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...

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

Termites effectively feed on many types of lignocellulose assisted by their gut microbial symbionts. To better understand the microbial decomposition of biomass with varied chemical profiles, it is important to determine whether termites harbor different microbial symbionts with specialized functionalities geared toward different feeding regimens. In this study, we compared the microbiota in the hindgut paunch of Amitermes wheeleri collected from cow dung and Nasutitermes corniger feeding on sound wood by 16S rRNA pyrotag, comparative metagenomic and metatranscriptomic analyses. We found that Firmicutes and Spirochaetes were the most abundant phyla in A. wheeleri, in contrast to N. corniger where Spirochaetes and Fibrobacteres dominated. Despite this community divergence, a convergence was observed for functions essential to termite biology including hydrolytic enzymes, homoacetogenesis and cell motility and chemotaxis. Overrepresented functions in A. wheeleri relative to N. corniger microbiota included hemicellulose breakdown and fixed-nitrogen utilization. By contrast, glycoside hydrolases attacking celluloses and nitrogen fixation genes were overrepresented in N. corniger microbiota. These observations are consistent with dietary differences in carbohydrate composition and nutrient contents, but may also reflect the phylogenetic difference between the hosts.

A Correction to this paper has been published: https://doi.org/10.1038/s41587-021-00898-4.