Simple evolutionary pathways to complex proteins

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence-function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ∼400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

Specialization restricts the evolutionary paths available to yeast sugar transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence-function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning approximately 400 million years of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

Genomic Evolution and Recombination Dynamics of Human Adenovirus D Species: Insights from Comprehensive Bioinformatic Analysis

Human adenoviruses (HAdVs) can infect various epithelial mucosal cells, ultimately causing different symptoms in infected organ systems. With more than 110 types classified into seven species (A-G), HAdV-D species possess the highest number of viruses and are the fastest proliferating. The emergence of new adenovirus types and increased diversity are driven by homologous recombination (HR) between viral genes, primarily in structural elements such as the penton base, hexon and fiber proteins, and the E1 and E3 regions. A comprehensive analysis of the HAdV genome provides valuable insights into the evolution of human adenoviruses and identifies genes that display high variation across the entire genome to determine recombination patterns. Hypervariable regions within genetic sequences correlate with functional characteristics, thus allowing for adaptation to new environments and hosts. Proteotyping of newly emerging and already established adenoviruses allows for prediction of the characteristics of novel viruses. HAdV-D species evolved in a direction that increased diversity through gene recombination. Bioinformatics analysis across the genome, particularly in highly variable regions, allows for the verification or re-evaluation of recombination patterns in both newly introduced and pre-existing viruses, ultimately aiding in tracing various biological traits such as virus tropism and pathogenesis. Our research does not only assist in predicting the emergence of new adenoviruses but also offers critical guidance in regard to identifying potential regulatory factors of homologous recombination hotspots.

The waiting time problem in a model hominin population

Background

Functional information is normally communicated using specific, context-dependent strings of symbolic characters. This is true within the human realm (texts and computer programs), and also within the biological realm (nucleic acids and proteins). In biology, strings of nucleotides encode much of the information within living cells. How do such information-bearing nucleotide strings arise and become established?

Methods

This paper uses comprehensive numerical simulation to understand what types of nucleotide strings can realistically be established via the mutation/selection process, given a reasonable timeframe. The program Mendel’s Accountant realistically simulates the mutation/selection process, and was modified so that a starting string of nucleotides could be specified, and a corresponding target string of nucleotides could be specified. We simulated a classic pre-human hominin population of at least 10,000 individuals, with a generation time of 20 years, and with very strong selection (50 % selective elimination). Random point mutations were generated within the starting string. Whenever an instance of the target string arose, all individuals carrying the target string were assigned a specified reproductive advantage. When natural selection had successfully amplified an instance of the target string to the point of fixation, the experiment was halted, and the waiting time statistics were tabulated. Using this methodology we tested the effect of mutation rate, string length, fitness benefit, and population size on waiting time to fixation.

Results

Biologically realistic numerical simulations revealed that a population of this type required inordinately long waiting times to establish even the shortest nucleotide strings. To establish a string of two nucleotides required on average 84 million years. To establish a string of five nucleotides required on average 2 billion years. We found that waiting times were reduced by higher mutation rates, stronger fitness benefits, and larger population sizes. However, even using the most generous feasible parameters settings, the waiting time required to establish any specific nucleotide string within this type of population was consistently prohibitive.

Conclusion

We show that the waiting time problem is a significant constraint on the macroevolution of the classic hominin population. Routine establishment of specific beneficial strings of two or more nucleotides becomes very problematic.

The Jackprot Simulation Couples Mutation Rate with Natural Selection to Illustrate How Protein Evolution Is Not Random

Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke "design creationism" to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane's hydrophobic/philic nature; a selective "pore" for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the "jackprot," which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the "jackprot," or highest-fitness complete-peptide sequence, required cumulative smaller "wins" (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons ("jackdons" that led to "jackacids" that led to the "jackprot"). The "jackprot" is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide "edition" and gene duplications to generate the 6TMs. Ion channels are essential to the physiology of neurons, ganglia, and brains, and were crucial to the evolutionary advent of consciousness. The Jackprot Simulation illustrates in a computer model that evolution is not and cannot be a random process as conceived by design creationists.

