Reducing codon redundancy and screening effort of combinatorial protein libraries created by saturation mutagenesis

Modification of the peroxygenative:peroxidative activity ratio in the unspecific peroxygenase from Agrocybe aegerita by structure-guided evolution

Unspecific peroxygenase (UPO) is a heme-thiolate peroxidase capable of performing with high-selectivity C-H oxyfunctionalizations of great interest in organic synthesis through its peroxygenative activity. However, the convergence of such activity with an unwanted peroxidative activity encumbers practical applications. In this study, we have modified the peroxygenative:peroxidative activity ratio (P:p ratio) of UPO from Agrocybe aegerita by structure-guided evolution. Several flexible loops (Glu1-Pro35, Gly103-Asp131, Ser226-Gly243, Gln254-Thr276 and Ty293-Arg327) were selected on the basis on their B-factors and ΔΔG values. The full ensemble of segments (43% of UPO sequence) was subjected to focused evolution by the Mutagenic Organized Recombination Process by Homologous IN vivo Grouping (MORPHING) method in Saccharomyces cerevisiae. Five independent mutant libraries were screened in terms of P:p ratio and thermostability. We identified several variants that harbored substitutions at positions 120 and 320 with a strong enhancement in the P:p ratio albeit at the cost of stability. The most thermostable mutant of this process (S226G with an increased T50 of 2°C) was subjected to further combinatorial saturation mutagenesis on Thr120 and Thr320 yielding a collection of variants with modified P:p ratio and recovered stability. Our results seem to indicate the coexistence of several oxidation sites for peroxidative and peroxygenative activities in UPO.

CorNet: Assigning function to networks of co-evolving residues by automated literature mining

CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.

Biocatalysts for the pharmaceutical industry created by structure-guided directed evolution of stereoselective enzymes

Enzymes have been used for a long time as catalysts in the asymmetric synthesis of chiral intermediates needed in the production of therapeutic drugs. However, this alternative to man-made catalysts has suffered traditionally from distinct limitations, namely the often observed wrong or insufficient enantio- and/or regioselectivity, low activity, narrow substrate range, and insufficient thermostability. With the advent of directed evolution, these problems can be generally solved. The challenge is to develop and apply the most efficient mutagenesis methods which lead to highest-quality mutant libraries requiring minimal screening. Structure-guided saturation mutagenesis and its iterative form have emerged as the method of choice for evolving stereo- and regioselective mutant enzymes needed in the asymmetric synthesis of chiral intermediates. The number of (industrial) applications in the preparation of chiral pharmaceuticals is rapidly increasing. This review features and analyzes typical case studies.

Orthogonal Luciferase-Luciferin Pairs for Bioluminescence Imaging

Bioluminescence imaging with luciferase-luciferin pairs is widely used in biomedical research. Several luciferases have been identified in nature, and many have been adapted for tracking cells in whole animals. Unfortunately, the optimal luciferases for imaging in vivo utilize the same substrate and therefore cannot easily differentiate multiple cell types in a single subject. To develop a broader set of distinguishable probes, we crafted custom luciferins that can be selectively processed by engineered luciferases. Libraries of mutant enzymes were iteratively screened with sterically modified luciferins, and orthogonal enzyme-substrate "hits" were identified. These tools produced light when complementary enzyme-substrate partners interacted both in vitro and in cultured cell models. Based on their selectivity, these designer pairs will bolster multicomponent imaging and enable the direct interrogation of cell networks not currently possible with existing tools. Our screening platform is also general and will expedite the identification of more unique luciferases and luciferins, further expanding the bioluminescence toolkit.

One-step combined focused epPCR and saturation mutagenesis for thermostability evolution of a new cold-active xylanase

