An experimental phylogeny to benchmark ancestral sequence reconstruction

Ancestral Sequence Reconstruction and Comprehensive Computational Simulations Unmask an Efficient PET Hydrolase with the Wobbled Catalytic Triad

Beyond directed evolution, ancestral sequence reconstruction (ASR) has emerged as a powerful strategy for engineering proteins with superior functional properties. Herein, we harnessed ASR to uncover robust PET hydrolase variants, expanding the repertoire of PET-degrading enzymes and providing deeper insights into the underlying mechanisms of PET hydrolysis. As a result, ASR1-PETase, featuring a unique cysteine catalytic site, was discovered. Despite having only 19.3 % sequence identity with IsPETase, ASR1-PETase demonstrated improved PET degradation efficiency, with a finely-tuned substrate-binding cleft. Comprehensive experimental validation, including mutagenesis studies and comparisons with six state-of-the-art PET hydrolases, combined with microsecond-scale molecular dynamics (MD) simulations and QM-cluster calculations, revealed that ASR1-PETase's C161 catalytic residue assisted with the wobbled H242 can simultaneously cleave both ester bonds of BHET - a feature not commonly observed in other PET hydrolases. This mechanism may serve as the primary driving force for accelerating PET hydrolysis while minimizing the accumulation of the intermediate MHET, thereby enhancing the efficiency of TPA production.

The tree labeling polytope: a unified approach to ancestral reconstruction problems

Motivation

Reconstructing unobserved ancestral states of a phylogenetic tree provides insight into the history of evolving systems and is one of the fundamental problems in phylogenetics. For a fixed phylogenetic tree, the most parsimonious ancestral reconstruction - a solution to the small parsimony problem - can be efficiently found using the dynamic programming algorithms of Fitch-Hartigan and Sankoff. Ancestral reconstruction is important in many applications including inferring the routes of metastases in cancer, deriving the transmission history of viruses, determining the direction of cellular differentiation in organismal development, and detecting recombination and horizontal gene transfer in phylogenetic networks. However, most of these applications impose additional global constraints on the reconstructed ancestral states, which break the local structure required in the recurrences of Fitch-Hartigan and Sankoff.

Results

We introduce an alternative, polyhedral approach to ancestral reconstruction problems using the tree labeling polytope , a geometric object whose vertices represent the feasible ancestral labelings of a tree. This framework yields a polynomial-time linear programming algorithm for the small parsimony problem . More importantly, the tree labeling polytope facilitates the incorporation of additional constraints that arise in modern ancestral reconstruction problems. We demonstrate the utility of our approach by deriving mixed-integer programming algorithms with a small number of integer variables and strong linear relaxations for three such problems: the parsimonious migration history problem, the softwired small parsimony problem on phylogenetic networks, and the convex recoloring problem on trees. Our algorithms outperform existing state-of-the-art methods on both simulated and real datasets. For instance, our algorithm scales to trace routes of cancer metastases in trees with thousands of leaves, enabling the analysis of large trees generated by recent single-cell sequencing technologies. On a mouse model of metastatic lung adenocarcinoma, the tree labeling polytope allows us to infer simpler migration histories compared to previous results.

Availability

Python implementations of the algorithms provided in this work are available at: github.com/raphael-group/tree-labeling-polytope .

Applications of ancestral sequence reconstruction for understanding the evolution of plant specialized metabolism

Studies of enzymes in modern-day plants have documented the diversity of metabolic activities retained by species today but only provide limited insight into how those properties evolved. Ancestral sequence reconstruction (ASR) is an approach that provides statistical estimates of ancient plant enzyme sequences which can then be resurrected to test hypotheses about the evolution of catalytic activities and pathway assembly. Here, I review the insights that have been obtained using ASR to study plant metabolism and highlight important methodological aspects. Overall, studies of resurrected plant enzymes show that (i) exaptation is widespread such that even low or undetectable levels of ancestral activity with a substrate can later become the apparent primary activity of descendant enzymes, (ii) intramolecular epistasis may or may not limit evolutionary paths towards catalytic or substrate preference switches, and (iii) ancient pathway flux often differs from modern-day metabolic networks. These and other insights gained from ASR would not have been possible using only modern-day sequences. Future ASR studies characterizing entire ancestral metabolic networks as well as those that link ancient structures with enzymatic properties should continue to provide novel insights into how the chemical diversity of plants evolved. This article is part of the theme issue 'The evolution of plant metabolism'.

Evolution, structure, and drug-metabolizing activity of mammalian prenylcysteine oxidases

Prenylcysteine oxidases (PCYOXs) metabolize prenylated cysteines produced by protein degradation. They utilize oxygen as a co-substrate to produce free cysteine, an aldehyde, and hydrogen peroxide through the unusual oxidation of a thioether bond. In this study, we explore the evolution, structure, and mechanism of the two mammalian PCYOXs. A gene duplication event in jawed vertebrates originated in these two paralogs. Both enzymes are active on farnesyl- and geranylgeranylcysteine, but inactive on molecules with shorter prenyl groups. Kinetics experiments outline a mechanism where flavin reduction and re-oxidation occur rapidly without any detectable intermediates, with the overall reaction rate limited by product release. The experimentally determined three-dimensional structure of PCYOX1 reveals long and wide tunnels leading from the surface to the flavin. They allow the isoprene substrate to curl up within the protein and position its reactive cysteine group close to the flavin. A hydrophobic patch on the surface mediates membrane association, enabling direct substrate and product exchange with the lipid bilayer. Leveraging established knowledge of flavoenzyme inhibition, we designed sub-micromolar PCYOX inhibitors. Additionally, we discovered that PCYOXs bind and slowly degrade salisirab, an anti-RAS compound. This activity suggests potential and previously unknown roles of PCYOXs in drug metabolism.

