Selection Dynamics in Transient Compartmentalization

Abstract

Transient compartments have been recently shown to be able to maintain functional replicators in the context of prebiotic studies. Here, we show that a broad class of selection dynamics is able to achieve this goal. We identify two key parameters, the relative amplification of nonactive replicators (parasites) and the size of compartments. These parameters account for competition and diversity, and the results are relevant to similar multilevel selection problems, such as those found in virus-host ecology and trait group selection.

Transient Compartmentalization dynamics in the presence of mutations and noise

“…If parasites grow faster, we have γ > α, and thus Λ > 1, which is the regime considered in Ref. [15].…”

“…The motivation of discussing noise in more details comes from the realization that replication is inherently stochastic when a small number of replicators are present in compartments. Therefore, the deterministic approach used in our previous work [15] may seem like a severe approximation. In fact, it is important to appreciate that although our deterministic model neglects some sources of noise such as fluctuations in the growth rates, it includes fluctuations due to the smallness of the number of replicators present in the initial condition.…”

“…In order to address this point, and also to assess the role of transient compartmentalization using a quantitative theoretical model, we introduced a general class of multilevel selection with transient compartmentalization [15]. This class includes several scenarios for the origin of life based on various types of compartments (lipid vesicles [16], pores [17,18], inorganic compartments [19], .. ) or various protocols of transient compartmentalization [20,21] and a recent experiment, in which small droplets containing RNA in a microfluidic device [22] were used as compartments.…”

“…In this paper, we go beyond the analysis carried out in our previous work [15] by including the effect of mutations and noise. The motivation of including mutations comes from experiments, since mutations play a role in the RNA droplet experiment [22] which inspired us.…”

“…In Sec. 2, we recapitulate the essence of the mutation-free model which we have introduced in [15], then in Sec. 3, we introduce an extension of that model to include deterministic mutations.…”