Structure-guided engineering of Lactococcus lactis alcohol dehydrogenase LlAdhA for improved conversion of isobutyraldehyde to isobutanol

We have determined the X-ray crystal structures of the NADH-dependent alcohol dehydrogenase LlAdhA from Lactococcus lactis and its laboratory-evolved variant LlAdhA(RE1) at 1.9Å and 2.5Å resolution, respectively. LlAdhA(RE1), which contains three amino acid mutations (Y50F, I212T, and L264V), was engineered to increase the microbial production of isobutanol (2-methylpropan-1-ol) from isobutyraldehyde (2-methylpropanal). Structural comparison of LlAdhA and LlAdhA(RE1) indicates that the enhanced activity on isobutyraldehyde stems from increases in the protein's active site size, hydrophobicity, and substrate access. Further structure-guided mutagenesis generated a quadruple mutant (Y50F/N110S/I212T/L264V), whose KM for isobutyraldehyde is ∼17-fold lower and catalytic efficiency (kcat/KM) is ∼160-fold higher than wild-type LlAdhA. Combining detailed structural information and directed evolution, we have achieved significant improvements in non-native alcohol dehydrogenase activity that will facilitate the production of next-generation fuels such as isobutanol from renewable resources.

Random field model reveals structure of the protein recombinational landscape

We are interested in how intragenic recombination contributes to the evolution of proteins and how this mechanism complements and enhances the diversity generated by random mutation. Experiments have revealed that proteins are highly tolerant to recombination with homologous sequences (mutation by recombination is conservative); more surprisingly, they have also shown that homologous sequence fragments make largely additive contributions to biophysical properties such as stability. Here, we develop a random field model to describe the statistical features of the subset of protein space accessible by recombination, which we refer to as the recombinational landscape. This model shows quantitative agreement with experimental results compiled from eight libraries of proteins that were generated by recombining gene fragments from homologous proteins. The model reveals a recombinational landscape that is highly enriched in functional sequences, with properties dominated by a large-scale additive structure. It also quantifies the relative contributions of parent sequence identity, crossover locations, and protein fold to the tolerance of proteins to recombination. Intragenic recombination explores a unique subset of sequence space that promotes rapid molecular diversification and functional adaptation.

Mutation and recombination are the primary sources of genetic variation in evolving populations. The relative benefit of these two diversification mechanisms and how they complement each other has been a long-standing question in evolutionary biology. While it is clear what types of genetic diversity these two mechanisms can create, a significant challenge is relating these sequence changes to changes in fitness. The fitness landscape, which describes this mapping from genotype to phenotype, is extraordinarily complex and defined over an incomprehensibly large space of sequences. Here, we develop a model of the landscape that relies not on the details of this mapping, but rather on the statistical relationships between sequences. By studying the expected values of landscape properties, we can gain insights into the structure of the landscape that are independent of the details of how genotype dictates phenotype. We use this random field model to understand how recombination explores a functionally enriched and diverse subset of protein sequence space.

Highly thermostable fungal cellobiohydrolase I (Cel7A) engineered using predictive methods

Building on our previous efforts to generate thermostable chimeric fungal cellobiohydrolase I (CBH I, also known as Cel7A) cellulases by structure-guided recombination, we used FoldX and a 'consensus' sequence approach to identify individual mutations present in the five homologous parent CBH I enzymes which further stabilize the chimeras. Using the FoldX force field, we calculated the effect on ΔG(Folding) of each candidate mutation in a number of CBH I structures and chose those predicted to be stabilizing in multiple structures. With an alignment of 41 CBH I sequences, we also used amino acid frequencies at each candidate position to calculate predicted effects on ΔG(Folding). A combination of mutations chosen using these methods increased the T(50) of the most thermostable chimera by an additional 4.7°C, to yield a CBH I with T(50) of 72.1°C, which is 9.2°C higher than that of the most stable native CBH I, from Talaromyces emersonii. This increased stability resulted in a 10°C increase in the optimal temperature for activity, to 65°C, and a 50% increase in total sugar production from crystalline cellulose at the optimal temperature, compared with native T.emersonii CBH I.

