Rational evolutionary design: the theory of in vitro protein evolution

Mathematical consideration of massive estimation of dissociation rate constant for genotype-phenotype linking molecules bound to targets through washing/selection and next-generation sequencing

As one of methods for in vitro selection, a flow reactor type washing/selection system seems to be effective, where a ligand library is composed of "genotype-phenotype linking molecules". In this system, high affinity ligands are selected by their respective "residual ratio" given by exp(-koff×t), where koff is the dissociation rate constant and t is the washing time. In this paper, we mathematically considered the following possibility. When the washing/selection dynamics obeys the residual ratio exp(-koff×t) deterministically and mole fraction measurement for sampled sequences by next-generation sequencing (NGS) is performed ideally, the "relative value" of koff for each of high-ranking sequences can be estimated simultaneously. In addition to these, when the residual ratio for the whole ligand population is measured correctly, the "absolute value" for each sequence can be estimated. We deduced formulas to present the relative and absolute estimates, and mathematically analyzed the effect of fluctuations in the number of NGS reads on the estimates in details. These were confirmed by numerical simulations.

Evolved cytidine and adenine base editors with high precision and minimized off-target activity by a continuous directed evolution system in mammalian cells

Continuous directed evolution of base editors (BEs) has been successful in bacteria cells, but not yet in mammalian cells. Here, we report the development of a Continuous Directed Evolution system in Mammalian cells (CDEM). CDEM enables the BE evolution in a full-length manner with Cas9 nickase. We harness CDEM to evolve the deaminases of cytosine base editor BE3 and adenine base editors, ABEmax and ABE8e. The evolved cytidine deaminase variants on BE4 architecture show not only narrowed editing windows, but also higher editing purity and low off-target activity without a trade-off in on-targeting activity. The evolved ABEmax and ABE8e variants exhibit narrowed or shifted editing windows to different extents, and lower off-target effects. The results illustrate that CDEM is a simple but powerful approach to continuously evolve BEs without size restriction in the mammalian environment, which is advantageous over continuous directed evolution system in bacteria cells.

Engineering is evolution: a perspective on design processes to engineer biology

Careful consideration of how we approach design is crucial to all areas of biotechnology. However, choosing or developing an effective design methodology is not always easy as biology, unlike most areas of engineering, is able to adapt and evolve. Here, we put forward that design and evolution follow a similar cyclic process and therefore all design methods, including traditional design, directed evolution, and even random trial and error, exist within an evolutionary design spectrum. This contrasts with conventional views that often place these methods at odds and provides a valuable framework for unifying engineering approaches for challenging biological design problems.

Biomanufacturing by In Vitro Biotransformation (ivBT) Using Purified Cascade Multi-enzymes

In vitro biotransformation (ivBT) refers to the use of an artificial biological reaction system that employs purified enzymes for the one-pot conversion of low-cost materials into biocommodities such as ethanol, organic acids, and amino acids. Unshackled from cell growth and metabolism, ivBT exhibits distinct advantages compared with metabolic engineering, including but not limited to high engineering flexibility, ease of operation, fast reaction rate, high product yields, and good scalability. These characteristics position ivBT as a promising next-generation biomanufacturing platform. Nevertheless, challenges persist in the enhancement of bulk enzyme preparation methods, the acquisition of enzymes with superior catalytic properties, and the development of sophisticated approaches for pathway design and system optimization. In alignment with the workflow of ivBT development, this chapter presents a systematic introduction to pathway design, enzyme mining and engineering, system construction, and system optimization. The chapter also proffers perspectives on ivBT development.

A unified model of ketamine's dissociative and psychedelic properties

Ketamine is an N-methyl-d-aspartate antagonist which is increasingly being researched and used as a treatment for depression. In low doses, it can cause a transitory modification in consciousness which was classically labelled as 'dissociation'. However, ketamine is also commonly classified as an atypical psychedelic and it has been recently reported that ego dissolution experiences during ketamine administration are associated with greater antidepressant response. Neuroimaging studies have highlighted several similarities between the effects of ketamine and those of serotonergic psychedelics in the brain; however, no unified account has been proposed for ketamine's multi-level effects - from molecular to network and psychological levels. Here, we propose that the fast, albeit transient, antidepressant effects observed after ketamine infusions are mainly driven by its acute modulation of reward circuits and sub-acute increase in neuroplasticity, while its dissociative and psychedelic properties are driven by dose- and context-dependent disruption of large-scale functional networks. Computationally, as nodes of the salience network (SN) represent high-level priors about the body ('minimal' self) and nodes of the default-mode network (DMN) represent the highest-level priors about narrative self-experience ('biographical' self), we propose that transitory SN desegregation and disintegration accounts for ketamine's 'dissociative' state, while transitory DMN desegregation and disintegration accounts for ketamine's 'psychedelic' state. In psychedelic-assisted psychotherapy, a relaxation of the highest-level beliefs with psychotherapeutic support may allow a revision of pathological self-representation models, for which neuroplasticity plays a permissive role. Our account provides a multi-level rationale for using the psychedelic properties of ketamine to increase its long-term benefits.

