Natural selection in compartmentalized environment with reshuffling

TL;DR

This paper provides a theoretical analysis of how compartmentalization and reshuffling affect natural selection efficiency in in vitro evolution, showing resilience of selection even with multiple genotypes per compartment.

Contribution

It derives a general update equation for selection dynamics in subdivided populations with various fitness functions and distributions, extending understanding of compartmentalized selection processes.

Findings

Selection remains effective regardless of mean occupancy.

Selection speed decreases inversely with mean occupancy at high values.

Results apply to natural genetic replicators like viruses and RNA.

Abstract

The emerging field of high-throughput compartmentalized in vitro evolution is a promising new approach to protein engineering. In these experiments, libraries of mutant genotypes are randomly distributed and expressed in microscopic compartments - droplets of an emulsion. The selection of desirable variants is performed according to the phenotype of each compartment. The random partitioning leads to a fraction of compartments receiving more than one genotype making the whole process a lab implementation of the group selection. From a practical point of view (where efficient selection is typically sought), it is important to know the impact of the increase in the mean occupancy of compartments on the selection efficiency. We carried out a theoretical investigation of this problem in the context of selection dynamics for an infinite non-mutating subdivided population that randomly colonizes an infinite number of patches (compartments) at each reproduction cycle. We derive here an update equation for any distribution of phenotypes and any value of the mean occupancy. Using this result, we demonstrate that, for the linear additive fitness, the best genotype is still selected regardless of the mean occupancy. Furthermore, the selection process is remarkably resilient to the presence of multiple genotypes per compartments, and slows down approximately inversely proportional to the mean occupancy at high values. We extend out results to more general expressions that cover nonadditive and non-linear fitnesses, as well non-Poissonian distribution among compartments. Our conclusions may also apply to natural genetic compartmentalized replicators, such as viruses or early trans-acting RNA replicators.