SCHEMA-designed variants of human Arginase I and II reveal sequence elements important to stability and catalysis

Arginases catalyze the divalent cation-dependent hydrolysis of L-arginine to urea and L-ornithine. There is significant interest in using arginase as a therapeutic antineogenic agent against L-arginine auxotrophic tumors and in enzyme replacement therapy for treating hyperargininemia. Both therapeutic applications require enzymes with sufficient stability under physiological conditions. To explore sequence elements that contribute to arginase stability we used SCHEMA-guided recombination to design a library of chimeric enzymes composed of sequence fragments from the two human isozymes Arginase I and II. We then developed a novel active learning algorithm that selects sequences from this library that are both highly informative and functional. Using high-throughput gene synthesis and our two-step active learning algorithm, we were able to rapidly create a small but highly informative set of seven enzymatically active chimeras that had an average variant distance of 40 mutations from the closest parent arginase. Within this set of sequences, linear regression was used to identify the sequence elements that contribute to the long-term stability of human arginase under physiological conditions. This approach revealed a striking correlation between the isoelectric point and the long-term stability of the enzyme to deactivation under physiological conditions.

Structure-guided directed evolution of highly selective p450-based magnetic resonance imaging sensors for dopamine and serotonin

New tools that allow dynamic visualization of molecular neural events are important for studying the basis of brain activity and disease. Sensors that permit ligand-sensitive magnetic resonance imaging (MRI) are useful reagents due to the noninvasive nature and good temporal and spatial resolution of MR methods. Paramagnetic metalloproteins can be effective MRI sensors due to the selectivity imparted by the protein active site and the ability to tune protein properties using techniques such as directed evolution. Here, we show that structure-guided directed evolution of the active site of the cytochrome P450-BM3 heme domain produces highly selective MRI probes with submicromolar affinities for small molecules. We report a new, high-affinity dopamine sensor as well as the first MRI reporter for serotonin, with which we demonstrate quantification of neurotransmitter release in vitro. We also present a detailed structural analysis of evolved cytochrome P450-BM3 heme domain lineages to systematically dissect the molecular basis of neurotransmitter binding affinity, selectivity, and enhanced MRI contrast activity in these engineered proteins.

A structural study of Hypocrea jecorina Cel5A

Interest in generating lignocellulosic biofuels through enzymatic hydrolysis continues to rise as nonrenewable fossil fuels are depleted. The high cost of producing cellulases, hydrolytic enzymes that cleave cellulose into fermentable sugars, currently hinders economically viable biofuel production. Here, we report the crystal structure of a prevalent endoglucanase in the biofuels industry, Cel5A from the filamentous fungus Hypocrea jecorina. The structure reveals a general fold resembling that of the closest homolog with a high-resolution structure, Cel5A from Thermoascus aurantiacus. Consistent with previously described endoglucanase structures, the H. jecorina Cel5A active site contains a primarily hydrophobic substrate binding groove and a series of hydrogen bond networks surrounding two catalytic glutamates. The reported structure, however, demonstrates stark differences between side-chain identity, loop regions, and the number of disulfides. Such structural information may aid efforts to improve the stability of this protein for industrial use while maintaining enzymatic activity through revealing nonessential and immutable regions.

High throughput screening of fungal endoglucanase activity in Escherichia coli

Cellulase enzymes (endoglucanases, cellobiohydrolases, and β-glucosidases) hydrolyze cellulose into component sugars, which in turn can be converted into fuel alcohols. The potential for enzymatic hydrolysis of cellulosic biomass to provide renewable energy has intensified efforts to engineer cellulases for economical fuel production. Of particular interest are fungal cellulases, which are already being used industrially for foods and textiles processing. Identifying active variants among a library of mutant cellulases is critical to the engineering process; active mutants can be further tested for improved properties and/or subjected to additional mutagenesis. Efficient engineering of fungal cellulases has been hampered by a lack of genetic tools for native organisms and by difficulties in expressing the enzymes in heterologous hosts. Recently, Morikawa and coworkers developed a method for expressing in E. coli the catalytic domains of endoglucanases from H. jecorina, an important industrial fungus with the capacity to secrete cellulases in large quantities. Functional E. coli expression has also been reported for cellulases from other fungi, including Macrophomina phaseolina and Phanerochaete chrysosporium. We present a method for high throughput screening of fungal endoglucanase activity in E. coli. This method uses the common microbial dye Congo Red (CR) to visualize enzymatic degradation of carboxymethyl cellulose (CMC) by cells growing on solid medium. The activity assay requires inexpensive reagents, minimal manipulation, and gives unambiguous results as zones of degradation ("halos") at the colony site. Although a quantitative measure of enzymatic activity cannot be determined by this method, we have found that halo size correlates with total enzymatic activity in the cell. Further characterization of individual positive clones will determine , relative protein fitness. Traditional bacterial whole cell CMC/CR activity assays involve pouring agar containing CMC onto colonies, which is subject to cross-contamination, or incubating cultures in CMC agar wells, which is less amenable to large-scale experimentation. Here we report an improved protocol that modifies existing wash methods for cellulase activity: cells grown on CMC agar plates are removed prior to CR staining. Our protocol significantly reduces cross-contamination and is highly scalable, allowing the rapid screening of thousands of clones. In addition to H. jecorina enzymes, we have expressed and screened endoglucanase variants from the Thermoascus aurantiacus and Penicillium decumbens, suggesting that this protocol is applicable to enzymes from a range of organisms.