Stable monomers in the ancestral sequence reconstruction of the last opisthokont common ancestor of dimeric triosephosphate isomerase

Function and structure are strongly coupled in obligated oligomers such as Triosephosphate isomerase (TIM). In animals and fungi, TIM monomers are inactive and unstable. Previously, we used ancestral sequence reconstruction to study TIM evolution and found that before these lineages diverged, the last opisthokonta common ancestor of TIM (LOCATIM) was an obligated oligomer that resembles those of extant TIMs. Notably, calorimetric evidence indicated that ancestral TIM monomers are more structured than extant ones. To further increase confidence about the function, structure, and stability of the LOCATIM, in this work, we applied two different inference methodologies and the worst plausible case scenario for both of them, to infer four sequences of this ancestor and test the robustness of their physicochemical properties. The extensive biophysical characterization of the four reconstructed sequences of LOCATIM showed very similar hydrodynamic and spectroscopic properties, as well as ligand-binding energetics and catalytic parameters. Their 3D structures were also conserved. Although differences were observed in melting temperature, all LOCATIMs showed reversible urea-induced unfolding transitions, and for those that reached equilibrium, high conformational stability was estimated (ΔGTot = 40.6-46.2 kcal/mol). The stability of the inactive monomeric intermediates was also high (ΔGunf = 12.6-18.4 kcal/mol), resembling some protozoan TIMs rather than the unstable monomer observed in extant opisthokonts. A comparative analysis of the 3D structure of ancestral and extant TIMs shows a correlation between the higher stability of the ancestral monomers with the presence of several hydrogen bonds located in the "bottom" part of the barrel.

Structure, mechanism, and evolution of the last step in vitamin C biosynthesis

Photosynthetic organisms, fungi, and animals comprise distinct pathways for vitamin C biosynthesis. Besides this diversity, the final biosynthetic step consistently involves an oxidation reaction carried out by the aldonolactone oxidoreductases. Here, we study the origin and evolution of the diversified activities and substrate preferences featured by these flavoenzymes using molecular phylogeny, kinetics, mutagenesis, and crystallographic experiments. We find clear evidence that they share a common ancestor. A flavin-interacting amino acid modulates the reactivity with the electron acceptors, including oxygen, and determines whether an enzyme functions as an oxidase or a dehydrogenase. We show that a few side chains in the catalytic cavity impart the reaction stereoselectivity. Ancestral sequence reconstruction outlines how these critical positions were affixed to specific amino acids along the evolution of the major eukaryotic clades. During Eukarya evolution, the aldonolactone oxidoreductases adapted to the varying metabolic demands while retaining their overarching vitamin C-generating function.

Ancestral terpene cyclases: From fundamental science to applications in biosynthesis

Terpenes constitute one of the largest family of natural products with potent applications as renewable platform chemicals and medicines. The low activity, selectivity and stability displayed by terpene biosynthetic machineries can constitute an obstacle towards achieving expedient biosynthesis of terpenoids in processes that adhere to the 12 principles of green chemistry. Accordingly, engineering of terpene synthase enzymes is a prerequisite for industrial biotechnology applications, but obstructed by their complex catalysis that depend on reactive carbocationic intermediates that are prone to undergo bifurcation mechanisms. Rational redesign of terpene synthases can be tedious and requires high-resolution structural information, which is not always available. Furthermore, it has proven difficult to link sequence space of terpene synthase enzymes to specific product profiles. Herein, the author shows how ancestral sequence reconstruction (ASR) can favorably be used as a protein engineering tool in the redesign of terpene synthases without the need of a structure, and without excessive screening. A detailed workflow of ASR is presented along with associated limitations, with a focus on applying this methodology on terpene synthases. From selected examples of both class I and II enzymes, the author advocates that ancestral terpene cyclases constitute valuable assets to shed light on terpene-synthase catalysis and in enabling accelerated biosynthesis.

Extant Sequence Reconstruction: The Accuracy of Ancestral Sequence Reconstructions Evaluated by Extant Sequence Cross-Validation

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term "extant sequence reconstruction" (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

HetMM: A Michaelis-Menten model for non-homogeneous enzyme mixtures

The Michaelis-Menten model requires its reaction velocities to come from a preparation of homogeneous enzymes, with identical or near-identical catalytic activities. However, this condition is not always met. We introduce a kinetic model that relaxes this requirement, by assuming there are an unknown number of enzyme species drawn from a probability distribution whose standard deviation is estimated. Through simulation studies, we demonstrate the method accurately discriminates between homogeneous and heterogeneous data, even with moderate levels of experimental error. We applied this model to three homogeneous and three heterogeneous biological systems, showing that the standard and heterogeneous models outperform respectively. Lastly, we show that heterogeneity is not readily distinguished from negatively cooperative binding under the Hill model. These two distinct attributes-inequality in catalytic ability and interference between binding sites-yield similar Michaelis-Menten curves that are not readily resolved without further experimentation. Our user-friendly software package allows homogeneity testing and parameter estimation.