Selective loss of cysteine residues and disulphide bonds in a potato proteinase inhibitor II family

Disulphide bonds between cysteine residues in proteins play a key role in protein folding, stability, and function. Loss of a disulphide bond is often associated with functional differentiation of the protein. The evolution of disulphide bonds is still actively debated; analysis of naturally occurring variants can promote understanding of the protein evolutionary process. One of the disulphide bond-containing protein families is the potato proteinase inhibitor II (PI-II, or Pin2, for short) superfamily, which is found in most solanaceous plants and participates in plant development, stress response, and defence. Each PI-II domain contains eight cysteine residues (8C), and two similar PI-II domains form a functional protein that has eight disulphide bonds and two non-identical reaction centres. It is still unclear which patterns and processes affect cysteine residue loss in PI-II. Through cDNA sequencing and data mining, we found six natural variants missing cysteine residues involved in one or two disulphide bonds at the first reaction centre. We named these variants Pi7C and Pi6C for the proteins missing one or two pairs of cysteine residues, respectively. This PI-II-7C/6C family was found exclusively in potato. The missing cysteine residues were in bonding pairs but distant from one another at the nucleotide/protein sequence level. The non-synonymous/synonymous substitution (Ka/Ks) ratio analysis suggested a positive evolutionary gene selection for Pi6C and various Pi7C. The selective deletion of the first reaction centre cysteine residues that are structure-level-paired but sequence-level-distant in PI-II illustrates the flexibility of PI-II domains and suggests the functionality of their transient gene versions during evolution.

The rate of establishment of complex adaptations

A central problem in evolutionary theory concerns the mechanisms by which adaptations requiring multiple mutations emerge in natural populations. We develop a series of expressions that clarify the scaling of the time to establishment of complex adaptations with population size, mutation rate, magnitude of the selective disadvantage of intermediate-state alleles, and the complexity of the adaptation. In general, even in the face of deleterious intermediate steps, the time to establishment is minimized in populations with very large size. Under a broad range of conditions, the time to establishment also scales by no more than the square of the mutation rate, regardless of the number of sites contributing to the adaptive change, demonstrating that the emergence of complex adaptations is only weakly constrained by the independent acquisition of mutations at the underlying sites. Mutator alleles with deleterious side effects have only moderate effects on the rate of adaptation in large populations but can cause a quantum decrease in the time to establishment of some adaptive alleles in small populations, although probably not at a high enough rate to offset the increased deleterious mutation load. Transient hypermutability, whereby a subset of gamete-producing cells mutate at an elevated rate in a nonheritable manner, may also elevate the rate of adaptation, although the effect is modest and appears to result from a simple increase in the rate of transitions between intermediate states rather than from the saltational production of doublet mutations. Taken together, these results illustrate the plausibility of the relatively rapid emergence of specific complex adaptations by conventional population genetic mechanisms and provide insight into the relative incidences of various paths of allelic adaptation in organisms with different population genetic features.

Integrating horizontal gene transfer and common descent to depict evolution and contrast it with "common design"