Engineered ketol-acid reductoisomerase and alcohol dehydrogenase enable anaerobic 2-methylpropan-1-ol production at theoretical yield in Escherichia coli

2-methylpropan-1-ol (isobutanol) is a leading candidate biofuel for the replacement or supplementation of current fossil fuels. Recent work has demonstrated glucose to isobutanol conversion through a modified amino acid pathway in a recombinant organism. Although anaerobic conditions are required for an economically competitive process, only aerobic isobutanol production has been feasible due to an imbalance in cofactor utilization. Two of the pathway enzymes, ketol-acid reductoisomerase and alcohol dehydrogenase, require nicotinamide dinucleotide phosphate (NADPH); glycolysis, however, produces only nicotinamide dinucleotide (NADH). Here, we compare two solutions to this imbalance problem: (1) over-expression of pyridine nucleotide transhydrogenase PntAB and (2) construction of an NADH-dependent pathway, using engineered enzymes. We demonstrate that an NADH-dependent pathway enables anaerobic isobutanol production at 100% theoretical yield and at higher titer and productivity than both the NADPH-dependent pathway and transhydrogenase over-expressing strain. Our results show how engineering cofactor dependence can overcome a critical obstacle to next-generation biofuel commercialization.

Metal-substituted protein MRI contrast agents engineered for enhanced relaxivity and ligand sensitivity

Engineered metalloproteins constitute a flexible new class of analyte-sensitive molecular imaging agents detectable by magnetic resonance imaging (MRI), but their contrast effects are generally weaker than synthetic agents. To augment the proton relaxivity of agents derived from the heme domain of cytochrome P450 BM3 (BM3h), we formed manganese(III)-containing proteins that have higher electron spin than their native ferric iron counterparts. Metal substitution was achieved by coexpressing BM3h variants with the bacterial heme transporter ChuA in Escherichia coli and supplementing the growth medium with Mn3+-protoporphyrin IX. Manganic BM3h variants exhibited up to 2.6-fold higher T1 relaxivities relative to native BM3h at 4.7 T. Application of ChuA-mediated porphyrin substitution to a collection of thermostable chimeric P450 domains resulted in a stable, high-relaxivity BM3h derivative displaying a 63% relaxivity change upon binding of arachidonic acid, a natural ligand for the P450 enzyme and an important component of biological signaling pathways. This work demonstrates that protein-based MRI sensors with robust ligand sensitivity may be created with ease by including metal substitution among the toolkit of methods available to the protein engineer.

Enzymatic functionalization of carbon-hydrogen bonds

The development of new catalytic methods to functionalize carbon-hydrogen (C-H) bonds continues to progress at a rapid pace due to the significant economic and environmental benefits of these transformations over traditional synthetic methods. In nature, enzymes catalyze regio- and stereoselective C-H bond functionalization using transformations ranging from hydroxylation to hydroalkylation under ambient reaction conditions. The efficiency of these enzymes relative to analogous chemical processes has led to their increased use as biocatalysts in preparative and industrial applications. Furthermore, unlike small molecule catalysts, enzymes can be systematically optimized via directed evolution for a particular application and can be expressed in vivo to augment the biosynthetic capability of living organisms. While a variety of technical challenges must still be overcome for practical application of many enzymes for C-H bond functionalization, continued research on natural enzymes and on novel artificial metalloenzymes will lead to improved synthetic processes for efficient synthesis of complex molecules. In this critical review, we discuss the most prevalent mechanistic strategies used by enzymes to functionalize non-acidic C-H bonds, the application and evolution of these enzymes for chemical synthesis, and a number of potential biosynthetic capabilities uniquely enabled by these powerful catalysts (110 references).

Cytochrome P450: taming a wild type enzyme

Protein engineering of cytochrome P450 monooxygenases (P450s) has been very successful in generating valuable non-natural activities and properties, allowing these powerful catalysts to be used for the synthesis of drug metabolites and in biosynthetic pathways for the production of precursors of artemisinin and paclitaxel. Collected experience indicates that the P450s are highly 'evolvable' - they are particularly robust to mutation in their active sites and readily accept new substrates and exhibit new selectivities. Their ability to adapt to new challenges upon mutation may reflect the nonpolar nature of their active sites as well as their high degree of conformational variability.