Enzymes active at low temperature are of great interest for industrial bioprocesses due to their high efficiency at a low energy cost. One of the particularities of naturally evolved cold-active enzymes is their increased enzymatic activity at low temperature, however the low thermostability presented in this type of enzymes is still a major drawback for their application in biocatalysis. Directed evolution of cold-adapted enzymes to a more thermostable version, appears as an attractive strategy to fulfill the stability and activity requirements for the industry. This paper describes the recombinant expression and characterization of a new and highly active cold-adapted xylanase from the GH-family 10 (Xyl-L), and the use of a novel one step combined directed evolution technique that comprises saturation mutagenesis and focused epPCR as a feasible semi-rational strategy to improve the thermostability. The Xyl-L enzyme was cloned from a marine-Antarctic bacterium, Psychrobacter sp. strain 2-17, recombinantly expressed in E. coli strain BL21(DE3) and characterized enzymatically. Molecular dynamic simulations using a homology model of the catalytic domain of Xyl-L were performed to detect flexible regions and residues, which are considered to be the possible structural elements that define the thermolability of this enzyme. Mutagenic libraries were designed in order to stabilize the protein introducing mutations in some of the flexible regions and residues identified. Twelve positive mutant clones were found to improve the T₅₀¹⁵ value of the enzyme, in some cases without affecting the activity at 25°C. The best mutant showed a 4.3°C increase in its T₅₀¹⁵. The efficiency of the directed evolution approach can also be expected to work in the protein engineering of stereoselectivity.

Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening

The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstrate its advantageous use to engineer a biocatalyst. Hot-spots for mutations were individuated in three distinct regions of Candida antarctica lipase A (Cal-A), the biocatalyst chosen as a target to demonstrate the versatility of this recombination method. The three corresponding gene segments were subjected to the most appropriate method of mutagenesis (targeted or random). Their straightforward reassembly allowed combining products of different mutagenesis methods in a single round for rapid production of a series of diverse libraries, thus facilitating directed evolution. Screening to improve discrimination of short-chain versus long-chain fatty acid substrates was aided by development of a general, automated method for visual discrimination of the hydrolysis of varied substrates by whole cells.

Single mutations of ketoreductase ChKRED20 enhance the bioreductive production of (1S)-2-chloro-1-(3, 4-difluorophenyl) ethanol

(1S)-2-chloro-1-(3, 4-difluorophenyl) ethanol ((S)-CFPL) is an intermediate for the drug ticagrelor, and is manufactured via chemical approaches. To develop a biocatalytic solution to (S)-CFPL, an inventory of ketoreductases from Chryseobacterium sp. CA49 were rescreened, and ChKRED20 was found to catalyze the reduction of the ketone precursor with excellent stereoselectivity (>99 % ee). After screening an error-prone PCR library of the wild-type ChKRED20, two mutants, each bearing a single amino acid substitution of H145L or L205M, were identified with significantly increased activity. Then, the two critical positions were each randomized by constructing saturation mutagenesis libraries, which delivered several mutants with further enhanced activity. Among them, the mutant L205A was the best performer with a specific activity of 178 μmol/min/mg, ten times of that of the wild-type. Its k _cat/K _m increased by 15 times and half-life at 50 °C increased by 70 %. The mutant catalyzed the complete conversion of 150 and 200 g/l substrate within 6 and 20 h, respectively, to yield enantiopure (S)-CFPL with an isolated yield of 95 %.

A general and efficient strategy for generating the stable enzymes

The local flexibility of an enzyme's active center plays pivotal roles in catalysis, however, little is known about how the flexibility of these flexible residues affects stability. In this study, we proposed an active center stabilization (ACS) strategy to improve the kinetic thermostability of Candida rugosa lipase1. Based on the B-factor ranking at the region ~10 Å within the catalytic Ser209, 18 residues were selected for site-saturation mutagenesis. Based on three-tier high-throughput screening and ordered recombination mutagenesis, the mutant VarB3 (F344I/F434Y/F133Y/F121Y) was shown to be the most stable, with a 40-fold longer in half-life at 60 °C and a 12.7 °C higher Tm value than that of the wild type, without a decrease in catalytic activity. Further analysis of enzymes with different structural complexities revealed that focusing mutations on the flexible residues within around 10 Å of the catalytic residue might increase the success rate for enzyme stabilization. In summary, this study identifies a panel of flexible residues within the active center that affect enzyme stability. This finding not only provides clues regarding the molecular evolution of enzyme stability but also indicates that ACS is a general and efficient strategy for exploring the functional robustness of enzymes for industrial applications.

A Web Interface for Codon Compression

Saturation mutagenesis is widely used in protein engineering and other experiments. A common practice is to utilize the single degenerate codon NNK. However, this approach suffers from amino acid bias and the presence of a stop codon and of the wild type amino acid. These extra features needlessly increase library size and consequently downstream screening load. Recently, we developed the DYNAMCC algorithms for codon compression that find the minimal set of degenerate codons, covering any defined set of amino acids, with no off-target codons and with redundancy control. Additionally, we experimentally demonstrated the advantages of this approach over the standard NNK method. While the code is freely available from our Web site, we have now made this method more accessible to a broader audience without any computational background by building a user-friendly web-based interface for those algorithms. The Web site can be accessed through: www.dynamcc.com .