Horizontal gene transfer (HGT) and common descent interact in space and time. Because events of HGT co-occur with phylogenetic evolution, it is difficult to depict evolutionary patterns graphically. Tree-like representations of life's diversification are useful, but they ignore the significance of HGT in evolutionary history, particularly of unicellular organisms, ancestors of multicellular life. Here we integrate the reticulated-tree model, ring of life, symbiogenesis whole-organism model, and eliminative pattern pluralism to represent evolution. Using Entamoeba histolytica alcohol dehydrogenase 2 (EhADH2), a bifunctional enzyme in the glycolytic pathway of amoeba, we illustrate how EhADH2 could be the product of both horizontally acquired features from ancestral prokaryotes (i.e. aldehyde dehydrogenase [ALDH] and alcohol dehydrogenase [ADH]), and subsequent functional integration of these enzymes into EhADH2, which is now inherited by amoeba via common descent. Natural selection has driven the evolution of EhADH2 active sites, which require specific amino acids (cysteine 252 in the ALDH domain; histidine 754 in the ADH domain), iron- and NAD(+) as cofactors, and the substrates acetyl-CoA for ALDH and acetaldehyde for ADH. Alternative views invoking "common design" (i.e. the non-naturalistic emergence of major taxa independent from ancestry) to explain the interaction between horizontal and vertical evolution are unfounded.

Revealing evolutionary pathways by fitness landscape reconstruction

The concept of epistasis has since long been used to denote non-additive fitness effects of genetic changes and has played a central role in understanding the evolution of biological systems. Owing to an array of novel experimental methodologies, it has become possible to experimentally determine epistatic interactions as well as more elaborate genotype-fitness maps. These data have opened up the investigation of a host of long-standing questions in evolutionary biology, such as the ruggedness of fitness landscapes and the accessibility of mutational trajectories, the evolution of sex, and the origin of robustness and modularity. Here we review this recent and timely marriage between systems biology and evolutionary biology, which holds the promise to understand evolutionary dynamics in a more mechanistic and predictive manner.

Waiting for two mutations: with applications to regulatory sequence evolution and the limits of Darwinian evolution

Results of Nowak and collaborators concerning the onset of cancer due to the inactivation of tumor suppressor genes give the distribution of the time until some individual in a population has experienced two prespecified mutations and the time until this mutant phenotype becomes fixed in the population. In this article we apply these results to obtain insights into regulatory sequence evolution in Drosophila and humans. In particular, we examine the waiting time for a pair of mutations, the first of which inactivates an existing transcription factor binding site and the second of which creates a new one. Consistent with recent experimental observations for Drosophila, we find that a few million years is sufficient, but for humans with a much smaller effective population size, this type of change would take > 100 million years. In addition, we use these results to expose flaws in some of Michael Behe's arguments concerning mathematical limits to Darwinian evolution.

The look-ahead effect of phenotypic mutations

BACKGROUND

The evolution of complex molecular traits such as disulphide bridges often requires multiple mutations. The intermediate steps in such evolutionary trajectories are likely to be selectively neutral or deleterious. Therefore, large populations and long times may be required to evolve such traits.

RESULTS

We propose that errors in transcription and translation may allow selection for the intermediate mutations, if the final trait provides a large enough selective advantage. We test this hypothesis using a population based model of protein evolution.

CONCLUSION

If an individual acquires one of two mutations needed for a novel trait, the second mutation can be introduced into the phenotype due to transcription and translation errors. If the novel trait is advantageous enough, the allele with only one mutation will spread through the population, even though the gene sequence does not yet code for the complettrait. Thus, errors allow protein sequences to "look-ahead" for a more direct path to a complex trait.

Post-duplication charge evolution of phosphoglucose isomerases in teleost fishes through weak selection on many amino acid sites

Background

The partitioning of ancestral functions among duplicated genes by neutral evolution, or subfunctionalization, has been considered the primary process for the evolution of novel proteins (neofunctionalization). Nonetheless, how a subfunctionalized protein can evolve into a more adaptive protein is poorly understood, mainly due to the limitations of current analytical methods, which can detect only strong selection for amino acid substitutions involved in adaptive molecular evolution. In this study, we employed a comparative evolutionary approach to this question, focusing on differences in the structural properties of a protein, specifically the electric charge, encoded by fish-specific duplicated phosphoglucose isomerase (Pgi) genes.

