IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata.

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

Hyperinsulinemia acts via acinar insulin receptors to initiate pancreatic cancer by increasing digestive enzyme production and inflammation.

The rising pancreatic cancer incidence due to obesity and type 2 diabetes is closely tied to hyperinsulinemia, an independent cancer risk factor. Previous studies demonstrated reducing insulin production suppressed pancreatic intraepithelial neoplasia (PanIN) pre-cancerous lesions in Kras-mutant mice. However, the pathophysiological and molecular mechanisms remained unknown, and in particular it was unclear whether hyperinsulinemia affected PanIN precursor cells directly or indirectly. Here, we demonstrate that insulin receptors (Insr) in KrasG12D-expressing pancreatic acinar cells are dispensable for glucose homeostasis but necessary for hyperinsulinemia-driven PanIN formation in the context of diet-induced hyperinsulinemia and obesity. Mechanistically, this was attributed to amplified digestive enzyme protein translation, triggering of local inflammation, and PanIN metaplasia in vivo. In vitro, insulin dose-dependently increased acinar-to-ductal metaplasia formation in a trypsin- and Insr-dependent manner. Collectively, our data shed light on the mechanisms connecting obesity-driven hyperinsulinemia and pancreatic cancer development.

Gill surface area allometry does not constrain the body mass scaling of maximum oxygen uptake rate in the tidepool sculpin, Oligocottus maculosus.

The gill oxygen limitation hypothesis (GOLH) suggests that hypometric scaling of metabolic rate in fishes is a consequence of oxygen supply constraints imposed by the mismatched growth rates of gill surface area (a two-dimensional surface) and body mass (a three-dimensional volume). GOLH may, therefore, explain the size-dependent spatial distribution of fish in temperature- and oxygen-variable environments through size-dependent respiratory capacity, but this question is unstudied. We tested GOLH in the tidepool sculpin, Oligocottus maculosus, a species in which body mass decreases with increasing temperature- and oxygen-variability in the intertidal, a pattern consistent with GOLH. We statistically evaluated support for GOLH versus distributed control of [Formula: see text] allometry by comparing scaling coefficients for gill surface area, standard and maximum [Formula: see text] ([Formula: see text],Standard and [Formula: see text],Max, respectively), ventricle mass, hematocrit, and metabolic enzyme activities in white muscle. To empirically evaluate whether there is a proximate constraint on oxygen supply capacity with increasing body mass, we measured [Formula: see text],Max across a range of Po2s from normoxia to Pcrit, calculated the regulation value (R), a measure of oxyregulatory capacity, and analyzed the R-body mass relationship. In contrast with GOLH, gill surface area scaling either matched or was more than sufficient to meet [Formula: see text] demands with increasing body mass and R did not change with body mass. Ventricle mass (b = 1.22) scaled similarly to [Formula: see text],Max (b = 1.18) suggesting a possible role for the heart in the scaling of [Formula: see text],Max. Together our results do not support GOLH as a mechanism structuring the distribution of O. maculosus and suggest distributed control of oxyregulatory capacity.

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata.

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.

The IMG/M data management and analysis system v.7: content updates and new features.

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).

Aerobic scope falls to nil at Pcrit and anaerobic ATP production increases below Pcrit in the tidepool sculpin, Oligocottus maculosus.

The critical oxygen tension of whole-animal oxygen uptake rate, or Pcrit, has historically been defined as the oxygen partial pressure (PO2) at which aerobic scope falls to zero and further declines in PO2 require substrate-level phosphorylation to meet shortfalls in aerobic ATP production, thereby time-limiting survival. Despite the inclusion of aerobic scope and anaerobic ATP production in the definition, little effort has been made to verify that Pcrit measurements, the vast majority of which are obtained using respirometry in resting animals, actually reflect the predictions of zero aerobic scope and a transition to increasing reliance on anaerobic ATP production. To test these predictions, we compared aerobic scope and levels of whole-body lactate at oxygen partial pressures (PO2s) bracketing Pcrit obtained in resting fish during progressive hypoxia in the tidepool sculpin, Oligocottus maculosus. We found that aerobic scope falls to zero at Pcrit and, in resting fish exposed to PO2s < Pcrit, whole-body lactate accumulated pointing to an increased reliance on anaerobic ATP production. These results support the interpretation of Pcrit as a key oxygen threshold at which aerobic scope falls to nil and, below Pcrit, survival is time-limited based on anaerobic metabolic capacity.