Designing Artificial Metalloenzymes by Tuning of the Environment beyond the Primary Coordination Sphere

Metalloenzymes catalyze a variety of reactions using a limited number of natural amino acids and metallocofactors. Therefore, the environment beyond the primary coordination sphere must play an important role in both conferring and tuning their phenomenal catalytic properties, enabling active sites with otherwise similar primary coordination environments to perform a diverse array of biological functions. However, since the interactions beyond the primary coordination sphere are numerous and weak, it has been difficult to pinpoint structural features responsible for the tuning of activities of native enzymes. Designing artificial metalloenzymes (ArMs) offers an excellent basis to elucidate the roles of these interactions and to further develop practical biological catalysts. In this review, we highlight how the secondary coordination spheres of ArMs influence metal binding and catalysis, with particular focus on the use of native protein scaffolds as templates for the design of ArMs by either rational design aided by computational modeling, directed evolution, or a combination of both approaches. In describing successes in designing heme, nonheme Fe, and Cu metalloenzymes, heteronuclear metalloenzymes containing heme, and those ArMs containing other metal centers (including those with non-native metal ions and metallocofactors), we have summarized insights gained on how careful controls of the interactions in the secondary coordination sphere, including hydrophobic and hydrogen bonding interactions, allow the generation and tuning of these respective systems to approach, rival, and, in a few cases, exceed those of native enzymes. We have also provided an outlook on the remaining challenges in the field and future directions that will allow for a deeper understanding of the secondary coordination sphere a deeper understanding of the secondary coordintion sphere to be gained, and in turn to guide the design of a broader and more efficient variety of ArMs.

Understanding the human antibody repertoire

The origins of the various elements in the human antibody repertoire have been and still are subject to considerable uncertainty. Uncertainty in respect of whether the various elements have always served a specific defense function or whether they were co-opted from other organismal roles to form a crude naïve repertoire that then became more complex as combinatorial mechanisms were added. Estimates of the current size of the human antibody naïve repertoire are also widely debated with numbers anywhere from 10 million members, based on experimentally derived numbers, to in excess of one thousand trillion members or more, based on the different sequences derived from theoretical combinatorial calculations. There are questions that are relevant at both ends of this number spectrum. At the lower bound it could be questioned whether this is an insufficient repertoire size to counter all the potential antigen-bearing pathogens. At the upper bound the question is rather simpler: How can any individual interrogate such an astronomical number of antibody-bearing B cells in a timeframe that is meaningful? This review evaluates the evolutionary aspects of the adaptive immune system, the calculations that lead to the large repertoire estimates, some of the experimental evidence pointing to a more restricted repertoire whose variation appears to derive from convergent 'structure and specificity features', and includes a theoretical model that seems to support it. Finally, a solution that may reconcile the size difference anomaly, which is still a hot subject of debate, is suggested.

GeneORator: An Effective Strategy for Navigating Protein Sequence Space More Efficiently through Boolean OR-Type DNA Libraries

Directed evolution requires the creation of genetic diversity and subsequent screening or selection for improved variants. For DNA mutagenesis, conventional site-directed methods implicitly utilize the Boolean AND operator (creating all mutations simultaneously), producing a combinatorial explosion in the number of genetic variants as the number of mutations increases. We introduce GeneORator, a novel strategy for creating DNA libraries based on the Boolean logical OR operator. Here, a single library is divided into many subsets, each containing different combinations of the desired mutations. Consequently, the effect of adding more mutations on the number of genetic combinations is additive (Boolean OR logic) and not exponential (AND logic). We demonstrate this strategy with large-scale mutagenesis studies, using monoamine oxidase-N ( Aspergillus niger) as the exemplar target. First, we mutated every residue in the secondary structure-containing regions (276 out of a total 495 amino acids) to screen for improvements in k_cat. Second, combinatorial OR-type libraries permitted screening of diverse mutation combinations in the enzyme active site to detect activity toward novel substrates. In both examples, OR-type libraries effectively reduced the number of variants searched up to 10¹⁰-fold, dramatically reducing the screening effort required to discover variants with improved and/or novel activity. Importantly, this approach enables the screening of a greater diversity of mutation combinations, accessing a larger area of a protein's sequence space. OR-type libraries can be applied to any biological engineering objective requiring DNA mutagenesis, and the approach has wide ranging applications in, for example, enzyme engineering, antibody engineering, and synthetic biology.