Performance of tree-building methods using a morphological dataset and a well-supported Hexapoda phylogeny

Recently, many studies have addressed the performance of phylogenetic tree-building methods (maximum parsimony, maximum likelihood, and Bayesian inference), focusing primarily on simulated data. However, for discrete morphological data, there is no consensus yet on which methods recover the phylogeny with better performance. To address this lack of consensus, we investigate the performance of different methods using an empirical dataset for hexapods as a model. As an empirical test of performance, we applied normalized indices to effectively measure accuracy (normalized Robinson-Foulds metric, nRF) and precision, which are measured via resolution, one minus Colless' consensus fork index (1-CFI). Additionally, to further explore phylogenetic accuracy and support measures, we calculated other statistics, such as the true positive rate (statistical power) and the false positive rate (type I error), and constructed receiver operating characteristic plots to visualize the relationship between these statistics. We applied the normalized indices to the reconstructed trees from the reanalyses of an empirical discrete morphological dataset from extant Hexapoda using a well-supported phylogenomic tree as a reference. Maximum likelihood and Bayesian inference applying the k-state Markov (Mk) model (without or with a discrete gamma distribution) performed better, showing higher precision (resolution). Additionally, our results suggest that most available tree topology tests are reliable estimators of the performance measures applied in this study. Thus, we suggest that likelihood-based methods and tree topology tests should be used more often in phylogenetic tree studies based on discrete morphological characters. Our study provides a fair indication that morphological datasets have robust phylogenetic signal.

Correlation Analysis of Key Residue Sites between Computational-Aided Design Thermostability d-Amino Acid Oxidase and Ancestral Enzymes

The d-amino acid oxidase (DAAO) from Rhodotorula taiwanensis has proven to have great potential for applications due to its excellent catalytic kinetic parameters. However, its poor thermal stability has limited its performance in biocatalysis. Herein, starting from the variant SHVG of RtwDAAO, this study employed a comprehensive computational design approach for protein stability engineering, resulting in positive substitutions at specific sites (A43S, T45M, C234L, E195Y). The generated variant combination, SHVG/SMLY, exhibited a significant synergistic effect, leading to an extension of the half-life and Tmapp. The ancestral sequence reconstruction revealed the conservation of the variant sites. The association of the variant sites with the highly stable ancestral enzyme was further explored. After determining the contribution of the variant sites to thermal stability, it was applied to other homologous sequences and validated. Molecular dynamics simulations indicated that the increased hydrophobicity of the variant SHVG/SMLY was a key factor for the increased stability, with strengthened intersubunit interactions playing an important role. In addition, the physical properties of the amino acids themselves were identified as crucial factors for thermal stability generality in homologous enzymes, which is important for the rapid acquisition of a series of stable enzymes.

Integrated evolutionary pattern analyses reveal multiple origins of steroidal saponins in plants

Steroidal saponins are a class of specialized metabolites essential for plant's response to biotic and abiotic stresses. They are also important raw materials for the industrial production of steroid drugs. Steroidal saponins are present in some monocots, such as Dioscorea and Paris, but their distribution, origin, and evolution in plants remain poorly understood. By reconstructing the evolutionary history of the steroidal saponin-associated module (SSAM) in plants, we reveal that the steroidal saponin pathway has its origin in Asparagus and Dioscorea. Through evaluating the distribution and evolutionary pattern of steroidal saponins in angiosperms, we further show that steroidal saponins originated multiple times in angiosperms, and exist in early diverged lineages of certain monocot lineages including Asparagales, Dioscoreales, and Liliales. In these lineages, steroidal saponins are synthesized through the high copy and/or high expression mechanisms of key genes in SSAM. Together with shifts in gene evolutionary rates and amino acid usage, these molecular mechanisms shape the current distribution and diversity of steroidal saponins in plants. Consequently, our results provide new insights into the distribution, diversity and evolutionary history of steroidal saponins in plants, and enhance our understanding of plants' resistance to abiotic and biotic stresses. Additionally, fundamental understanding of the steroidal saponin biosynthesis will facilitate their industrial production and pharmacological applications.

An Inferred Ancestral CotA Laccase with Improved Expression and Kinetic Efficiency

Laccases are widely used in industrial production due to their broad substrate availability and environmentally friendly nature. However, the pursuit of laccases with superior stability and increased heterogeneous expression to meet industry demands appears to be an ongoing challenge. To address this challenge, we resurrected five ancestral sequences of laccase BsCotA and their homologues. All five variants were successfully expressed in soluble and functional forms with improved expression levels in Escherichia coli. Among the five variants, three exhibited higher catalytic rates, thermal stabilities, and acidic stabilities. Notably, AncCotA2, the best-performing variant, displayed a k_cat/K_M of 7.5 × 10⁵ M^-1·s^-1, 5.2-fold higher than that of the wild-type BsCotA, an improved thermo- and acidic stability, and better dye decolorization ability. This study provides a laccase variant with high application potential and presents a new starting point for future enzyme engineering.

Ancestral reconstruction reveals catalytic inactivation of activation-induced cytidine deaminase concomitant with cold water adaption in the Gadiformes bony fish

BACKGROUND

Antibody affinity maturation in vertebrates requires the enzyme activation-induced cytidine deaminase (AID) which initiates secondary antibody diversification by mutating the immunoglobulin loci. AID-driven antibody diversification is conserved across jawed vertebrates since bony and cartilaginous fish. Two exceptions have recently been reported, the Pipefish and Anglerfish, in which the AID-encoding aicda gene has been lost. Both cases are associated with unusual reproductive behavior, including male pregnancy and sexual parasitism. Several cold water fish in the Atlantic cod (Gadinae) family carry an aicda gene that encodes for a full-length enzyme but lack affinity-matured antibodies and rely on antibodies of broad antigenic specificity. Hence, we examined the functionality of their AID.

