Evolvability of random polypeptides through functional selection within a small library

A directed evolution with phage-displayed random polypeptides of about 140 amino acid residues was followed until the sixth generation under a selection based on affinity to a transition state analog for an esterase reaction. The experimental design deliberately limits the observation to only 10 clones per generation. The first generation consists of three soluble random polypeptides and seven arbitrarily chosen clones from a previously constructed library. The clone showing the highest affinity in a generation was selected and subjected to random mutagenesis to generate variants for the next generation. Even within only 10 arbitrarily chosen polypeptides in each of the generations, there are enough variants in accord to capacity of binding affinity. In addition, the binding capacity of the selected polypeptides showed a gradual continuous increase over the generation. Furthermore, the purified selected random polypeptides exhibited a gradual but significant increase in esterase activity. The ease of the functional development within a small sequence variety implies that enzyme evolution is prompted even within a small population of random polypeptides.     

Evolution of an Arbitrary Sequence in Solubility

We have investigated the evolvability of an insoluble random polypeptide, RP3-34, to a soluble form through iterative mutation and selection with the aid of the green fluorescent protein (GFP) folding reporter. To assess the solubility of the polypeptides in the selected clones of each generation, the polypeptide genes were detached from the GFP fusions and expressed with a His₆ tag. The solubility of the variant random polypeptides increased in each generation within the scope of the evolutionary process, and the polypeptides assumed a soluble form from the fourth generation. Analysis of the synonymous and nonsynonymous mutations found in the deduced amino acid sequence of the selected polypeptides revealed that selection had accelerated the evolutionary rate. The solubility and hydrophobicity of the polypeptides and the 25 arbitrarily chosen random polypeptides found in a previously prepared library were determined, analyzed, and interpreted from the landscape on the protein sequence space. This study showed the evolvability of an insoluble arbitrary sequence toward a soluble one, hence, it provides a new perspective on the field of artificial evolution.     

Molecular evolutionary clock and the neutral theory

Summary From the standpoint of the neutral theory of molecular evolution, it is expected that a universally valid and exact molecular evolutionary clock would exist if, for a given molecule, the mutation rate for neutral allelesper year were exactly equal among all organisms at all times. Any deviation from the equality of neutral mutation rate per year makes the molecular clock less exact. Such deviation may be due to two causes: one is the change of the mutation rate per year (such as due to change of generation span), and the other is the alteration of the selective constraint of each molecule (due to change of internal molecular environment). A statistical method was developed to investigate the equality of evolutionary rates among lineages. This was used to analyze protein data to demonstrate that these two causes are actually at work in molecular evolution. It was emphasized that departures from exact clockwise progression of molecular evolution by no means invalidates the neutral theory. It was pointed out that experimental studies should be done to settle the issue of whether the mutation rate for nucleotide change is more constant per year or per generation among organisms whose generation spans are very different.     

FOUNDER EFFECTS AND PEAK SHIFTS WITHOUT GENETIC DRIFT: ADAPTIVE PEAK SHIFTS OCCUR EASILY WHEN ENVIRONMENTS FLUCTUATE SLIGHTLY

Two similar evolutionary theories, the shifting balance theory and founder-flush models, invoke random genetic drift to allow evolution on complex adaptive landscapes. These models, in their usual incarnations, deal with fitness as a static entity, and the probability of transition from one form to another is predicted to be quite small by analysis of these models. Fitness itself can change, however, and the amount of change in the parameters of the fitness functions required to allow deterministic evolution to new adaptive peaks is very small. The probability of environmental changes sufficient to allow substantial morphological evolution or reproductive isolation is large relative to the probability that similar changes could occur by processes requiring genetic drift, even with very small population sizes. The rapid evolution or speciation following a population founding event is more closely linked with environmental changes than genetic drift.     

The interface of protein structure, protein biophysics, and molecular evolution

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.     

Extracting characteristic properties of fitness landscape from in vitro molecular evolution: a case study on infectivity of fd phage to E.coli

We have developed a methodology for extracting characteristic properties of a fitness landscape of interest by analyzing fitness data on an in vitro molecular evolution. The in vitro evolution is required to be conducted as the following "adaptive walk": a single parent sequence generates N mutant sequences as its offsprings, and the fittest individual among the N offsprings will become a new parent in the next generation. N is the library size of mutants to be screened in a single generation. Our theory of the adaptive walk on the "NK landscape" suggests the following: the adaptive walker starting from a random sequence climbs the landscape easily in an early stage, and then reaches a stationary phase in which the mutation-selection-random drift balance sets in. The stationary fitness value is nearly proportional to square root of ln N. Our analysis is performed from the following points: (1) stationary fitness values, (2) time series of fitness in the transitional state, (3) mutant's fitness distribution, and (4) the strength of selection pressure. Applying our methodology, we analyzed experimental data on the in vitro evolution of a random polypeptide (139 amino acids) toward acquiring infectivity (= ability to infect) of fd phage. As a result, we estimated that k is about 27 in this system, indicating that an arbitrary residue in a sequence is affected from other 23% residues. In this article, we demonstrated that the experimental data is consistent with our theoretical equations quantitatively, and that our methodology for extracting characteristic properties of a fitness landscape may be effective.     

