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Asset Tag: Metagenomics

April 21, 2020

Improving the sensitivity of long read overlap detection using grouped short k-mer matches.

Single-molecule, real-time sequencing (SMRT) developed by Pacific BioSciences produces longer reads than second-generation sequencing technologies such as Illumina. The increased read length enables PacBio sequencing to close gaps in genome assembly, reveal structural variations, and characterize the intra-species variations. It also holds the promise to decipher the community structure in complex microbial communities because long reads help metagenomic assembly. One key step in genome assembly using long reads is to quickly identify reads forming overlaps. Because PacBio data has higher sequencing error rate and lower coverage than popular short read sequencing technologies (such as Illumina), efficient detection of true overlaps requires specially designed algorithms. In particular, there is still a need to improve the sensitivity of detecting small overlaps or overlaps with high error rates in both reads. Addressing this need will enable better assembly for metagenomic data produced by third-generation sequencing technologies.In this work, we designed and implemented an overlap detection program named GroupK, for third-generation sequencing reads based on grouped k-mer hits. While using k-mer hits for detecting reads’ overlaps has been adopted by several existing programs, our method uses a group of short k-mer hits satisfying statistically derived distance constraints to increase the sensitivity of small overlap detection. Grouped k-mer hit was originally designed for homology search. We are the first to apply group hit for long read overlap detection. The experimental results of applying our pipeline to both simulated and real third-generation sequencing data showed that GroupK enables more sensitive overlap detection, especially for datasets of low sequencing coverage.GroupK is best used for detecting small overlaps for third-generation sequencing data. It provides a useful supplementary tool to existing ones for more sensitive and accurate overlap detection. The source code is freely available at https://github.com/Strideradu/GroupK .

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April 21, 2020

Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community.

DNA methylation plays important roles in prokaryotes, and their genomic landscapes-prokaryotic epigenomes-have recently begun to be disclosed. However, our knowledge of prokaryotic methylation systems is focused on those of culturable microbes, which are rare in nature. Here, we used single-molecule real-time and circular consensus sequencing techniques to reveal the ‘metaepigenomes’ of a microbial community in the largest lake in Japan, Lake Biwa. We reconstructed 19 draft genomes from diverse bacterial and archaeal groups, most of which are yet to be cultured. The analysis of DNA chemical modifications in those genomes revealed 22 methylated motifs, nine of which were novel. We identified methyltransferase genes likely responsible for methylation of the novel motifs, and confirmed the catalytic specificities of four of them via transformation experiments using synthetic genes. Our study highlights metaepigenomics as a powerful approach for identification of the vast unexplored variety of prokaryotic DNA methylation systems in nature.

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April 21, 2020

Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation.

We describe a method that adds long-read sequencing to a mix of technologies used to assemble a highly complex cattle rumen microbial community, and provide a comparison to short read-based methods. Long-read alignments and Hi-C linkage between contigs support the identification of 188 novel virus-host associations and the determination of phage life cycle states in the rumen microbial community. The long-read assembly also identifies 94 antimicrobial resistance genes, compared to only seven alleles in the short-read assembly. We demonstrate novel techniques that work synergistically to improve characterization of biological features in a highly complex rumen microbial community.

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April 21, 2020

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.

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.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.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.

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April 21, 2020

CAMISIM: simulating metagenomes and microbial communities.

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required.We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM.CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.

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October 23, 2019

High resolution profiling of coral-associated bacterial communities using full-length 16S rRNA sequence data from PacBio SMRT sequencing system.

Coral reefs are a complex ecosystem consisting of coral animals and a vast array of associated symbionts including the dinoflagellate Symbiodinium, fungi, viruses and bacteria. Several studies have highlighted the importance of coral-associated bacteria and their fundamental roles in fitness and survival of the host animal. The scleractinian coral Porites lutea is one of the dominant reef-builders in the Indo-West Pacific. Currently, very little is known about the composition and structure of bacterial communities across P. lutea reefs. The purpose of this study is twofold: to demonstrate the advantages of using PacBio circular consensus sequencing technology in microbial community studies and to investigate the diversity and structure of P. lutea-associated microbiome in the Indo-Pacific. This is the first metagenomic study of marine environmental samples that utilises the PacBio sequencing system to capture full-length 16S rRNA sequences. We observed geographically distinct coral-associated microbial profiles between samples from the Gulf of Thailand and Andaman Sea. Despite the geographical and environmental impacts on the coral-host interactions, we identified a conserved community of bacteria that were present consistently across diverse reef habitats. Finally, we demonstrated the superior performance of full-length 16S rRNA sequences in resolving taxonomic uncertainty of coral associates at the species level.