Discovery, Molecular Mechanisms, and Industrial Applications of Cold-Active Enzymes

Cold-active enzymes constitute an attractive resource for biotechnological applications. Their high catalytic activity at temperatures below 25°C makes them excellent biocatalysts that eliminate the need of heating processes hampering the quality, sustainability, and cost-effectiveness of industrial production. Here we provide a review of the isolation and characterization of novel cold-active enzymes from microorganisms inhabiting different environments, including a revision of the latest techniques that have been used for accomplishing these paramount tasks. We address the progress made in the overexpression and purification of cold-adapted enzymes, the evolutionary and molecular basis of their high activity at low temperatures and the experimental and computational techniques used for their identification, along with protein engineering endeavors based on these observations to improve some of the properties of cold-adapted enzymes to better suit specific applications. We finally focus on examples of the evaluation of their potential use as biocatalysts under conditions that reproduce the challenges imposed by the use of solvents and additives in industrial processes and of the successful use of cold-adapted enzymes in biotechnological and industrial applications.

One-Tube-Only Standardized Site-Directed Mutagenesis: An Alternative Approach to Generate Amino Acid Substitution Collections

Site-directed mutagenesis (SDM) is a powerful tool to create defined collections of protein variants for experimental and clinical purposes, but effectiveness is compromised when a large number of mutations is required. We present here a one-tube-only standardized SDM approach that generates comprehensive collections of amino acid substitution variants, including scanning- and single site-multiple mutations. The approach combines unified mutagenic primer design with the mixing of multiple distinct primer pairs and/or plasmid templates to increase the yield of a single inverse-PCR mutagenesis reaction. Also, a user-friendly program for automatic design of standardized primers for Ala-scanning mutagenesis is made available. Experimental results were compared with a modeling approach together with stochastic simulation data. For single site-multiple mutagenesis purposes and for simultaneous mutagenesis in different plasmid backgrounds, combination of primer sets and/or plasmid templates in a single reaction tube yielded the distinct mutations in a stochastic fashion. For scanning mutagenesis, we found that a combination of overlapping primer sets in a single PCR reaction allowed the yield of different individual mutations, although this yield did not necessarily follow a stochastic trend. Double mutants were generated when the overlap of primer pairs was below 60%. Our results illustrate that one-tube-only SDM effectively reduces the number of reactions required in large-scale mutagenesis strategies, facilitating the generation of comprehensive collections of protein variants suitable for functional analysis.

Designer protein delivery: From natural to engineered affinity-controlled release systems

Exploiting binding affinities between molecules is an established practice in many fields, including biochemical separations, diagnostics, and drug development; however, using these affinities to control biomolecule release is a more recent strategy. Affinity-controlled release takes advantage of the reversible nature of noncovalent interactions between a therapeutic protein and a binding partner to slow the diffusive release of the protein from a vehicle. This process, in contrast to degradation-controlled sustained-release formulations such as poly(lactic-co-glycolic acid) microspheres, is controlled through the strength of the binding interaction, the binding kinetics, and the concentration of binding partners. In the context of affinity-controlled release--and specifically the discovery or design of binding partners--we review advances in in vitro selection and directed evolution of proteins, peptides, and oligonucleotides (aptamers), aided by computational design.

A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules

A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis.

ANT: Software for Generating and Evaluating Degenerate Codons for Natural and Expanded Genetic Codes

The Ambiguous Nucleotide Tool (ANT) is a desktop application that generates and evaluates degenerate codons. Degenerate codons are used to represent DNA positions that have multiple possible nucleotide alternatives. This is useful for protein engineering and directed evolution, where primers specified with degenerate codons are used as a basis for generating libraries of protein sequences. ANT is intuitive and can be used in a graphical user interface or by interacting with the code through a defined application programming interface. ANT comes with full support for nonstandard, user-defined, or expanded genetic codes (translation tables), which is important because synthetic biology is being applied to an ever widening range of natural and engineered organisms. The Python source code for ANT is freely distributed so that it may be used without restriction, modified, and incorporated in other software or custom data pipelines.