Effects of hyperinsulinemia on pancreatic cancer development and the immune microenvironment revealed through single-cell transcriptomics.

BACKGROUND: Hyperinsulinemia is independently associated with increased risk and mortality of pancreatic cancer. We recently reported that genetically reduced insulin production resulted in ~ 50% suppression of pancreatic intraepithelial neoplasia (PanIN) precancerous lesions in mice. However, only female mice remained normoglycemic, and only the gene dosage of the rodent-specific Ins1 alleles was tested in our previous model. Moreover, we did not delve into the molecular and cellular mechanisms associated with modulating hyperinsulinemia. METHODS: We studied how reduced Ins2 gene dosage affects PanIN lesion development in both male and female Ptf1aCreER;KrasLSL-G12D mice lacking the rodent-specific Ins1 gene (Ins1-/-). We generated control mice having two alleles of the wild-type Ins2 gene (Ptf1aCreER;KrasLSL-G12D;Ins1-/-;Ins2+/+) and experimental mice having one allele of Ins2 gene (Ptf1aCreER;KrasLSL-G12D;Ins1-/-;Ins2+/-). We then performed thorough histopathological analyses and single-cell transcriptomics for both genotypes and sexes. RESULTS: High-fat diet-induced hyperinsulinemia was transiently or modestly reduced in female and male mice, respectively, with only one allele of Ins2. This occurred without dramatically affecting glucose tolerance. Genetic reduction of insulin production resulted in mice with a tendency for less PanIN and acinar-to-ductal metaplasia (ADM) lesions. Using single-cell transcriptomics, we found hyperinsulinemia affected multiple cell types in the pancreas, with the most statistically significant effects on local immune cell types that were highly represented in our sampled cell population. Specifically, hyperinsulinemia modulated pathways associated with protein translation, MAPK-ERK signaling, and PI3K-AKT signaling, which were changed in epithelial cells and subsets of immune cells. CONCLUSIONS: These data suggest a potential role for the immune microenvironment in hyperinsulinemia-driven PanIN development. Together with our previous work, we propose that mild suppression of insulin levels may be useful in preventing pancreatic cancer by acting on multiple cell types.

The IMG/M data management and analysis system v.6.0: new tools and advanced capabilities.

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.

IMG/VR v3: an integrated ecological and evolutionary framework for interrogating genomes of uncultivated viruses.

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.

IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase.

Microbial secondary metabolism is a reservoir of bioactive compounds of immense biotechnological and biomedical potential. The biosynthetic machinery responsible for the production of these secondary metabolites (SMs) (also called natural products) is often encoded by collocated groups of genes called biosynthetic gene clusters (BGCs). High-throughput genome sequencing of both isolates and metagenomic samples combined with the development of specialized computational workflows is enabling systematic identification of BGCs and the discovery of novel SMs. In order to advance exploration of microbial secondary metabolism and its diversity, we developed the largest publicly available database of predicted BGCs combined with experimentally verified BGCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc-public). Here we describe the first major content update of the IMG-ABC knowledgebase, since its initial release in 2015, refreshing the BGC prediction pipeline with the latest version of antiSMASH (v5) as well as presenting the data in the context of underlying environmental metadata sourced from GOLD (https://gold.jgi.doe.gov/). This update has greatly improved the quality and expanded the types of predicted BGCs compared to the previous version.

IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes.

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.

IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes.

