Polishing the craft of genetic diversity creation in directed evolution

Genetic diversity creation is a core technology in directed evolution where a high quality mutant library is crucial to its success. Owing to its importance, the technology in genetic diversity creation has seen rapid development over the years and its application has diversified into other fields of scientific research. The advances in molecular cloning and mutagenesis since 2008 were reviewed. Specifically, new cloning techniques were classified based on their principles of complementary overhangs, homologous sequences, overlapping PCR and megaprimers and the advantages, drawbacks and performances of these methods were highlighted. New mutagenesis methods developed for random mutagenesis, focused mutagenesis and DNA recombination were surveyed. The technical requirements of these methods and the mutational spectra were compared and discussed with references to commonly used techniques. The trends of mutant library preparation were summarised. Challenges in genetic diversity creation were discussed with emphases on creating “smart” libraries, controlling the mutagenesis spectrum and specific challenges in each group of mutagenesis methods. An outline of the wider applications of genetic diversity creation includes genome engineering, viral evolution, metagenomics and a study of protein functions. The review ends with an outlook for genetic diversity creation and the prospective developments that can have future impact in this field.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

Laboratory-Directed Protein Evolution

Systematic approaches to directed evolution of proteins have been documented since the 1970s. The ability to recruit new protein functions arises from the considerable substrate ambiguity of many proteins. The substrate ambiguity of a protein can be interpreted as the evolutionary potential that allows a protein to acquire new specificities through mutation or to regain function via mutations that differ from the original protein sequence. All organisms have evolutionarily exploited this substrate ambiguity. When exploited in a laboratory under controlled mutagenesis and selection, it enables a protein to “evolve” in desired directions. One of the most effective strategies in directed protein evolution is to gradually accumulate mutations, either sequentially or by recombination, while applying selective pressure. This is typically achieved by the generation of libraries of mutants followed by efficient screening of these libraries for targeted functions and subsequent repetition of the process using improved mutants from the previous screening. Here we review some of the successful strategies in creating protein diversity and the more recent progress in directed protein evolution in a wide range of scientific disciplines and its impacts in chemical, pharmaceutical, and agricultural sciences.     

Incremental truncation as a strategy in the engineering of novel biocatalysts

The application and success of combinatorial approaches to protein engineering problems have increased dramatically. However, current directed evolution strategies lack a combinatorial methodology for creating libraries of hybrid enzymes which lack high homology or for creating libraries of highly homologous genes with fusions at regions of non-identity. To create such hybrid enzyme libraries, we have developed a series of combinatorial approaches that utilize the incremental truncation of genes, gene fragments or gene libraries. For incremental truncation, Exonuclease III is used to create a library of all possible single base-pair deletions of a given piece of DNA. Incremental truncation libraries (ITLs) have applications in protein engineering as well as protein folding, enzyme evolution, and the chemical synthesis of proteins. In addition, we are developing a methodology of DNA shuffling which is independent of DNA sequence homology.     

Structure‐based design of combinatorial mutagenesis libraries

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high‐throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general‐purpose method, called “Structure‐based Optimization of Combinatorial Mutagenesis ” (SOCoM ), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library‐averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β‐lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure‐based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large‐scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure‐based assessments, such as the energy gap between alternative conformational or bound states.     

Circular permutation in the Ω-loop of TEM-1 β-lactamase results in improved activity and altered substrate specificity

Generating diverse protein libraries that contain improved variants at a sufficiently high frequency is critical for improving the properties of proteins using directed evolution. Many studies have illustrated how random mutagenesis, cassette mutagenesis, DNA shuffling and similar approaches are effective diversity generating methods for directed evolution. Very few studies have explored random circular permutation, the intramolecular relocation of the N- and C-termini of a protein, as a diversity-generating step for directed evolution. We subjected a library of random circular permutations of TEM-1 β-lactamase to selections on increasing concentrations of a variety of β-lactam antibiotics including cefotaxime. We identified two circularly permuted variants that conferred elevated resistance to cefotaxime but decreased resistance to other antibiotics. These variants were circularly permuted in the Ω-loop proximal to the active site. Remarkably, one variant was circularly permuted such that the key catalytic residue Glu166 was located at the N-terminus of the mature protein.     

