Evidence map›Paper›PMID 38285940›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2024

Structured community transitions explain the switching capacity of microbial systems.

Chengyi Long, Jie Deng, Jen Nguyen, Yang-Yu Liu, Eric J Alm, Ricard Solé, Serguei Saavedra

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
22.6field-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

12 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
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  9. Observational
  10. Modeling tumors as species-rich ecological communities.bioRxiv : the preprint server for biology · 2024
    Article
  11. Article
  12. Towards a fundamental theory of taxon transitions in microbial communities.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Chengyi LongDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0002-6005-3740
Jie DengDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0002-0604-7884
Jen NguyenCenter for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0002-8286-0738
Yang-Yu LiuChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115.ORCID 0000-0003-2728-4907
Eric J AlmDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.
Ricard SoléComplex Systems Lab, Universitat Pompeu Fabra, Barcelona 08003, Spain.
Serguei SaavedraInstitució Catalana de Recerca i Estudis Avançats, Barcelona 08010, Spain.ORCID 0000-0003-1768-363X
Massachusetts Institute of Technology · USInstitució Catalana de Recerca i Estudis Avançats · ESBrigham and Women's Hospital · US

Funding

Functional Redundancy of Human Microbiome and its Implication in Fecal Microbiota TransplantationR01AI141529 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI LIU, YANG-YU · 2019 to 2023
$4.5M
NIAID NIH HHS R01 AI141529
6 · The paper itself

Abstract

Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.

Indexed as

EcologyEnvironmentMicrobiotacommunity dynamicsfeasibilityinformation theorymicrobiotastructuralism

Identifiers

PMID38285940
PMCPMC10861894
OpenAlexW4391308366

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.