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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.


September 22, 2019  |  

A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing.

RNA-sequencing (RNA-seq) enables in-depth exploration of transcriptomes, but typical sequencing depth often limits its comprehensiveness. In this study, we generated nearly 3 billion RNA-Seq reads, totaling 341 Gb of sequence, from a Zea mays seedling sample. At this depth, a near complete snapshot of the transcriptome was observed consisting of over 90% of the annotated transcripts, including lowly expressed transcription factors. A novel hybrid strategy combining de novo and reference-based assemblies yielded a transcriptome consisting of 126,708 transcripts with 88% of expressed known genes assembled to full-length. We improved current annotations by adding 4,842 previously unannotated transcript variants and many new features, including 212 maize transcripts, 201 genes, 10 genes with undocumented potential roles in seedlings as well as maize lineage specific gene fusion events. We demonstrated the power of deep sequencing for large transcriptome studies by generating a high quality transcriptome, which provides a rich resource for the research community.


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.


September 22, 2019  |  

Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.

Pan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.Analysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of >?90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.Our microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt ) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.


September 22, 2019  |  

Robust and effective methodologies for cryopreservation and DNA extraction from anaerobic gut fungi.

Cell storage and DNA isolation are essential to developing an expanded suite of microorganisms for biotechnology. However, many features of non-model microbes, such as an anaerobic lifestyle and rigid cell wall, present formidable challenges to creating strain repositories and extracting high quality genomic DNA. Here, we establish accessible, high efficiency, and robust techniques to store lignocellulolytic anaerobic gut fungi long term without specialized equipment. Using glycerol as a cryoprotectant, gut fungal isolates were preserved for a minimum of 23 months at -80 °C. Unlike previously reported approaches, this improved protocol is non-toxic and rapid, with samples surviving twice as long with negligible growth impact. Genomic DNA extraction for these isolates was optimized to yield samples compatible with next generation sequencing platforms (e.g. Illumina, PacBio). Popular DNA isolation kits and precipitation protocols yielded preps that were unsuitable for sequencing due to carbohydrate contaminants from the chitin-rich cell wall and extensive energy reserves of gut fungi. To address this, we identified a proprietary method optimized for hardy plant samples that rapidly yielded DNA fragments in excess of 10 kb with minimal RNA, protein or carbohydrate contamination. Collectively, these techniques serve as fundamental tools to manipulate powerful biomass-degrading gut fungi and improve their accessibility among researchers. Copyright © 2015 Elsevier Ltd. All rights reserved.


September 22, 2019  |  

ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies.

Researchers need general purpose methods for objectively evaluating the accuracy of single and metagenome assemblies and for automatically detecting any errors they may contain. Current methods do not fully meet this need because they require a reference, only consider one of the many aspects of assembly quality or lack statistical justification, and none are designed to evaluate metagenome assemblies.In this article, we present an Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences’ own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.ALE is released as open source software under the UoI/NCSA license at http://www.alescore.org. It is implemented in C and Python.


September 22, 2019  |  

Widespread polycistronic transcripts in fungi revealed by single-molecule mRNA sequencing.

Genes in prokaryotic genomes are often arranged into clusters and co-transcribed into polycistronic RNAs. Isolated examples of polycistronic RNAs were also reported in some higher eukaryotes but their presence was generally considered rare. Here we developed a long-read sequencing strategy to identify polycistronic transcripts in several mushroom forming fungal species including Plicaturopsis crispa, Phanerochaete chrysosporium, Trametes versicolor, and Gloeophyllum trabeum. We found genome-wide prevalence of polycistronic transcription in these Agaricomycetes, involving up to 8% of the transcribed genes. Unlike polycistronic mRNAs in prokaryotes, these co-transcribed genes are also independently transcribed. We show that polycistronic transcription may interfere with expression of the downstream tandem gene. Further comparative genomic analysis indicates that polycistronic transcription is conserved among a wide range of mushroom forming fungi. In summary, our study revealed, for the first time, the genome prevalence of polycistronic transcription in a phylogenetic range of higher fungi. Furthermore, we systematically show that our long-read sequencing approach and combined bioinformatics pipeline is a generic powerful tool for precise characterization of complex transcriptomes that enables identification of mRNA isoforms not recovered via short-read assembly.


September 22, 2019  |  

Single cell genomic study of Dehalococcoidetes species from deep-sea sediments of the Peruvian Margin.

