Ancestral lysozymes reconstructed, neutrality tested, and thermostability linked to hydrocarbon packing

Quantifying higher-order epistasis: beware the chimera

Epistasis, or interactions in which alleles at one locus modify the fitness effects of alleles at other loci, plays a fundamental role in genetics, protein evolution, and many other areas of biology. Epistasis is typically quantified by computing the deviation from the expected fitness under an additive or multiplicative model using one of several formulae. However, these formulae are not all equivalent. Importantly, one widely used formula - which we call the chimeric formula - measures deviations from a multiplicative fitness model on an additive scale, thus mixing two measurement scales. We show that for pairwise interactions, the chimeric formula yields a different magnitude, but the same sign (synergistic vs. antagonistic) of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitude and sign compared to the multiplicative formula - thus confusing negative epistatic interactions with positive interactions, and vice versa. We resolve these inconsistencies by deriving fundamental connections between the different epistasis formulae and the parameters of the multivariate Bernoulli distribution . Our results demonstrate that the additive and multiplicative epistasis formulae are more mathematically sound than the chimeric formula. Moreover, we demonstrate that the mathematical issues with the chimeric epistasis formula lead to markedly different biological interpretations of real data. Analyzing multi-gene knockout data in yeast, multi-way drug interactions in E. coli , and deep mutational scanning (DMS) of several proteins, we find that 10 - 60% of higher-order interactions have a change in sign with the multiplicative or additive epistasis formula. These sign changes result in qualitatively different findings on functional divergence in the yeast genome, synergistic vs. antagonistic drug interactions, and and epistasis between protein mutations. In particular, in the yeast data, the more appropriate multiplicative formula identifies nearly 500 additional negative three-way interactions, thus extending the trigenic interaction network by 25%.

Sampling Strategies for Experimentally Mapping Molecular Fitness Landscapes Using High-Throughput Methods

Empirical studies of genotype-phenotype-fitness maps of proteins are fundamental to understanding the evolutionary process, in elucidating the space of possible genotypes accessible through mutations in a landscape of phenotypes and fitness effects. Yet, comprehensively mapping molecular fitness landscapes remains challenging since all possible combinations of amino acid substitutions for even a few protein sites are encoded by an enormous genotype space. High-throughput mapping of genotype space can be achieved using large-scale screening experiments known as multiplexed assays of variant effect (MAVEs). However, to accommodate such multi-mutational studies, the size of MAVEs has grown to the point where a priori determination of sampling requirements is needed. To address this problem, we propose calculations and simulation methods to approximate minimum sampling requirements for multi-mutational MAVEs, which we combine with a new library construction protocol to experimentally validate our approximation approaches. Analysis of our simulated data reveals how sampling trajectories differ between simulations of nucleotide versus amino acid variants and among mutagenesis schemes. For this, we show quantitatively that marginal gains in sampling efficiency demand increasingly greater sampling effort when sampling for nucleotide sequences over their encoded amino acid equivalents. We present a new library construction protocol that efficiently maximizes sequence variation, and demonstrate using ultradeep sequencing that the library encodes virtually all possible combinations of mutations within the experimental design. Insights learned from our analyses together with the methodological advances reported herein are immediately applicable toward pooled experimental screens of arbitrary design, enabling further assay upscaling and expanded testing of genotype space.

Epistasis facilitates functional evolution in an ancient transcription factor

A protein's genetic architecture - the set of causal rules by which its sequence produces its functions - also determines its possible evolutionary trajectories. Prior research has proposed that the genetic architecture of proteins is very complex, with pervasive epistatic interactions that constrain evolution and make function difficult to predict from sequence. Most of this work has analyzed only the direct paths between two proteins of interest - excluding the vast majority of possible genotypes and evolutionary trajectories - and has considered only a single protein function, leaving unaddressed the genetic architecture of functional specificity and its impact on the evolution of new functions. Here, we develop a new method based on ordinal logistic regression to directly characterize the global genetic determinants of multiple protein functions from 20-state combinatorial deep mutational scanning (DMS) experiments. We use it to dissect the genetic architecture and evolution of a transcription factor's specificity for DNA, using data from a combinatorial DMS of an ancient steroid hormone receptor's capacity to activate transcription from two biologically relevant DNA elements. We show that the genetic architecture of DNA recognition consists of a dense set of main and pairwise effects that involve virtually every possible amino acid state in the protein-DNA interface, but higher-order epistasis plays only a tiny role. Pairwise interactions enlarge the set of functional sequences and are the primary determinants of specificity for different DNA elements. They also massively expand the number of opportunities for single-residue mutations to switch specificity from one DNA target to another. By bringing variants with different functions close together in sequence space, pairwise epistasis therefore facilitates rather than constrains the evolution of new functions.