Can an arbitrary sequence evolve towards acquiring a biological function?

Abstract To explore the possibility that an arbitrary sequence can evolve towards acquiring functional role when fused with other pre-existing protein modules, we replaced the D2 domain of the fd-tet phage genome with the soluble random polypeptide RP3-42. The replacement yielded an fd-RP defective phage that is six-order magnitude lower infectivity than the wild-type fd-tet phage. The evolvability of RP3-42 was investigated through iterative mutation and selection. Each generation consists of a maximum of ten arbitrarily chosen clones, whereby the clone with highest infectivity was selected to be the parent clone of the generation that followed. The experimental evolution attested that, from an initial single random sequence, there will be selectable variation in a property of interest and that the property in question was able to improve over several generations. fd-7, the clone with highest infectivity at the end of the experimental evolution, showed a 240-fold increase in infectivity as compared to its origin, fd-RP. Analysis by phage ELISA using anti-M13 antibody and anti-T7 antibody revealed that about 37-fold increase in the infectivity of fd-7 was attributed to the changes in the molecular property of the single polypeptide that replaced the D2 domain of the g3p protein. This study therefore exemplifies the process of a random polypeptide generating a functional role in rejuvenating the infectivity of a defective bacteriophage when fused to some preexisting protein modules, indicating that an arbitrary sequence can evolve toward acquiring a functional role. Overall, this study could herald the conception of new perspective regarding primordial polypeptides in the field of molecular evolution.     

Emergence of polyproline II-like structure at early stages of experimental evolution from random polypeptides

To examine whether a primordial functional protein at the early stages of evolution has structural features, we carried out experimental evolution consisting of 25 cycles (generations) of mutation and selection toward DNA-binding function using a random-sequence polypeptide of 139 amino acid residues with no secondary structure as the initial sequence. In each generation, 16 clones were sampled arbitrarily for sequence analysis, and a phylogenetic tree was constructed. Polypeptide evolution proceeded from the initial point on branch I in 2 main directions of branches II and III. The initial and 2 evolved polypeptides (one at the 24th generation on branch III and the other at the 25th generation on branch II) were purified to examine their functional and structural properties. Although binding of the initial polypeptide to the target DNA was not detected by surface plasmon resonance measurements, the 2 evolved polypeptides bound to the DNA with dissociation constants of 1.6 and 1.0 microM, respectively, indicating an increase in affinity during the experimental evolution. Circular dichroism spectra of the evolved polypeptides, but not of the initial polypeptide, showed features characteristic of the polyproline II (PPII)-like structure, a left-handed helical structure commonly found in natural proteins, suggesting that the structure emerged through the experimental evolution. The same structural feature was found in another experimental evolution toward catalytic activity. These results demonstrate that the PPII-like structure is one of the common features that could have appeared in the early evolutionary stages of primordial functional protein.     

Intraindividual variability in behavior shapes fitness landscapes

Although intraindividual variability (IIV) in behavior is fundamental to ecological dynamics, the factors that contribute to the expression of IIV are poorly understood. Using an individual‐based model, this study examined the effects of stochasticity on the evolution of IIV represented by the residual variability of behavior. The model describes a population of prey with nonoverlapping generations, in which prey take refuge upon encountering a predator. The strategy of a prey is characterized by the mean and IIV (i.e., standard deviation) of hiding duration. Prey with no IIV will spend the same duration hiding in a refuge at each predator encounter, while prey with IIV will have variable hiding durations among encounters. For the sources of stochasticity, within‐generation stochasticity (represented by random predator encounters) and between‐generation stochasticity (represented by random resource availability) were considered. Analysis of the model indicates that individuals with high levels of IIV are maintained in a population in the presence of between‐generation stochasticity even though the optimal strategy in each generation is a strategy with no IIV, regardless of the presence or absence of within‐generation stochasticity. This contradictory pattern emerges because the mean behavioral trait and IIV do not independently influence fitness (e.g., the sign of the selection gradient with respect to IIV depends on the mean trait). Consequently, even when evolution eventually leads toward a strategy with no IIV (i.e., the optimal strategy), greater IIV may be transiently selected. Between‐generation stochasticity consistently imposes such transient selection and maintain high levels of IIV in a population.     

