Evolution of multicellularity by collective integration of spatial information
Abstract
At the origin of multicellularity, cells may have evolved aggregation in response to predation, for functional specialisation or to allow large-scale integration of environmental cues. These group-level properties emerged from the interactions between cells in a group, and determined the selection pressures experienced by these cells. We investigate the evolution of multicellularity with an evolutionary model where cells search for resources by chemotaxis in a shallow, noisy gradient. Cells can evolve their adhesion to others in a periodically changing environment, where a cell's fitness solely depends on its distance from the gradient source. We show that multicellular aggregates evolve because they perform chemotaxis more efficiently than single cells. Only when the environment changes too frequently, a unicellular state evolves which relies on cell dispersal. Both strategies prevent the invasion of the other through interference competition, creating evolutionary bi-stability. Therefore, collective behaviour can be an emergent selective driver for undifferentiated multicellularity.
Data availability
All data in this study are produced with custom-made software. The source code is freely available at https://github.com/escolizzi/Cell_Evolution_stickymoves
Article and author information
Author details
Funding
Nederlands Wetenschap Agenda (StartImpuls)
- Enrico Sandro Colizzi
Nederlands Wetenschap Agenda (StartImpuls)
- Renske MA Vroomans
NWO/ENW-VICI (865.17.004)
- Roeland MH Merks
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Colizzi 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
-
- 20,752
- views
-
- 909
- downloads
-
- 23
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.