The Integrated Microbial Genome/Virus (IMG/VR) system v.2.0 (https://img.jgi.doe.gov/vr/) is the largest publicly available data management and analysis platform dedicated to viral genomics. Since the last report published in the 2016, NAR Database Issue, the data has tripled in size and currently contains genomes of 8389 cultivated reference viruses, 12 498 previously published curated prophages derived from cultivated microbial isolates, and 735 112 viral genomic fragments computationally predicted from assembled shotgun metagenomes. Nearly 60% of the viral genomes and genome fragments are clustered into 110 384 viral Operational Taxonomic Units (vOTUs) with two or more members. To improve data quality and predictions of host specificity, IMG/VR v.2.0 now separates prokaryotic and eukaryotic viruses, utilizes known prophage sequences to improve taxonomic assignments, and provides viral genome quality scores based on the estimated genome completeness. New features also include enhanced BLAST search capabilities for external queries. Finally, geographic map visualization to locate user-selected viral genomes or genome fragments has been implemented and download options have been extended. All of these features make IMG/VR v.2.0 a key resource for the study of viruses.

IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses.

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community.

IMG/M: integrated genome and metagenome comparative data analysis system.

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system.

BACKGROUND: The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. RESULTS: Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. CONCLUSION: By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.

Ten years of maintaining and expanding a microbial genome and metagenome analysis system.

Launched in March 2005, the Integrated Microbial Genomes (IMG) system is a comprehensive data management system that supports multidimensional comparative analysis of genomic data. At the core of the IMG system is a data warehouse that contains genome and metagenome datasets sequenced at the Joint Genome Institute or provided by scientific users, as well as public genome datasets available at the National Center for Biotechnology Information Genbank sequence data archive. Genomes and metagenome datasets are processed using IMG's microbial genome and metagenome sequence data processing pipelines and are integrated into the data warehouse using IMG's data integration toolkits. Microbial genome and metagenome application specific data marts and user interfaces provide access to different subsets of IMG's data and analysis toolkits. This review article revisits IMG's original aims, highlights key milestones reached by the system during the past 10 years, and discusses the main challenges faced by a rapidly expanding system, in particular the complexity of maintaining such a system in an academic setting with limited budgets and computing and data management infrastructure.

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

UNLABELLED: In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMPORTANCE: IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

Pooled nucleic acid testing increases the diagnostic yield of acute HIV infections in a high-risk population compared to 3rd and 4th generation HIV enzyme immunoassays.

OBJECTIVES: We compared a 3rd generation (gen) and two 4th gen HIV enzyme immunoassays (EIA) to pooled nucleic acid testing (PNAT) for the identification of pre- and early seroconversion acute HIV infection (AHI). STUDY DESIGN: 9550 specimens from males >18 year from clinics attended by men who have sex with men were tested by Siemens ADVIA Centaur(®) HIV 1/O/2 (3rd gen) and HIV Combo (4th gen), as well as by Abbott ARCHITECT(®) HIV Ag/Ab Combo (4th gen). Third gen non-reactive specimens were also tested by Roche COBAS(®) Ampliprep/COBAS® TaqMan HIV-1 Test v.2 in pools of 24 samples. Sensitivity and specificity of the three EIAs for AHI detection were compared. RESULTS: 7348 persons contributed 9435 specimens and had no evidence of HIV infection, 79 (94 specimens) had established HIV infection, 6 (9 specimens) had pre-seroconversion AHI and 9 (12 specimens) had early seroconversion AHI. Pre-seroconversion AHI cases were not detected by 3rd gen EIA, whereas 2/6 (33.3%) were detected by Siemens 4th gen, 4/6 (66.7%) by Abbott 4th gen and 6/6 (100%) by PNAT. All three EIAs and PNAT detected all individuals with early seroconversion AHI. Overall sensitivity/specificity for the EIAs relative to WB or NAT resolved infection status was 93.6%/99.9% for Siemens 3rd gen, 95.7%/99.7% for Siemens 4th gen and 97.9%/99.2% for Abbott 4th gen. CONCLUSIONS: While both 4th gen EIAs demonstrated improved sensitivity for AHI compared to 3rd gen EIA, PNAT identified more AHI cases than either 4th gen assay. PNAT is likely to remain a useful strategy to identify AHI in high-risk populations.

IMG/M 4 version of the integrated metagenome comparative analysis system.

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M's data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M's database architecture, annotation and data integration pipelines and analysis tools have been extended to copewith the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/imgm_hmp).