Takuyo Aita

Experimental rugged fitness landscape in protein sequence space.

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffmans n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Quantifying epistatic interactions among the components constituting the protein translation system

In principle, the accumulation of knowledge regarding the molecular basis of biological systems should allow the development of large‐scale kinetic models of their functions. However, the development of such models requires vast numbers of parameters, which are difficult to obtain in practice. Here, we used an in vitro translation system, consisting of 69 defined components, to quantify the epistatic interactions among changes in component concentrations through Bahadur expansion, thereby obtaining a coarse‐grained model of protein synthesis activity. Analyses of the data measured using various combinations of component concentrations indicated that the contributions of larger than 2‐body inter‐component epistatic interactions are negligible, despite the presence of larger than 2‐body physical interactions. These findings allowed the prediction of protein synthesis activity at various combinations of component concentrations from a small number of samples, the principle of which is applicable to analysis and optimization of other biological systems. Moreover, the average ratio of 2‐ to 1‐body terms was estimated to be as small as 0.1, implying high adaptability and evolvability of the protein translation system.

Y-ligation: An efficient method for ligating single-stranded DNAs and RNAs with T4 RNA ligase

Very efficient ligation ofoligodeoxyribonucleotides was attained through asimple molecular construct, which is composed of onestem and two branches (Y-shape), with use of T4 RNAligase. Single-stranded DNAs (naturally, RNAs also) ofmore than 100 nucleotides (even 800 nts) wereconsiderably ligated, approximately as theoreticallyexpected. Owing to the molecular construct adopted,such a tiny amount of ligation products could beamplified to a sufficient amount by PCR and thenrecovered as single-stranded DNAs. This advantage ofbeing amplifiable is shown to be useful for bothcombinatorial chemistry and evolutionary molecularengineering, which deal with a pool of diversity molecules.

Modified substrate specificity of pyrroloquinoline quinone glucose dehydrogenase by biased mutation assembling with optimized amino acid substitution

A biased mutation-assembling method—that is, a directed evolution strategy to facilitate an optimal accumulation of multiple mutations on the basis of additivity principles, was applied to the directed evolution of water-soluble PQQ glucose dehydrogenase (PQQGDH-B) to reduce its maltose oxidation activity, which can lead to errors in blood glucose determination. Mutations appropriate for the reduction without fatal deterioration of its glucose oxidation activity were developed by an error-prone PCR method coupled with a saturation mutagenesis method. Moreover, two types of incorporation frequency based on their contribution were assigned to the mutations: high (80%) and evens (50%), in constructing a multiple mutant library. The best mutant created showed a marked reduction in maltose oxidation activity, corresponding to 4% of that of the wild-type enzyme, with 35% retention of glucose oxidation activity. In addition, this mutant showed a reduction in galactose oxidation activity corresponding to 5% of that of the wild-type enzyme. In conclusion, we succeeded in developing the PQQGDH-B mutants with improved substrate specificity and validated our method coupled with optimized mutations and their contribution-based incorporation frequencies by applying it to the development.

Research article: Toward the fast blind docking of a peptide to a target protein by using a four-body statistical pseudo-potential

In vitro molecular evolution creates a lot of peptide aptamers that bind to each target protein. In many cases, their binding sites on a protein surface are not known. Then, predicting the binding sites through computation within a reasonable time is desirable. With this aim, we have developed a novel system of fast and robust blind docking of a peptide to a fixed protein structure at low computational costs. Our algorithm is based on the following scheme. Representing each of the amino acid residues by a single point corresponding to its side-chain center, the structure of a target protein and that of a ligand peptide are coarse-grained. The peptide, which is described as a flexible bead model, is movable along the grid-points which are set surrounding the protein. An arbitrary state of the protein-peptide complex is subjected to Delaunay tessellation. Then, the fitness of a peptide-coordination to the protein is measured by a four-body statistical pseudo-potential. Through 1000 trials of a simple hill-climbing optimization, the best 15 peptide-coordinations with the 1st-15th highest fitness values are selected as candidates for the putative coordination. Retrieving the available 28 protein-peptide complexes from the Protein Databank, we carried out the blind docking test for each system. The best 15 peptide-coordinations fell into several clusters by the cluster analysis based on their spatial distribution. We found that, in most cases, the largest cluster or second largest cluster correspond to nearly correct binding sites, and that the mean (+/- standard deviation) of GTGD over all the 28 cases is 4.8 A(+/-3.8 A), where GTGD represents the distance from the putative binding site to the correct binding site.