The phylum Chloroflexi is one of the most frequently detected phyla in the subseafloor of the Pacific Ocean margins. Dehalogenating Chloroflexi (Dehalococcoidetes) was originally discovered as the key microorganisms mediating reductive dehalogenation via their key enzymes reductive dehalogenases (Rdh) as sole mode of energy conservation in terrestrial environments. The frequent detection of Dehalococcoidetes-related 16S rRNA and rdh genes in the marine subsurface implies a role for dissimilatory dehalorespiration in this environment; however, the two genes have never been linked to each other. To provide fundamental insights into the metabolism, genomic population structure and evolution of marine subsurface Dehalococcoidetes sp., we analyzed a non-contaminated deep-sea sediment core sample from the Peruvian Margin Ocean Drilling Program (ODP) site 1230, collected 7.3?m below the seafloor by a single cell genomic approach. We present for the first time single cell genomic data on three deep-sea Chloroflexi (Dsc) single cells from a marine subsurface environment. Two of the single cells were considered to be part of a local Dehalococcoidetes population and assembled together into a 1.38-Mb genome, which appears to be at least 85% complete. Despite a high degree of sequence-level similarity between the shared proteins in the Dsc and terrestrial Dehalococcoidetes, no evidence for catabolic reductive dehalogenation was found in Dsc. The genome content is however consistent with a strictly anaerobic organotrophic or lithotrophic lifestyle.


September 22, 2019  |  

Genome and evolution of the shade-requiring medicinal herb Panax ginseng.

Panax ginseng C. A. Meyer, reputed as the king of medicinal herbs, has slow growth, long generation time, low seed production and complicated genome structure that hamper its study. Here, we unveil the genomic architecture of tetraploid P. ginseng by de novo genome assembly, representing 2.98 Gbp with 59 352 annotated genes. Resequencing data indicated that diploid Panax species diverged in association with global warming in Southern Asia, and two North American species evolved via two intercontinental migrations. Two whole genome duplications (WGD) occurred in the family Araliaceae (including Panax) after divergence with the Apiaceae, the more recent one contributing to the ability of P. ginseng to overwinter, enabling it to spread broadly through the Northern Hemisphere. Functional and evolutionary analyses suggest that production of pharmacologically important dammarane-type ginsenosides originated in Panax and are produced largely in shoot tissues and transported to roots; that newly evolved P. ginseng fatty acid desaturases increase freezing tolerance; and that unprecedented retention of chlorophyll a/b binding protein genes enables efficient photosynthesis under low light. A genome-scale metabolic network provides a holistic view of Panax ginsenoside biosynthesis. This study provides valuable resources for improving medicinal values of ginseng either through genomics-assisted breeding or metabolic engineering.© 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.


September 22, 2019  |  

Genomic and metabolic diversity of Marine Group I Thaumarchaeota in the mesopelagic of two subtropical gyres.

Marine Group I (MGI) Thaumarchaeota are one of the most abundant and cosmopolitan chemoautotrophs within the global dark ocean. To date, no representatives of this archaeal group retrieved from the dark ocean have been successfully cultured. We used single cell genomics to investigate the genomic and metabolic diversity of thaumarchaea within the mesopelagic of the subtropical North Pacific and South Atlantic Ocean. Phylogenetic and metagenomic recruitment analysis revealed that MGI single amplified genomes (SAGs) are genetically and biogeographically distinct from existing thaumarchaea cultures obtained from surface waters. Confirming prior studies, we found genes encoding proteins for aerobic ammonia oxidation and the hydrolysis of urea, which may be used for energy production, as well as genes involved in 3-hydroxypropionate/4-hydroxybutyrate and oxidative tricarboxylic acid pathways. A large proportion of protein sequences identified in MGI SAGs were absent in the marine cultures Cenarchaeum symbiosum and Nitrosopumilus maritimus, thus expanding the predicted protein space for this archaeal group. Identifiable genes located on genomic islands with low metagenome recruitment capacity were enriched in cellular defense functions, likely in response to viral infections or grazing. We show that MGI Thaumarchaeota in the dark ocean may have more flexibility in potential energy sources and adaptations to biotic interactions than the existing, surface-ocean cultures.


September 22, 2019  |  

In vitro characterization of phenylacetate decarboxylase, a novel enzyme catalyzing toluene biosynthesis in an anaerobic microbial community.

Anaerobic bacterial biosynthesis of toluene from phenylacetate was reported more than two decades ago, but the biochemistry underlying this novel metabolism has never been elucidated. Here we report results of in vitro characterization studies of a novel phenylacetate decarboxylase from an anaerobic, sewage-derived enrichment culture that quantitatively produces toluene from phenylacetate; complementary metagenomic and metaproteomic analyses are also presented. Among the noteworthy findings is that this enzyme is not the well-characterized clostridial p-hydroxyphenylacetate decarboxylase (CsdBC). However, the toluene synthase under study appears to be able to catalyze both phenylacetate and p-hydroxyphenylacetate decarboxylation. Observations suggesting that phenylacetate and p-hydroxyphenylacetate decarboxylation in complex cell-free extracts were catalyzed by the same enzyme include the following: (i) the specific activity for both substrates was comparable in cell-free extracts, (ii) the two activities displayed identical behavior during chromatographic separation of cell-free extracts, (iii) both activities were irreversibly inactivated upon exposure to O2, and (iv) both activities were similarly inhibited by an amide analog of p-hydroxyphenylacetate. Based upon these and other data, we hypothesize that the toluene synthase reaction involves a glycyl radical decarboxylase. This first-time study of the phenylacetate decarboxylase reaction constitutes an important step in understanding and ultimately harnessing it for making bio-based toluene.


September 22, 2019  |  

Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection.