Deep learning to predict the lab-of-origin of engineered DNA

Genetic engineering projects are rapidly growing in scale and complexity, driven by new tools to design and construct DNA. There is increasing concern that widened access to these technologies could lead to attempts to construct cells for malicious intent, illegal drug production, or to steal intellectual property. Determining the origin of a DNA sequence is difficult and time-consuming. Here deep learning is applied to predict the lab-of-origin of a DNA sequence. A convolutional neural network was trained on the Addgene plasmid dataset that contained 42,364 engineered DNA sequences from 2230 labs as of February 2016. The network correctly identifies the source lab 48% of the time and 70% it appears in the top 10 predicted labs. Often, there is not a single "smoking gun" that affiliates a DNA sequence with a lab. Rather, it is a combination of design choices that are individually common but collectively reveal the designer.

Surveying the expanding prokaryotic Rubisco multiverse

The universal, but catalytically modest, CO2-fixing enzyme Rubisco is currently experiencing intense interest by researchers aiming to enhance crop photosynthesis. These efforts are mostly focused on the highly conserved hexadecameric enzyme found in land plants. In comparison, prokaryotic organisms harbor a far greater diversity in Rubisco forms. Recent work towards improving our appreciation of microbial Rubisco properties and harnessing their potential is surveyed. New structural models are providing informative glimpses into catalytic subtleties and diverse oligomeric states. Ongoing characterization is informing us about the conservation of constraints, such as sugar phosphate inhibition and the associated dependence on Rubisco activase helper proteins. Prokaryotic Rubiscos operate under a far wider range of metabolic contexts than the photosynthetic function of higher plant enzymes. Relaxed selection pressures may have resulted in the exploration of a larger volume of sequence space than permitted in organisms performing oxygenic photosynthesis. To tap into the potential of microbial Rubiscos, in vivo selection systems are being used to discover functional metagenomic Rubiscos. Various directed evolution systems to optimize their function have been developed. It is anticipated that this approach will provide access to biotechnologically valuable enzymes that cannot be encountered in the higher plant Rubisco space.

SpeedyGenes: Exploiting an Improved Gene Synthesis Method for the Efficient Production of Synthetic Protein Libraries for Directed Evolution

Gene synthesis is a fundamental technology underpinning much research in the life sciences. In particular, synthetic biology and biotechnology utilize gene synthesis to assemble any desired DNA sequence, which can then be incorporated into novel parts and pathways. Here, we describe SpeedyGenes, a gene synthesis method that can assemble DNA sequences with greater fidelity (fewer errors) than existing methods, but that can also be used to encode extensive, statistically designed sequence variation at any position in the sequence to create diverse (but accurate) variant libraries. We summarize the integrated use of GeneGenie to design DNA and oligonucleotide sequences, followed by the procedure for assembling these accurately and efficiently using SpeedyGenes.

Balancing gene expression without library construction via a reusable sRNA pool

Balancing protein expression is critical when optimizing genetic systems. Typically, this requires library construction to vary the genetic parts controlling each gene, which can be expensive and time-consuming. Here, we develop sRNAs corresponding to 15nt ‘target’ sequences that can be inserted upstream of a gene. The targeted gene can be repressed from 1.6- to 87-fold by controlling sRNA expression using promoters of different strength. A pool is built where six sRNAs are placed under the control of 16 promoters that span a ∼10³-fold range of strengths, yielding ∼10⁷ combinations. This pool can simultaneously optimize up to six genes in a system. This requires building only a single system-specific construct by placing a target sequence upstream of each gene and transforming it with the pre-built sRNA pool. The resulting library is screened and the top clone is sequenced to determine the promoter controlling each sRNA, from which the fold-repression of the genes can be inferred. The system is then rebuilt by rationally selecting parts that implement the optimal expression of each gene. We demonstrate the versatility of this approach by using the same pool to optimize a metabolic pathway (β-carotene) and genetic circuit (XNOR logic gate).

