Evidence map›Paper›PMID 30833550›Full record

ArticleNature communications2019

Microbial abundance, activity and population genomic profiling with mOTUs2.

Alessio Milanese, Daniel R Mende, Lucas Paoli, Guillem Salazar, Hans-Joachim Ruscheweyh, Miguelangel Cuenca, Pascal Hingamp, Renato Alves, Paul I Costea, Luis Pedro Coelho and 8 more

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 244 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
244citing papers in PubMed, 2 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.

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

244 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
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  7. Article
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  11. 16S rRNA sequence captures microbial functional potential.bioRxiv : the preprint server for biology · 2026
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Deconvolving Phylogenetic Distance Mixtures.bioRxiv : the preprint server for biology · 2026
    Article
  17. Article
  18. Article
  19. Article
  20. The Japanese gut microbiome: ecology, uniqueness, and impact on health and disease.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2026
    Review

184 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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

18 authors.

Alessio MilaneseEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-7050-2239
Daniel R MendeDaniel K. Inouye Center for Microbial Oceanography Research and Education, University of Hawai'i at Mānoa, 1950 East West Road, Honolulu, USA, 96822, United States.ORCID http://orcid.org/0000-0001-6831-4557
Lucas PaoliDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland.
Guillem SalazarDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland.
Hans-Joachim RuscheweyhDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland.
Miguelangel CuencaDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland.ORCID http://orcid.org/0000-0003-3435-9102
Pascal HingampAix Marseille Univ, Université de Toulon, CNRS, IRD, MIO UM 110, 13288, Marseille, France.
Renato AlvesEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-7212-0234
Paul I CosteaEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0003-1645-3947
Luis Pedro CoelhoEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-9280-7885
Thomas S B SchmidtEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-8587-4177
Alexandre AlmeidaEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK.ORCID http://orcid.org/0000-0001-8803-0893
Alex L MitchellEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK.
Robert D FinnEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK.ORCID http://orcid.org/0000-0001-8626-2148
Jaime Huerta-CepasEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.
Peer BorkEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-2627-833X
Georg ZellerEuropean Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany. zeller@embl.de.ORCID http://orcid.org/0000-0003-1429-7485
Shinichi SunagawaDepartment of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland. ssunagawa@ethz.ch.ORCID http://orcid.org/0000-0003-3065-0314

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces estimation biases. We present an updated and functionally extended tool based on universal (i.e., reference-independent), phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) enabling the profiling of >7700 microbial species. As more than 30% of them could not previously be quantified at this taxonomic resolution, relative abundance estimates based on mOTUs are more accurate compared to other methods. As a new feature, we show that mOTUs, which are based on essential housekeeping genes, are demonstrably well-suited for quantification of basal transcriptional activity of community members. Furthermore, single nucleotide variation profiles estimated using mOTUs reflect those from whole genomes, which allows for comparing microbial strain populations (e.g., across different human body sites).

Indexed as

MetagenomicsPhylogenyAlgorithmsCluster AnalysisComputational BiologyGene Expression ProfilingGenes, EssentialGenetic MarkersGenomeHost Microbial InteractionsHumansMicrobiotaMolecular Sequence AnnotationSequence AlignmentSequence Analysis, DNAGenetic Markers

Identifiers

PMID30833550
PMCPMC6399450

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Registered trials

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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.