Modulation of the thermostability and substrate specificity of Candida rugosa lipase1 by altering the acyl-binding residue Gly414 at the α-helix-connecting bend

Candida rugosa Lipase1 (LIP1) is widely used in industrial applications. Optimizing its catalytic performance is still a challenging goal for protein engineers. Mutagenesis of key residues in the active site of the enzyme may provide an effective strategy for enhancing stability and altering substrate specificity. In this study, multiple sequence alignment and structural analysis revealed that the acyl-binding residue, Gly414, of LIP1, which is located at a bend connecting α-helixes, was the non-conserved residue in five other isoenzymes. Using saturation mutagenesis, four mutants with improved stability (G414A, G414M, G414H and G414W) were obtained. Compared to the wild type, the best mutant (G414W) exhibited a remarkable 6.5-fold enhancement in half-life at 60 °C and a 14 °C higher T50(15). Its optimum temperature was increased by 15 °C. Simultaneously, G414W displayed a shift in substrate preference from medium-chain to short-chain pNP-ester. Modeling analysis showed that the multiple interactions formed by hydrophobic clusters and hydrogen bonds in the acyl-binding tunnel might lead to the observed thermostability improvement. Additionally, the bulky tryptophan substitution formed a strong steric hindrance to the accommodation of long-chain substrates in the tunnel. These results indicate that the key acyl-binding residues at the α-helix-connecting bend could mediate enzyme stability and catalytic substrate spectra.

Genetically Encoded Spy Peptide Fusion System to Detect Plasma Membrane-Localized Proteins In Vivo

Membrane proteins are the main gatekeepers of cellular state, especially in neurons, serving either to maintain homeostasis or instruct response to synaptic input or other external signals. Visualization of membrane protein localization and trafficking in live cells facilitates understanding the molecular basis of cellular dynamics. We describe here a method for specifically labeling the plasma membrane-localized fraction of heterologous membrane protein expression using channelrhodopsins as a case study. We show that the genetically encoded, covalent binding SpyTag and SpyCatcher pair from the Streptococcus pyogenes fibronectin-binding protein FbaB can selectively label membrane-localized proteins in living cells in culture and in vivo in Caenorhabditis elegans. The SpyTag/SpyCatcher covalent labeling method is highly specific, modular, and stable in living cells. We have used the binding pair to develop a channelrhodopsin membrane localization assay that is amenable to high-throughput screening for opsin discovery and engineering.

Economical analysis of saturation mutagenesis experiments

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced.

Biomathematical description of synthetic peptide libraries

Libraries of randomised peptides displayed on phages or viral particles are essential tools in a wide spectrum of applications. However, there is only limited understanding of a library's fundamental dynamics and the influences of encoding schemes and sizes on their quality. Numeric properties of libraries, such as the expected number of different peptides and the library's coverage, have long been in use as measures of a library's quality. Here, we present a graphical framework of these measures together with a library's relative efficiency to help to describe libraries in enough detail for researchers to plan new experiments in a more informed manner. In particular, these values allow us to answer-in a probabilistic fashion-the question of whether a specific library does indeed contain one of the "best" possible peptides. The framework is implemented in a web-interface based on two packages, discreteRV and peptider, to the statistical software environment R. We further provide a user-friendly web-interface called PeLiCa (Peptide Library Calculator, http://www.pelica.org), allowing scientists to plan and analyse their peptide libraries.

Codon compression algorithms for saturation mutagenesis

Saturation mutagenesis is employed in protein engineering and genome-editing efforts to generate libraries that span amino acid design space. Traditionally, this is accomplished by using degenerate/compressed codons such as NNK (N = A/C/G/T, K = G/T), which covers all amino acids and one stop codon. These solutions suffer from two types of redundancy: (a) different codons for the same amino acid lead to bias, and (b) wild type amino acid is included within the library. These redundancies increase library size and downstream screening efforts. Here, we present a dynamic approach to compress codons for any desired list of amino acids, taking into account codon usage. This results in a unique codon collection for every amino acid to be mutated, with the desired redundancy level. Finally, we demonstrate that this approach can be used to design precise oligo libraries amendable to recombineering and CRISPR-based genome editing to obtain a diverse population with high efficiency.

