We previously reported on MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here, we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat.

New insights into other importantPublisher: NPG; Journal: Nature: Nature; Article Type: Biology letter DOI: 10.1038/nature06269Page 2 of 33 symbiotic functions including H 2 metabolism, CO 2 -reductive acetogenesis and N 2 fixation are also provided by this first system-wide gene analysis of a microbial community specialized towards plant lignocellulose degradation. Our results underscore how complex even a 1-μl environment can be.All known termite species form obligate, nutritional mutualisms with diverse gut microbial species found nowhere else in nature 3 . Despite nearly a century of study, however, science still has only a meagre understanding of the exact roles of the host and symbiotic microbiota in the complex processes of lignocellulose degradation and conversion. Especially conspicuous is our poor understanding of the hindgut communities of wood-feeding 'higher'termites, the most species-rich and abundant of all termite lineages 4 . Higher termites do not contain hindgut flagellate protozoa, which have long been known to be sources of cellulases and hemicellulases in the 'lower' termites. The host tissue of all wood-feeding termites is known to be the source of one cellulase, a single-domain glycohydrolase family 9 enzyme that is secreted and active in the anterior compartments of the gut tract 5 . Only in recent years has research provided support for a role of termite gut bacteria in the production of relevant hydrolytic enzymes. That evidence includes the observed tight attachment of bacteria to wood particles, the antibacterial sensitivity of particle-bound cellulase activity 2 , and the discovery of a gene encoding a novel endoxylanase (glycohydrolase family 11) from bacterial DNA harvested from the gut tract of a Nasutitermes species 6 . Here, in an effort to learn about gene-centred details relevant to the diverse roles of bacterial symbionts in these successful wood-degrading insects,we initiated a metagenomic analysis of a wood-feeding 'higher' termite hindgut community, performed a proteomic analysis with clarified gut fluid from the same sample, and examined a set of candidate enzymes identified during the course of the study for demonstrable cellulase activity.A nest of an arboreal species closely related to Nasutitermes ephratae and N. corniger ( Supplementary Fig. 1) was collected near Guápiles, Costa Rica. From worker specimens, luminal contents were sampled specifically from the largest hindgut compartment, the microbedense, microlitre-sized region alternatively known as the paunch or the third proctodeal segment (P3; Fig. 1a). In the interest of interpretive clarity, we specifically excluded sampling from and analysis of the microbiota attached to the P3 epithelium and the other distinct microbial communities associated with the other hindgut compartments.Publisher: NPG; Journal: Nature: Nature; Article Type: Biology letter DOI: 10.1038/nature06269Page 3 of 33Total community DNA from pooled P3 luminal contents was purified, cloned and sequenced. About 71 million base pairs of Sang...

The Integrated Microbial Genomes & Microbiomes system v.5.0 (IMG/M: https://img.jgi.doe.gov/m/) contains annotated datasets categorized into: archaea, bacteria, eukarya, plasmids, viruses, genome fragments, metagenomes, cell enrichments, single particle sorts, and metatranscriptomes. Source datasets include those generated by the DOE’s Joint Genome Institute (JGI), submitted by external scientists, or collected from public sequence data archives such as NCBI. All submissions are typically processed through the IMG annotation pipeline and then loaded into the IMG data warehouse. IMG’s web user interface provides a variety of analytical and visualization tools for comparative analysis of isolate genomes and metagenomes in IMG. IMG/M allows open access to all public genomes in the IMG data warehouse, while its expert review (ER) system (IMG/MER: https://img.jgi.doe.gov/mer/) allows registered users to access their private genomes and to store their private datasets in workspace for sharing and for further analysis. IMG/M data content has grown by 60% since the last report published in the 2017 NAR Database Issue. IMG/M v.5.0 has a new and more powerful genome search feature, new statistical tools, and supports metagenome binning.

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

We previously reported MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.27522v1 | CC BY 4.0 Open Access | rec:ABSTRACT 16 We previously reported MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat. 17 18 19 20 21 22 23 24 25 26 27 28 29 Recently we have witnessed exciting progress in metagenome binning as several automatic binning 37 tools become available. Our group developed MetaBAT (Kang et al., 2015) in 2015, among a few others 38 developed around the same time, including MyCC (Lin and Liao, 2016), MaxBin 2.0 (Wu et al., 2015), 39 MetaWatt-3.5 (Strous et al., 2012) a...