Toggle Main Menu Toggle Search

Open Access padlockePrints

Multispecies population dynamics of prebiotic compositional assemblies

Lookup NU author(s): Omer Markovitch


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Present life portrays a two-tier phenomenology: molecules compose supramolecular structures, such as cells or organisms, which in turn portray population behaviors, including selection, evolution and ecological dynamics. Prebiotic models have often focused on evolution in populations of self-replicating molecules, without explicitly invoking the intermediate molecular-to-supramolecular transition. Here, we explore a prebiotic model that allows one to relate parameters of chemical interaction networks within molecular assemblies to emergent population dynamics. We use the graded autocatalysis replication domain (GARD) model, which simulates the network dynamics within amphiphile-containing molecular assemblies, and exhibits quasi-stationary compositional states termed compotype species. These grow by catalyzed accretion, divide and propagate their compositional information to progeny in a replication-like manner. The model allows us to ask how molecular network parameters influence assembly evolution and population dynamics parameters. In 1000 computer simulations, each embodying different parameter set of the global chemical interaction network parameters, we observed a wide range of behaviors. These were analyzed by a multi species logistic model often used for analyzing population ecology (rK or Lotka–Volterra competition model). We found that compotypes with a larger intrinsic molecular repertoire show a higher intrinsic growth (r) and lower carrying capacity (K), as well as lower replication fidelity. This supports a prebiotic scenario initiated by fast-replicating assemblies with a high molecular diversity, evolving into more faithful replicators with narrower molecular repertoires.

Publication metadata

Author(s): Markovitch O, Lancet D

Publication type: Article

Publication status: Published

Journal: Journal of Theoretical Biology

Year: 2014

Volume: 357

Pages: 26-34

Print publication date: 21/09/2014

Online publication date: 14/05/2014

Acceptance date: 01/05/2014

ISSN (print): 0022-5193

ISSN (electronic): 1095-8541

Publisher: Academic Press


DOI: 10.1016/j.jtbi.2014.05.005


Altmetrics provided by Altmetric