Research Article: Predicting species emergence in simulated complex pre-biotic networks

Date Published: February 15, 2018

Publisher: Public Library of Science

Author(s): Omer Markovitch, Natalio Krasnogor, Ricard V. Solé.


An intriguing question in evolution is what would happen if one could “replay” life’s tape. Here, we explore the following hypothesis: when replaying the tape, the details (“decorations”) of the outcomes would vary but certain “invariants” might emerge across different life-tapes sharing similar initial conditions. We use large-scale simulations of an in silico model of pre-biotic evolution called GARD (Graded Autocatalysis Replication Domain) to test this hypothesis. GARD models the temporal evolution of molecular assemblies, governed by a rates matrix (i.e. network) that biases different molecules’ likelihood of joining or leaving a dynamically growing and splitting assembly. Previous studies have shown the emergence of so called compotypes, i.e., species capable of replication and selection response. Here, we apply networks’ science to ascertain the degree to which invariants emerge across different life-tapes under GARD dynamics and whether one can predict these invariant from the chemistry specification alone (i.e. GARD’s rates network representing initial conditions). We analysed the (complex) rates’ network communities and asked whether communities are related (and how) to the emerging species under GARD’s dynamic, and found that the communities correspond to the species emerging from the simulations. Importantly, we show how to use the set of communities detected to predict species emergence without performing any simulations. The analysis developed here may impact complex systems simulations in general.

Partial Text

The Origins of Life (OOL) field attempts to understand the transition from a mixture of life-less molecules to life-full entities, with protocells [1–4] as intermediate (potentially viable) milestones along the non-living to living spectrum [5]. A widely accepted definition of minimal life is: a self-sustaining system capable of undergoing Darwinian evolution [6], while other definitions are often similar (e.g. [7]). A minimally living entity needs not be a cell as we know it but could be a much simpler protocell [2, 8–15], i.e. container with some necessary molecular content. Two major schools tackle the problem of transition from non-life to life: the genetic, or replicator-first approach, and the metabolism-first approach. The replicator-first approach focuses on a single self-perpetuating informational biopolymer, e.g., RNA, as the first step, and it is thus often referred to as the “RNA world” [16–20]. In contrast, the metabolism-first approach [2, 9, 11, 21–23] focuses on a network of chemical reactions among simpler chemical components that became endowed with some reproductive characteristics [2, 8, 9, 11–13].

The GARD model performs biased and far from equilibrium random walks on a network that has previously been linked to pre-biotic evolutionary dynamics. Via community analyses, we were able to bypass the dynamic trajectories of the stochastic simulator and use the ensemble of detected communities to predict the emergence of (proto) species of this system as well as their invariant content. Interestingly, the morphology of assigned communities is different than that of non-assigned ones, which deserve further scrutiny in order to understand the nature of this difference, how the various topological characteristics affect dynamics as well as the precise role of those un-assigned communities.




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