Selection platforms for directed evolution in synthetic biology

Abstract

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code.

Keywords: directed evolution; protein engineering; selection methodologies; synthetic biology; synthetic nucleic acid (XNA); xenobiology.

Figure 1. Principles of selection in directed evolution

The goal of all selection (and screening) platforms is to partition a potentially large population (shown in grey as the bulk diversity) by function (phenotype) ensuring the recovery of the genetic information that accounts for that phenotype. Strong phenotype–genotype linkages allow efficient isolation of mutants with the desired function (green). Breakdown of that linkage results in false negatives (variants that have the desired function but that are not efficiently recovered–yellow) and false positives (variants that are recovered independently of the desired function–blue), which are integral aspects of all selection strategies.

Figure 2. In vivo and ex vivo directed evolution

Both strategies use the cell (or phage particle) as the physical linkage between genotype and phenotype through the directed evolution process. Ex vivo platforms tend to focus diversity (a) on to a single target gene, whereas in vivo platforms can extend that to metabolic pathways or even whole genomes. Once generated, the diverse repertoires are partitioned (b) with active (blue) variants preferentially recovered over inactive variants (orange). Partition by phenotype is linked to genotype recovery and amplification (c) which can take place in a single step if cells are still viable (as is the norm for in vivo methodologies). Alternatively, as shown for the ex vivo selection (light green boxes), genotype recovery and amplification can be separated, introducing different limitations to the process. The amplified recovered genotypes are the starting point of a subsequent round of selection.

Figure 3. In vitro selection

Platforms for in vitro selection can be broadly divided by the available redundancy of phenotype and genotype linkages. In a number of selection strategies, the link is unique–a lone genotype molecule is linked to a lone molecule that may have the phenotype being selected (a). Compartmentalization strategies enable redundancy in the system with one-to-many [redundant genotype to lone phenotype (b) or lone genotype to pooled phenotype (not shown)] and many-to-many [redundant genotype to pooled phenotype (c)] mappings between phenotype and genotype available.