RESULTS

By combining genomics, transcriptomics, immune responsiveness, and functional enzymology of AID from 36 extant species, we demonstrate that AID of that Atlantic cod and related fish have extremely lethargic or no catalytic activity. Through ancestral reconstruction and functional enzymology of 71 AID enzymes, we show that this enzymatic inactivation likely took place relatively recently at the emergence of the true cod family (Gadidae) from their ancestral Gadiformes order. We show that this AID inactivation is not only concordant with the previously shown loss of key adaptive immune genes and expansion of innate and cell-based immune genes in the Gadiformes but is further reflected in the genomes of these fish in the form of loss of AID-favored sequence motifs in their immunoglobulin variable region genes.

CONCLUSIONS

Recent demonstrations of the loss of the aicda gene in two fish species challenge the paradigm that AID-driven secondary antibody diversification is absolutely conserved in jawed vertebrates. These species have unusual reproductive behaviors forming an evolutionary pressure for a certain loss of immunity to avoid tissue rejection. We report here an instance of catalytic inactivation and functional loss of AID rather than gene loss in a conventionally reproducing vertebrate. Our data suggest that an expanded innate immunity, in addition to lower pathogenic pressures in a cold environment relieved the pressure to maintain robust secondary antibody diversification. We suggest that in this unique scenario, the AID-mediated collateral genome-wide damage would form an evolutionary pressure to lose AID function.

Resurrecting Enzymes by Ancestral Sequence Reconstruction

Ancestral Sequence Reconstruction (ASR) allows one to infer the sequences of extinct proteins using the phylogeny of extant proteins. It consists of disclosing the evolutionary history-i.e., the phylogeny-of a protein family of interest and then inferring the sequences of its ancestors-i.e., the nodes in the phylogeny. Assisted by gene synthesis, the selected ancestors can be resurrected in the lab and experimentally characterized. The crucial step to succeed with ASR is starting from a reliable phylogeny. At the same time, it is of the utmost importance to have a clear idea on the evolutionary history of the family under study and the events that influenced it. This allows us to implement ASR with well-defined hypotheses and to apply the appropriate experimental methods. In the last years, ASR has become popular to test hypotheses about the origin of functionalities, changes in activities, understanding physicochemical properties of proteins, among others. In this context, the aim of this chapter is to present the ASR approach applied to the reconstruction of enzymes-i.e., proteins with catalytic roles. The spirit of this contribution is to provide a basic, hands-to-work guide for biochemists and biologists who are unfamiliar with molecular phylogenetics.

Ancestral Sequence Reconstruction for Exploring Alkaloid Evolution

The complex and bioactive monoterpene indole alkaloids (MIAs) found in Catharanthus roseus and related species are the products of many millions of years of evolution through mutation and natural selection. Ancestral sequence reconstruction (ASR) is a method that combines phylogenetic analysis and experimental biochemistry to infer details about past events in protein evolution. Here, I propose that ASR could be leveraged to understand how enzymes catalyzing the formation of complex alkaloids arose over evolutionary time. I discuss the steps of ASR, including sequence selection, multiple sequence alignment, tree inference, and the generation and characterization of inferred ancestral enzymes.

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.

Combining Ancestral Reconstruction with Folding-Landscape Simulations to Engineer Heterologous Protein Expression

Obligate symbionts typically exhibit high evolutionary rates. Consequently, their proteins may differ considerably from their modern and ancestral homologs in terms of both sequence and properties, thus providing excellent models to study protein evolution. Also, obligate symbionts are challenging to culture in the lab and proteins from uncultured organisms must be produced in heterologous hosts using recombinant DNA technology. Obligate symbionts thus replicate a fundamental scenario of metagenomics studies aimed at the functional characterization and biotechnological exploitation of proteins from the bacteria in soil. Here, we use the thioredoxin from Candidatus Photodesmus katoptron, an uncultured symbiont of flashlight fish, to explore evolutionary and engineering aspects of protein folding in heterologous hosts. The symbiont protein is a standard thioredoxin in terms of 3D-structure, stability and redox activity. However, its folding outside the original host is severely impaired, as shown by a very slow refolding in vitro and an inefficient expression in E. coli that leads mostly to insoluble protein. By contrast, resurrected Precambrian thioredoxins express efficiently in E. coli, plausibly reflecting an ancient adaptation to unassisted folding. We have used a statistical-mechanical model of the folding landscape to guide back-to-ancestor engineering of the symbiont protein. Remarkably, we find that the efficiency of heterologous expression correlates with the in vitro (i.e., unassisted) folding rate and that the ancestral expression efficiency can be achieved with only 1-2 back-to-ancestor replacements. These results demonstrate a minimal-perturbation, sequence-engineering approach to rescue inefficient heterologous expression which may potentially be useful in metagenomics efforts targeting recent adaptations.

Adaptive Evolution in TRIF Leads to Discordance between Human and Mouse Innate Immune Signaling

The TIR domain-containing adapter inducing IFN-β (TRIF) protein is an innate immune system protein that mediates the MyD88-independent toll-like receptor response pathway in mice and humans. Previously, we identified positive selection at seven distinct residues in mouse TRIF (mTRIF), as compared with human and other mammalian orthologs, thus predicting protein functional shift in mTRIF. We reconstructed TRIF for the most recent common ancestor of mouse and human, and mutated this at the seven sites to their extant mouse/human states. We overexpressed these TRIF mutants in immortalized human and mouse cell lines and monitored TRIF-dependent cytokine production and gene expression induction. We show that optimal TRIF function in human and mouse is dependent on the identity of the positively selected sites. These data provide us with molecular data relating observed differences in response between mouse and human MyD88-independent signaling in the innate immune system with protein functional change.

