1. Ecology
  2. Evolutionary Biology
Download icon

Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

  1. Guilhem Doulcier  Is a corresponding author
  2. Amaury Lambert
  3. Silvia De Monte
  4. Paul B Rainey
  1. École supérieure de physique et de chimie industrielle de la ville de Paris, PSL University, France
  2. Collège de France, France
  3. École Normale Supérieure, France
  4. Max Planck Institute for Evolutionary Biology, Germany
Research Article
  • Cited 10
  • Views 2,150
  • Annotations
Cite this article as: eLife 2020;9:e53433 doi: 10.7554/eLife.53433


Interactions among microbial cells can generate new chemistries and functions, but exploitation requires establishment of communities that reliably recapitulate community-level phenotypes. Using mechanistic mathematical models, we show how simple manipulations to population structure can exogenously impose Darwinian-like properties on communities. Such scaffolding causes communities to participate directly in the process of evolution by natural selection and drives the evolution of cell-level interactions to the point where, despite underlying stochasticity, derived communities give rise to offspring communities that faithfully re-establish parental phenotype. The mechanism is akin to a developmental process (developmental correction) that arises from density dependent interactions among cells. Knowledge of ecological factors affecting evolution of developmental correction has implications for understanding the evolutionary origin of major egalitarian transitions, symbioses, and for top-down engineering of microbial communities.

Data availability

The source code for all simulations and figures in the manuscript isavailable as a zip file uploaded with the manuscript and in a public gitrepository (https://gitlab.com/ecoevomath/estaudel).

Article and author information

Author details

  1. Guilhem Doulcier

    Laboratoire de Génétique de l'Evolution, CNRS UMR 8231, École supérieure de physique et de chimie industrielle de la ville de Paris, PSL University, Paris, France
    For correspondence
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3720-9089
  2. Amaury Lambert

    Center for Interdisciplinary Research in Biology(CIRB), Collège de France, Paris, France
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7248-9955
  3. Silvia De Monte

    Institut de Biologie de l'´Ecole Normale Sup´erieure, École Normale Supérieure, Paris, France
    Competing interests
    No competing interests declared.
  4. Paul B Rainey

    Department of Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Plön, Germany
    Competing interests
    Paul B Rainey, PBR is a founder of MilliDrop InstrumentsReviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0879-5795


Agence Nationale de la Recherche (ANR-10-IDEX-001-02)

  • Guilhem Doulcier
  • Paul B Rainey

Agence Nationale de la Recherche (ANR-10-LABX-54)

  • Silvia De Monte

Agence Nationale de la Recherche (ANR-11-IDEX-0001-02)

  • Silvia De Monte


  • Paul B Rainey

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Wenying Shou, Fred Hutchinson Cancer Research Center, United States

Publication history

  1. Received: November 7, 2019
  2. Accepted: June 12, 2020
  3. Accepted Manuscript published: July 7, 2020 (version 1)
  4. Version of Record published: August 20, 2020 (version 2)


© 2020, Doulcier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


  • 2,150
    Page views
  • 345
  • 10

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Cell Biology
    2. Ecology
    Basile Jacquel et al.
    Tools and Resources Updated

    The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that nonmonotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein superassemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.

    1. Ecology
    Alexander J Werth, Joseph E Corbett

    How fast the brain and muscles can respond to information about prey location constrains visual and echolocating predators in similar ways.