Directed molecular evolution by machine learning and the influence of nonlinear interactions

Alternative search strategies for the directed evolution of proteins are presented and compared with each other. In particular, two different machine learning strategies based on partial least-squares regression are developed: the first contains only linear terms that represent a given residue's independent contribution to fitness, the second contains additional nonlinear terms to account for potential epistatic coupling between residues. The nonlinear modeling strategy is further divided into two types, one that contains all possible nonlinear terms and another that makes use of a genetic algorithm to select a subset of important interaction terms. The performance of each modeling type as a function of training set size is analysed. Simulated molecular evolution on a synthetic protein landscape shows the use of machine learning techniques to guide library design can be a powerful addition to library generation methods such as DNA shuffling.     

A systematic study of the vibrational free energies of polypeptides in folded and random states

Molecular vibrations, especially low frequency motions, may be used as an indication of the rigidity or the flatness of the protein folding energy landscape. We have studied the vibrational properties of native folded as well as random coil structures of more than 60 polypeptides. The picture we obtain allows us to perceive how and why the energy landscape progressively rigidifies while still allowing potential flexibility. Compared with random coil structures, both alpha-helices and beta-hairpins are vibrationally more flexible. The vibrational properties of loop structures are similar to those of the corresponding random coil structures. Inclusion of an alpha-helix tends to rigidify peptides and so-called building blocks of the structure, whereas the addition of a beta-structure has less effect. When small building blocks coalesce to form larger domains, the protein rigidifies. However, some folded native conformations are still found to be vibrationally more flexible than random coil structures, for example, beta(2)-microglobulin and the SH3 domain. Vibrational free energy contributes significantly to the thermodynamics of protein folding and affects the distribution of the conformational substates. We found a weak correlation between the vibrational folding energy and the protein size, consistent with both previous experimental estimates and theoretical partition of the heat capacity change in protein folding.     

Molecular evolutionary analysis of the psbP gene family of the photosystem II oxygen-evolving complex in Nicotiana.

Photosystem II psbP protein of the oxygen-evolving complex is involved in the photosynthetic oxygen evolution in plants. Four psbP polypeptides were detected in Nicotiana tabacum on a two-dimensional gel by immunostaining the proteins with antiserum against the pea psbP Comparison of the protein patterns of psbP from N. tabacum and its ancestral parents, N. sylvestris and N. tomentosiformis, indicated that each of the ancestral parents has contributed a pair of psbP proteins. This was supported by Southern hybridization results, which suggested that psbP in Nicotiana is encoded by a gene family consisting of four members in N. tabacum and two members each in N. glauca, N. langsdorffii, N. sylvestris, and N. tomentosiformis. A scheme of molecular evolution of the psbP genes in Nicotiana is also proposed.     

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.     

Plasticity of Fitness and Diversification Process During an Experimental Molecular Evolution

A simplified experimental evolution encompassing the essence of natural one was designed in an attempt to understand the involved mechanism. In our system, molecular evolution was observed through three serial cycles of consecutive random mutagenesis of the glutamine synthetase gene and chemostat culture of the transformed Escherichia coli cells containing the mutated genes. Selection pressure was imposed solely on the glutamine synthetase gene when varieties of mutant genes compete in an unstructured environment of the chemostat. The molecular phylogeny and population dynamics were deduced from the nucleotide sequences of the genes isolated from each of the chemostat runs. An initial mutant population in each cycle, comprised of diversified closely-related genes, ended up with several varieties of mutants in a state of coexistence. Competition between two mutant genes in the final population of the first cycle ascertained that the observed coexisting state is not an incidental event and that cellular interaction via environmental nutrients is a possible mechanism of coexistence. In addition, the mutant gene once extinct in the previous passage was found to have the capacity to reinvade and constitute the gene pool of the later cycle of molecular evolution. These results, including the kinetic characteristics of the purified wild-type and mutant glutamine synthetases in the phylogenetic tree, revealed that the enzyme activity had diverged, rather than optimized, to a fittest value during the course of evolution. Here, we proposed that the plasticity of gene fitness in consequence of cellular interaction via the environment is an essential mechanism governing molecular evolution. Received: 29 August 2000 / Accepted: 25 January 2001     

Simulated evolution and artificial selection

A highly simplified evolving system was investigated by computer simulation. The genetic complement of each simulated organism in the population was represented by a single chromosome that consisted of a string of symbols. Individual fitness was measured as the number of symbols that corresponded to a specified rule. Reproduction was simulated with a non-breeding algorithm and two variants of a breeding algorithm, and was subject to random point mutations. In each generation, selection was effected by replacing the less fit members of the population with offspring of the more fit. The size of the population and the fraction replaced, though under experimental control, were constant for each simulation run. It was found that even such a simplified system is able to mimic a variety of properties observed in natural systems. In addition, the effect of the simulation parameters on the course of fitness increase provides a basis for using a genetic algorithm as an optimization technique.     

