Evidence map›Paper›PMID 35577982›Full record

ReviewNature ecology & evolution2022

Ecological modelling approaches for predicting emergent properties in microbial communities.

Naomi Iris van den Berg, Daniel Machado, Sophia Santos, Isabel Rocha, Jeremy Chacón, William Harcombe, Sara Mitri, Kiran R Patil

Open access · goldAbstract readReview
In one paragraph

Review in Nature ecology & evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 2 pooled it
18.2field-weighted citation impact, top 1% of its field
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

113 citing papers in PubMed, 2 syntheses or guidelines pooled it, 233 citations in OpenAlex.

  1. Principles for Rigorous Design and Application of Synthetic Microbial Communities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  10. Biofilm synergy byBiofilm · 2026
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  19. Microbial biotechnology meets ecological theory: a unified framework to design industrial microbial consortia.International microbiology : the official journal of the Spanish Society for Microbiology · 2026
    Review
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53 more citing papers are in PubMed but not listed here.

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 at 6 institutions in 5 countries.

Naomi Iris van den BergMedical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-4516-8558
Daniel MachadoDepartment of Biotechnology and Food Science, Norwegian University of Science and Technology, Trondheim, Norway.
Sophia SantosCentre of Biological Engineering, University of Minho, Braga, Portugal.ORCID http://orcid.org/0000-0003-4700-6066
Isabel RochaInstituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal.
Jeremy ChacónEcology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA.
William HarcombeEcology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0001-8445-2052
Sara MitriDépartement de Microbiologie Fondamentale, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0003-3930-5357
Kiran R PatilMedical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK. kp533@cam.ac.uk.ORCID http://orcid.org/0000-0002-6166-8640
University of Cambridge · GBUniversity of Minnesota · USNorwegian University of Science and Technology · NOUniversidade Nova de Lisboa · PTUniversity of Lausanne · CHUniversity of Minho · PT

Funding

Systems biology and the evolutionary dynamics in a synthetic microbial communityR01GM121498 · NIGMS · UNIVERSITY OF MINNESOTA · PI HARCOMBE, WILLIAM · 2017 to 2021
$1.5M
European Research Council 715097European Research Council 866028Medical Research Council MC_UU_00025/11NIGMS NIH HHS R01 GM121498
6 · The paper itself

Abstract

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.

Indexed as

MicrobiotaModels, BiologicalModels, Theoretical

Identifiers

PMID35577982
PMCPMC7613029
OpenAlexW4280615884

What OpenQuestion holds

Textmetadata
LicenceTDM
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.