing depth. By comparing the performance of InteMAP with current assemblers on both synthetic and real NGS metagenomic data, we demonstrated that InteMAP achieves better performance with a longer total contig length and higher contiguity, and contains more genes than others.

Conclusions

We developed a de novo pipeline, named InteMAP, that integrates existing tools for metagenomics assembly. The pipeline outperforms previous assembly methods on metagenomic assembly by providing a longer total contig length, a higher contiguity and covering more genes. InteMAP, therefore, could potentially be a useful tool for the research community of metagenomics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0686-x) contains supplementary material, which is available to authorized users.

Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions

Wetland restoration on peat islands previously drained for agriculture has potential to reverse land subsidence and sequester atmospheric carbon dioxide as peat accretes. However, the emission of methane could potentially offset the greenhouse gas benefits of captured carbon. As microbial communities play a key role in governing wetland greenhouse gas fluxes, we are interested in how microbial community composition and functions are associated with wetland hydrology, biogeochemistry, and methane emission, which is critical to modeling the microbial component in wetland methane fluxes and to managing restoration projects for maximal carbon sequestration. Here, we couple sequence-based methods with biogeochemical and greenhouse gas measurements to interrogate microbial communities from a pilot-scale restored wetland in the Sacramento-San Joaquin Delta of California, revealing considerable spatial heterogeneity even within this relatively small site. A number of microbial populations and functions showed strong correlations with electron acceptor availability and methane production; some also showed a preference for association with plant roots. Marker gene phylogenies revealed a diversity of major methane-producing and -consuming populations and suggested novel diversity within methanotrophs. Methanogenic archaea were observed in all samples, as were nitrate-, sulfate-, and metal-reducing bacteria, indicating that no single terminal electron acceptor was preferred despite differences in energetic favorability and suggesting spatial microheterogeneity and microniches. Notably, methanogens were negatively correlated with nitrate-, sulfate-, and metal-reducing bacteria and were most abundant at sampling sites with high peat accretion and low electron acceptor availability, where methane production was highest.

IMPORTANCE

Wetlands are the largest nonanthropogenic source of atmospheric methane but also a key global carbon reservoir. Characterizing belowground microbial communities that mediate carbon cycling in wetlands is critical to accurately predicting their responses to changes in land management and climate. Here, we studied a restored wetland and revealed substantial spatial heterogeneity in biogeochemistry, methane production, and microbial communities, largely associated with the wetland hydraulic design. We observed patterns in microbial community composition and functions correlated with biogeochemistry and methane production, including diverse microorganisms involved in methane production and consumption. We found that methanogenesis gene abundance is inversely correlated with genes from pathways exploiting other electron acceptors, yet the ubiquitous presence of genes from all these pathways suggests that diverse electron acceptors contribute to the energetic balance of the ecosystem. These investigations represent an important step toward effective management of wetlands to reduce methane flux to the atmosphere and enhance belowground carbon storage.