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Natural selection in compartmentalized environment with reshuffling.

A S Zadorin1,2, Y Rondelez3

  • 1Gulliver, ESPCI Paris, PSL University, CNRS, 75005, Paris, France. anton.zadorin@espci.fr.

Journal of Mathematical Biology
|July 15, 2019
PubMed
Summary
This summary is machine-generated.

High-throughput compartmentalized in vitro evolution enables protein engineering by grouping genotypes in microscopic compartments. This study shows selection efficiency is resilient to multiple genotypes per compartment, even with increased occupancy.

Keywords:
Acellular genotype-phenotype linkageCo-compartmentalizationDirected evolutionFrequency-dependent selectionGroup selection

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Area of Science:

  • Biotechnology
  • Evolutionary Biology
  • Protein Engineering

Background:

  • High-throughput compartmentalized in vitro evolution is a novel protein engineering technique.
  • Genotypes are distributed in microscopic compartments (emulsion droplets) for phenotype-based selection.
  • Random partitioning can lead to multiple genotypes within a single compartment, mimicking group selection.

Purpose of the Study:

  • To investigate the impact of increased mean compartment occupancy on selection efficiency in compartmentalized in vitro evolution.
  • To develop a theoretical framework for analyzing selection dynamics with varying genotype distributions and occupancies.
  • To assess the resilience of selection processes to multiple genotypes per compartment.

Main Methods:

  • Theoretical investigation of selection dynamics in a subdivided population.
  • Derivation of an update equation for phenotype distributions and mean occupancy.
  • Analysis of selection efficiency under linear additive fitness models.
  • Extension of results to non-linear/non-additive fitnesses and non-Poissonian distributions.

Main Results:

  • The best genotype is selected irrespective of mean compartment occupancy for linear additive fitness.
  • Selection remains robust even with multiple genotypes per compartment.
  • Selection efficiency decreases approximately inversely proportional to mean occupancy at high values.

Conclusions:

  • Compartmentalized in vitro evolution is a resilient protein engineering method.
  • Mean occupancy has a predictable impact on selection speed but not on the selection of the best genotype.
  • Findings are applicable to both engineered systems and natural compartmentalized replicators like viruses and RNA.