Phylogenetic articulation of uric acid evolution in mammals and how it informs a therapeutic uricase

The role of uric acid during primate evolution has remained elusive ever since it was discovered over 100 years ago that humans have unusually high levels of the small molecule in our serum. It has been difficult to generate a neutral or adaptive explanation in part because the uricase enzyme evolved to become a pseudogene in apes thus masking typical signals of sequence evolution. Adding to the difficulty is a lack of clarity on the functional role of uric acid in apes. One popular hypothesis proposes that uric acid is a potent antioxidant that increased in concentration to compensate for the lack of vitamin C synthesis in primate species ∼65 million years ago (Mya). Here, we have expanded on our previous work with resurrected ancient uricase proteins to better resolve the reshaping of uricase enzymatic activity prior to ape evolution. Our results suggest that the pivotal death-knell to uricase activity occurred between 20-30 Mya despite small sequential modifications to its catalytic efficiency for the tens of millions of years since primates lost their ability to synthesize vitamin C, and thus the two appear uncorrelated. We also use this opportunity to demonstrate how molecular evolution can contribute to biomedicine by presenting ancient uricases to human immune cells that assay for innate reactivity against foreign antigens. A highly stable and highly catalytic ancient uricase is shown to elicit a lower immune response in more human haplotypes than other uricases currently in therapeutic development.

Molecular reconstruction of recurrent evolutionary switching in olfactory receptor specificity

Olfactory receptor repertoires exhibit remarkable functional diversity, but how these proteins have evolved is poorly understood. Through analysis of extant and ancestrally reconstructed drosophilid olfactory receptors from the Ionotropic receptor (Ir) family, we investigated evolution of two organic acid-sensing receptors, Ir75a and Ir75b. Despite their low amino acid identity, we identify a common ‘hotspot’ in their ligand-binding pocket that has a major effect on changing the specificity of both Irs, as well as at least two distinct functional transitions in Ir75a during evolution. Moreover, we show that odor specificity is refined by changes in additional, receptor-specific sites, including those outside the ligand-binding pocket. Our work reveals how a core, common determinant of ligand-tuning acts within epistatic and allosteric networks of substitutions to lead to functional evolution of olfactory receptors.

Exploiting enzyme evolution for computational protein design

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies.

Identification of coagulation factor IX variants with enhanced activity through ancestral sequence reconstruction

Orthologous proteins contain sequence disparity guided by natural selection. In certain cases, species-specific protein functionality predicts pharmacological enhancement, such as greater specific activity or stability. However, immunological barriers generally preclude use of nonhuman proteins as therapeutics, and difficulty exists in the identification of individual sequence determinants among the overall sequence disparity. Ancestral sequence reconstruction (ASR) represents a platform for the prediction and resurrection of ancient gene and protein sequences. Recently, we demonstrated that ASR can be used as a platform to facilitate the identification of therapeutic protein variants with enhanced properties. Specifically, we identified coagulation factor VIII (FVIII) variants with improved specific activity, biosynthesis, stability, and resistance to anti-human FVIII antibody-based inhibition. In the current study, we resurrected a panel of ancient mammalian coagulation factor IX (FIX) variants with the goal of identifying improved pharmaceutical candidates. One variant (An96) demonstrated 12-fold greater FIX activity production than human FIX. Addition of the R338L Padua substitution further increased An96 activity, suggesting independent but additive mechanisms. after adeno-associated virus 2 (AAV2)/8-FIX gene therapy, 10-fold greater plasma FIX activity was observed in hemophilia B mice administered AAV2/8-An96-Padua as compared with AAV2/8-human FIX-Padua. Furthermore, phenotypic correction conferred by the ancestral variant was confirmed using a saphenous vein bleeding challenge and thromboelastography. Collectively, these findings validate the ASR drug discovery platform as well as identify an ancient FIX candidate for pharmaceutical development.

Two NLR immune receptors acquired high-affinity binding to a fungal effector through convergent evolution of their integrated domain

A subset of plant NLR immune receptors carry unconventional integrated domains in addition to their canonical domain architecture. One example is rice Pik-1 that comprises an integrated heavy metal-associated (HMA) domain. Here, we reconstructed the evolutionary history of Pik-1 and its NLR partner, Pik-2, and tested hypotheses about adaptive evolution of the HMA domain. Phylogenetic analyses revealed that the HMA domain integrated into Pik-1 before Oryzinae speciation over 15 million years ago and has been under diversifying selection. Ancestral sequence reconstruction coupled with functional studies showed that two Pik-1 allelic variants independently evolved from a weakly binding ancestral state to high-affinity binding of the blast fungus effector AVR-PikD. We conclude that for most of its evolutionary history the Pik-1 HMA domain did not sense AVR-PikD, and that different Pik-1 receptors have recently evolved through distinct biochemical paths to produce similar phenotypic outcomes. These findings highlight the dynamic nature of the evolutionary mechanisms underpinning NLR adaptation to plant pathogens.