Synonymous and Nonsynonymous Substitutions in Dictyostelium discoideum Ammonium Transporter amtA Are Necessary for Functional Complementation in Saccharomyces cerevisiae

Ammonium transporters are present in all three domains of life. They have undergone extensive horizontal gene transfer (HGT), gene duplication, and functional diversification and therefore offer an excellent paradigm to study protein evolution. We attempted to complement a mep1Δmep2Δmep3Δ strain of Saccharomyces cerevisiae (triple-deletion strain), which otherwise cannot grow on ammonium as a sole nitrogen source at concentrations of <3 mM, with amtA of Dictyostelium discoideum, an orthologue of S. cerevisiae MEP2. We observed that amtA did not complement the triple-deletion strain of S. cerevisiae for growth on low-ammonium medium. We isolated two mutant derivatives of amtA (amtA M1 and amtA M2) from a PCR-generated mutant plasmid library that complemented the triple-deletion strain of S. cerevisiae. amtA M1 bears three nonsynonymous and two synonymous substitutions, which are necessary for its functionality. amtA M2 bears two nonsynonymous substitutions and one synonymous substitution, all of which are necessary for functionality. Interestingly, AmtA M1 transports ammonium but does not confer methylamine toxicity, while AmtA M2 transports ammonium and confers methylamine toxicity, demonstrating functional diversification. Preliminary biochemical analyses indicated that the mutants differ in their conformations as well as their mechanisms of ammonium transport. These intriguing results clearly point out that protein evolution cannot be fathomed by studying nonsynonymous and synonymous substitutions in isolation. The above-described observations have significant implications for various facets of biological processes and are discussed in detail. IMPORTANCE Functional diversification following gene duplication is one of the major driving forces of protein evolution. While the role of nonsynonymous substitutions in the functional diversification of proteins is well recognized, knowledge of the role of synonymous substitutions in protein evolution is in its infancy. Using functional complementation, we isolated two functional alleles of the D. discoideum ammonium transporter gene (amtA), which otherwise does not function in S. cerevisiae as an ammonium transporters. One of them is an ammonium transporter, while the other is an ammonium transporter that also confers methylammonium (ammonium analogue) toxicity, suggesting functional diversification. Surprisingly, both alleles require a combination of synonymous and nonsynonymous substitutions for their functionality. These results bring out a hitherto-unknown pathway of protein evolution and pave the way for not only understanding protein evolution but also interpreting single nucleotide polymorphisms (SNPs).

Storage and Lyophilization of Pure Proteins

This chapter outlines empirical procedures for the storage of pure proteins with preservation of high levels of biological activity. It describes simple and workable means of preventing microbial contamination and proteolytic degradation and the use of various types of stabilizing additives. It sets out the principles of lyophilization (a complex process comprising freezing, primary drying, and secondary drying stages, otherwise known as freeze-drying). There follows a general procedure for the use of lyophilizer apparatus with emphasis on best practice and on pitfalls to avoid. The use of modulated differential scanning calorimetry to measure the glass transition temperature, a key parameter in the design and successful operation of lyophilization processes, is described. This chapter concludes with brief summaries of interesting recent work in the field.

Ancestral sequence reconstruction as a tool to study the evolution of wood decaying fungi

The study of evolution is limited by the techniques available to do so. Aside from the use of the fossil record, molecular phylogenetics can provide a detailed characterization of evolutionary histories using genes, genomes and proteins. However, these tools provide scarce biochemical information of the organisms and systems of interest and are therefore very limited when they come to explain protein evolution. In the past decade, this limitation has been overcome by the development of ancestral sequence reconstruction (ASR) methods. ASR allows the subsequent resurrection in the laboratory of inferred proteins from now extinct organisms, becoming an outstanding tool to study enzyme evolution. Here we review the recent advances in ASR methods and their application to study fungal evolution, with special focus on wood-decay fungi as essential organisms in the global carbon cycling.

Methodologies for Microbial Ancestral Sequence Reconstruction

The reconstruction of genetic material of ancestral organisms constitutes a powerful application of evolutionary biology. A fundamental step in this inference is the ancestral sequence reconstruction (ASR), which can be performed with diverse methodologies implemented in computer frameworks. However, most of these methodologies ignore evolutionary properties frequently observed in microbes, such as genetic recombination and complex selection processes, that can bias the traditional ASR. From a practical perspective, here I review methodologies for the reconstruction of ancestral DNA and protein sequences, with particular focus on microbes, and including biases, recommendations, and software implementations. I conclude that microbial ASR is a complex analysis that should be carefully performed and that there is a need for methods to infer more realistic ancestral microbial sequences.

An Integrated Method to Reconstruct Ancient Proteins

Proteins have played a fundamental role throughout life's history on Earth. Despite their biological importance, ancient origin, early function, and evolution of proteins are seldom able to be directly studied because few of these attributes are preserved across geologic timescales. Ancestral sequence reconstruction (ASR) provides a method to infer ancestral amino acid sequences and determine the evolutionary predecessors of modern-day proteins using phylogenetic tools. Laboratory application of ASR allows ancient sequences to be deduced from genetic information available in extant organisms and then experimentally resurrected to elucidate ancestral characteristics. In this article, we provide a generalized, stepwise protocol that considers the major elements of a well-designed ASR study and details potential sources of reconstruction bias that can reduce the relevance of historical inferences. We underscore key stages in our approach so that it may be broadly utilized to reconstruct the evolutionary histories of proteins.

A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling

Stochastic signaling dynamics expand living cells' information processing capabilities. An increasing number of studies report that regulators encode information in their pulsatile dynamics. The evolutionary mechanisms that lead to complex signaling dynamics remain uncharacterized, perhaps because key interactions of signaling proteins are encoded in intrinsically disordered regions (IDRs), whose evolution is difficult to analyze. Here we focused on the IDR that controls the stochastic pulsing dynamics of Crz1, a transcription factor in fungi downstream of the widely conserved calcium signaling pathway. We find that Crz1 IDRs from anciently diverged fungi can all respond transiently to calcium stress; however, only Crz1 IDRs from the Saccharomyces clade support pulsatility, encode extra information, and rescue fitness in competition assays, while the Crz1 IDRs from distantly related fungi do none of the three. On the other hand, we find that Crz1 pulsing is conserved in the distantly related fungi, consistent with the evolutionary model of stabilizing selection on the signaling phenotype. Further, we show that a calcineurin docking site in a specific part of the IDRs appears to be sufficient for pulsing and show evidence for a beneficial increase in the relative calcineurin affinity of this docking site. We propose that evolutionary flexibility of functionally divergent IDRs underlies the conservation of stochastic signaling by stabilizing selection.

Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond

As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.

Enzyme dynamics: Looking beyond a single structure

Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.

Ancestral Resurrection and Directed Evolution of Fungal Mesozoic Laccases

Ancestral sequence reconstruction and resurrection provides useful information for protein engineering, yet its alliance with directed evolution has been little explored. In this study, we have resurrected several ancestral nodes of fungal laccases dating back ∼500 to 250 million years. Unlike modern laccases, the resurrected Mesozoic laccases were readily secreted by yeast, with similar kinetic parameters, a broader stability, and distinct pH activity profiles. The resurrected Agaricomycetes laccase carried 136 ancestral mutations, a molecular testimony to its origin, and it was subjected to directed evolution in order to improve the rate of 1,3-cyclopentanedione oxidation, a β-diketone initiator commonly used in vinyl polymerization reactions.IMPORTANCE The broad variety of biotechnological uses of fungal laccases is beyond doubt (food, textiles, pulp and paper, pharma, biofuels, cosmetics, and bioremediation), and protein engineering (in particular, directed evolution) has become the key driver for adaptation of these enzymes to harsh industrial conditions. Usually, the first requirement for directed laccase evolution is heterologous expression, which presents an important hurdle and often a time-consuming process. In this work, we resurrected a fungal Mesozoic laccase node which showed strikingly high heterologous expression and pH stability. As a proof of concept that the ancestral laccase is a suitable blueprint for engineering, we performed a quick directed evolution campaign geared to the oxidation of the β-diketone 1,3-cyclopentanedione, a poor laccase substrate that is used in the polymerization of vinyl monomers.

How to resurrect ancestral proteins as proxies for ancient biogeochemistry

Throughout the history of life, enzymes have served as the primary molecular mediators of biogeochemical cycles by catalyzing the metabolic pathways that interact with geochemical substrates. The byproducts of enzymatic activities have been preserved as chemical and isotopic signatures in the geologic record. However, interpretations of these signatures are limited by the assumption that such enzymes have remained functionally conserved over billions of years of molecular evolution. By reconstructing ancient genetic sequences in conjunction with laboratory enzyme resurrection, preserved biogeochemical signatures can instead be related to experimentally constrained, ancestral enzymatic properties. We may thereby investigate instances within molecular evolutionary trajectories potentially tied to significant biogeochemical transitions evidenced in the geologic record. Here, we survey recent enzyme resurrection studies to provide a reasoned assessment of areas of success and common pitfalls relevant to ancient biogeochemical applications. We conclude by considering the Great Oxidation Event, which provides a constructive example of a significant biogeochemical transition that warrants investigation with ancestral enzyme resurrection. This event also serves to highlight the pitfalls of facile interpretation of paleophenotype models and data, as applied to two examples of enzymes that likely both influenced and were influenced by the rise of atmospheric oxygen - RuBisCO and nitrogenase.

Weak Chemical Interactions That Drive Protein Evolution: Crowding, Sticking, and Quinary Structure in Folding and Function

In recent years, better instrumentation and greater computing power have enabled the imaging of elusive biomolecule dynamics in cells, driving many advances in understanding the chemical organization of biological systems. The focus of this Review is on interactions in the cell that affect both biomolecular stability and function and modulate them. The same protein or nucleic acid can behave differently depending on the time in the cell cycle, the location in a specific compartment, or the stresses acting on the cell. We describe in detail the crowding, sticking, and quinary structure in the cell and the current methods to quantify them both in vitro and in vivo. Finally, we discuss protein evolution in the cell in light of current biophysical evidence. We describe the factors that drive protein evolution and shape protein interaction networks. These interactions can significantly affect the free energy, ΔG, of marginally stable and low-population proteins and, due to epistasis, direct the evolutionary pathways in an organism. We finally conclude by providing an outlook on experiments to come and the possibility of collaborative evolutionary biology and biophysical efforts.

High-Throughput Reconstruction of Ancestral Protein Sequence, Structure, and Molecular Function

Ancestral protein sequence reconstruction is a powerful technique for explicitly testing hypotheses about the evolution of molecular function, allowing researchers to meticulously dissect how historical changes in protein sequence impacted functional repertoire by altering the protein's 3D structure. These techniques have provided concrete, experimentally validated insights into ancient evolutionary processes and help illuminate the complex relationship between protein sequence, structure, and function. Inferring the protein family phylogenies on which ancestral sequence reconstruction depends and reconstructing the sequences, themselves, are amenable to high-throughput computational analysis. However, determining the structures of ancestral-reconstructed proteins and characterizing their functions typically rely on time-consuming and expensive laboratory analyses, limiting most current studies to examining a relatively small number of specific hypotheses. For this reason, we have little detailed, unbiased information about how molecular function evolves across large protein family phylogenies. Here we describe a generalized protocol that integrates ancestral sequence reconstruction with structural homology modeling and structure-based molecular affinity prediction to characterize historical changes in protein function across families with thousands of individual sequences. We highlight key steps in the analysis protocol requiring particularly careful attention to avoid introducing potential errors as well as steps for which computationally efficient subroutines can be substituted for more intensive approaches, allowing researchers to scale the analysis up or down, depending on available resources and requirements for reproducibility and scientific rigor. In our view, this approach provides a compelling compliment to more laboratory-intensive procedures, generating important contextual information that can help guide detailed experiments.