Results

Full-length cDNA cloning, RT-PCR based gene expression analyses, and comparative sequence analyses showed that after subfunctionalization with respect to the expression organ of duplicate Pgi genes, the net electric charge of the PGI-1 protein expressed mainly in internal tissues became more negative, and that of PGI-2 expressed mainly in muscular tissues became more positive. The difference in net protein charge was attributable not to specific amino acid sites but to the sum of various amino acid sites located on the surface of the PGI molecule.

Conclusion

This finding suggests that the surface charge evolution of PGI proteins was not driven by strong selection on individual amino acid sites leading to permanent fixation of a particular residue, but rather was driven by weak selection on a large number of amino acid sites and consequently by steady directional and/or purifying selection on the overall structural properties of the protein, which is derived from many modifiable sites. The mode of molecular evolution presented here may be relevant to various cases of adaptive modification in proteins, such as hydrophobic properties, molecular size, and electric charge.

Biochemistry by design

Creationists are attempting to use biochemistry to win acceptance for their doctrine in the public mind and especially in state-funded schools. Biochemist Michael Behe is a major figure in this effort. His contention that certain cellular structures and biochemical processes - bacterial flagella, the blood-clotting cascade and the vertebrate immune system - cannot be the products of evolution has generated vigorous opposition from fellow scientists, many of whom have refuted Behe's claims. Yet, despite these refutations and a decisive defeat in a US federal court case, Behe and his associates at the Discovery Institute continue to cultivate American supporters. They are also stepping up their efforts abroad and, worryingly, have achieved some success. Should biochemists (and other scientists) be concerned? We think they should be.

Latent evolutionary potentials under the neutral mutational drift of an enzyme

Biological systems exhibit mutational robustness, or neutrality, whereby the impact of mutations is minimized. Does neutrality hamper their ability to adapt in the face of changing environments? We monitored changes in genotype and phenotype that occur within a neutral mutational network of an enzyme, experimentally and computationally (see accompanying article). Using the enzyme PON1 as a model, we performed random mutagenesis and purifying selection to purge deleterious mutations. We characterized approximately 300 variants that are apparently neutral, or close to neutral, with respect to PON1's levels of expression and native lactonase activity. Their activities with promiscuous substrates and ligands indicated significant changes in adaptive potentials. Almost half of the variants exhibited changes in promiscuous activities, specificities, or inhibition, and several of these were found to be one or two mutations, closer to potentially new phenotypes: aryl esterase, thiolactonase, phosphotriesterase, or drug resistance. This empirical measure of phenotypic changes under neutrality supports the notion that sequence changes that are neutral, i.e., non-adaptive, in a current context can facilitate adaptation under changing circumstances, by both expanding the activity range of existing enzymes and thus providing an immediate advantage, and by reducing the number of mutations required for divergence of new functions.

Characterization of compensated mutations in terms of structural and physico-chemical properties

The study of the evolution of compensatory mechanisms among amino acids is paramount to our understanding of intramolecular epistatic interactions. It has been addressed from different points of view, for example much effort has been devoted to establish the number of compensatory mutations required per deleterious mutation. However, we still do not know how the nature of the compensated mutation determines the existence of compensatory mutations. Within this context, recent studies have produced several instances of an interesting phenomenon: human disease-associated residues may sometimes appear as wild-type residues in non-human proteins. This can be explained in terms of compensatory mutations, present in the non-human protein, which would neutralize the damage caused by the disease-associated residue. Therefore, comparison between these compensated mutations and non-compensated pathological mutations provides a simple approach to understand how the nature of the compensated deleterious mutation determines the existence of compensatory mutations. To address this issue, we have obtained a large set of compensated mutations and characterised them with a series of different properties. When comparing the resulting distributions with those from pathological mutations we find that in general compensated mutations are milder than pathological mutations. More precisely, we find that the probability that a compensatory mutation will evolve is directly related (i) to the location in the protein structure and (ii) to changes in physico-chemical properties (e.g. amino acid volume or hydrophobicity) of the compensated mutation.

