Growth and Division in a Dynamic Protocell Model


1 Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, v. Campi 213a, 41125 Modena, Italy
2 Department of Environmental Sciences (DAIS), University Ca’ Foscari, Ca’ Minich, S. Marco 2940, 30124 Venice, Italy
3 Department of Informatics, Systems and Communication, University of Milan-Bicocca, Viale Sarca, 336, 20126 Milano, Italy
4 SYSBIO—Centre for Systems Biology, University of Milan-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
5 Department of Mathematics and Namur Center for Complex Systems—naXys, University of Namur, rue de Bruxelles 61, B-5000 Namur, Belgium
6 European Centre for Living Technology, University Ca’ Foscari, Ca’ Minich, S. Marco 2940, 30124 Venice, Italy
*Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Life 20144(4), 837-864;
Received: 30 August 2014 / Revised: 25 October 2014 / Accepted: 10 November 2014 / Published: 3 December 2014
In this paper a new model of growing and dividing protocells is described, whose main features are (i) a lipid container that grows according to the composition of the molecular milieu (ii) a set of “genetic memory molecules” (GMMs) that undergo catalytic reactions in the internal aqueous phase and (iii) a set of stochastic kinetic equations for the GMMs. The mass exchange between the external environment and the internal phase is described by simulating a semipermeable membrane and a flow driven by the differences in chemical potentials, thereby avoiding to resort to sometimes misleading simplifications, e.g., that of a flow reactor. Under simple assumptions, it is shown that synchronization takes place between the rate of replication of the GMMs and that of the container, provided that the set of reactions hosts a so-called RAF (Reflexive Autocatalytic, Food-generated) set whose influence on synchronization is hereafter discussed. It is also shown that a slight modification of the basic model that takes into account a rate-limiting term, makes possible the growth of novelties, allowing in such a way suitable evolution: so the model represents an effective basis for understanding the main abstract properties of populations of protocells. View Full-Text

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