Two NLR immune receptors acquired high-affinity binding to a fungal effector through convergent evolution of their integrated domain

A subset of plant NLR immune receptors carry unconventional integrated domains in addition to their canonical domain architecture. One example is rice Pik-1 that comprises an integrated heavy metal-associated (HMA) domain. Here, we reconstructed the evolutionary history of Pik-1 and its NLR partner, Pik-2, and tested hypotheses about adaptive evolution of the HMA domain. Phylogenetic analyses revealed that the HMA domain integrated into Pik-1 before Oryzinae speciation over 15 million years ago and has been under diversifying selection. Ancestral sequence reconstruction coupled with functional studies showed that two Pik-1 allelic variants independently evolved from a weakly binding ancestral state to high-affinity binding of the blast fungus effector AVR-PikD. We conclude that for most of its evolutionary history the Pik-1 HMA domain did not sense AVR-PikD, and that different Pik-1 receptors have recently evolved through distinct biochemical paths to produce similar phenotypic outcomes. These findings highlight the dynamic nature of the evolutionary mechanisms underpinning NLR adaptation to plant pathogens.

The Molecular Determinants of Thermoadaptation: Methanococcales as a Case Study

Previous reports have shown that environmental temperature impacts proteome evolution in Bacteria and Archaea. However, it is unknown whether thermoadaptation mainly occurs via the sequential accumulation of substitutions, massive horizontal gene transfers, or both. Measuring the real contribution of amino acid substitution to thermoadaptation is challenging, because of confounding environmental and genetic factors (e.g., pH, salinity, genomic G + C content) that also affect proteome evolution. Here, using Methanococcales, a major archaeal lineage, as a study model, we show that optimal growth temperature is the major factor affecting variations in amino acid frequencies of proteomes. By combining phylogenomic and ancestral sequence reconstruction approaches, we disclose a sequential substitutional scheme in which lysine plays a central role by fine tuning the pool of arginine, serine, threonine, glutamine, and asparagine, whose frequencies are strongly correlated with optimal growth temperature. Finally, we show that colonization to new thermal niches is not associated with high amounts of horizontal gene transfers. Altogether, although the acquisition of a few key proteins through horizontal gene transfer may have favored thermoadaptation in Methanococcales, our findings support sequential amino acid substitutions as the main factor driving thermoadaptation.

Revenant: a database of resurrected proteins

Revenant is a database of resurrected proteins coming from extinct organisms. Currently, it contains a manually curated collection of 84 resurrected proteins derived from bibliographic data. Each protein is extensively annotated, including structural, biochemical and biophysical information. Revenant contains a browse capability designed as a timeline from where the different proteins can be accessed. The oldest Revenant entries are between 4200 and 3500 million years ago, while the younger entries are between 8.8 and 6.3 million years ago. These proteins have been resurrected using computational tools called ancestral sequence reconstruction techniques combined with wet-laboratory synthesis and expression. Resurrected proteins are commonly used, with a noticeable increase during the past years, to explore and test different evolutionary hypotheses such as protein stability, to explore the origin of new functions, to get biochemical insights into past metabolisms and to explore specificity and promiscuous behaviour of ancient proteins.

Evolution of bacterial steroid biosynthesis and its impact on eukaryogenesis

Steroids are one of three major lipid components of the eukaryotic cellular membrane, along with glycerophospolipids and sphingolipids. Steroids have critical roles in eukaryotic endocytosis and thus may have been structural prerequisites for the endocytic acquisition of mitochondria during eukaryogenesis. The evolutionary history of the eukaryotic cellular membrane is poorly understood and, as such, has limited our understanding of eukaryogenesis. We address the evolution of steroid biosynthesis by combining ancestral sequence reconstruction and phylogenetic analyses of steroid biosynthesis genes. Our results indicate that steroid biosynthesis evolved within bacteria in response to the rise of oxygen and was later horizontally transferred to eukaryotes. Membrane properties of early eukaryotes are inferred to have been different than that of modern eukaryotes.

Steroids are components of the eukaryotic cellular membrane and have indispensable roles in the process of eukaryotic endocytosis by regulating membrane fluidity and permeability. In particular, steroids may have been a structural prerequisite for the acquisition of mitochondria via endocytosis during eukaryogenesis. While eukaryotes are inferred to have evolved from an archaeal lineage, there is little similarity between the eukaryotic and archaeal cellular membranes. As such, the evolution of eukaryotic cellular membranes has limited our understanding of eukaryogenesis. Despite evolving from archaea, the eukaryotic cellular membrane is essentially a fatty acid bacterial-type membrane, which implies a substantial bacterial contribution to the evolution of the eukaryotic cellular membrane. Here, we address the evolution of steroid biosynthesis in eukaryotes by combining ancestral sequence reconstruction and comprehensive phylogenetic analyses of steroid biosynthesis genes. Contrary to the traditional assumption that eukaryotic steroid biosynthesis evolved within eukaryotes, most steroid biosynthesis genes are inferred to be derived from bacteria. In particular, aerobic deltaproteobacteria (myxobacteria) seem to have mediated the transfer of key genes for steroid biosynthesis to eukaryotes. Analyses of resurrected steroid biosynthesis enzymes suggest that the steroid biosynthesis pathway in early eukaryotes may have been similar to the pathway seen in modern plants and algae. These resurrected proteins also experimentally demonstrate that molecular oxygen was required to establish the modern eukaryotic cellular membrane during eukaryogenesis. Our study provides unique insight into relationships between early eukaryotes and other bacteria in addition to the well-known endosymbiosis with alphaproteobacteria.