Evaluation of models for the evolution of protein sequences and functions under structural constraint

In the field of evolutionary structural genomics, methods are needed to evaluate why genomes evolved to contain the fold distributions that are observed. In order to study the effects of population dynamics in the evolved genomes we need fast and accurate evolutionary models which can analyze the effects of selection, drift and fixation of a protein sequence in a population that are grounded by physical parameters governing the folding and binding properties of the sequence. In this study, various knowledge-based, force field, and statistical methods for protein folding have been evaluated with four different folds: SH2 domains, SH3 domains, Globin-like, and Flavodoxin-like, to evaluate the speed and accuracy of the energy functions. Similarly, knowledge-based and force field methods have been used to predict ligand binding specificity in SH2 domain. To demonstrate the applicability of these methods, the dynamics of evolution of new binding capabilities by an SH2 domain is demonstrated.

Evolutionary potential of a duplicated repressor-operator pair: simulating pathways using mutation data

Ample evidence has accumulated for the evolutionary importance of duplication events. However, little is known about the ensuing step-by-step divergence process and the selective conditions that allow it to progress. Here we present a computational study on the divergence of two repressors after duplication. A central feature of our approach is that intermediate phenotypes can be quantified through the use of in vivo measured repression strengths of Escherichia coli lac mutants. Evolutionary pathways are constructed by multiple rounds of single base pair substitutions and selection for tight and independent binding. Our analysis indicates that when a duplicated repressor co-diverges together with its binding site, the fitness landscape allows funneling to a new regulatory interaction with early increases in fitness. We find that neutral mutations do not play an essential role, which is important for substantial divergence probabilities. By varying the selective pressure we can pinpoint the necessary ingredients for the observed divergence. Our findings underscore the importance of coevolutionary mechanisms in regulatory networks, and should be relevant for the evolution of protein-DNA as well as protein-protein interactions.

The evolution of a new trait critically depends on the existence of a path of viable intermediates. Generally speaking, fitness decreasing steps in this path hamper evolution, whereas fitness increasing steps accelerate it. Unfortunately, intermediates are hard to catch in action since they occur only transiently, which is why they have largely been neglected in evolutionary studies.

The novelty of this study is that intermediate phenotypes can be predicted using published measurements of Escherichia coli mutants. Using this approach, the evolution of a small genetic network is simulated by computer. Following the duplication of one of its components, a new protein-DNA interaction develops via the accumulation of point mutations and selection. The resulting paths reveal a high potential to obtain a new regulatory interaction, in which neutral drift plays an almost negligible role. This study provides a mechanistic rationale for why such rapid divergence can occur and under which minimal selective conditions. In addition it yields a quantitative prediction for the minimum number of essential mutations.

On the evolution of the standard amino-acid alphabet

Although one standard amino-acid 'alphabet' is used by most organisms on Earth, the evolutionary cause(s) and significance of this alphabet remain elusive. Fresh insights into the origin of the alphabet are now emerging from disciplines as diverse as astrobiology, biochemical engineering and bioinformatics.

Cryptic genetic variation is enriched for potential adaptations

Cryptic genetic variation accumulates under weakened selection and has been proposed as a source of evolutionary innovations. Weakened selection may, however, also lead to the accumulation of strongly deleterious or lethal alleles, swamping the effect of any potentially adaptive alleles when they are revealed. Here I model variation that is partially shielded from selection, assuming that unconditionally deleterious variation is more strongly deleterious than variation that is potentially adaptive in a future environment. I find that cryptic genetic variation can be substantially enriched for potential adaptations under a broad range of realistic parameter values, including those applicable to alternative splices and readthrough products generated by the yeast prion [PSI+]. This enrichment is dramatically stronger when multiple simultaneous changes are required to generate a potentially adaptive phenotype. Cryptic genetic variation is likely to be an effective source of useful adaptations at a time of environmental change, relative to an equivalent source of variation that has not spent time in a hidden state.