Evolutionary dynamics of a polymorphic self-replicator population with a finite population size and hyper mutation rate

Self-replicating biomolecules, subject to experimental evolution, exhibit hyper mutation rates where the genotypes of most offspring have at least a one point mutation. Thus, we formulated the evolutionary dynamics of an asexual self-replicator population with a finite population size and hyper mutation rate, based on the probability density of fitnesses (fitness distribution) for the evolving population. As a case study, we used a Kauffman's "NK fitness landscape". We deduced recurrence relations for the first three cumulants of the fitness distribution and compared them with the results of computer simulations. We found that the evolutionary dynamics is classified in terms of two modes of selection: the "radical mode" and the "gentle mode". In the radical mode, only a small number of genotypes with the highest or near highest fitness values can leave offspring. In the gentle mode, genotypes with moderate fitness values can leave offspring. We clarified how the evolutionary equilibrium and climbing rate depend on given parameters such as gradient and ruggedness of the landscape, mutation rate and population size, in terms of the two modes of selection. Roughly, the radical mode conducts the fast climbing but attains to the stationary states with low fitness, while the gentle mode conducts the slow climbing but attains to the stationary states with high fitness.

The virtue of innovation: innovation through the lenses of biological evolution

We rehearse the processes of innovation and discovery in general terms, using as our main metaphor the biological concept of an evolutionary fitness landscape. Incremental and disruptive innovations are seen, respectively, as successful searches carried out locally or more widely. They may also be understood as reflecting evolution by mutation (incremental) versus recombination (disruptive). We also bring a platonic view, focusing on virtue and memory. We use 'virtue' as a measure of efforts, including the knowledge required to come up with disruptive and incremental innovations, and 'memory' as a measure of their lifespan, i.e. how long they are remembered. Fostering innovation, in the evolutionary metaphor, means providing the wherewithal to promote novelty, good objective functions that one is trying to optimize, and means to improve one's knowledge of, and ability to navigate, the landscape one is searching. Recombination necessarily implies multi- or inter-disciplinarity. These principles are generic to all kinds of creativity, novel ideas formation and the development of new products and technologies.

Protein Thermostability Is Owing to Their Preferences to Non-Polar Smaller Volume Amino Acids, Variations in Residual Physico-Chemical Properties and More Salt-Bridges

Introduction

Protein thermostability is an important field for its evolutionary perspective of mesophilic versus thermophilic relationship and for its industrial/ therapeutic applications.

Methods

Presently, a total 400 (200 thermophilic and 200 mesophilic homologue) proteins were studied utilizing several software/databases to evaluate their amino acid preferences. Randomly selected 50 homologous proteins with available PDB-structure of each group were explored for the understanding of the protein charges, isoelectric-points, hydrophilicity, hydrophobicity, tyrosine phosphorylation and salt-bridge occurrences. These 100 proteins were further probed to generate Ramachandran plot/data for the gross secondary structure prediction in and comparison between the thermophilic and mesophilic proteins.

Results

Present results strongly suggest that nonpolar smaller volume amino acids Ala (χ² = 238.54, p<0.001) and Gly (χ² = 73.35, p<0.001) are highly and Val moderately (χ² = 144.43, p<0.001) occurring in the 85% of thermophilic proteins. Phospho-regulated Tyr and redox-sensitive Cys are also moderately distributed (χ²~20.0, p<0.01) in a larger number of thermophilic proteins. A consistent lower distribution of thermophilicity and discretely higher distribution of hydrophobicity is noticed in a large number of thermophilic versus their mesophilic protein homolog. The mean differences of isoelectric points and charges are found to be significantly less (7.11 vs. 6.39, p<0.05 and 1 vs. -0.6, p<0.01, respectively) in thermophilic proteins compared to their mesophilic counterpart. The possible sites for Tyr phosphorylation are noticed to be 25% higher (p<0.05) in thermophilic proteins. The 60% thermophiles are found with higher number of salt bridges in this study. The average percentage of salt-bridge of thermophiles is found to be higher by 20% than their mesophilic homologue. The GLU-HIS and GLU-LYS salt-bridge dyads are calculated to be significantly higher (p<0.05 and p<0.001, respectively) in thermophilic and GLU-ARG is higher in the mesophilic proteins. The Ramachandran plot/ data suggest a higher abundance of the helix, left-handed helix, sheet, nonplanar peptide and lower occurrence of cis peptide, loop/ turn and outlier in thermophiles. Pearson’s correlation result suggests that the isoelectric points of mesophilic and thermophilic proteins are positively correlated (r = 0.93 and 0.84, respectively; p<0.001) to their corresponding charges. And their hydrophilicity is negatively associated with the corresponding hydrophobicity (r = -0.493, p<0.001 and r = -0.324, p<0.05) suggesting their reciprocal evolvement.

Conclusions

Present results for the first time with this large amount of datasets and multiple contributing factors suggest the greater occurrence of hydrophobicity, salt-bridges and smaller volume nonpolar residues (Gly, Ala and Val) and lesser occurrence of bulky polar residues in the thermophilic proteins. A more stoichiometric relationship amongst these factors minimized the hindrance due to side chain burial and increased compactness and secondary structural stability in thermophilic proteins.