Alignment-Integrated Reconstruction of Ancestral Sequences Improves Accuracy

Ancestral sequence reconstruction (ASR) uses an alignment of extant protein sequences, a phylogeny describing the history of the protein family and a model of the molecular-evolutionary process to infer the sequences of ancient proteins, allowing researchers to directly investigate the impact of sequence evolution on protein structure and function. Like all statistical inferences, ASR can be sensitive to violations of its underlying assumptions. Previous studies have shown that, whereas phylogenetic uncertainty has only a very weak impact on ASR accuracy, uncertainty in the protein sequence alignment can more strongly affect inferred ancestral sequences. Here, we show that errors in sequence alignment can produce errors in ASR across a range of realistic and simplified evolutionary scenarios. Importantly, sequence reconstruction errors can lead to errors in estimates of structural and functional properties of ancestral proteins, potentially undermining the reliability of analyses relying on ASR. We introduce an alignment-integrated ASR approach that combines information from many different sequence alignments. We show that integrating alignment uncertainty improves ASR accuracy and the accuracy of downstream structural and functional inferences, often performing as well as highly accurate structure-guided alignment. Given the growing evidence that sequence alignment errors can impact the reliability of ASR studies, we recommend that future studies incorporate approaches to mitigate the impact of alignment uncertainty. Probabilistic modeling of insertion and deletion events has the potential to radically improve ASR accuracy when the model reflects the true underlying evolutionary history, but further studies are required to thoroughly evaluate the reliability of these approaches under realistic conditions.

Reenacting the Birth of a Function: Functional Divergence of HIUases and Transthyretins as Inferred by Evolutionary and Biophysical Studies

Transthyretin was discovered in the 1940s, named after its ability to bind thyroid hormones and retinol. In the genomic era, transthyretins were found to be part of a larger family with homologs of no obvious function, then called transthyretin-related proteins. Thus, it was proposed that the transthyretin gene could be the result of gene duplication of an ancestral of this newly identified homolog, later found out to be an enzyme involved in uric acid degradation, then named HIUase (5-hydroxy-isourate hydrolase). Here, we sought to re-enact the evolutionary history of this protein family by reconstructing, from a phylogeny inferred from 123 vertebrate sequences, three ancestors corresponding to key moments in their evolution-before duplication; the common transthyretin ancestor after gene duplication and the common ancestor of Eutheria transthyretins. Experimental and computational characterization showed the reconstructed ancestor before duplication was unable to bind thyroxine and likely presented the modern HIUase reaction mechanism, while the substitutions after duplication prevented that activity and were enough to provide stable thyroxine binding, as confirmed by calorimetry and x-ray diffraction. The Eutheria transthyretin ancestor was less prone to characterization, but limited data suggested thyroxine binding as expected. Sequence/structure analysis suggests an early ability to bind the Retinol Binding Protein. We solved the X-ray structures from the two first ancestors, the first at 1.46 resolution, the second at 1.55 resolution with well-defined electron density for thyroxine, providing a useful tool for the understanding of structural adaptation from enzyme to hormone distributor.

De novo proteins from random sequences through in vitro evolution

Natural proteins are the result of billions of years of evolution. The earliest predecessors of today's proteins are believed to have emerged from random polypeptides. While we have no means to determine how this process exactly happened, there is great interest in understanding how it reasonably could have happened. We are reviewing how researchers have utilized in vitro selection and molecular evolution methods to investigate plausible scenarios for the emergence of early functional proteins. The studies range from analyzing general properties and structural features of unevolved random polypeptides to isolating de novo proteins with specific functions from synthetic randomized sequence libraries or generating novel proteins by combining evolution with rational design. While the results are exciting, more work is needed to fully unravel the mechanisms that seeded protein-dominated biology.

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.

Heme-binding enables allosteric modulation in an ancient TIM-barrel glycosidase

Glycosidases are phylogenetically widely distributed enzymes that are crucial for the cleavage of glycosidic bonds. Here, we present the exceptional properties of a putative ancestor of bacterial and eukaryotic family-1 glycosidases. The ancestral protein shares the TIM-barrel fold with its modern descendants but displays large regions with greatly enhanced conformational flexibility. Yet, the barrel core remains comparatively rigid and the ancestral glycosidase activity is stable, with an optimum temperature within the experimental range for thermophilic family-1 glycosidases. None of the ∼5500 reported crystallographic structures of ∼1400 modern glycosidases show a bound porphyrin. Remarkably, the ancestral glycosidase binds heme tightly and stoichiometrically at a well-defined buried site. Heme binding rigidifies this TIM-barrel and allosterically enhances catalysis. Our work demonstrates the capability of ancestral protein reconstructions to reveal valuable but unexpected biomolecular features when sampling distant sequence space. The potential of the ancestral glycosidase as a scaffold for custom catalysis and biosensor engineering is discussed.

Family 1 glycosidases (GH1) are present in the three domains of life and share classical TIM-barrel fold. Structural and biochemical analyses of a resurrected ancestral GH1 enzyme reveal heme binding, not known in its modern descendants. Heme rigidifies the TIM-barrel and allosterically enhances catalysis.

Using in silico predicted ancestral genomes to improve the efficiency of paleogenome reconstruction

Paleogenomics is the nascent discipline concerned with sequencing and analysis of genome-scale information from historic, ancient, and even extinct samples. While once inconceivable due to the challenges of DNA damage, contamination, and the technical limitations of PCR-based Sanger sequencing, following the dawn of the second-generation sequencing revolution, it has rapidly become a reality. However, a significant challenge facing ancient DNA studies on extinct species is the lack of closely related reference genomes against which to map the sequencing reads from ancient samples. Although bioinformatic efforts to improve the assemblies have focused mainly in mapping algorithms, in this article we explore the potential of an alternative approach, namely using reconstructed ancestral genome as reference for mapping DNA sequences of ancient samples. Specifically, we present a preliminary proof of concept for a general framework and demonstrate how under certain evolutionary divergence thresholds, considerable mapping improvements can be easily obtained.