Directed evolution of phenylacetone monooxygenase as an active catalyst for the Baeyer-Villiger conversion of cyclohexanone to caprolactone

Phenylacetone monooxygenase (PAMO) is an exceptionally robust Baeyer-Villiger monooxygenase, which makes it ideal for potential industrial applications. However, its substrate scope is limited, unreactive cyclohexanone being a prominent example. Such a limitation is unfortunate, because this particular transformation in an ecologically viable manner would be highly desirable, the lactone and the respective lactam being of considerable interest as monomers in polymer science. We have applied directed evolution in search of an active mutant for this valuable C-C activating reaction. Using iterative saturation mutagenesis (ISM), several active mutants were evolved, with only a minimal trade-off in terms of stability. The best mutants allow for quantitative conversion of 2 mM cyclohexanone within 1 h reaction time. In order to circumvent the NADP(+) regeneration problem, whole E. coli resting cells were successfully applied. Molecular dynamics simulations and induced fit docking throw light on the origin of enhanced PAMO activity. The PAMO mutants constitute ideal starting points for future directed evolution optimization necessary for an industrial process.

Assembly of Designed Oligonucleotides: a useful tool in synthetic biology for creating high-quality combinatorial DNA libraries

The method dubbed Assembly of Designed Oligonucleotides (ADO) is a powerful tool in synthetic biology to create combinatorial DNA libraries for gene, protein, metabolic, and genome engineering. In directed evolution of proteins, ADO benefits from using reduced amino acid alphabets for saturation mutagenesis and/or DNA shuffling, but all 20 canonical amino acids can be also used as building blocks. ADO is performed in a two-step reaction. The first involves a primer-free, polymerase cycling assembly or overlap extension PCR step using carefully designed overlapping oligonucleotides. The second step is a PCR amplification using the outer primers, resulting in a high-quality and bias-free double-stranded DNA library that can be assembled with other gene fragments and/or cloned into a suitable plasmid subsequently. The protocol can be performed in a few hours. In theory, neither the length of the DNA library nor the number of DNA changes has any limits. Furthermore, with the costs of synthetic DNA dropping every year, after an initial investment is made in the oligonucleotides, these can be exchanged for alternative ones with different sequences at any point in the process, fully exploiting the potential of creating highly diverse combinatorial libraries. In the example chosen here, we show the construction of a high-quality combinatorial ADO library targeting sixteen different codons simultaneously with nonredundant degenerate codons encoding various reduced alphabets of four amino acids along the heme region of the monooxygenase P450-BM3.

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.

Substrate channel evolution of an esterase for the synthesis of cilastatin

Error-prone PCR and site-directed mutagenesis around substrate channel were employed for improving an esterase (RhEst1) activity towards Cilastatin building block. RhEst1_{A147I/V148F/G254A} showed 20 times higher activity than the native enzyme in whole cell biotransformation.

SwiftLib: rapid degenerate-codon-library optimization through dynamic programming

Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.

A review of metabolic and enzymatic engineering strategies for designing and optimizing performance of microbial cell factories

Microbial cell factories (MCFs) are of considerable interest to convert low value renewable substrates to biofuels and high value chemicals. This review highlights the progress of computational models for the rational design of an MCF to produce a target bio-commodity. In particular, the rational design of an MCF involves: (i) product selection, (ii) de novo biosynthetic pathway identification (i.e., rational, heterologous, or artificial), (iii) MCF chassis selection, (iv) enzyme engineering of promiscuity to enable the formation of new products, and (v) metabolic engineering to ensure optimal use of the pathway by the MCF host. Computational tools such as (i) de novo biosynthetic pathway builders, (ii) docking, (iii) molecular dynamics (MD) and steered MD (SMD), and (iv) genome-scale metabolic flux modeling all play critical roles in the rational design of an MCF. Genome-scale metabolic flux models are of considerable use to the design process since they can reveal metabolic capabilities of MCF hosts. These can be used for host selection as well as optimizing precursors and cofactors of artificial de novo biosynthetic pathways. In addition, recent advances in genome-scale modeling have enabled the derivation of metabolic engineering strategies, which can be implemented using the genomic tools reviewed here as well.

