Evidence map›Paper›PMID 41840729›Full record

ArticleMicrobiome2026

Microbiome Datahub: an open-access platform integrating environmental metadata, taxonomy, and functional annotation for comprehensive metagenome-assembled genome datasets.

Hiroshi Mori, Takatomo Fujisawa, Koichi Higashi, Yasuhiro Tanizawa, Zenichi Nakagawa, Hiroyo Nishide, Masaki Fujiyoshi, Yasukazu Nakamura, Ikuo Uchiyama, Motomu Matsui and 1 more

Abstract read
In one paragraph

Article in Microbiome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Hiroshi MoriDepartment of Informatics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan. hmori@nig.ac.jp.
Takatomo FujisawaDepartment of Informatics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
Koichi HigashiDepartment of Informatics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
Yasuhiro TanizawaDepartment of Informatics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
Zenichi NakagawaSchool of Life Science and Technology, Institute of Science Tokyo, Tokyo, 152-8550, Japan.
Hiroyo NishideNational Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Japan.
Masaki FujiyoshiDepartment of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, 277-8561, Japan.
Yasukazu NakamuraDepartment of Informatics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
Ikuo UchiyamaNational Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Japan.
Motomu MatsuiInstitute for Chemical Research, Kyoto University, Uji, Kyoto, 611-0011, Japan.
Takuji YamadaSchool of Life Science and Technology, Institute of Science Tokyo, Tokyo, 152-8550, Japan.

Funding

Japan Science and Technology Agency JPMJND2206
6 · The paper itself

Abstract

backgroundMetagenome-assembled genomes (MAGs) provide crucial insights into the genomic diversity of uncultured microbes. However, MAG datasets deposited in public repositories such as INSDC are often difficult to reuse due to heterogeneous quality, inconsistent taxonomic and functional annotations, and insufficiently curated environmental metadata. While secondary MAG databases such as MGnify, IMG/M, and SPIRE provide standardized resources, they reconstruct MAGs de novo from public metagenomic reads and therefore do not represent the original MAGs reported in publications.

resultsTo address this gap, we developed Microbiome Datahub, an open-access platform that systematically aggregates and re-annotates original MAGs from INSDC. We collected 214,427 MAGs, predicted genes by DFAST, performed quality assessment with CheckM, standardized taxonomic assignments with GTDB-Tk, inferred 27 phenotypic traits using Bac2Feature, assigned proteins to MBGD ortholog clusters and KEGG Orthology IDs using PZLAST, and annotated environmental metadata with the Metagenome and Microbes Environmental Ontology. Across these MAGs, the average completeness was 80.5% and contamination 1.8%; notably, the most frequent values were >95% completeness and <1% contamination, indicating that the majority of MAGs are of high quality. Comparative analyses showed that Microbiome Datahub provides phylogenetically and environmentally diverse MAGs: while the majority originated from vertebrate gut environments, a substantial number were also recovered from other habitats such as groundwater, including nearly 10,000 MAGs from the Patescibacteria. Inference of 27 phenotypic traits, including optimum growth temperature, further revealed ecological differentiation across phyla. Protein clustering revealed 56 million identity 40% clusters, with the majority unique compared with MGnify and GlobDB, and ~19% of proteins unassigned to MBGD ortholog clusters, underscoring their novelty.

conclusionsMicrobiome Datahub integrates MAG genome sequences, gene and protein predictions, quality metrics, environmental and taxonomic annotations, ortholog cluster assignments, and phenotype predictions, all accessible via a web interface, API, and bulk downloads. By combining original MAGs with curated metadata and functional annotations, Microbiome Datahub constitutes a comprehensive and reusable resource that will accelerate microbiome and microbial genomics research. Video Abstract.

Indexed as

BacteriaDatabases, GeneticMetadataMetagenomeMetagenomicsMicrobiotaBiocurationComputational BiologyMolecular Sequence AnnotationDatabaseDiversityEnvironmentMAGMetagenome

Identifiers

PMID41840729
PMCPMC13104272

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.