Biophysics of protein evolution and evolutionary protein biophysics

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

In vitro affinity maturation of a natural human antibody overcomes a barrier to in vivo affinity maturation

Antibodies isolated from human donors are increasingly being developed for anti-infective therapeutics. These antibodies undergo affinity maturation in vivo, minimizing the need for engineering of therapeutic leads for affinity. However, the affinities required for some therapeutic applications may be higher than the affinities of the leads obtained, requiring further affinity maturation in vitro. To improve the neutralization potency of natural human antibody MSL-109 targeting human cytomegalovirus (CMV), we affinity matured the antibody against the gH/gL glycoprotein complex. A phage display library where most of the six complementary-determining regions (CDRs) were allowed to vary in only one amino acid residue at a time was used to scan for mutations that improve binding affinity. A T55R mutation and multiple mutations in position 53 of the heavy chain were identified that, when present individually or in combination, resulted in higher apparent affinities to gH/gL and improved CMV neutralization potency of Fab fragments expressed in bacterial cells. Three of these mutations in position 53 introduced glycosylation sites in heavy chain CDR 2 (CDR H2) that impaired binding of antibodies expressed in mammalian cells. One high affinity (KD<10 pM) variant was identified that combined the D53N and T55R mutations while avoiding glycosylation of CDR H2. However, all the amino acid substitutions identified by phage display that improved binding affinity without introducing glycosylation sites required between two and four simultaneous nucleotide mutations to avoid glycosylation. These results indicate that the natural human antibody MSL-109 is close to a local affinity optimum. We show that affinity maturation by phage display can be used to identify and bypass barriers to in vivo affinity maturation of antibodies imposed by glycosylation and codon usage. These constraints may be relatively prevalent in human antibodies due to the codon usage and the amino acid sequence encoded by the natural human repertoire.

Chemical synthetic biology

Although both the most popular form of synthetic biology (SB) and chemical synthetic biology (CSB) share the biotechnologically useful aim of making new forms of life, SB does so by using genetic manipulation of extant microorganism, while CSB utilises classic chemical procedures in order to obtain biological structures which are non-existent in nature. The main query concerning CSB is the philosophical question: why did nature do this, and not that? The idea then is to synthesise alternative structures in order to understand why nature operated in such a particular way. We briefly present here some various examples of CSB, including those cases of nucleic acids synthesised with pyranose instead of ribose, and proteins with a reduced alphabet of amino acids; also we report the developing research on the "never born proteins" (NBP) and "never born RNA" (NBRNA), up to the minimal cell project, where the issue is the preparation of semi-synthetic cells that can perform the basic functions of biological cells.

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.

Helical ambivalency induced by point mutations

Background

Mutation of amino acid sequences in a protein may have diverse effects on its structure and function. Point mutations of even a single amino acid residue in the helices of the non-redundant database may lead to sequentially identical peptides which adopt different secondary structures in different proteins. However, various physico-chemical factors which govern the formation of these ambivalent helices generated by point mutations of a sequence are not clearly known.

Results

Sequences generated by point mutations of helices are mapped on to their non-helical counterparts in the SCOP database. The results show that short helices are prone to transform into non-helical conformations upon point mutations. Mutation of amino acid residues by helix breakers preferentially yield non-helical conformations, while mutation with residues of intermediate helix propensity display least preferences for non-helical conformations. Differences in the solvent accessibility of the mutating/mutated residues are found to be a major criteria for these sequences to conform to non-helical conformations. Even with minimal differences in the amino acid distributions of the sequences flanking the helical and non-helical conformations, helix-flanking sequences are found be more solvent accessible.

Conclusions

All types of mutations from helical to non-helical conformations are investigated. The primary factors attributing such changes in conformation can be: i) type/propensity of the mutating and mutant residues ii) solvent accessibility of the residue at the mutation site iii) context/environment dependence of the flanking sequences. The results from the present study may be used to design de novo proteins via point mutations.

The spatial architecture of protein function and adaptation

Statistical analysis of protein evolution suggests a design for natural proteins in which sparse networks of coevolving amino acids (termed sectors) comprise the essence of three-dimensional structure and function. However, proteins are also subject to pressures deriving from the dynamics of the evolutionary process itself--the ability to tolerate mutation and to be adaptive to changing selection pressures. To understand the relationship of the sector architecture to these properties, we developed a high-throughput quantitative method for a comprehensive single-mutation study in which every position is substituted individually to every other amino acid. Using a PDZ domain (PSD95(pdz3)) model system, we show that sector positions are functionally sensitive to mutation, whereas non-sector positions are more tolerant to substitution. In addition, we find that adaptation to a new binding specificity initiates exclusively through variation within sector residues. A combination of just two sector mutations located near and away from the ligand-binding site suffices to switch the binding specificity of PSD95(pdz3) quantitatively towards a class-switching ligand. The localization of functional constraint and adaptive variation within the sector has important implications for understanding and engineering proteins.

