Evidence map›Paper›PMID 41296543›Full record

ArticleNucleic acids research2026

metaTraits: a large-scale integration of microbial phenotypic trait information.

Daniel Podlesny, Chan Yeong Kim, Shahriyar Mahdi Robbani, Christian Schudoma, Anthony Fullam, Lorenz C Reimer, Julia Koblitz, Isabel Schober, Anandhi Iyappan, Thea Van Rossum and 4 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
  2. Article
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

14 authors.

Daniel PodlesnyEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-5685-0915
Chan Yeong KimEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-0868-9872
Shahriyar Mahdi RobbaniEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0003-0161-0559
Christian SchudomaEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0003-1157-1354
Anthony FullamEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-0884-8124
Lorenz C ReimerLeibniz Institute DSMZ, 38124 Braunschweig, Germany.ORCID 0000-0002-7805-0660
Julia KoblitzLeibniz Institute DSMZ, 38124 Braunschweig, Germany.ORCID 0000-0002-7260-2129
Isabel SchoberLeibniz Institute DSMZ, 38124 Braunschweig, Germany.ORCID 0000-0002-4894-1913
Anandhi IyappanEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-5571-4962
Thea Van RossumEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-3598-5001
Jonas SchillerEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-5745-0892
Anastasia GrekovaEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0009-0002-9092-8584
Michael KuhnEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-2841-872X
Peer BorkEuropean Molecular Biology Laboratory, Molecular Systems Biology Unit, 69117 Heidelberg, Germany.ORCID 0000-0002-2627-833X

Funding

Deutsche Forschungsgemeinschaft 460129525Ministry of Science, Research and the Arts Baden-Württemberg (MWK)National Research Foundation of Korea RS-2023-00240807
6 · The paper itself

Abstract

Microbes differ greatly in their organismal structure, physiology, and environmental adaptation, yet information about these phenotypic traits is dispersed across multiple databases and is largely unavailable for taxa that remain uncultured. Here, we present metaTraits, a unified and accessible trait resource that integrates culture-derived trait information from BacDive, BV-BRC, JGI IMG, and GOLD with genome-based predictions for medium and high-quality isolate and metagenome-assembled genomes (MAGs) from proGenomes and SPIRE. metaTraits covers over 2.2 million genomes and >140 harmonized traits mapped to standardized ontologies, spanning cell morphology (e.g. shape, size, and Gram staining), physiology (e.g. motility and sporulation), metabolic and enzymatic activities, environmental preferences (e.g. temperature, salinity, and oxygen tolerance), and lifestyle categories. All records are linked to the original evidence, and species are cross-linked to NCBI and GTDB taxonomies. The interactive metaTraits website provides search and visualization tools, taxonomy-level summaries, and two workflows for annotating user-submitted genomes or community profiles. metaTraits substantially advances accessibility and interoperability of microbial trait data, enabling comprehensive trait-based analyses of microbiomes across diverse environments. metaTraits is accessible via https://metatraits.embl.de.

Indexed as

BacteriaDatabases, GeneticPhenotypeSoftwareGenome, BacterialInternetMetagenomeMetagenomics

Identifiers

PMID41296543
PMCPMC12807735

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.