Understanding molecular mechanisms in cell signaling through natural and artificial sequence variation

The functionally tolerated sequence space of proteins can now be explored in an unprecedented way, owing to the expansion of genomic databases and the development of high-throughput methods to interrogate protein function. For signaling proteins, several recent studies have shown how the analysis of sequence variation leverages the available protein-structure information to provide new insights into specificity and allosteric regulation. In this Review, we discuss recent work that illustrates how this emerging approach is providing a deeper understanding of signaling proteins.

Coupled molecular dynamics mediate long- and short-range epistasis between mutations that affect stability and aggregation kinetics

Multiple mutations are typically required to significantly improve protein stability or aggregation kinetics. However, when several substitutions are made in a single protein, the mutations can potentially interact in a nonadditive manner, resulting in epistatic effects, which can hamper protein-engineering strategies to improve thermostability or aggregation kinetics. Here, we have examined the role of protein dynamics in mediating epistasis between pairs of mutations. With Escherichia coli transketolase (TK) as a model, we explored the epistatic interactions between two single variants H192P and A282P, and also between the double-mutant H192P/A282P and two single variants, I365L or G506A. Epistasis was determined for several measures of protein stability, including the following: the free-energy barrier to kinetic inactivation, ∆∆G ^‡; thermal transition midpoint temperatures, T _m; and aggregation onset temperatures, T _agg Nonadditive epistasis was observed between neighboring mutations as expected, but also for distant mutations located in the surface and core regions of different domains. Surprisingly, the epistatic behaviors for each measure of stability were often different for any given pairwise recombination, highlighting that kinetic and thermodynamic stabilities do not always depend on the same structural features. Molecular-dynamics simulations and a pairwise cross-correlation analysis revealed that mutations influence the dynamics of their local environment, but also in some cases the dynamics of regions distant in the structure. This effect was found to mediate epistatic interactions between distant mutations and could therefore be exploited in future protein-engineering strategies.

Evolutionary constraints in fitness landscapes

In the last years, several genotypic fitness landscapes-combinations of a small number of mutations-have been experimentally resolved. To learn about the general properties of "real" fitness landscapes, it is key to characterize these experimental landscapes via simple measures of their structure, related to evolutionary features. Some of the most relevant measures are based on the selectively acessible paths and their properties. In this paper, we present some measures of evolutionary constraints based on (i) the similarity between accessible paths and (ii) the abundance and characteristics of "chains" of obligatory mutations, that are paths going through genotypes with a single fitter neighbor. These measures have a clear evolutionary interpretation. Furthermore, we show that chains are only weakly correlated to classical measures of epistasis. In fact, some of these measures of constraint are non-monotonic in the amount of epistatic interactions, but have instead a maximum for intermediate values. Finally, we show how these measures shed light on evolutionary constraints and predictability in experimentally resolved landscapes.

The Influence of Higher-Order Epistasis on Biological Fitness Landscape Topography

The effect of a mutation on the organism often depends on what other mutations are already present in its genome. Geneticists refer to such mutational interactions as epistasis. Pairwise epistatic effects have been recognized for over a century, and their evolutionary implications have received theoretical attention for nearly as long. However, pairwise epistatic interactions themselves can vary with genomic background. This is called higher-order epistasis, and its consequences for evolution are much less well understood. Here, we assess the influence that higher-order epistasis has on the topography of 16 published, biological fitness landscapes. We find that on average, their effects on fitness landscape declines with order, and suggest that notable exceptions to this trend may deserve experimental scrutiny. We conclude by highlighting opportunities for further theoretical and experimental work dissecting the influence that epistasis of all orders has on fitness landscape topography and on the efficiency of evolution by natural selection.

Exploration of Protein Unfolding by Modelling Calorimetry Data from Reheating

Studies of protein unfolding mechanisms are critical for understanding protein functions inside cells, de novo protein design as well as defining the role of protein misfolding in neurodegenerative disorders. Calorimetry has proven indispensable in this regard for recording full energetic profiles of protein unfolding and permitting data fitting based on unfolding pathway models. While both kinetic and thermodynamic protein stability are analysed by varying scan rates and reheating, the latter is rarely used in curve-fitting, leading to a significant loss of information from experiments. To extract this information, we propose fitting both first and second scans simultaneously. Four most common single-peak transition models are considered: (i) fully reversible, (ii) fully irreversible, (iii) partially reversible transitions, and (iv) general three-state models. The method is validated using calorimetry data for chicken egg lysozyme, mutated Protein A, three wild-types of haloalkane dehalogenases, and a mutant stabilized by protein engineering. We show that modelling of reheating increases the precision of determination of unfolding mechanisms, free energies, temperatures, and heat capacity differences. Moreover, this modelling indicates whether alternative refolding pathways might occur upon cooling. The Matlab-based data fitting software tool and its user guide are provided as a supplement.

