Simulating the origins of life: The dual role of RNA replicases as an obstacle to evolution

Abstract

Despite years of study, it is still not clear how life emerged from inanimate matter and evolved into the complex forms that we observe today. One of the most recognized hypotheses for the origins of life, the RNA World hypothesis, assumes that life was sparked by prebiotic replicating RNA chains. In this paper, we address the problems caused by the interplay between hypothetical prebiotic RNA replicases and RNA parasitic species. We consider the coexistence of parasite RNAs and RNA replicases as well as the impact of parasites on the further evolution of replicases. For these purposes, we used multi-agent modeling techniques that allow for realistic assumptions regarding the movement and spatial interactions of modeled species. The general model used in this study is based on work by Takeuchi and Hogeweg. Our results confirm that the coexistence of parasite RNAs and replicases is possible in a spatially extended system, even if we take into consideration more realistic assumptions than Takeuchi and Hogeweg. However, we also showed that the presence of trade-off that takes into the account an RNA folding process could still pose a serious obstacle to the evolution of replication. We conclude that this might be a cause for one of the greatest transitions in life that took place early in evolution-the separation of the function between DNA templates and protein enzymes, with a central role for RNA species.

Fig 1. Interactions modeled by the multi-agent system.

Parasites or replicases can form complexes with other replicases at a_P(1 − l_P) and a_R(1 − l_R) rates, respectively. A two replicase complex can either dissociate at a rate of (1 − a_R) or produce a new replicase at rate K. Analogously, a replicase-parasite complex can either dissociate at a rate of (1 − a_P) or produce a new parasite at rate K. Parasites and replicases can also decay at rate d and move at rate D. Similarly, complexes can move at rate D′. The parameters (rate constants) used in this simulation were following: d = 0.182; D = 0.75; D′ = 0.0476; K = 239800; Δt = 1; ∀_i r_i = 0.5.

Fig 2. Images taken during the simulation of the first experiment.

The presented frames were taken after 7k, 40k, 75k and 158k steps. The full movie is available as supplemental material S1 Video, S2 Video, S3 Video, and S4 Video. It is split into four parts because of file size constraints. It is also available in higher quality on the YouTube (https://www.youtube.com/watch?v=mKpiUH0iDoQ). The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 3. Average values of a_P changing over time during the first experiment.

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 4. Average values of l_P changing over time during the first experiment.

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 5. Average values for l_P during the second experiment with l_P0 = 0.0 and l_P0 = 0.7.

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 6. Average values for l_P during the second experiment with l_P0 ranging from 0.1 to 0.6 (0.1 step).

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 7. Average values for a_P during the third experiment with a_P0 ranging from 0 to 1.

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 8. Screen shots from the fourth experiment for various of a_P initial values taken after approximately 80k simulation steps.

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 9. Average values of l_P during the fourth experiment when a_P0 = 0.4 (blue), a_P0 = 0.5 (orange) and a_P0 = 0.6 (green).

The values of parameters used during the experiment are presented in Table 1 and label of Fig 1.

Fig 10. Plots showing the average a_P, a_R, l_P and l_R values during the simulations in the fifth experiment.

The initial values for the investigated parameters were a_P0 = 0.55, a_R0 = 0.7, l_P0 = 0.2, l_R0 = 0.2. The probability of mutation for each parameter was set to 0.01 and the agents were initially distributed on a circle. The values of remaining parameters used during the experiment are presented in label of Fig 1.