Evidence map›Paper›PMID 36464731›Full record

ArticleMicrobiome2022

Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments.

Hans-Joachim Ruscheweyh, Alessio Milanese, Lucas Paoli, Nicolai Karcher, Quentin Clayssen, Marisa Isabell Keller, Jakob Wirbel, Peer Bork, Daniel R Mende, Georg Zeller and 1 more

Abstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 1 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  19. Description ofInternational journal of systematic and evolutionary microbiology · 2026
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

11 authors.

Hans-Joachim Ruscheweyh *Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093, Zürich, Switzerland.
Alessio Milanese *Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093, Zürich, Switzerland.
Lucas PaoliDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093, Zürich, Switzerland.
Nicolai KarcherStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.
Quentin ClayssenDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093, Zürich, Switzerland.
Marisa Isabell KellerStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.
Jakob WirbelStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.
Peer BorkStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany.
Daniel R MendeDepartment of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Georg ZellerStructural and Computational Biology Unit, European Molecular Biology Laboratory, 69117, Heidelberg, Germany. zeller@embl.de.
Shinichi SunagawaDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093, Zürich, Switzerland. ssunagawa@ethz.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTaxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes.

resultsWe present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies.

conclusionsWe developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.

Indexed as

MetagenomeMicrobiotaAnimalsCattleMetagenomicsRNA, Ribosomal, 16SSoilSwineRNA, Ribosomal, 16SSoilBenchmarkingMarker geneMetagenome-assembled genomeMetagenomicsMicrobial communityReference genomeSingle-cell genomeTaxonomic profiling

Identifiers

PMID36464731
PMCPMC9721005

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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.