Exploring the past and the future of protein evolution with ancestral sequence reconstruction: the 'retro' approach to protein engineering

A central goal in molecular evolution is to understand the ways in which genes and proteins evolve in response to changing environments. In the absence of intact DNA from fossils, ancestral sequence reconstruction (ASR) can be used to infer the evolutionary precursors of extant proteins. To date, ancestral proteins belonging to eubacteria, archaea, yeast and vertebrates have been inferred that have been hypothesized to date from between several million to over 3 billion years ago. ASR has yielded insights into the early history of life on Earth and the evolution of proteins and macromolecular complexes. Recently, however, ASR has developed from a tool for testing hypotheses about protein evolution to a useful means for designing novel proteins. The strength of this approach lies in the ability to infer ancestral sequences encoding proteins that have desirable properties compared with contemporary forms, particularly thermostability and broad substrate range, making them good starting points for laboratory evolution. Developments in technologies for DNA sequencing and synthesis and computational phylogenetic analysis have led to an escalation in the number of ancient proteins resurrected in the last decade and greatly facilitated the use of ASR in the burgeoning field of synthetic biology. However, the primary challenge of ASR remains in accurately inferring ancestral states, despite the uncertainty arising from evolutionary models, incomplete sequences and limited phylogenetic trees. This review will focus, firstly, on the use of ASR to uncover links between sequence and phenotype and, secondly, on the practical application of ASR in protein engineering.

Convergence of Domain Architecture, Structure, and Ligand Affinity in Animal and Plant RNA-Binding Proteins

Reconstruction of ancestral protein sequences using phylogenetic methods is a powerful technique for directly examining the evolution of molecular function. Although ancestral sequence reconstruction (ASR) is itself very efficient, downstream functional, and structural studies necessary to characterize when and how changes in molecular function occurred are often costly and time-consuming, currently limiting ASR studies to examining a relatively small number of discrete functional shifts. As a result, we have very little direct information about how molecular function evolves across large protein families. Here we develop an approach combining ASR with structure and function prediction to efficiently examine the evolution of ligand affinity across a large family of double-stranded RNA binding proteins (DRBs) spanning animals and plants. We find that the characteristic domain architecture of DRBs-consisting of 2-3 tandem double-stranded RNA binding motifs (dsrms)-arose independently in early animal and plant lineages. The affinity with which individual dsrms bind double-stranded RNA appears to have increased and decreased often across both animal and plant phylogenies, primarily through convergent structural mechanisms involving RNA-contact residues within the β1-β2 loop and a small region of α2. These studies provide some of the first direct information about how protein function evolves across large gene families and suggest that changes in molecular function may occur often and unassociated with major phylogenetic events, such as gene or domain duplications.

Stability-Mediated Epistasis Restricts Accessible Mutational Pathways in the Functional Evolution of Avian Hemoglobin

If the fitness effects of amino acid mutations are conditional on genetic background, then mutations can have different effects depending on the sequential order in which they occur during evolutionary transitions in protein function. A key question concerns the fraction of possible mutational pathways connecting alternative functional states that involve transient reductions in fitness. Here we examine the functional effects of multiple amino acid substitutions that contributed to an evolutionary transition in the oxygenation properties of avian hemoglobin (Hb). The set of causative changes included mutations at intradimer interfaces of the Hb tetramer. Replacements at such sites may be especially likely to have epistatic effects on Hb function since residues at intersubunit interfaces are enmeshed in networks of salt bridges and hydrogen bonds between like and unlike subunits; mutational reconfigurations of these atomic contacts can affect allosteric transitions in quaternary structure and the propensity for tetramer-dimer dissociation. We used ancestral protein resurrection in conjunction with a combinatorial protein engineering approach to synthesize genotypes representing the complete set of mutational intermediates in all possible forward pathways that connect functionally distinct ancestral and descendent genotypes. The experiments revealed that 1/2 of all possible forward pathways included mutational intermediates with aberrant functional properties because particular combinations of mutations promoted tetramer-dimer dissociation. The subset of mutational pathways with unstable intermediates may be selectively inaccessible, representing evolutionary roads not taken. The experimental results also demonstrate how epistasis for particular functional properties of proteins may be mediated indirectly by mutational effects on quaternary structural stability.

Uniting Natural History with the Molecular Sciences. The Ultimate Multidisciplinarity

Life and the Earth have coevolved over the past four billion years to deliver a rich diversity of biological structure, from biomolecules to macrophysiology. One grand challenge seeks to interconnect these structures, in ways acceptable to both natural historians and physical scientists, to give an interconnecting web of models and experiments to create a planetary understanding of the phenomenon that we call "life". The molecular scientist wants experiments; the natural historian wants reference to Darwinian fitness. Paleogenetics offers both.

Evolutionary history of versatile-lipases from Agaricales through reconstruction of ancestral structures

BACKGROUND

Fungal "Versatile carboxylic ester hydrolases" are enzymes with great biotechnological interest. Here we carried out a bioinformatic screening to find these proteins in genomes from Agaricales, by means of searching for conserved motifs, sequence and phylogenetic analysis, and three-dimensional modeling. Moreover, we reconstructed the molecular evolution of these enzymes along the time by inferring and analyzing the sequence of ancestral intermediate forms.

RESULTS

The properties of the ancestral candidates are discussed on the basis of their three-dimensional structural models, the hydrophobicity of the lid, and the substrate binding intramolecular tunnel, revealing all of them featured properties of these enzymes. The evolutionary history of the putative lipases revealed an increase on the length and hydrophobicity of the lid region, as well as in the size of the substrate binding pocket, during evolution time. These facts suggest the enzymes' specialization towards certain substrates and their subsequent loss of promiscuity.

CONCLUSIONS

These results bring to light the presence of different pools of lipases in fungi with different habitats and life styles. Despite the consistency of the data gathered from reconstruction of ancestral sequences, the heterologous expression of some of these candidates would be essential to corroborate enzymes' activities.