Mutations at the putative active cavity of styrene monooxygenase: enhanced activity and reversed enantioselectivity

Styrene monooxygenase (SMO) catalyzes the first step of styrene degradation, and also serves as an important enzyme for the synthesis of enantiopure epoxides. To enhance its activity, molecular docking of styrene was performed based on the X-ray crystal structure of the oxygenase subunit of SMO to identify three amino acid residues (Tyr73, His76 and Ser96) being adjacent to the phenyl ring of styrene. Variants at those positions were constructed and their enzymatic activities were analyzed. Three mutants (Y73V, Y73F, and S96A) were found to exhibit higher enzymatic activities than the wild-type in the epoxidation of styrene, while retaining excellent stereoselectivity. The specific epoxidation activity of the most active mutant S96A toward styrene and trans-β-methyl styrene were 2.6 and 2.3-fold of the wild-type, respectively. In addition, the Y73V mutant showed an unexpected reversal of enantiomeric preference toward 1-phenylcyclohexene.

Multiple genetic pathways to similar fitness limits during viral adaptation to a new host

The gain in fitness during adaptation depends on the supply of beneficial mutations. Despite a good theoretical understanding of how evolution proceeds for a defined set of mutations, there is little understanding of constraints on net fitness-whether fitness will reach a limit despite ongoing selection and mutation, and if there is a limit, what determines it. Here, the dsDNA bacteriophage SP6, a virus of Salmonella, was adapted to Escherichia coli K-12. From an isolate capable of modest growth on E. coli, four lines were adapted for rapid growth by protocols differing in use of mutagen, propagation method, and duration, but using the same media, temperature, and a continual excess of the novel host. Nucleotide changes underlying those adaptations differed greatly in number and identity, but the four lines achieved similar absolute fitness at the end, an increase of more than 4000-fold phage descendants per hour. Thus, the fitness landscape allows multiple genetic paths to the same approximate fitness limit. The existence and causes of fitness limits have ramifications to genome engineering, vaccine design, and "lethal mutagenesis" treatments to cure viral infections.

Uricases as therapeutic agents to treat refractory gout: Current states and future directions

Treatment of refractory gout remains a challenge on drug development. While pegloticase, a recombinant mammalian uricase modified with monomethoxyl-poly(ethylene glycol) (mPEG) is effective in treating refractory gout, after continued treatment for three months biweekly at a therapeutic dose of 0.14 mg/kg body weight, it elicits an immune response against mPEG in nearly 20% of patients. For continued treatment of refractory gout PEGylated uricases at monthly therapeutic doses below 4 μg/kg body weight have promise. To formulate uricases to achieve monthly therapeutic regimens requires pharmacodynamics simulation and experimentation including: (a) molecular engineering of uricases based on rational design and evolution biotechnology in combination to improve their inherent catalytic efficiency, thermostability and selectivity for urate over xanthine and; (b) optimization of the number and distribution of accessible reactive amino acid residues in native uricases for site-specific PEGylation with PEG derivatives with lower of immunogenicity than mPEG to retain activity, minimize immunogenicity and enhance the pharmacokinetics of the PEGylated uricase. These issues are briefly reviewed as a means to stimulate the development of safer uricase formulations for continued treatment of refractory gout.

Predictability of evolutionary trajectories in fitness landscapes

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.

Is evolution deterministic, hence predictable, or stochastic, that is unpredictable? What would happen if one could “replay the tape of evolution”: will the outcomes of evolution be completely different or is evolution so constrained that history will be repeated? Arguably, these questions are among the most intriguing and most difficult in evolutionary biology. In other words, the predictability of evolution depends on the fraction of the trajectories on fitness landscapes that are accessible for evolutionary exploration. Because direct experimental investigation of fitness landscapes is technically challenging, the available studies only explore a minuscule portion of the landscape for individual enzymes. We therefore sought to investigate the topography of fitness landscapes within the framework of a previously developed model of protein folding and evolution where fitness is equated with robustness to misfolding. We show that model-derived and experimental landscapes are significantly smoother than random landscapes and resemble moderately perturbed additive landscapes; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. Thus, the smoothness and substantial deficit of peaks in fitness landscapes of protein evolution could be fundamental consequences of the physics of protein folding.

