Evidence map›Paper›PMID 30194430›Full record

ArticleThe ISME journal2019

Consistent microbial dynamics and functional community patterns derived from first principles.

Hadrien Delattre, Elie Desmond-Le Quéméner, Christian Duquennoi, Ahlem Filali, Théodore Bouchez

Abstract read
In one paragraph

Article in The ISME journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Ecosystems as adaptive living circuits.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Proto-dolomite formation in microbial consortia dominated by Halomonas strains.Extremophiles : life under extreme conditions · 2019
    Article
  12. 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

5 authors.

Hadrien DelattreIrstea, UR HBAN, F-92761, Antony, France.
Elie Desmond-Le QuéménerIrstea, UR HBAN, F-92761, Antony, France.
Christian DuquennoiIrstea, UR HBAN, F-92761, Antony, France.
Ahlem FilaliIrstea, UR HBAN, F-92761, Antony, France.
Théodore BouchezIrstea, UR HBAN, F-92761, Antony, France. theodore.bouchez@irstea.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial communities are key engines that drive earth's biogeochemical cycles. However, existing ecosystem models have only limited ability to predict microbial dynamics and require the calibration of multiple population-specific empirical equations. In contrast, we build on a new kinetic "Microbial Transition State" (MTS) theory of growth derived from first principles. We show how the theory coupled to simple mass and energy balance calculations provides a framework with intrinsically important qualitative properties to model microbial community dynamics. We first show how the theory can simultaneously account for the influence of all the resources needed for growth (electron donor, acceptor, and nutrients) while still producing consistent dynamics that fulfill the Liebig rule of a single limiting substrate. We also show consistent patterns of energy-dependent microbial successions in mixed culture without the need for calibration of population-specific parameters. We then show how this approach can be used to model a simplified activated sludge community. To this end, we compare MTS-derived dynamics with those of a widely used activated sludge model and show that similar growth yields and overall dynamics can be obtained using two parameters instead of twelve. This new kinetic theory of growth grounded by a set of generic physical principles parsimoniously gives rise to consistent microbial population and community dynamics, thereby paving the way for the development of a new class of more predictive microbial ecosystem models.

Indexed as

EcosystemKineticsModels, BiologicalSewageSewage

Identifiers

PMID30194430
PMCPMC6331576

What OpenQuestion holds

Textmetadata
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.