Directed evolution: selecting today's biocatalysts

Directed evolution has become a full-grown tool in molecular biology nowadays. The methods that are involved in creating a mutant library are extensive and can be divided into several categories according to their basic ideas. Furthermore, both screening and selection can be used to target the enzyme towards the desired direction. Nowadays, this technique is broadly used in two major applications: (industrial) biocatalysis and research. In the first field enzymes are engineered in order to produce suitable biocatalysts with high catalytic activity and stability in an industrial environment. In the latter area methods are established to quickly engineer new enzymes for every possible catalytic step, thereby creating a universal biotechnological toolbox. Furthermore, directed evolution can be used to try to understand the natural evolutionary processes. This review deals with new mutagenesis and recombination strategies published recently. A full overview of new methods for creating more specialised mutant libraries is given. The importance of selection in directed evolution strategies is being exemplified by some current successes including the beta-lactam acylases.     

High-throughput screening for enhanced protein stability

High thermostability of proteins is a prerequisite for their implementation in biocatalytic processes and in the evolution of new functions. Various protein engineering methods have been applied to the evolution of increased thermostability, including the use of combinatorial design where a diverse library of proteins is generated and screened for variants with increased stability. Current trends are toward the use of data-driven methods that reduce the library size by using available data to choose areas of the protein to target, without specifying the precise changes. For example, the half-lives of subtilisin and a Bacillus subtilis lipase were increased 1500-fold and 300-fold, respectively, using a crystal structure to guide mutagenesis choices. Sequence homology based methods have also produced libraries where 50% of the variants have improved thermostability. Moreover, advances in the high-throughput measurement of denaturation curves and the application of selection methods to thermostability evolution have enabled the screening of larger libraries. The combination of these methods will lead to the rapid improvement of protein stability for biotechnological purposes.     

Protein and Genome Evolution in Mammalian Cells for Biotechnology Applications

Mutation and selection are the essential steps of evolution. Researchers have long used in vitro mutagenesis, expression, and selection techniques in laboratory bacteria and yeast cultures to evolve proteins with new properties, termed directed evolution. Unfortunately, the nature of mammalian cells makes applying these mutagenesis and whole-organism evolution techniques to mammalian protein expression systems laborious and time consuming. Mammalian evolution systems would be useful to test unique mammalian cell proteins and protein characteristics, such as complex glycosylation. Protein evolution in mammalian cells would allow for generation of novel diagnostic tools and designer polypeptides that can only be tested in a mammalian expression system. Recent advances have shown that mammalian cells of the immune system can be utilized to evolve transgenes during their natural mutagenesis processes, thus creating proteins with unique properties, such as fluorescence. On a more global level, researchers have shown that mutation systems that affect the entire genome of a mammalian cell can give rise to cells with unique phenotypes suitable for commercial processes. This review examines the advances in mammalian cell and protein evolution and the application of this work toward advances in commercial mammalian cell biotechnology.     

Steering directed protein evolution: strategies to manage combinatorial complexity of mutant libraries

How to explore protein sequence space efficiently and how to generate high-quality mutant libraries that allow to identify improved variants with current screening technologies are key questions for any directed protein evolution experiment. High-quality mutant libraries can be generated through improved random mutagenesis methodologies and by restricting diversity generation through computational methods to residues which have high success probabilities. Advances in mutant library design and computational tools to focus diversity generation are summarized in this minireview and discussed from an experimentalist point of view in the context of directed protein evolution.     

Directed evolution for enzyme development in biocatalysis

As an important sector of the chemical industry, biocatalysis requires the continuous development of enzymes with tailor-made activity, selectivity, stability, or tolerance to unnatural environments. This is now routinely achieved by directed evolution based on iterative cycles of genetic diversification and activity screening. Here, we highlight its recent developments. First, the design of “smarter” libraries by focused mutagenesis may be a crucial start-up for a fast and successful outcome. Then library assembly and expression are also key steps that benefits from modern molecular biology progresses. Finally, various strategies may be considered for library screening depending on the final objective: while low-throughput direct assays have been very successful in generating enzymes for important biocatalytic processes, even in bringing completely new chemistries to the enzyme world, ultrahigh-throughput screening methods are emerging as powerful approaches for engineering the next generation of industrial enzymes.     

