Stochastic Emergence of Two Distinct Self-Replicators from a Dynamic Combinatorial Library

Abstract

Unraveling how chemistry can give rise to biology is one of the greatest challenges of contemporary science. Achieving life-like properties in chemical systems is therefore a popular topic of research. Synthetic chemical systems are usually deterministic: the outcome is determined by the experimental conditions. In contrast, many phenomena that occur in nature are not deterministic but caused by random fluctuations (stochastic). Here, we report on how, from a mixture of two synthetic molecules, two different self-replicators emerge in a stochastic fashion. Under the same experimental conditions, the two self-replicators are formed in various ratios over several repeats of the experiment. We show that this variation is caused by a stochastic nucleation process and that this stochasticity is more pronounced close to a phase boundary. While stochastic nucleation processes are common in crystal growth and chiral symmetry breaking, it is unprecedented for systems of synthetic self-replicators.

Figure 1

Molecular structures of building blocks 1 and 2 and schematic representation of the self-replication mechanism. Dithiol-building blocks, 1 and 2, are oxidized (1) to form a mixture of macrocycles with various ring sizes (2) that interconvert using thiol–disulfide chemistry. Two different nucleation steps can occur (3), leading to the formation of stacks of macrocycles containing six or eight monomer units. Both nuclei can elongate (4) to form fibers by consuming smaller macrocycles from the solution. Fragmentation of the fibers by mechanical agitation when the stack is sufficiently long (5) leads to an elongation/fragmentation regime, enabling exponential growth.

Figure 2

Final compositions of a DCL made from equimolar amounts of 1 and 2, split into 10 smaller aliquots. Different outcomes with different ratios between hexamer, octamer, and trimer + tetramer were found.

Figure 3

Kinetic traces of DCLs seeded with preformed self-replicators. (a, b) Seeded with 10 mol % preformed mixed octamer, (c, d) seeded with 10 mol % preformed mixed hexamer, and (e, f) seeded with 5 mol % each of preformed mixed hexamer as well as 5 mol % preformed mixed octamer.

Figure 4

Resulting fit parameters for three repeats, with 10 aliquots each, of the emergence experiments described in Figure 2. X axis depicts nucleation time of the hexamer replicators, Y axis of the octamer replicators. If a data point is found above the diagonal (dashed line) hexamers nucleated before octamers, and vice versa, showing the spread in nucleation times. Error bars indicate standard deviations in the fitting parameters, but these are too small to be observed for most points (R² = 0.933). The weighted average nucleation time is indicated in red, showing that on average, octamers nucleate before hexamers. This observation is consistent with the fact that octamers are the dominant species in the majority of the samples. Above the axes, histograms of the found nucleation times are plotted.

Figure 5

Variation in the fraction of the hexamer (blue) and octamer (green) replicators in the final library composition (determined by RP-UPLC) as a function of the amount of 1. The fraction is defined as the amount of observed replicators divided by the total amount of replicators (hexamers + octamers). The data points show the average and the error bars the standard deviation. The data points at 33, 45, 55, and 67% 1 are averaged over two repeats with five samples each and the data point at 85% 1 is averaged over five samples. The data point at 50% 1 is averaged over five repeats with a total of 45 samples. The dotted red line indicates the boundary between DCLs that are rich in hexamers (below the line) and rich in octamers (above the line).