Optimizing non-natural protein function with directed evolution

Developing technologies such as unnatural amino acid mutagenesis, non-natural cofactor engineering, and computational design are generating proteins with novel functions; these proteins, however, often do not reach performance targets and would benefit from further optimization. Evolutionary methods can complement these approaches: recent work combining unnatural amino acid mutagenesis and phage selection has created useful proteins of novel composition. Weak initial activity in a computationally designed enzyme has been improved by iterative rounds of mutagenesis and screening. A marriage of ingenuity and evolution will expand the scope of protein function well beyond Mother Nature's designs.

Combinatorial recombination of gene fragments to construct a library of chimeras

Recombination of distantly related and nonrelated genes is difficult using traditional PCR-based techniques, and truncation-based methods result in a large proportion of nonviable sequences due to frame shifts, deletions, and insertions. This unit describes a method for creating libraries of chimeras through combinatorial assembly of gene fragments. It allows the experimenter to recombine genes of any identity and to select the sites where recombination takes place. Combinatorial recombination is achieved by generating gene fragments with specific overhangs, or sticky ends. The overhangs permit the fragments to be ligated in the correct order while allowing independent assortment of blocks with identical overhangs. Genes of any identity can be recombined so long as they share 3 to 5 base pairs of identity at the desired recombination sites. Simple adaptations of the method allow incorporation of specific gene fragments.

Improved product-per-glucose yields in P450-dependent propane biotransformations using engineered Escherichia coli

P450-dependent biotransformations in Escherichia coli are attractive for the selective oxidation of organic molecules using mild and sustainable procedures. The overall efficiency of these processes, however, relies on how effectively the NAD(P)H cofactors derived from oxidation of the carbon source are utilized inside the cell to support the heterologous P450-catalyzed reaction. In this work, we investigate the use of metabolic and protein engineering to enhance the product-per-glucose yield (Y(PPG)) in whole-cell reactions involving a proficient NADPH-dependent P450 propane monooxygenase prepared by directed evolution [P450(PMO)R2; Fasan et al. (2007); Angew Chem Int Ed 46:8414-8418]. Our studies revealed that the metabolism of E. coli (W3110) is able to support only a modest propanol: glucose molar ratio (YPPG ~ 0.5) under aerobic, nongrowing conditions. By altering key processes involved in NAD(P)H metabolism of the host, considerable improvements of this ratio could be achieved. A metabolically engineered E. coli strain featuring partial inactivation of the endogenous respiratory chain (Δndh) combined with removal of two fermentation pathways (ΔadhE, Δldh) provided the highest Y(PPG) (1.71) among the strains investigated, enabling a 230% more efficient utilization of the energy source (glucose) in the propane biotransformation compared to the native E. coli strain. Using an engineered P450(PMO)R2 variant which can utilize NADPH and NADH with equal efficiency, we also established that dual cofactor specificity of the P450 enzyme can provide an appreciable improvement in Y(PPG). Kinetic analyses suggest, however, that much more favorable parameters (K(M), k(cat)) for the NADH-driven reaction are required to effectively compete with the host's endogenous NADH-utilizing enzymes. Overall, the metabolic/protein engineering strategies described here can be of general value for improving the performance of NAD(P)H-dependent whole-cell biotransformations in E. coli.

A general mechanism for network-dosage compensation in gene circuits

Coping with variations in network dosage is crucial for maintaining optimal function in gene networks. We explored how network structure facilitates network-level dosage compensation. By using the yeast galactose network as a model, we combinatorially deleted one of the two copies of its four regulatory genes and found that network activity was robust to the change in network dosage. A mathematical analysis revealed that a two-component genetic circuit with elements of opposite regulatory activity (activator and inhibitor) constitutes a minimal requirement for network-dosage invariance. Specific interaction topologies and a one-to-one interaction stoichiometry between the activating and inhibiting agents were additional essential elements facilitating dosage invariance. This mechanism of network-dosage invariance could represent a general design for gene network structure in cells.

