Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity
Abstract
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
Funding
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
Max-Planck-Gesellschaft
- Paul B Rainey
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 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.
Metrics
-
- 3,300
- views
-
- 515
- downloads
-
- 60
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 60
- citations for umbrella DOI https://doi.org/10.7554/eLife.53433