Evidence map›Paper›PMID 41634049›Full record

ArticleScientific data2026

BactoTraits: a trait database for exploring functional diversity of bacterial communities.

Vincent Laderriere, Philippe Usseglio-Polatera, Florence Maunoury-Danger, Aurélie Cébron

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Vincent LaderriereUniversité de Lorraine, CNRS, LIEC, F-57000, Metz, France.ORCID http://orcid.org/0000-0003-1023-4890
Philippe Usseglio-PolateraUniversité de Lorraine, CNRS, LIEC, F-57000, Metz, France.
Florence Maunoury-DangerUniversité de Lorraine, CNRS, LIEC, F-57000, Metz, France.
Aurélie CébronUniversité de Lorraine, CNRS, LIEC, F-54000, Nancy, France. aurelie.cebron@univ-lorraine.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is still a need for a better understanding of how abiotic/biotic factors affect the functional structure and composition of biological assemblages, given that living organisms are in constant interaction with their environment and with each other. Here, we present a comprehensive dataset of 31 functional traits of bacteria using information from BacDive, a bacterial diversity meta-database, as well as from the rrnDB and genomesizeR datasets. This updated version of the BactoTraits dataset, in addition to now offering more traits for more strains (97,721 strains with at least one trait described), makes R scripts available to the scientific community. These traits include physiological characteristics, metabolic processes, genome properties and biotope preferences. They could be inferred to the whole bacterial community thanks to taxonomic affiliation obtained from traditional high throughput 16S rRNA gene amplicon sequencing methods. This taxonomic affiliation is based on the regularly updated SILVA database and thus allows to study combinations of weighted mean trait profiles of bacterial communities at different taxonomic levels. BactoTraits can be used, for example, to improve predictions of ecological responses to natural/anthropogenic pressures and to support biomonitoring, management and conservation strategies. The R scripts, as well as the dataset encoded in BactoTraits, are available at: https://doi.org/10.24396/ORDAR-182 .

Indexed as

BacteriaBiodiversityMicrobiotaRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID41634049
PMCPMC12966283

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.