Storage and Lyophilization of Pure Proteins

This article outlines empirical procedures for the storage of pure proteins with preservation of high levels of biological activity. It describes simple and workable means of preventing microbial contamination and proteolytic degradation, and the use of various types of stabilizing additives. It sets out the principles of lyophilization (otherwise known as freeze-drying, a complex process comprising freezing, primary dying, and secondary drying stages). There follows a general procedure for the use of lyophilizer apparatus with emphasis on best practice and on pitfalls to avoid. The use of modulated differential scanning calorimetry to measure the glass transition temperature, a key parameter in the design and successful operation of lyophilization processes, is described.

The thermostability and specificity of ancient proteins

Were ancient proteins systematically different than modern proteins? The answer to this question is profoundly important, shaping how we understand the origins of protein biochemical, biophysical, and functional properties. Ancestral sequence reconstruction (ASR), a phylogenetic approach to infer the sequences of ancestral proteins, may reveal such trends. We discuss two proposed trends: a transition from higher to lower thermostability and a tendency for proteins to acquire higher specificity over time. We review the evidence for elevated ancestral thermostability and discuss its possible origins in a changing environmental temperature and/or reconstruction bias. We also conclude that there is, as yet, insufficient data to support a trend from promiscuity to specificity. Finally, we propose future work to understand these proposed evolutionary trends.

Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher's Geometric Model?

The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes.

Rapid bursts and slow declines: on the possible evolutionary trajectories of enzymes

The evolution of enzymes is often viewed as following a smooth and steady trajectory, from barely functional primordial catalysts to the highly active and specific enzymes that we observe today. In this review, we summarize experimental data that suggest a different reality. Modern examples, such as the emergence of enzymes that hydrolyse human-made pesticides, demonstrate that evolution can be extraordinarily rapid. Experiments to infer and resurrect ancient sequences suggest that some of the first organisms present on the Earth are likely to have possessed highly active enzymes. Reconciling these observations, we argue that rapid bursts of strong selection for increased catalytic efficiency are interspersed with much longer periods in which the catalytic power of an enzyme erodes, through neutral drift and selection for other properties such as cellular energy efficiency or regulation. Thus, many enzymes may have already passed their catalytic peaks.

Antiplasmodial Activity Is an Ancient and Conserved Feature of Tick Defensins

Ancestral sequence reconstruction has been widely used to test evolution-based hypotheses. The genome of the European tick vector, Ixodes ricinus, encodes for defensin peptides with diverse antimicrobial activities against distantly related pathogens. These pathogens include fungi, Gram-negative, and Gram-positive bacteria, i.e., a wide antimicrobial spectrum. Ticks do not transmit these pathogens, suggesting that these defensins may act against a wide range of microbes encountered by ticks during blood feeding or off-host periods. As demonstrated here, these I. ricinus defensins are also effective against the apicomplexan parasite Plasmodium falciparum. To study the general evolution of antimicrobial activity in tick defensins, the ancestral amino acid sequence of chelicerate defensins, which existed approximately 444 million years ago, was reconstructed using publicly available scorpion and tick defensin sequences (named Scorpions-Ticks Defensins Ancestor, STiDA). The activity of STiDA was tested against P. falciparum and the same Gram-negative and Gram-positive bacteria that were used for the I. ricinus defensins. While some extant tick defensins exhibit a wide antimicrobial spectrum, the ancestral defensin showed moderate activity against one of the tested microbes, P. falciparum. This study suggests that amino acid variability and defensin family expansion increased the antimicrobial spectrum of ancestral tick defensins.

Reconstructed Ancestral Enzymes Impose a Fitness Cost upon Modern Bacteria Despite Exhibiting Favourable Biochemical Properties

Ancestral sequence reconstruction has been widely used to study historical enzyme evolution, both from biochemical and cellular perspectives. Two properties of reconstructed ancestral proteins/enzymes are commonly reported--high thermostability and high catalytic activity--compared with their contemporaries. Increased protein stability is associated with lower aggregation rates, higher soluble protein abundance and a greater capacity to evolve, and therefore, these proteins could be considered "superior" to their contemporary counterparts. In this study, we investigate the relationship between the favourable in vitro biochemical properties of reconstructed ancestral enzymes and the organismal fitness they confer in vivo. We have previously reconstructed several ancestors of the enzyme LeuB, which is essential for leucine biosynthesis. Our initial fitness experiments revealed that overexpression of ANC4, a reconstructed LeuB that exhibits high stability and activity, was only able to partially rescue the growth of a ΔleuB strain, and that a strain complemented with this enzyme was outcompeted by strains carrying one of its descendants. When we expanded our study to include five reconstructed LeuBs and one contemporary, we found that neither in vitro protein stability nor the catalytic rate was correlated with fitness. Instead, fitness showed a strong, negative correlation with estimated evolutionary age (based on phylogenetic relationships). Our findings suggest that, for reconstructed ancestral enzymes, superior in vitro properties do not translate into organismal fitness in vivo. The molecular basis of the relationship between fitness and the inferred age of ancestral LeuB enzymes is unknown, but may be related to the reconstruction process. We also hypothesise that the ancestral enzymes may be incompatible with the other, contemporary enzymes of the metabolic network.