Directed evolution of a far-red fluorescent rhodopsin

Microbial rhodopsins are a diverse group of photoactive transmembrane proteins found in all three domains of life. A member of this protein family, Archaerhodopsin-3 (Arch) of halobacterium Halorubrum sodomense, was recently shown to function as a fluorescent indicator of membrane potential when expressed in mammalian neurons. Arch fluorescence, however, is very dim and is not optimal for applications in live-cell imaging. We used directed evolution to identify mutations that dramatically improve the absolute brightness of Arch, as confirmed biochemically and with live-cell imaging (in Escherichia coli and human embryonic kidney 293 cells). In some fluorescent Arch variants, the pK(a) of the protonated Schiff-base linkage to retinal is near neutral pH, a useful feature for voltage-sensing applications. These bright Arch variants enable labeling of biological membranes in the far-red/infrared and exhibit the furthest red-shifted fluorescence emission thus far reported for a fluorescent protein (maximal excitation/emission at ∼ 620 nm/730 nm).

Improving the NADH-cofactor specificity of the highly active AdhZ3 and AdhZ2 from Escherichia coli K-12

Biocatalysis is a promising tool for the sustainable production of chemicals. When cofactor depending enzymatic reactions are involved the applicability of the right cofactor is a central issue. One important example in this regard is the production of alcohols by nicotinamide cofactor (NAD(P)(+)) depending alcohol dehydrogenases. AdhZ3 from Escherichia coli, which is important for the production of alcohols from biomass, has a preference for NADPH as cofactor. We used a structure guided site-specific random approach, to change the cofactor preference towards NADH and to deduce more general rules for redesigning the cofactor specificity. Transfer of a triplet motif from NADH preferring horse liver ADH to AdhZ3 showed an insufficient switch in the preference towards NADH. A combinatorial site saturation mutagenesis altering three residues at once was applied. Library screening with two different cofactor concentrations (0.1 and 0.3mM) resulted in nine improved variants with AdhZ3-LND having the highest vmax and AdhZ3-CND having the lowest K(m). Asparagine was the most frequent amino acid found in eight of nine triplet motifs. To verify the triplet-motif, two variants of E. coli AdhZ2 DIN and LND were designed and confirmed for improved activity with NADH.

MDC-Analyzer: a novel degenerate primer design tool for the construction of intelligent mutagenesis libraries with contiguous sites

Recent computational and bioinformatics advances have enabled the efficient creation of novel biocatalysts by reducing amino acid variability at hot spot regions. To further expand the utility of this strategy, we present here a tool called Multi-site Degenerate Codon Analyzer (MDC-Analyzer) for the automated design of intelligent mutagenesis libraries that can completely cover user-defined randomized sequences, especially when multiple contiguous and/or adjacent sites are targeted. By initially defining an objective function, the possible optimal degenerate PCR primer profiles could be automatically explored using the heuristic approach of Greedy Best-First-Search. Compared to the previously developed DC-Analyzer, MDC-Analyzer allows for the existence of a small amount of undesired sequences as a tradeoff between the number of degenerate primers and the encoded library size while still providing all the benefits of DC-Analyzer with the ability to randomize multiple contiguous sites. MDC-Analyzer was validated using a series of randomly generated mutation schemes and experimental case studies on the evolution of halohydrin dehalogenase, which proved that the MDC methodology is more efficient than other methods and is particularly well-suited to exploring the sequence space of proteins using data-driven protein engineering strategies.

ProxiMAX randomization: a new technology for non-degenerate saturation mutagenesis of contiguous codons

Back in 2003, we published ‘MAX’ randomization, a process of non-degenerate saturation mutagenesis using exactly 20 codons (one for each amino acid) or else any required subset of those 20 codons. ‘MAX’ randomization saturates codons located in isolated positions within a protein, as might be required in enzyme engineering, or else on one face of an α-helix, as in zinc-finger engineering. Since that time, we have been asked for an equivalent process that can saturate multiple contiguous codons in a non-degenerate manner. We have now developed ‘ProxiMAX’ randomization, which does just that: generating DNA cassettes for saturation mutagenesis without degeneracy or bias. Offering an alternative to trinucleotide phosphoramidite chemistry, ProxiMAX randomization uses nothing more sophisticated than unmodified oligonucleotides and standard molecular biology reagents. Thus it requires no specialized chemistry, reagents or equipment, and simply relies on a process of saturation cycling comprising ligation, amplification and digestion for each cycle. The process can encode both unbiased representation of selected amino acids or else encode them in predefined ratios. Each saturated position can be defined independently of the others. We demonstrate accurate saturation of up to 11 contiguous codons. As such, ProxiMAX randomization is particularly relevant to antibody engineering.

