Evidence map›Paper›PMID 31339876›Full record

ArticlePLoS computational biology2019

Syntrophy emerges spontaneously in complex metabolic systems.

Eric Libby, Laurent Hébert-Dufresne, Sayed-Rzgar Hosseini, Andreas Wagner

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. The sparse macroecology of microbiology.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  6. Closed ecosystems extract energy through self-organized nutrient cycles.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Metabolic compatibility and the rarity of prokaryote endosymbioses.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  13. Article
  14. Review
  15. Symbiosis and the Anthropocene.Symbiosis (Philadelphia, Pa.) · 2021
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. From Microbial Communities to Distributed Computing Systems.Frontiers in bioengineering and biotechnology · 2020
    Review
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.

Eric LibbyIntegrated Science Lab, Umeå University, Umeå, Sweden.ORCID 0000-0002-6569-5793
Laurent Hébert-DufresneSanta Fe Institute, Santa Fe, New Mexico, United States of America.
Sayed-Rzgar HosseiniDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-7711-4207
Andreas WagnerSanta Fe Institute, Santa Fe, New Mexico, United States of America.

Funding

Using Dengue Controlled Human Infection Model to Identify Adaptive Immune Correlates of ProtectionP20GM125498 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Ellen Kozelka · 2018 to 2026
$24.9M
NIGMS NIH HHS P20 GM125498
6 · The paper itself

Abstract

Syntrophy allows a microbial community as a whole to survive in an environment, even though individual microbes cannot. The metabolic interdependence typical of syntrophy is thought to arise from the accumulation of degenerative mutations during the sustained co-evolution of initially self-sufficient organisms. An alternative and underexplored possibility is that syntrophy can emerge spontaneously in communities of organisms that did not co-evolve. Here, we study this de novo origin of syntrophy using experimentally validated computational techniques to predict an organism's viability from its metabolic reactions. We show that pairs of metabolisms that are randomly sampled from a large space of possible metabolism and viable on specific primary carbon sources often become viable on new carbon sources by exchanging metabolites. The same biochemical reactions that are required for viability on primary carbon sources also confer viability on novel carbon sources. Our observations highlight a new and important avenue for the emergence of metabolic adaptations and novel ecological interactions.

Indexed as

Metabolic Networks and PathwaysModels, BiologicalAdaptation, PhysiologicalAlgorithmsCarbonComputational BiologyEscherichia coliMarkov ChainsMicrobiotaMonte Carlo MethodMutationSymbiosisCarbon

Identifiers

PMID31339876
PMCPMC6655585

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.