Resurrecting phenotypes from ancient DNA sequences: promises and perspectives

Anatomical changes in extinct mammalian lineages over evolutionary time, such as the loss of fingers and teeth and the rapid increase in body size that accompanied the late Miocene dispersal of the progenitors of Steller’s sea cows (Hydrodamalis gigas (Zimmermann, 1780)) into North Pacific waters and the convergent development of a thick pelage and accompanying reductions in ear and tail surface area of woolly mammoths (Mammuthus primigenius (Blumenbach, 1799)) and woolly rhinoceros (Coelodonta antiquitatis (Blumenbach, 1799)), are prime examples of adaptive evolution underlying the exploitation of new habitats. It is likely, however, that biochemical specializations adopted during these evolutionary transitions were of similar or even greater biological importance. As these “living” processes do not fossilize, direct information regarding the physiological attributes of extinct species has largely remained beyond the range of scientific inquiry. However, the ability to retrieve genomic sequences from ancient DNA samples, combined with ectopic expression systems, now permit the evolutionary origins and structural and functional properties of authentic prehistoric proteins to be examined in great detail. Exponential technical advances in ancient DNA retrieval, enrichment, and sequencing will soon permit targeted generation of complete genomes from hundreds of extinct species across the last one million years that, in combination with emerging in vitro expression, genome engineering, and cell differentiation techniques, promises to herald an exciting new trajectory of evolutionary research at the interface of biochemistry, genomics, palaeontology, and cell biology.

Quantitative Description of a Protein Fitness Landscape Based on Molecular Features

Understanding the driving forces behind protein evolution requires the ability to correlate the molecular impact of mutations with organismal fitness. To address this issue, we employ here metallo-β-lactamases as a model system, which are Zn(II) dependent enzymes that mediate antibiotic resistance. We present a study of all the possible evolutionary pathways leading to a metallo-β-lactamase variant optimized by directed evolution. By studying the activity, stability and Zn(II) binding capabilities of all mutants in the preferred evolutionary pathways, we show that this local fitness landscape is strongly conditioned by epistatic interactions arising from the pleiotropic effect of mutations in the different molecular features of the enzyme. Activity and stability assays in purified enzymes do not provide explanatory power. Instead, measurement of these molecular features in an environment resembling the native one provides an accurate description of the observed antibiotic resistance profile. We report that optimization of Zn(II) binding abilities of metallo-β-lactamases during evolution is more critical than stabilization of the protein to enhance fitness. A global analysis of these parameters allows us to connect genotype with fitness based on quantitative biochemical and biophysical parameters.

Toward more accurate ancestral protein genotype-phenotype reconstructions with the use of species tree-aware gene trees

The resurrection of ancestral proteins provides direct insight into how natural selection has shaped proteins found in nature. By tracing substitutions along a gene phylogeny, ancestral proteins can be reconstructed in silico and subsequently synthesized in vitro. This elegant strategy reveals the complex mechanisms responsible for the evolution of protein functions and structures. However, to date, all protein resurrection studies have used simplistic approaches for ancestral sequence reconstruction (ASR), including the assumption that a single sequence alignment alone is sufficient to accurately reconstruct the history of the gene family. The impact of such shortcuts on conclusions about ancestral functions has not been investigated. Here, we show with simulations that utilizing information on species history using a model that accounts for the duplication, horizontal transfer, and loss (DTL) of genes statistically increases ASR accuracy. This underscores the importance of the tree topology in the inference of putative ancestors. We validate our in silico predictions using in vitro resurrection of the LeuB enzyme for the ancestor of the Firmicutes, a major and ancient bacterial phylum. With this particular protein, our experimental results demonstrate that information on the species phylogeny results in a biochemically more realistic and kinetically more stable ancestral protein. Additional resurrection experiments with different proteins are necessary to statistically quantify the impact of using species tree-aware gene trees on ancestral protein phenotypes. Nonetheless, our results suggest the need for incorporating both sequence and DTL information in future studies of protein resurrections to accurately define the genotype-phenotype space in which proteins diversify.

What can we learn from fitness landscapes?

A combinatorially complete data set consists of studies of all possible combinations of a set of mutant sites in a gene or mutant alleles in a genome. Among the most robust conclusions from these studies is that epistasis between beneficial mutations often shows a pattern of diminishing returns, in which favorable mutations are less fit when combined than would be expected. Another robust inference is that the number of adaptive evolutionary paths is often limited to a relatively small fraction of the theoretical possibilities, owing largely to sign epistasis requiring evolutionary steps that would entail a decrease in fitness. Here we summarize these and other results while also examining issues that remain unresolved and future directions that seem promising.

Empirical fitness landscapes and the predictability of evolution

The genotype-fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

Strong epistatic interactions within a single protein

A central question in protein molecular evolution is whether an amino acid that occurs at a given site makes an independent contribution to fitness or whether its contribution depends on other amino acid sites in the protein sequence, a phenomenon known as intragenic epistasis. In the absence of intragenic epistasis, natural selection acts on a protein mutation independent of its genetic background, and the experimentally determined fitness for a mutation should be the same across all genetic backgrounds. We tested this hypothesis by using site-directed mutagenesis to introduce a well-characterized deleterious single amino acid substitution in 56 different hepatitis C virus NS3 protease variants. The catalytic efficiency of the mutated proteases was determined and compared with the corresponding wild-type protein. Fitness effects ranged from lethality to significantly beneficial. Although primarily deleterious and lethal effects were observed (41 and 5 out of 56 tested variants, respectively), deleterious effects ranged from near neutral (-26.7% reduction of fitness) to near lethal (-98.5%). Our findings demonstrate that the introduced amino acid substitution has different fitness effects in different protein variants and provide independent support for the relevant role of intragenic epistasis in protein evolution.

Should evolutionary geneticists worry about higher-order epistasis?

