Fitness loss and library size determination in saturation mutagenesis

Nondegenerate Saturation Mutagenesis: Library Construction and Analysis via MAX and ProxiMAX Randomization

Protein engineering can enhance desirable features and improve performance outside of the natural context. Several strategies have been adopted over the years for gene diversification, and engineering of modular proteins in particular is most effective when a high-throughput, library-based approach is employed. Nondegenerate saturation mutagenesis plays a dynamic role in engineering proteins by targeting multiple codons to generate massively diverse gene libraries. Herein, we describe the nondegenerate saturation mutagenesis techniques that we have developed for contiguous (ProxiMAX) and noncontiguous (MAX) randomized codon generation to create precisely defined, diverse gene libraries, in the context of other fully nondegenerate strategies. ProxiMAX randomization comprises saturation cycling with repeated cycles of blunt-ended ligation, type IIS restriction, and PCR amplification, and is now a commercially automated process predominantly used for antibody library generation. MAX randomization encompasses a manual process of selective hybridisation between individual custom oligonucleotide mixes and a conventionally randomized template and is principally employed in the research laboratory setting, to engineer alpha helical proteins and active sites of enzymes. DNA libraries generated using either technology create high-throughput amino acid substitutions via codon randomization, to generate genetically diverse clones.

Darwin Assembly: fast, efficient, multi-site bespoke mutagenesis

Engineering proteins for designer functions and biotechnological applications almost invariably requires (or at least benefits from) multiple mutations to non-contiguous residues. Several methods for multiple site-directed mutagenesis exist, but there remains a need for fast and simple methods to efficiently introduce such mutations – particularly for generating large, high quality libraries for directed evolution. Here, we present Darwin Assembly, which can deliver high quality libraries of >10⁸ transformants, targeting multiple (>10) distal sites with minimal wild-type contamination (<0.25% of total population) and which takes a single working day from purified plasmid to library transformation. We demonstrate its efficacy with whole gene codon reassignment of chloramphenicol acetyl transferase, mutating 19 codons in a single reaction in KOD DNA polymerase and generating high quality, multiple-site libraries in T7 RNA polymerase and Tgo DNA polymerase. Darwin Assembly uses commercially available enzymes, can be readily automated, and offers a cost-effective route to highly complex and customizable library generation.

Speeding up directed evolution: Combining the advantages of solid-phase combinatorial gene synthesis with statistically guided reduction of screening effort

Efficient and economic methods in directed evolution at the protein, metabolic, and genome level are needed for biocatalyst development and the success of synthetic biology. In contrast to random strategies, semirational approaches such as saturation mutagenesis explore the sequence space in a focused manner. Although several combinatorial libraries based on saturation mutagenesis have been reported using solid-phase gene synthesis, direct comparison with traditional PCR-based methods is currently lacking. In this work, we compare combinatorial protein libraries created in-house via PCR versus those generated by commercial solid-phase gene synthesis. Using descriptive statistics and probabilistic distributions on amino acid occurrence frequencies, the quality of the libraries was assessed and compared, revealing that the outsourced libraries are characterized by less bias and outliers than the PCR-based ones. Afterward, we screened all libraries following a traditional algorithm for almost complete library coverage and compared this approach with an emergent statistical concept suggesting screening a lower portion of the protein sequence space. Upon analyzing the biocatalytic landscapes and best hits of all combinatorial libraries, we show that the screening effort could have been reduced in all cases by more than 50%, while still finding at least one of the best mutants.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Site-saturation mutagenesis by overlap extension PCR

Site-saturation mutagenesis is a proven strategy for generating high-quality variant gene libraries of a defined size. Variation is introduced via incorporation of degenerate base combinations at specific codon locations, giving rise to a precise series of amino acid substitutions in the encoded protein. Here we describe a simple and efficient overlap PCR protocol for the introduction of degenerate bases at either single or multiple codon locations. The resulting libraries can then be directly screened for improved protein function as either an independent directed evolution study or an adjunct to random mutagenesis strategies (such as error-prone PCR) that are, in isolation, unlikely to access the full repertoire of possible amino acid substitutions at any given position.