Productivity of ruminant livestock depends on the rumen microbiota, which ferment indigestible plant polysaccharides into nutrients used for growth. Understanding the functions carried out by the rumen microbiota is important for reducing greenhouse gas production by ruminants and for developing biofuels from lignocellulose. We present 410 cultured bacteria and archaea, together with their reference genomes, representing every cultivated rumen-associated archaeal and bacterial family. We evaluate polysaccharide degradation, short-chain fatty acid production and methanogenesis pathways, and assign specific taxa to functions. A total of 336 organisms were present in available rumen metagenomic data sets, and 134 were present in human gut microbiome data sets. Comparison with the human microbiome revealed rumen-specific enrichment for genes encoding de novo synthesis of vitamin B12, ongoing evolution by gene loss and potential vertical inheritance of the rumen microbiome based on underrepresentation of markers of environmental stress. We estimate that our Hungate genome resource represents ~75% of the genus-level bacterial and archaeal taxa present in the rumen.


September 22, 2019  |  

Next generation sequencing data of a defined microbial mock community.

Generating sequence data of a defined community composed of organisms with complete reference genomes is indispensable for the benchmarking of new genome sequence analysis methods, including assembly and binning tools. Moreover the validation of new sequencing library protocols and platforms to assess critical components such as sequencing errors and biases relies on such datasets. We here report the next generation metagenomic sequence data of a defined mock community (Mock Bacteria ARchaea Community; MBARC-26), composed of 23 bacterial and 3 archaeal strains with finished genomes. These strains span 10 phyla and 14 classes, a range of GC contents, genome sizes, repeat content and encompass a diverse abundance profile. Short read Illumina and long-read PacBio SMRT sequences of this mock community are described. These data represent a valuable resource for the scientific community, enabling extensive benchmarking and comparative evaluation of bioinformatics tools without the need to simulate data. As such, these data can aid in improving our current sequence data analysis toolkit and spur interest in the development of new tools.


September 22, 2019  |  

PCR and omics based techniques to study the diversity, ecology and biology of anaerobic fungi: Insights, challenges andopportunities.

Anaerobic fungi (phylum Neocallimastigomycota) are common inhabitants of the digestive tract of mammalian herbivores, and in the rumen, can account for up to 20% of the microbial biomass. Anaerobic fungi play a primary role in the degradation of lignocellulosic plant material. They also have a syntrophic interaction with methanogenic archaea, which increases their fiber degradation activity. To date, nine anaerobic fungal genera have been described, with further novel taxonomic groupings known to exist based on culture-independent molecular surveys. However, the true extent of their diversity may be even more extensively underestimated as anaerobic fungi continue being discovered in yet unexplored gut and non-gut environments. Additionally many studies are now known to have used primers that provide incomplete coverage of the Neocallimastigomycota. For ecological studies the internal transcribed spacer 1 region (ITS1) has been the taxonomic marker of choice, but due to various limitations the large subunit rRNA (LSU) is now being increasingly used. How the continued expansion of our knowledge regarding anaerobic fungal diversity will impact on our understanding of their biology and ecological role remains unclear; particularly as it is becoming apparent that anaerobic fungi display niche differentiation. As a consequence, there is a need to move beyond the broad generalization of anaerobic fungi as fiber-degraders, and explore the fundamental differences that underpin their ability to exist in distinct ecological niches. Application of genomics, transcriptomics, proteomics and metabolomics to their study in pure/mixed cultures and environmental samples will be invaluable in this process. To date the genomes and transcriptomes of several characterized anaerobic fungal isolates have been successfully generated. In contrast, the application of proteomics and metabolomics to anaerobic fungal analysis is still in its infancy. A central problem for all analyses, however, is the limited functional annotation of anaerobic fungal sequence data. There is therefore an urgent need to expand information held within publicly available reference databases. Once this challenge is overcome, along with improved sample collection and extraction, the application of these techniques will be key in furthering our understanding of the ecological role and impact of anaerobic fungi in the wide range of environments they inhabit.


September 22, 2019  |  

Discovery of enzymes for toluene synthesis from anoxic microbial communities.

Microbial toluene biosynthesis was reported in anoxic lake sediments more than three decades ago, but the enzyme catalyzing this biochemically challenging reaction has never been identified. Here we report the toluene-producing enzyme PhdB, a glycyl radical enzyme of bacterial origin that catalyzes phenylacetate decarboxylation, and its cognate activating enzyme PhdA, a radical S-adenosylmethionine enzyme, discovered in two distinct anoxic microbial communities that produce toluene. The unconventional process of enzyme discovery from a complex microbial community (>300,000 genes), rather than from a microbial isolate, involved metagenomics- and metaproteomics-enabled biochemistry, as well as in vitro confirmation of activity with recombinant enzymes. This work expands the known catalytic range of glycyl radical enzymes (only seven reaction types had been characterized previously) and aromatic-hydrocarbon-producing enzymes, and will enable first-time biochemical synthesis of an aromatic fuel hydrocarbon from renewable resources, such as lignocellulosic biomass, rather than from petroleum.


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