Directed evolution is a mimic of the natural evolution cycle in a laboratory setting. Evolution requires three things to happen: variation between replicators, that the variation causes fitness differences upon which selection acts, and that this variation is heritable. In DE, a single gene is evolved by iterative rounds of mutagenesis, selection or screening, and amplification. Rounds of these steps are typically repeated, using the best variant from one round as the template for the next to achieve stepwise improvements.
The likelihood of success in a directed evolution experiment is directly related to the total library size, as evaluating more mutants increases the chances of finding one with the desired properties.
The first step in performing a cycle of directed evolution is the generation of a library of variant genes. The sequence space for random sequence is vast (10130 possible sequences for a 100 amino acid protein) and extremely sparsely populated by functional proteins. Neither experimental, nor natural evolution can ever get close to sampling so many sequences. Of course, natural evolution samples variant sequences close to functional protein sequences and this is imitated in DE by mutagenising an already functional gene.
Some calculations suggest it is entirely feasible that for all practical (i.e. functional and structural) purposes, protein sequence space has been fully explored during the course of evolution of life on Earth.
An alternative to selection is a screening system. Each variant gene is individually expressed and assayed to quantitatively measure the activity (most often by a colourgenic or fluorogenic product). The variants are then ranked and the experimenter decides which variants to use as templates for the next round of DE. Even the most high throughput assays usually have lower coverage than selection methods but give the advantage of producing detailed information on each one of the screened variants. This disaggregated data can also be used to characterise the distribution of activities in libraries which is not possible in simple selection systems. Screening systems, therefore, have advantages when it comes to experimentally characterising adaptive evolution and fitness landscapes.
When functional proteins have been isolated, it is necessary that their genes are too, therefore a genotype–phenotype link is required. This can be covalent, such as mRNA display where the mRNA gene is linked to the protein at the end of translation by puromycin. Alternatively the protein and its gene can be co-localised by compartmentalisation in living cells or emulsion droplets. The gene sequences isolated are then amplified by PCR or by transformed host bacteria. Either the single best sequence, or a pool of sequences can be used as the template for the next round of mutagenesis. The repeated cycles of Diversification-Selection-Amplification generate protein variants adapted to the applied selection pressures.
A restriction of directed evolution is that a high-throughput assay is required in order to measure the effects of a large number of different random mutations. This can require extensive research and development before it can be used for directed evolution. Additionally, such assays are often highly specific to monitoring a particular activity and so are not transferable to new DE experiments.
Additionally, selecting for improvement in the assayed function simply generates improvements in the assayed function. To understand how these improvements are achieved, the properties of the evolving enzyme have to be measured. Improvement of the assayed activity can be due to improvements in enzyme catalytic activity or enzyme concentration. There is also no guarantee that improvement on one substrate will improve activity on another. This is particularly important when the desired activity cannot be directly screened or selected for and so a ‘proxy’ substrate is used. DE can lead to evolutionary specialisation to the proxy without improving the desired activity. Consequently, choosing appropriate screening or selection conditions is vital for successful DE.
The speed of evolution in an experiment also poses a limitation on the utility of directed evolution. For instance, evolution of a particular phenotype, while theoretically feasible, may occur on time-scales that are not practically feasible. Recent theoretical approaches have aimed to overcome the limitation of speed through an application of counter-diabatic driving techniques from statistical physics, though this has yet to be implemented in a directed evolution experiment.
Combined, 'semi-rational' approaches are being investigated to address the limitations of both rational design and directed evolution. Beneficial mutations are rare, so large numbers of random mutants have to be screened to find improved variants. 'Focused libraries' concentrate on randomising regions thought to be richer in beneficial mutations for the mutagenesis step of DE. A focused library contains fewer variants than a traditional random mutagenesis library and so does not require such high-throughput screening.
Creating a focused library requires some knowledge of which residues in the structure to mutate. For example, knowledge of the active site of an enzyme may allow just the residues known to interact with the substrate to be randomised. Alternatively, knowledge of which protein regions are variable in nature can guide mutagenesis in just those regions.
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