Evidence map›Paper›PMID 36482420›Full record

ArticleMicrobiome2022

Multi-genome metabolic modeling predicts functional inter-dependencies in the Arabidopsis root microbiome.

Alice Mataigne, Nathan Vannier, Philippe Vandenkoornhuyse, Stéphane Hacquard

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 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing 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.

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

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

  1. Root colonization by beneficial rhizobacteria.FEMS microbiology reviews · 2024
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  12. The Need for a Systems Biology Approach in Cancer Explained.International journal of molecular sciences · 2025
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  15. Evaluating plant growth-defense trade-offs by modeling the interaction between primary and secondary metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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.

Alice MataigneUniversité de Rennes 1, CNRS, UMR6553 ECOBIO, Campus Beaulieu, 35000, Rennes, France.
Nathan VannierMax Planck Institute for Plant Breeding Research, Department of Plant Microbe Interactions, 50829, Cologne, Germany.
Philippe VandenkoornhuyseUniversité de Rennes 1, CNRS, UMR6553 ECOBIO, Campus Beaulieu, 35000, Rennes, France. philippe.vandenkoornhuyse@univ-rennes1.fr.
Stéphane HacquardMax Planck Institute for Plant Breeding Research, Department of Plant Microbe Interactions, 50829, Cologne, Germany. hacquard@mpipz.mpg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrom a theoretical ecology point of view, microbiomes are far more complex than expected. Besides competition and competitive exclusion, cooperative microbe-microbe interactions have to be carefully considered. Metabolic dependencies among microbes likely explain co-existence in microbiota. METHODOLOGY: In this in silico study, we explored genome-scale metabolic models (GEMs) of 193 bacteria isolated from Arabidopsis thaliana roots. We analyzed their predicted producible metabolites under simulated nutritional constraints including "root exudate-mimicking growth media" and assessed the potential of putative metabolic exchanges of by- and end-products to avoid those constraints.

resultsWe found that the genome-encoded metabolic potential is quantitatively and qualitatively clustered by phylogeny, highlighting metabolic differentiation between taxonomic groups. Random, synthetic combinations of increasing numbers of strains (SynComs) indicated that the number of producible compounds by GEMs increased with average phylogenetic distance, but that most SynComs were centered around an optimal phylogenetic distance. Moreover, relatively small SynComs could reflect the capacity of the whole community due to metabolic redundancy. Inspection of 30 specific end-product metabolites (i.e., target metabolites: amino acids, vitamins, phytohormones) indicated that the majority of the strains had the genetic potential to produce almost all the targeted compounds. Their production was predicted (1) to depend on external nutritional constraints and (2) to be facilitated by nutritional constraints mimicking root exudates, suggesting nutrient availability and root exudates play a key role in determining the number of producible metabolites. An answer set programming solver enabled the identification of numerous combinations of strains predicted to depend on each other to produce these targeted compounds under severe nutritional constraints thus indicating a putative sub-community level of functional redundancy.

conclusionsThis study predicts metabolic restrictions caused by available nutrients in the environment. By extension, it highlights the importance of the environment for niche potential, realization, partitioning, and overlap. Our results also suggest that metabolic dependencies and cooperation among root microbiota members compensate for environmental constraints and help maintain co-existence in complex microbial communities. Video Abstract.

Indexed as

ArabidopsisArabidopsis ProteinsMicrobiotaEcologyIntracellular Signaling Peptides and ProteinsPhylogenyArabidopsis ProteinsGEM protein, ArabidopsisIntracellular Signaling Peptides and Proteins

Identifiers

PMID36482420
PMCPMC9733318

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LicenceCC BY
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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.