Periodic pattern of genetic and fitness diversity during evolution of an artificial cell-like system

Genetic and phenotypic diversity are the basis of evolution. Despite their importance, however, little is known about how they change over the course of evolution. In this study, we analyzed the dynamics of the adaptive evolution of a simple evolvable artificial cell-like system using single-molecule real-time sequencing technology that reads an entire single artificial genome. We found that the genomic RNA population increases in fitness intermittently, correlating with a periodic pattern of genetic and fitness diversity produced by repeated diversification and domination. In the diversification phase, a genomic RNA population spreads within a genetic space by accumulating mutations until mutants with higher fitness are generated, resulting in an increase in fitness diversity. In the domination phase, the mutants with higher fitness dominate, decreasing both the fitness and genetic diversity. This study reveals the dynamic nature of genetic and fitness diversity during adaptive evolution and demonstrates the utility of a simplified artificial cell-like system to study evolution at an unprecedented resolution.

Theoretical consideration of selective enrichment in in vitro selection: Optimal concentration of target molecules

We considered an in vitro selection system composed of a peptide-ligand library and a single target protein receptor, and examined effective strategies to realize maximum efficiency in selection. In the system, a ligand molecule with sequence s binds to a target receptor with probability of [R]/(K(ds)+[R]) (specific binding) or binds to non-target materials with probability of q (non-specific binding), where [R] and K(ds) represent the free target-receptor concentration at equilibrium and dissociation constant K(d) of the ligand sequence s with the receptor, respectively. Focusing on the fittest sequence with the highest affinity (represented by K(d1) ≡ min{K(ds)|s=1,2,…,M}) in the ligand library with a library size N and diversity M, we examined how the target concentration [R] should be set in each round to realize the maximum enrichment of the fittest sequence. In conclusion, when N >> M (that realizes a deterministic process), it is desirable to adopt [R]=K(d1), and when N=M (that realizes a stochastic process), [R]=[Formula in text] only in the first round (where * represents the population average) and [R]=K(d1) in the subsequent rounds. Based on this strategy, the mole fraction of the fittest increases by (2q)(-r) times after the rth round. With realistic parameters, we calculated several quantities such as the optimal [R] values and number of rounds needed. These values were quite reasonable and consistent with observations, suggesting the validity of our theory.

Biomolecular information gained through in vitro evolution

An in vitro evolution is a simplified Darwinian evolution in well-controlled surroundings. This evolution process can be modeled as a hill-climbing or adaptive walk on a fitness landscape in sequence space. The evolving molecular system gains at least two kinds of information originating from the converged sequences and the fitness increment of the evolving biopolymer as the adaptive walker. These two represent two aspects of the biomolecular information, its extent and its content, respectively. Here, we review studies related to formulation of the “content” and “extent” of biomolecular information. The two aspects are interconnected through physicochemical properties of the biopolymer, contrary to the case of conventional information, which seems to be independent of matter. The interconnection was analyzed based on the analogy between the evolution process and thermodynamics. The linear combination of the two by a temperature-like fluctuation factor resulted in a free-energy-like monotonically increasing function during the evolution process.

Correlated flexible molecular coding and molecular evolvability.

Evolvability of biopolymers is based on molecular coding. The molecular coding is represented by biopolymer function vs monomeric sequence relationship, that is, a proper fitness landscape on the sequence space. On the other hand, molecular coding is mostly realized by monomeric sequence vs biopolymer structure relationship. We suggest the evolution of evolvability based on flexible or multiplex coding originating from flexible or polymorphic conformation of evolving biopolymers. We report a finding supporting that the amino acid landscape of the standard genetic code for an amino acid property which is more important to the protein function gives higher value of an evolvability measure. We developed a promising molecular construct which realized genotype-phenotype linking in order to study the in vitroprotein evolution to clarify above mentioned protein evolvability.

Biomolecular Information Gained through In Vitro Evolution on a Fitness Landscape in Sequence Space

Biological evolution at the molecular level is conceptually regarded as the genetic information gaining process. Analyzing the in vitro evolution process, which is a simplified Darwinian evolution under a well-controlled environment, we can clarify the concept of the information gaining process. This evolution process can be modeled as a hill-climbing or adaptive walk on a fitness landscape in sequence space. Through the hill-climbing process, the evolving biopolymer (as the adaptive walker) stores the following two aspects of information: one stems from the sequences converged in sequence space and the other stems from the fitness increment on the fitness landscape. In Eigen’s words, the former and latter are described as the “extent” and “content” of biological information, respectively [25]. In our approach, these two aspects can be interpreted based on the analogy between evolutionary dynamics and thermodynamics. Several studies introduced the concept of “free fitness” (which is analogous to free energy) as the Lyapunov function for evolution: Free fitness ≡ Fitness + Temperature − like parameter ×Entropy. Furthermore, we focus on the novel quantity of Fitness divided by \(\mbox{\it Temperature-like para\-meter}\), and regard this quantity as the content of information, while we regard Entropy as the extent of information. The quantity of Free fitness divided by Temperature-like parameter is a Lyapunov function of the evolution process, and then it should be called “biomolecular information”, which includes both aspects of information.