Natural selection drives evolving populations up the fitness landscape, the projection from nucleotide sequence space to organismal reproductive success. While it has long been appreciated that topographic complexities on fitness landscapes can arise only as a consequence of epistatic interactions between mutations, evolutionary genetics has mainly focused on epistasis between pairs of mutations. Here we propose a generalization to the classical population genetic treatment of pairwise epistasis that yields expressions for epistasis among arbitrary subsets of mutations of all orders (pairwise, three-way, etc.). Our approach reveals substantial higher-order epistasis in almost every published fitness landscape. Furthermore we demonstrate that higher-order epistasis is critically important in two systems we know best. We conclude that higher-order epistasis deserves empirical and theoretical attention from evolutionary geneticists.

Evolutionary biochemistry: revealing the historical and physical causes of protein properties

The repertoire of proteins and nucleic acids in the living world is determined by evolution; their properties are determined by the laws of physics and chemistry. Explanations of these two kinds of causality - the purviews of evolutionary biology and biochemistry, respectively - are typically pursued in isolation, but many fundamental questions fall squarely at the interface of fields. Here we articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution. We show how an integration of evolution with biochemistry moves us towards a more complete understanding of why biological molecules have the properties that they do.

Fisher's geometric model of adaptation meets the functional synthesis: data on pairwise epistasis for fitness yields insights into the shape and size of phenotype space

The functional synthesis uses experimental methods from molecular biology, biochemistry and structural biology to decompose evolutionarily important mutations into their more proximal mechanistic determinants. However these methods are technically challenging and expensive. Noting strong formal parallels between R.A. Fisher's geometric model of adaptation and a recent model for the phenotypic basis of protein evolution, we sought to use the former to make inferences into the latter using data on pairwise fitness epistasis between mutations. We present an analytic framework for classifying pairs of mutations with respect to similarity of underlying mechanism on this basis, and also show that these data can yield an estimate of the number of mutationally labile phenotypes underlying fitness effects. We use computer simulations to explore the robustness of our approach to violations of analytic assumptions and analyze several recently published datasets. This work provides a theoretical complement to the functional synthesis as well as a novel test of Fisher's geometric model.

Structure- and sequence-analysis inspired engineering of proteins for enhanced thermostability

Protein engineering strategies for increasing stability can be improved by replacing random mutagenesis and high-throughput screening by approaches that include bioinformatics and computational design. Mutations can be focused on regions in the structure that are most flexible and involved in the early steps of thermal unfolding. Sequence analysis can often predict the position and nature of stabilizing mutations, and may allow the reconstruction of thermostable ancestral sequences. Various computational tools make it possible to design stabilizing features, such as hydrophobic clusters and surface charges. Different methods for designing chimeric enzymes can also support the engineering of more stable proteins without the need of high-throughput screening.

Reconstruction of ancestral metabolic enzymes reveals molecular mechanisms underlying evolutionary innovation through gene duplication

Gene duplications are believed to facilitate evolutionary innovation. However, the mechanisms shaping the fate of duplicated genes remain heavily debated because the molecular processes and evolutionary forces involved are difficult to reconstruct. Here, we study a large family of fungal glucosidase genes that underwent several duplication events. We reconstruct all key ancestral enzymes and show that the very first preduplication enzyme was primarily active on maltose-like substrates, with trace activity for isomaltose-like sugars. Structural analysis and activity measurements on resurrected and present-day enzymes suggest that both activities cannot be fully optimized in a single enzyme. However, gene duplications repeatedly spawned daughter genes in which mutations optimized either isomaltase or maltase activity. Interestingly, similar shifts in enzyme activity were reached multiple times via different evolutionary routes. Together, our results provide a detailed picture of the molecular mechanisms that drove divergence of these duplicated enzymes and show that whereas the classic models of dosage, sub-, and neofunctionalization are helpful to conceptualize the implications of gene duplication, the three mechanisms co-occur and intertwine.

Optimal definition of inter-residual contact in globular proteins based on pairwise interaction energy calculations, its robustness, and applications

Although a contact is an essential measurement for the topology as well as strength of non-covalent interactions in biomolecules and their complexes, there is no general agreement in the definition of this feature. Most of the definitions work with simple geometric criteria which do not fully reflect the energy content or ability of the biomolecular building blocks to arrange their environment. We offer a reasonable solution to this problem by distinguishing between "productive" and "non-productive" contacts based on their interaction energy strength and properties. We have proposed a method which converts the protein topology into a contact map that represents interactions with statistically significant high interaction energies. We do not prove that these contacts are exclusively stabilizing, but they represent a gateway to thermodynamically important rather than geometry-based contacts. The process is based on protein fragmentation and calculation of interaction energies using the OPLS force field and relies on pairwise additivity of amino acid interactions. Our approach integrates the treatment of different types of interactions, avoiding the problems resulting from different contributions to the overall stability and the different effect of the environment. The first applications on a set of homologous proteins have shown the usefulness of this classification for a sound estimate of protein stability.

Tracing protein evolution through ancestral structures of fish galectin

Ancestral structures of fish galectins (congerins) were determined. The extant isoforms I and II of congerin are the components of a fish biological defense system and have rapidly differentiated under natural selection pressure, by which congerin I has experienced a protein-fold evolution. The dimer structure of the ancestral congerin demonstrated intermediate features of the extant isoforms. The protein-fold evolution was not observed in the ancestral structure, indicating it specifically occurred in congerin I lineage. Details of hydrogen bonding pattern at the dimer interface and the carbohydrate-binding site of the ancestor were different from the current proteins. The differences implied these proteins were under selection pressure for stabilizing dimer structure and differentiation in carbohydrate specificity. The ancestor had rather low cytotoxic activity than offspring, indicating selection was made to enhance this activity of congerins. Combined with functional analyses, the structure revealed atomic details of the differentiation process of the proteins.