Random mutagenesis to enhance the activity of subtilisin in organic solvents: Characterization of Q103R subtilisin E

Q103R subtilisin E was isolated following random mutagenesis and screening for improved activity in the presence of dimethylformamide (DMF). Our goal is to identify the mechanism(s) by which amino acid substitutions can enhance enzyme activity in polar organic solvents. A quantitative framework for comparing substrate binding and catalytic activities of mutant and wild-type enzymes in the presence and absence of DMF is outlined. Kinetic experiments performed at high salt concentration (1M KCl) reveal that the mechanism behind the Q103R variant's enhanced activity toward succinyl-Ala-Ala-Pro-Phe-p-nitroanilide is both electrostatic and nonelectrostatic in origin. Favorable electrostatic interactions between the negatively charged succinyl group of the substrate and the positive charge on Arg 103 are responsible for tighter substrate binding. This conclusion is supported by kinetic experiments performed on the related substrate Ala-Ala-Pro-Phe-p-nitroanilide and the hydrolysis kinetics of the Q103E, Q103K, and Q103S variants constructed by site-directed mutagenesis. These results highlight the importance of the choice of the substrate used to screen for improvements in catalytic activity.

Stabilization of substilisin E in organic solvents by site-directed mutagenesis

Subtilisin E was rationally engineered to improve its stability in polar organic solvents such as dimethylformamide (DMF). A charged surface residue, Asp248, was substituted by three amino acids of increasing hydrophobicity, Asn, Ala, and Leu; all three variants were stabilized with respect to wild type in 80% DMF. This stabilization was only observed in the presence of high concentrations of the organic solvent: no stability enhancements were observed in 40% DMF. In contrast, the mutation Asn218 --> Ser alters internal hydrogen bonding interactions and stabilizes subtilisin E in both 40% and 80% DMF. This study provides additional evidence that substitution of surface-charged residues is a generally useful mechanism for stabilizing enzymes in organic media and that the stabilizing effects of such substitutions are unique to highly altered solvent environments. The effects of the single amino acid substitutions on free energies of stabilization are additive in the Asp248 --> Asn + Asn218 --> Ser combination variant, yielding an enzyme that is 3.4 times more stable than wild type in 80% DMF.

Consensus protein design without phylogenetic bias

Consensus design is an appealing strategy for the stabilization of proteins. It exploits amino acid conservation in sets of homologous proteins to identify likely beneficial mutations. Nevertheless, its success depends on the phylogenetic diversity of the sequence set available. Here, we show that randomization of a single protein represents a reliable alternative source of sequence diversity that is essentially free of phylogenetic bias. A small number of functional protein sequences selected from binary-patterned libraries suffice as input for the consensus design of active enzymes that are easier to produce and substantially more stable than individual members of the starting data set. Although catalytic activity correlates less consistently with sequence conservation in these extensively randomized proteins, less extreme mutagenesis strategies might be adopted in practice to augment stability while maintaining function.

How proteins adapt: lessons from directed evolution

Applying artificial selection to create new proteins has allowed us to explore fundamental processes of molecular evolution. These "directed evolution" experiments have shown that proteins can readily adapt to new functions or environments via simple adaptive walks involving small numbers of mutations. With the entire "fossil record" available for detailed study, these experiments have provided new insight into adaptive mechanisms and the effects of mutation and recombination. Directed evolution has also shown how mutations that are functionally neutral can set the stage for further adaptation. Watching adaptation in real time helps one to appreciate the power of the evolutionary design algorithm.

Exploring protein fitness landscapes by directed evolution

Directed evolution circumvents our profound ignorance of how a protein's sequence encodes its function by using iterative rounds of random mutation and artificial selection to discover new and useful proteins. Proteins can be tuned to adapt to new functions or environments by simple adaptive walks involving small numbers of mutations. Directed evolution studies have shown how rapidly some proteins can evolve under strong selection pressures and, because the entire 'fossil record' of evolutionary intermediates is available for detailed study, they have provided new insight into the relationship between sequence and function. Directed evolution has also shown how mutations that are functionally neutral can set the stage for further adaptation.

A panel of cytochrome P450 BM3 variants to produce drug metabolites and diversify lead compounds

Herein we demonstrate that a small panel of variants of cytochrome P450 BM3 from Bacillus megaterium covers the breadth of reactivity of human P450s by producing 12 of 13 mammalian metabolites for two marketed drugs, verapamil and astemizole, and one research compound. The most active enzymes support preparation of individual metabolites for preclinical bioactivity and toxicology evaluations. Underscoring their potential utility in drug lead diversification, engineered P450 BM3 variants also produce novel metabolites by catalyzing reactions at carbon centers beyond those targeted by animal and human P450s. Production of a specific metabolite can be improved by directed evolution of the enzyme catalyst. Some variants are more active on the more hydrophobic parent drug than on its metabolites, which limits production of multiply-hydroxylated species, a preference that appears to depend on the evolutionary history of the P450 variant.