Probabilistic methods in directed evolution: library size, mutation rate, and diversity

Directed evolution has emerged as an important tool for engineering proteins with improved or novel properties. Because of their inherent reliance on randomness, directed evolution protocols are amenable to probabilistic modeling and analysis. This chapter summarizes and reviews in a nonmathematical way some of the probabilistic works related to directed evolution, with particular focus on three of the most widely used methods: saturation mutagenesis, error-prone PCR, and in vitro recombination. The ultimate aim is to provide the reader with practical information to guide the planning and design of directed evolution studies. Importantly, the applications and locations of freely available computational resources to assist with this process are described in detail.

Iterative saturation mutagenesis: a powerful approach to engineer proteins by systematically simulating Darwinian evolution

Iterative saturation mutagenesis (ISM) is a widely applicable and powerful strategy for the efficient directed evolution of enzymes. First, one or more amino acid positions from the chosen enzyme are assigned to multi-residue sites (i.e., groups of amino acids or "multisites"). Then, the residues in each multisite are mutated with a user-defined randomization scheme to all canonical amino acids or a reduced amino acid alphabet. Subsequently, the genes of chosen variants (usually the best but not necessarily) are used as templates for saturation mutagenesis at other multisites, and the process is repeated until the desired degree of biocatalyst improvement has been achieved. Addressing multisites iteratively results in a so-called ISM scheme or tree with various upward branches or pathways. The systematic character of ISM simulates in vitro the natural process of Darwinian evolution: variation (library creation), selection (library screening), and amplification (template chosen for the next round of randomization). However, the main feature of ISM that distinguishes it from other directed evolution methods is the systematic probing of a defined segment of the protein sequence space, as it has been shown that ISM is much more efficient in terms of biocatalyst optimization than random methods such as error-prone PCR. In addition, ISM trees have also shed light on the emergence of epistasis, thereby rationally improving the strategies for evolving better enzymes. ISM was developed to improve catalytic properties such as rate, substrate scope, stereo- and regioselectivity using the Combinatorial Active-site Saturation Test (CAST), as well as chemical and thermal stability employing the B-Factor Iterative Test (B-FIT). However, ISM can also be invoked to manipulate such protein properties as binding affinity among other possibilities, including protein-protein interactions. Herein, we provide general guidelines for ISM, using CAST as the case study in the quest to enhance the activity and regioselectivity of the monooxygenase P450BM3 toward testosterone.

Improvement of biocatalysts for industrial and environmental purposes by saturation mutagenesis

Laboratory evolution techniques are becoming increasingly widespread among protein engineers for the development of novel and designed biocatalysts. The palette of different approaches ranges from complete randomized strategies to rational and structure-guided mutagenesis, with a wide variety of costs, impacts, drawbacks and relevance to biotechnology. A technique that convincingly compromises the extremes of fully randomized vs. rational mutagenesis, with a high benefit/cost ratio, is saturation mutagenesis. Here we will present and discuss this approach in its many facets, also tackling the issue of randomization, statistical evaluation of library completeness and throughput efficiency of screening methods. Successful recent applications covering different classes of enzymes will be presented referring to the literature and to research lines pursued in our group. The focus is put on saturation mutagenesis as a tool for designing novel biocatalysts specifically relevant to production of fine chemicals for improving bulk enzymes for industry and engineering technical enzymes involved in treatment of waste, detoxification and production of clean energy from renewable sources.

Biocatalysis in organic chemistry and biotechnology: past, present, and future

Enzymes as catalysts in synthetic organic chemistry gained importance in the latter half of the 20th century, but nevertheless suffered from two major limitations. First, many enzymes were not accessible in large enough quantities for practical applications. The advent of recombinant DNA technology changed this dramatically in the late 1970s. Second, many enzymes showed a narrow substrate scope, often poor stereo- and/or regioselectivity and/or insufficient stability under operating conditions. With the development of directed evolution beginning in the 1990s and continuing to the present day, all of these problems can be addressed and generally solved. The present Perspective focuses on these and other developments which have popularized enzymes as part of the toolkit of synthetic organic chemists and biotechnologists. Included is a discussion of the scope and limitation of cascade reactions using enzyme mixtures in vitro and of metabolic engineering of pathways in cells as factories for the production of simple compounds such as biofuels and complex natural products. Future trends and problems are also highlighted, as is the discussion concerning biocatalysis versus nonbiological catalysis in synthetic organic chemistry. This Perspective does not constitute a comprehensive review, and therefore the author apologizes to those researchers whose work is not specifically treated here.