Investigation of de novo totally random biosequences, Part II: On the folding frequency in a totally random library of de novo proteins obtained by phage display

We present an investigation on theoretically possible protein structures which have not been selected by evolution and are, therefore, not present on our Earth ('Never Born Proteins' (NBP)). In particular, we attempt to assess whether and to what extent such polypeptides might be folded, thus acquiring a globular protein status. A library (ca. 10(9) clones) of totally random polypeptides, with a length of 50 amino acids, has been produced by phage display. The only structural bias in these sequences is a tripeptide substrate for thrombin: PRG, chosen according to the criteria described in the preceding Part I of this series. The presence of this substrate in an otherwise totally random sequence forms the basis for a qualitative experimental criterion which distinguishes unfolded from folded proteins, as folded proteins are more protected from protease digestion than unfolded ones. The investigation of 79 sequences, randomly selected from the initially large library, shows that over 20% of this population is thrombin-resistant, likely due to folding. Analysis of the amino acid sequences of these clones shows no significant homology to extant proteins, which indicates that they are indeed totally de novo. A few of these sequences have been expressed, and here we describe the structural properties of two thrombin-resistant randomly selected ones. These two de novo proteins have been characterized by spectroscopic methods and, in particular, by circular dichroism. The data show a stable three-dimensional folding, which is temperature-resistant and can be reversibly denatured by urea. The consequences of this finding within a library of 'Never Born Proteins' are discussed in terms of molecular evolution.     

The mode of evolution of molecular markers in populations of house mice under artificial selection for locomotor behavior

A complete understanding of the mode of evolution of molecular markers is important for making inferences about different population genetic parameters, especially because a number of studies have reported patterns of allelic variation at molecular markers that are not in agreement with neutral evolutionary expectations. In the present study, house mice (Mus domesticus) from the fourteenth generation of a selection experiment for increased voluntary wheel-running activity were used to test how selection on a complex behavior affects the distribution of allelic variation by examining patterns of variation at six microsatellite and four allozyme loci. This population had a hierarchical structure that allowed for simultaneous testing of the effects of selection and genetic drift on the distribution of allelic variation by comparing observed patterns of allele frequencies and estimates of genetic divergence at multiple hierarchical levels to expectations under models of neutral evolution. The levels of genetic divergence among replicate lines and between selection groups, estimated from microsatellite data or pooled microsatellite and allozyme data, were not significantly different from expectations under neutral evolution. Furthermore, the pattern of change of allele frequencies between the base population and generation 14 was largely in agreement with expectations under neutral evolution (although the PGM locus exhibited a pattern of change within populations that was difficult to explain under neutral evolution). Overall the results generally provide support for the neutral evolution of molecular markers.     

Similarity selection and the evolution of sex: revisiting the red queen

For over 25 years, many evolutionary ecologists have believed that sexual reproduction occurs because it allows hosts to change genotypes each generation and thereby evade their coevolving parasites. However, recent influential theoretical analyses suggest that, though parasites can select for sex under some conditions, they often select against it. These models assume that encounters between hosts and parasites are completely random. Because of this assumption, the fitness of a host depends only on its own genotype (“genotypic selection”). If a host is even slightly more likely to encounter a parasite transmitted by its mother than expected by random chance, then the fitness of a host also depends on its genetic similarity to its mother (“similarity selection”). A population genetic model is presented here that includes both genotypic and similarity selection, allowing them to be directly compared in the same framework. It is shown that similarity selection is a much more potent force with respect to the evolution of sex than is genotypic selection. Consequently, similarity selection can drive the evolution of sex even if it is much weaker than genotypic selection with respect to fitness. Examination of explicit coevolutionary models reveals that even a small degree of mother–offspring parasite transmission can cause parasites to favor sex rather than oppose it. In contrast to previous predictions, the model shows that weakly virulent parasites are more likely to favor sex than are highly virulent ones. Parasites have figured prominently in discussions of the evolution of sex, but recent models suggest that parasites often select against sex rather than for it. With the inclusion of small and realistic exposure biases, parasites are much more likely to favor sex. Though parasites alone may not provide a complete explanation for sex, the results presented here expand the potential for parasites to contribute to the maintenance of sex rather than act against it.