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September 22, 2019

Detecting epigenetic motifs in low coverage and metagenomics settings.

It has recently become possible to rapidly and accurately detect epigenetic signatures in bacterial genomes using third generation sequencing data. Monitoring the speed at which a single polymerase inserts a base in the read strand enables one to infer whether a modification is present at that specific site on the template strand. These sites can be challenging to detect in the absence of high coverage and reliable reference genomes.Here we provide a new method for detecting epigenetic motifs in bacteria on datasets with low-coverage, with incomplete references, and with mixed samples (i.e. metagenomic data). Our approach treats motif inference as a kmer comparison problem. First, genomes (or contigs) are deconstructed into kmers. Then, native genome-wide distributions of interpulse durations (IPDs) for kmers are compared with corresponding whole genome amplified (WGA, modification free) IPD distributions using log likelihood ratios. Finally, kmers are ranked and greedily selected by iteratively correcting for sequences within a particular kmer’s neighborhood.Our method can detect multiple types of modifications, even at very low-coverage and in the presence of mixed genomes. Additionally, we are able to predict modified motifs when genomes with “neighbor” modified motifs exist within the sample. Lastly, we show that these motifs can provide an alternative source of information by which to cluster metagenomics contigs and that iterative refinement on these clustered contigs can further improve both sensitivity and specificity of motif detection.https://github.com/alibashir/EMMCKmer.

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September 22, 2019

An environmental bacterial taxon with a large and distinct metabolic repertoire.

Cultivated bacteria such as actinomycetes are a highly useful source of biomedically important natural products. However, such ‘talented’ producers represent only a minute fraction of the entire, mostly uncultivated, prokaryotic diversity. The uncultured majority is generally perceived as a large, untapped resource of new drug candidates, but so far it is unknown whether taxa containing talented bacteria indeed exist. Here we report the single-cell- and metagenomics-based discovery of such producers. Two phylotypes of the candidate genus ‘Entotheonella’ with genomes of greater than 9 megabases and multiple, distinct biosynthetic gene clusters co-inhabit the chemically and microbially rich marine sponge Theonella swinhoei. Almost all bioactive polyketides and peptides known from this animal were attributed to a single phylotype. ‘Entotheonella’ spp. are widely distributed in sponges and belong to an environmental taxon proposed here as candidate phylum ‘Tectomicrobia’. The pronounced bioactivities and chemical uniqueness of ‘Entotheonella’ compounds provide significant opportunities for ecological studies and drug discovery.

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September 22, 2019

Novel syntrophic populations dominate an ammonia-tolerant methanogenic microbiome.

Biogas reactors operating with protein-rich substrates have high methane potential and industrial value; however, they are highly susceptible to process failure because of the accumulation of ammonia. High ammonia levels cause a decline in acetate-utilizing methanogens and instead promote the conversion of acetate via a two-step mechanism involving syntrophic acetate oxidation (SAO) to H2 and CO2, followed by hydrogenotrophic methanogenesis. Despite the key role of syntrophic acetate-oxidizing bacteria (SAOB), only a few culturable representatives have been characterized. Here we show that the microbiome of a commercial, ammonia-tolerant biogas reactor harbors a deeply branched, uncultured phylotype (unFirm_1) accounting for approximately 5% of the 16S rRNA gene inventory and sharing 88% 16S rRNA gene identity with its closest characterized relative. Reconstructed genome and quantitative metaproteomic analyses imply unFirm_1’s metabolic dominance and SAO capabilities, whereby the key enzymes required for acetate oxidation are among the most highly detected in the reactor microbiome. While culturable SAOB were identified in genomic analyses of the reactor, their limited proteomic representation suggests that unFirm_1 plays an important role in channeling acetate toward methane. Notably, unFirm_1-like populations were found in other high-ammonia biogas installations, conjecturing a broader importance for this novel clade of SAOB in anaerobic fermentations. IMPORTANCE The microbial production of methane or “biogas” is an attractive renewable energy technology that can recycle organic waste into biofuel. Biogas reactors operating with protein-rich substrates such as household municipal or agricultural wastes have significant industrial and societal value; however, they are highly unstable and frequently collapse due to the accumulation of ammonia. We report the discovery of a novel uncultured phylotype (unFirm_1) that is highly detectable in metaproteomic data generated from an ammonia-tolerant commercial reactor. Importantly, unFirm_1 is proposed to perform a key metabolic step in biogas microbiomes, whereby it syntrophically oxidizes acetate to hydrogen and carbon dioxide, which methanogens then covert to methane. Only very few culturable syntrophic acetate-oxidizing bacteria have been described, and all were detected at low in situ levels compared to unFirm_1. Broader comparisons produced the hypothesis that unFirm_1 is a key mediator toward the successful long-term stable operation of biogas production using protein-rich substrates.

