Evidence map›Paper›PMID 35384214›Full record

ArticleEcology letters2022

Contribution of genome-scale metabolic modelling to niche theory.

Antoine Régimbeau, Marko Budinich, Abdelhalim Larhlimi, Juan José Pierella Karlusich, Olivier Aumont, Laurent Memery, Chris Bowler, Damien Eveillard

Abstract readLetter
In one paragraph

Article in Ecology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Matters of life and death in computational cell biology.NPJ systems biology and applications · 2026
    Review
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  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
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  16. 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

8 authors.

Antoine RégimbeauUniversité de Nantes, CNRS, LS2N, Nantes, France.ORCID https://orcid.org/0000-0003-0456-6717
Marko BudinichUniversité de Nantes, CNRS, LS2N, Nantes, France.ORCID https://orcid.org/0000-0003-3541-0547
Abdelhalim LarhlimiUniversité de Nantes, CNRS, LS2N, Nantes, France.
Juan José Pierella KarlusichDépartement de Biologie, Institut de Biologie de l'ENS, École Normale supérieure, CNRS, INSERM, Université PSL, Paris, France.ORCID https://orcid.org/0000-0003-1739-4424
Olivier AumontLaboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques (LOCEAN), IRD-IPSL, Paris, France.ORCID https://orcid.org/0000-0003-3954-506X
Laurent MemeryUniversité de Brest (UBO), CNRS, IRD, Ifremer, Laboratoire des Sciences de l'Environnement Marin, Plouzané, France.
Chris BowlerDépartement de Biologie, Institut de Biologie de l'ENS, École Normale supérieure, CNRS, INSERM, Université PSL, Paris, France.ORCID https://orcid.org/0000-0003-3835-6187
Damien EveillardUniversité de Nantes, CNRS, LS2N, Nantes, France.ORCID https://orcid.org/0000-0002-8162-7360

Funding

BrownCut ANR-19-CE20-0020Centre National de la Recherche Scientifique 80 PRIMEFonds Français pour l'Environnement MondialFRANCE GENOMIQUE ANR-10-INBS-09-08H2020 Environment 835067H2020 Environment 862923MEMO LIFE ANR-10-LABX-54OCEANOMICS ANR-10-INBS-09-08Université de Recherche Paris Sciences et Lettres ANR-11-IDEX-0001-02
6 · The paper itself

Abstract

Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence-absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome-scale description in ecological studies.

Indexed as

EcosystemPhenotypemarine ecologymetabolic networkmetabolic nichemicrobial ecologymolecular ecologyniche modelling

Identifiers

PMID35384214
PMCPMC9324083

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.