Generation of recombinant antibodies and means for increasing their affinity

Highly specific interaction with foreign molecules is a unique feature of antibodies. Since 1975, when Keller and Milstein proposed the method of hybridoma technology and prepared mouse monoclonal antibodies, many antibodies specific to various antigens have been obtained. Recent development of methods for preparation of recombinant DNA libraries and in silico bioinformatics approaches for protein structure analysis makes possible antibody preparation using gene engineering approaches. The development of gene engineering methods allowed creating recombinant antibodies and improving characteristics of existing antibodies; this significantly extends the applicability of antibodies. By modifying biochemical and immunochemical properties of antibodies by changing their amino acid sequences it is possible to create antibodies with properties optimal for certain tasks. For example, application of recombinant technologies resulted in antibody preparation of high affinity significantly exceeding the initial affinity of natural antibodies. In this review we summarize information about the structure, modes of preparation, and application of recombinant antibodies and their fragments and also consider the main approaches used to increase antibody affinity.     

Thermostable DNA Ligase-Mediated PCR Production of Circular Plasmid (PPCP) and Its Application in Directed Evolution via In situ Error-Prone PCR

Polymerase chain reaction (PCR) is a powerful method to produce linear DNA fragments. Here we describe the Tma thermostable DNA ligase-mediated PCR production of circular plasmid (PPCP) and its application in directed evolution via in situ error-prone PCR. In this thermostable DNA ligase-mediated whole-plasmid amplification method, the resultant DNA nick between the 5′ end of the PCR primer and the extended newly synthesized DNA 3′ end of each PCR cycle is ligated by Tma DNA ligase, resulting in circular plasmid DNA product that can be directly transformed. The template plasmid DNA is eliminated by ‘selection marker swapping’ upon transformation. When performed under an error-prone condition with Taq DNA polymerase, PPCP allows one-step construction of mutagenesis libraries based on in situ error-prone PCR so that random mutations are introduced into the target gene without altering the expression vector plasmid. A significant difference between PPCP and previously published methods is that PPCP allows exponential amplification of circular DNA. We used this method to create random mutagenesis libraries of a xylanase gene and two cellulase genes. Screening of these libraries resulted in mutant proteins with desired properties, demonstrating the usefulness of in situ error-prone PPCP for creating random mutagenesis libraries for directed evolution.     

Evolving strategies for enzyme engineering

Directed evolution is a common technique to engineer enzymes for a diverse set of applications. Structural information and an understanding of how proteins respond to mutation and recombination are being used to develop improved directed evolution strategies by increasing the probability that mutant sequences have the desired properties. Strategies that target mutagenesis to particular regions of a protein or use recombination to introduce large sequence changes can complement full-gene random mutagenesis and pave the way to achieving ever more ambitious enzyme engineering goals.     

Genomic approaches to fungal pathogenicity

Within a few years, the genome sequences of a large number of medically and agriculturally important fungi will be known. With this resource come the promises of genomic approaches to study pathogenicity and host-fungus interactions. Genomics is particularly attractive for these questions, as conventional genetic and biochemical approaches are limited in many pathogenic fungi. Recent work has applied signature-tagged mutagenesis and DNA microarray analysis to virulence studies in several fungal species, and novel approaches, such as protein arrays and genomic deletion libraries, are being developed in Saccharomyces cerevisiae and have significant potential in other fungi. High-throughput gene-discovery approaches should greatly increase our understanding of fungal pathogenesis.     

Semi-rational approaches to engineering enzyme activity: combining the benefits of directed evolution and rational design

Many research groups successfully rely on whole-gene random mutagenesis and recombination approaches for the directed evolution of enzymes. Recent advances in enzyme engineering have used a combination of these random methods of directed evolution with elements of rational enzyme modification to successfully by-pass certain limitations of both directed evolution and rational design. Semi-rational approaches that target multiple, specific residues to mutate on the basis of prior structural or functional knowledge create 'smart' libraries that are more likely to yield positive results. Efficient sampling of mutations likely to affect enzyme function has been conducted both experimentally and, on a much greater scale, computationally, with remarkable improvements in substrate selectivity and specificity and in the de novo design of enzyme activities within scaffolds of known structure.     

Utilizing natural diversity to evolve protein function: applications towards thermostability

Protein evolution relies on designing a library of sequences that capture meaningful functional diversity in a limited number of protein variants. Several approaches take advantage of the sequence space already explored through natural selection by incorporating sequence diversity available from modern genomes (and their ancestors) when designing these libraries. The success of these approaches is, partly, owing to the fact that modern sequence diversity has already been subjected to evolutionary selective forces and thus the diversity has already been deemed 'fit to survive'. Five of these approaches will be discussed in this review to highlight how protein engineers can use evolutionary sequence history/diversity of homologous proteins in unique ways to design protein libraries.     

Active and machine learning-based approaches to rapidly enhance microbial chemical production

In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.     

Knowledge-based Fragment Binding Prediction

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE''s ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.