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September 22, 2019

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4).

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

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September 22, 2019

Is there foul play in the leaf pocket? The metagenome of floating fern Azolla reveals endophytes that do not fix N2 but may denitrify.

Dinitrogen fixation by Nostoc azollae residing in specialized leaf pockets supports prolific growth of the floating fern Azolla filiculoides. To evaluate contributions by further microorganisms, the A. filiculoides microbiome and nitrogen metabolism in bacteria persistently associated with Azolla ferns were characterized. A metagenomic approach was taken complemented by detection of N2 O released and nitrogen isotope determinations of fern biomass. Ribosomal RNA genes in sequenced DNA of natural ferns, their enriched leaf pockets and water filtrate from the surrounding ditch established that bacteria of A. filiculoides differed entirely from surrounding water and revealed species of the order Rhizobiales. Analyses of seven cultivated Azolla species confirmed persistent association with Rhizobiales. Two distinct nearly full-length Rhizobiales genomes were identified in leaf-pocket-enriched samples from ditch grown A. filiculoides. Their annotation revealed genes for denitrification but not N2 -fixation. 15 N2 incorporation was active in ferns with N. azollae but not in ferns without. N2 O was not detectably released from surface-sterilized ferns with the Rhizobiales. N2 -fixing N. azollae, we conclude, dominated the microbiome of Azolla ferns. The persistent but less abundant heterotrophic Rhizobiales bacteria possibly contributed to lowering O2 levels in leaf pockets but did not release detectable amounts of the strong greenhouse gas N2 O.© 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

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September 22, 2019

Draft genome sequence of Sulfurospirillum sp. strain MES, reconstructed from the metagenome of a microbial electrosynthesis system.

A draft genome of Sulfurospirillum sp. strain MES was isolated through taxonomic binning of a metagenome sequenced from a microbial electrosynthesis system (MES) actively producing acetate and hydrogen. The genome contains the nosZDFLY genes, which are involved in nitrous oxide reduction, suggesting the potential role of this strain in denitrification. Copyright © 2015 Ross et al.

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September 22, 2019

Advantages of genome sequencing by long-read sequencer using SMRT technology in medical area.

PacBio RS II is the first commercialized third-generation DNA sequencer able to sequence a single molecule DNA in real-time without amplification. PacBio RS II’s sequencing technology is novel and unique, enabling the direct observation of DNA synthesis by DNA polymerase. PacBio RS II confers four major advantages compared to other sequencing technologies: long read lengths, high consensus accuracy, a low degree of bias, and simultaneous capability of epigenetic characterization. These advantages surmount the obstacle of sequencing genomic regions such as high/low G+C, tandem repeat, and interspersed repeat regions. Moreover, PacBio RS II is ideal for whole genome sequencing, targeted sequencing, complex population analysis, RNA sequencing, and epigenetics characterization. With PacBio RS II, we have sequenced and analyzed the genomes of many species, from viruses to humans. Herein, we summarize and review some of our key genome sequencing projects, including full-length viral sequencing, complete bacterial genome and almost-complete plant genome assemblies, and long amplicon sequencing of a disease-associated gene region. We believe that PacBio RS II is not only an effective tool for use in the basic biological sciences but also in the medical/clinical setting.

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September 22, 2019

BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly.

The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools. BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

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September 22, 2019

Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation.

Shotgun metagenomics methods enable characterization of microbial communities in human microbiome and environmental samples. Assembly of metagenome sequences does not output whole genomes, so computational binning methods have been developed to cluster sequences into genome ‘bins’. These methods exploit sequence composition, species abundance, or chromosome organization but cannot fully distinguish closely related species and strains. We present a binning method that incorporates bacterial DNA methylation signatures, which are detected using single-molecule real-time sequencing. Our method takes advantage of these endogenous epigenetic barcodes to resolve individual reads and assembled contigs into species- and strain-level bins. We validate our method using synthetic and real microbiome sequences. In addition to genome binning, we show that our method links plasmids and other mobile genetic elements to their host species in a real microbiome sample. Incorporation of DNA methylation information into shotgun metagenomics analyses will complement existing methods to enable more accurate sequence binning.

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