A system for the continuous directed evolution of biomolecules

Laboratory evolution has generated many biomolecules with desired properties, but a single round of mutation, gene expression, screening or selection, and replication typically requires days or longer with frequent human intervention.1 Since evolutionary success is dependent on the total number of rounds performed,2 a means of performing laboratory evolution continuously and rapidly could dramatically enhance its effectiveness.3 While researchers have accelerated individual steps in the evolutionary cycle,4–9 the only previous example of continuous directed evolution was the landmark study of Joyce,10 who continuously evolved RNA ligase ribozymes with an in vitro replication cycle that unfortunately cannot be easily adapted to other biomolecules. Here we describe a system that enables the continuous directed evolution of gene-encoded molecules that can be linked to protein production in E. coli. During phage-assisted continuous evolution (PACE), evolving genes are transferred from host cell to host cell through a modified bacteriophage life cycle in a manner that is dependent on the activity of interest. Dozens of rounds of evolution can occur in a single day of PACE without human intervention. Using PACE, we evolved T7 RNA polymerases that recognize a distinct promoter, initiate transcripts with A instead of G, and initiate transcripts with C. In one example, PACE executed 200 rounds of protein evolution over the course of eight days. Starting from undetectable activity levels in two of these cases, enzymes with each of the three target activities emerged in less than one week of PACE. In all three cases, PACE-evolved polymerase activities exceeded or were comparable to that of the wild-type T7 RNAP on its wild-type promoter, representing improvements of up to several hundred-fold. By greatly accelerating laboratory evolution, PACE may provide solutions to otherwise intractable directed evolution problems and address novel questions about molecular evolution.

Convergent evolution to an aptamer observed in small populations on DNA microarrays

The development of aptamers on custom synthesized DNA microarrays, which has been demonstrated in recent publications, can facilitate detailed analyses of sequence and fitness relationships. Here we use the technique to observe the paths taken through sequence-fitness space by three different evolutionary regimes: asexual reproduction, recombination and model-based evolution. The different evolutionary runs are made on the same array chip in triplicate, each one starting from a small population initialized independently at random. When evolving to a common target protein, glucose-6-phosphate dehydrogenase (G6PD), these nine distinct evolutionary runs are observed to develop aptamers with high affinity and to converge on the same motif not present in any of the starting populations. Regime specific differences in the evolutions, such as speed of convergence, could also be observed.

Improving biocatalyst performance by integrating statistical methods into protein engineering

Directed evolution and rational design were used to generate active variants of toluene-4-monooxygenase (T4MO) on 2-phenylethanol (PEA), with the aim of producing hydroxytyrosol, a potent antioxidant. Due to the complexity of the enzymatic system-four proteins encoded by six genes-mutagenesis is labor-intensive and time-consuming. Therefore, the statistical model of Nov and Wein (J. Comput. Biol. 12:247-282) was used to reduce the number of variants produced and evaluated in a lab. From an initial data set of 24 variants, with mutations at nine positions, seven double or triple mutants were identified through statistical analysis. The average activity of these mutants was 4.6-fold higher than the average activity of the initial data set. In an attempt to further improve the enzyme activity to obtain PEA hydroxylation, a second round of statistical analysis was performed. Nine variants were considered, with 3, 4, and 5 point mutations. The average activity of the variants obtained in the second statistical round was 1.6-fold higher than in the first round and 7.3-fold higher than that of the initial data set. The best variant discovered, TmoA I100A E214G D285Q, exhibited an initial oxidation rate of 4.4 ± 0.3 nmol/min/mg protein, which is 190-fold higher than the rate obtained by the wild type. This rate was also 2.6-fold higher than the activity of the wild type on the natural substrate toluene. By considering only 16 preselected mutants (out of ∼13,000 possible combinations), a highly active variant was discovered with minimum time and effort.

A trade-off relationship between energetic cost and entropic cost for in vitro evolution

In this paper, we consider two complementary cost functions for the landscape exploring processes to obtain the global optimum sequence through in vitro evolution protocol: one is the entropic cost C(etp), which is based on the deviation from the uniformity of a mutant distribution in sequence space, and the other is the energetic cost C(eng), which is based on the total number of sequences to be generated and evaluated. Based on a prior knowledge about the structure of a given fitness landscapes, the conductor of the experiment can think up the efficient search algorithm (ESA), which requires the minimum number of points (=sequences) to be searched up to the global optimum. For five typical fitness landscapes, we considered their respective (putative) ESA, C(etp)(*) and C(eng)(*) based on the ESA. As a result, we found a trade-off relationship between C(etp)(*) and C(eng)(*) for every case, that is, C(eng)(*)+C(etp)(*) is approximately equal to the logarithm of the volume of the sequence space. C(etp)(*) and C(eng)(*) are interpreted in terms of the information-theoretic concepts.