Elimination of redundant and stop codons during the chemical synthesis of degenerate oligonucleotides. Combinatorial testing on the chromophore region of the red fluorescent protein mKate

Although some strategies have been reported for the elimination of stop and redundant codons during the chemical synthesis of degenerate oligonucleotides, incorporating an expensive cocktail of 20 trimer-phosphoramidites is currently a commonly employed and straightforward approach. As an alternative option, we describe here a cheaper strategy based on standard monomer-phosphoramidites and a simplified resin-splitting procedure. The accurate division of the resin, containing the growing oligonucleotide, into four columns represents the key step in this approach. The synthesis of the degenerate codon NDT in column 1, loaded with 60% of the resin, produces 12 codons, while a degenerate codon VMA in column 2, loaded with 30% of the resin, produces 6 codons. Codons ATG and TGG, independently synthesized in columns 3 and 4, respectively, and loaded with 5% each, completes the 20 different codons. The experimental frequency of each mutant codon in the library was assessed by randomizing 12 contiguous codons that encode for amino acids located in the chromophore region of the enhanced red fluorescent protein mKate-S158A. Furthermore, randomization of three contiguous codons that encode for the amino acids Phe62, Met63, and Tyr64, which are equivalent to Phe64, Ser65, and Tyr66 in GFP, gave rise to some red and golden yellow fluorescent mutants displaying interesting phenotypes and spectroscopic properties. The absorption and emission spectra of two of these mutants also suggested that the complete maturation of the red and golden yellow chromophores in mKate proceeds via the formation of a green-type chromophore and a cyan-type chromophore, respectively.

Optimal scanning of all single-point mutants of a protein

In protein engineering, useful information may be gained from systematically generating and screening all single-point mutants of a given protein. We model and analyze an iterative two-stage procedure to generate all these mutants. At each position, L variants are generated in the first stage via saturation mutagenesis and are sequenced. In the second stage, the missing variants (out of the 19 possible single-point substitutions) are produced via site-directed mutagenesis. We study the economic tradeoff associated with varying L, and derive its optimal value given the experimental parameters.

Fitness loss and library size determination in saturation mutagenesis

Saturation mutagenesis is a widely used directed evolution technique, in which a large number of protein variants, each having random amino acids in certain predetermined positions, are screened in order to discover high-fitness variants among them. Several metrics for determining the library size (the number of variants screened) have been suggested in the literature, but none of them incorporates the actual fitness of the variants discovered in the experiment. We present the results of an extensive simulation study, which is based on probabilistic models for protein fitness landscape, and which investigates how the result of a saturation mutagenesis experiment – the fitness of the best variant discovered – varies as a function of the library size. In particular, we study the loss of fitness in the experiment: the difference between the fitness of the best variant discovered, and the fitness of the best variant in variant space. Our results are that the existing criteria for determining the library size are conservative, so smaller libraries are often satisfactory. Reducing the library size can save labor, time, and expenses in the laboratory.

Optimal codon randomization via mathematical programming

Codon randomization via degenerate oligonucleotides is a widely used approach for generating protein libraries. We use integer programming methodology to model and solve the problem of computing the minimal mixture of oligonucleotides required to induce an arbitrary target probability over the 20 standard amino acids. We consider both randomization via conventional degenerate oligonucleotides, which incorporate at each position of the randomized codon certain nucleotides in equal probabilities, and randomization via spiked oligonucleotides, which admit arbitrary nucleotide distribution at each of the codon's positions. Existing methods for computing such mixtures rely on various heuristics.

Strategies for the discovery and engineering of enzymes for biocatalysis

Protein engineering is the most important method to overcome the limitations of natural enzymes as biocatalysts. The past few years have seen a tremendous increase in novel concepts to facilitate the design of mutant libraries for focused directed evolution mostly guided by advanced bioinformatic tools. In addition, advanced high-throughput methods were developed using, for example, FACS analysis or microfluidic systems. These achievements significantly facilitate the tailor-made design of enzymes to make them suitable for industrial applications.