Fibrobacter succinogenes is an important member of the rumen microbial community that converts plant biomass into nutrients usable by its host. This bacterium, which is also one of only two ...cultivated species in its phylum, is an efficient and prolific degrader of cellulose. Specifically, it has a particularly high activity against crystalline cellulose that requires close physical contact with this substrate. However, unlike other known cellulolytic microbes, it does not degrade cellulose using a cellulosome or by producing high extracellular titers of cellulase enzymes. To better understand the biology of F. succinogenes, we sequenced the genome of the type strain S85 to completion. A total of 3,085 open reading frames were predicted from its 3.84 Mbp genome. Analysis of sequences predicted to encode for carbohydrate-degrading enzymes revealed an unusually high number of genes that were classified into 49 different families of glycoside hydrolases, carbohydrate binding modules (CBMs), carbohydrate esterases, and polysaccharide lyases. Of the 31 identified cellulases, none contain CBMs in families 1, 2, and 3, typically associated with crystalline cellulose degradation. Polysaccharide hydrolysis and utilization assays showed that F. succinogenes was able to hydrolyze a number of polysaccharides, but could only utilize the hydrolytic products of cellulose. This suggests that F. succinogenes uses its array of hemicellulose-degrading enzymes to remove hemicelluloses to gain access to cellulose. This is reflected in its genome, as F. succinogenes lacks many of the genes necessary to transport and metabolize the hydrolytic products of non-cellulose polysaccharides. The F. succinogenes genome reveals a bacterium that specializes in cellulose as its sole energy source, and provides insight into a novel strategy for cellulose degradation.
Abstract
The Integrated Microbial Genomes & Microbiomes system (IMG/M: https://img.jgi.doe.gov/m/) contains annotated isolate genome and metagenome datasets sequenced at the DOE’s Joint Genome ...Institute (JGI), submitted by external users, or imported from public sources such as NCBI. IMG v 6.0 includes advanced search functions and a new tool for statistical analysis of mixed sets of genomes and metagenome bins. The new IMG web user interface also has a new Help page with additional documentation and webinar tutorials to help users better understand how to use various IMG functions and tools for their research. New datasets have been processed with the prokaryotic annotation pipeline v.5, which includes extended protein family assignments.
Viruses are the most abundant biological entities on Earth, but challenges in detecting, isolating, and classifying unknown viruses have prevented exhaustive surveys of the global virome. Here we ...analysed over 5 Tb of metagenomic sequence data from 3,042 geographically diverse samples to assess the global distribution, phylogenetic diversity, and host specificity of viruses. We discovered over 125,000 partial DNA viral genomes, including the largest phage yet identified, and increased the number of known viral genes by 16-fold. Half of the predicted partial viral genomes were clustered into genetically distinct groups, most of which included genes unrelated to those in known viruses. Using CRISPR spacers and transfer RNA matches to link viral groups to microbial host(s), we doubled the number of microbial phyla known to be infected by viruses, and identified viruses that can infect organisms from different phyla. Analysis of viral distribution across diverse ecosystems revealed strong habitat-type specificity for the vast majority of viruses, but also identified some cosmopolitan groups. Our results highlight an extensive global viral diversity and provide detailed insight into viral habitat distribution and host–virus interactions.
Abstract
Viruses are integral components of all ecosystems and microbiomes on Earth. Through pervasive infections of their cellular hosts, viruses can reshape microbial community structure and drive ...global nutrient cycling. Over the past decade, viral sequences identified from genomes and metagenomes have provided an unprecedented view of viral genome diversity in nature. Since 2016, the IMG/VR database has provided access to the largest collection of viral sequences obtained from (meta)genomes. Here, we present the third version of IMG/VR, composed of 18 373 cultivated and 2 314 329 uncultivated viral genomes (UViGs), nearly tripling the total number of sequences compared to the previous version. These clustered into 935 362 viral Operational Taxonomic Units (vOTUs), including 188 930 with two or more members. UViGs in IMG/VR are now reported as single viral contigs, integrated proviruses or genome bins, and are annotated with a new standardized pipeline including genome quality estimation using CheckV, taxonomic classification reflecting the latest ICTV update, and expanded host taxonomy prediction. The new IMG/VR interface enables users to efficiently browse, search, and select UViGs based on genome features and/or sequence similarity. IMG/VR v3 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.
Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of ...viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.
Motivation: A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the ...annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. Results: We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes. Contact: vmmarkowitz@lbl.gov Supplementary information: Supplementary data are available at Bioinformatics online.
Genome sequencing enhances our understanding of the biological world by providing blueprints for the evolutionary and functional diversity that shapes the biosphere. However, microbial genomes that ...are currently available are of limited phylogenetic breadth, owing to our historical inability to cultivate most microorganisms in the laboratory. We apply single-cell genomics to target and sequence 201 uncultivated archaeal and bacterial cells from nine diverse habitats belonging to 29 major mostly uncharted branches of the tree of life, so-called 'microbial dark matter'. With this additional genomic information, we are able to resolve many intra- and inter-phylum-level relationships and to propose two new superphyla. We uncover unexpected metabolic features that extend our understanding of biology and challenge established boundaries between the three domains of life. These include a novel amino acid use for the opal stop codon, an archaeal-type purine synthesis in Bacteria and complete sigma factors in Archaea similar to those in Bacteria. The single-cell genomes also served to phylogenetically anchor up to 20% of metagenomic reads in some habitats, facilitating organism-level interpretation of ecosystem function. This study greatly expands the genomic representation of the tree of life and provides a systematic step towards a better understanding of biological evolution on our planet.
The Integrated Microbial Genomes & Microbiomes system (IMG/M: https://img.jgi.doe.gov/m/) at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to ...perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. We also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).
PDF