High-throughput metabolic engineering: advances in small-molecule screening and selection

Metabolic engineering for the overproduction of high-value small molecules is dependent upon techniques in directed evolution to improve production titers. The majority of small molecules targeted for overproduction are inconspicuous and cannot be readily obtained by screening. We provide a review on the development of high-throughput colorimetric, fluorescent, and growth-coupled screening techniques, enabling inconspicuous small-molecule detection. We first outline constraints on throughput imposed during the standard directed evolution workflow (library construction, transformation, and screening) and establish a screening and selection ladder on the basis of small-molecule assay throughput and sensitivity. An in-depth analysis of demonstrated screening and selection approaches for small-molecule detection is provided. Particular focus is placed on in vivo biosensor-based detection methods that reduce or eliminate in vitro assay manipulations and increase throughput. We conclude by providing our prospectus for the future, focusing on transcription factor-based detection systems as a natural microbial mode of small-molecule detection.

CyDNA: synthesis and replication of highly Cy-dye substituted DNA by an evolved polymerase

DNA not only transmits genetic information but can also serve as a versatile supramolecular scaffold. Here we describe a strategy for the synthesis and replication of DNA displaying hundreds of substituents using directed evolution of polymerase function by short-patch compartmentalized self-replication (spCSR) and the widely used fluorescent dye labeled deoxinucleotide triphosphates Cy3-dCTP and Cy5-dCTP as substrates. In just two rounds of spCSR selection, we have isolated a polymerase that allows the PCR amplification of double stranded DNA fragments up to 1kb, in which all dC bases are substituted by its fluorescent dye-labeled equivalent Cy3- or Cy5-dC. The resulting "CyDNA" displays hundreds of aromatic heterocycles on the outside of the DNA helix and is brightly colored and highly fluorescent. CyDNA also exhibits significantly altered physicochemical properties compared to standard B-form DNA, including loss of silica and intercalating dye binding, resistance to cleavage by some endonucleases, an up to 40% increased apparent diameter as judged by atomic force microscopy and organic phase partitioning during phenol extraction. CyDNA also displays very bright fluorescence enabling significant signal gains in microarray and microfluidic applications. CyDNA represents a step toward a long-term goal of the encoded synthesis of DNA-based polymers of programmable and evolvable sequence and properties.

The free-energy principle: a unified brain theory?

A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories - optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.

Analysis of a complete DNA-protein affinity landscape

Properties of biological fitness landscapes are of interest to a wide sector of the life sciences, from ecology to genetics to synthetic biology. For biomolecular fitness landscapes, the information we currently possess comes primarily from two sources: sparse samples obtained from directed evolution experiments; and more fine-grained but less authentic information from 'in silico' models (such as NK-landscapes). Here we present the entire protein-binding profile of all variants of a nucleic acid oligomer 10 bases in length, which we have obtained experimentally by a series of highly parallel on-chip assays. The resulting complete landscape of sequence-binding pairs, comprising more than one million binding measurements in duplicate, has been analysed statistically using a number of metrics commonly applied to synthetic landscapes. These metrics show that the landscape is rugged, with many local optima, and that this arises from a combination of experimental variation and the natural structural properties of the oligonucleotides.

Evolution of protein modularity

Proteins in their evolution appear to follow several discrete stages, which is reflected in their modular organization. The sequences of the protein modules are highly variable while their functions and structures are rather conserved. The relatedness of the variable sequences is well represented by the networks in natural protein sequence space that also suggests evolutionary connections.

A framework for evolutionary systems biology

BACKGROUND

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.

RESULTS

Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.

CONCLUSION

EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

Directing the evolution of Rubisco and Rubisco activase: first impressions of a new tool for photosynthesis research

During the last decade the practice of laboratory-directed protein evolution has become firmly established as a versatile tool in biochemical research by enabling molecular evolution toward desirable phenotypes or detection of novel structure-function interactions. Applications of this technique in the field of photosynthesis research are still in their infancy, but recently first steps have been reported in the directed evolution of the CO(2)-fixing enzyme Rubisco and its helper protein Rubisco activase. Here we summarize directed protein evolution strategies and review the progressive advances that have been made to develop and apply suitable selection systems for screening mutant forms of these enzymes that improve the fitness of the host organism. The goal of increasing photosynthetic efficiency of plants by improving the kinetics of Rubisco has been a long-term goal scoring modest successes. We discuss how directed evolution methodologies may one day be able to circumvent the problems encountered during this venture.