Non-conservation of folding rates in the thioredoxin family reveals degradation of ancestral unassisted-folding

Evolution involves not only adaptation, but also the degradation of superfluous features. Many examples of degradation at the morphological level are known (vestigial organs, for instance). However, the impact of degradation on molecular evolution has been rarely addressed. Thioredoxins serve as general oxidoreductases in all cells. Here, we report extensive mutational analyses on the folding of modern and resurrected ancestral bacterial thioredoxins. Contrary to claims from recent literature, in vitro folding rates in the thioredoxin family are not evolutionarily conserved, but span at least a ∼100-fold range. Furthermore, modern thioredoxin folding is often substantially slower than ancestral thioredoxin folding. Unassisted folding, as probed in vitro, thus emerges as an ancestral vestigial feature that underwent degradation, plausibly upon the evolutionary emergence of efficient cellular folding assistance. More generally, our results provide evidence that degradation of ancestral features shapes, not only morphological evolution, but also the evolution of individual proteins.

Ancestral sequence reconstruction: accounting for structural information by averaging over replacement matrices

MOTIVATION

Ancestral sequence reconstruction (ASR) is widely used to understand protein evolution, structure and function. Current ASR methodologies do not fully consider differences in evolutionary constraints among positions imposed by the three-dimensional (3D) structure of the protein. Here, we developed an ASR algorithm that allows different protein sites to evolve according to different mixtures of replacement matrices. We show that assigning replacement matrices to protein positions based on their solvent accessibility leads to ASR with higher log-likelihoods compared to naïve models that assume a single replacement matrix for all sites. Improved ASR log-likelihoods are also demonstrated when solvent accessibility is predicted from protein sequences rather than inferred from a known 3D structure. Finally, we show that using such structure-aware mixture models results in substantial differences in the inferred ancestral sequences.

AVAILABILITY AND IMPLEMENTATION

http://fastml.tau.ac.il.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Deep Residual Neural Networks Resolve Quartet Molecular Phylogenies

Phylogenetic inference is of fundamental importance to evolutionary as well as other fields of biology, and molecular sequences have emerged as the primary data for this task. Although many phylogenetic methods have been developed to explicitly take into account substitution models of sequence evolution, such methods could fail due to model misspecification or insufficiency, especially in the face of heterogeneities in substitution processes across sites and among lineages. In this study, we propose to infer topologies of four-taxon trees using deep residual neural networks, a machine learning approach needing no explicit modeling of the subject system and having a record of success in solving complex nonlinear inference problems. We train residual networks on simulated protein sequence data with extensive amino acid substitution heterogeneities. We show that the well-trained residual network predictors can outperform existing state-of-the-art inference methods such as the maximum likelihood method on diverse simulated test data, especially under extensive substitution heterogeneities. Reassuringly, residual network predictors generally agree with existing methods in the trees inferred from real phylogenetic data with known or widely believed topologies. Furthermore, when combined with the quartet puzzling algorithm, residual network predictors can be used to reconstruct trees with more than four taxa. We conclude that deep learning represents a powerful new approach to phylogenetic reconstruction, especially when sequences evolve via heterogeneous substitution processes. We present our best trained predictor in a freely available program named Phylogenetics by Deep Learning (PhyDL, https://gitlab.com/ztzou/phydl; last accessed January 3, 2020).

Highly thermostable carboxylic acid reductases generated by ancestral sequence reconstruction

Carboxylic acid reductases (CARs) are biocatalysts of industrial importance. Their properties, especially their poor stability, render them sub-optimal for use in a bioindustrial pipeline. Here, we employed ancestral sequence reconstruction (ASR) - a burgeoning engineering tool that can identify stabilizing but enzymatically neutral mutations throughout a protein. We used a three-algorithm approach to reconstruct functional ancestors of the Mycobacterial and Nocardial CAR1 orthologues. Ancestral CARs (AncCARs) were confirmed to be CAR enzymes with a preference for aromatic carboxylic acids. Ancestors also showed varied tolerances to solvents, pH and in vivo-like salt concentrations. Compared to well-studied extant CARs, AncCARs had a Tm up to 35 °C higher, with half-lives up to nine times longer than the greatest previously observed. Using ancestral reconstruction we have expanded the existing CAR toolbox with three new thermostable CAR enzymes, providing access to the high temperature biosynthesis of aldehydes to drive new applications in biocatalysis.

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.

A functional genetic screen reveals sequence preferences within a key tertiary interaction in cobalamin riboswitches required for ligand selectivity

Riboswitches are structured mRNA sequences that regulate gene expression by directly binding intracellular metabolites. Generating the appropriate regulatory response requires the RNA rapidly and stably acquire higher-order structure to form the binding pocket, bind the appropriate effector molecule and undergo a structural transition to inform the expression machinery. These requirements place riboswitches under strong kinetic constraints, likely restricting the sequence space accessible by recurrent structural modules such as the kink turn and the T-loop. Class-II cobalamin riboswitches contain two T-loop modules: one directing global folding of the RNA and another buttressing the ligand binding pocket. While the T-loop module directing folding is highly conserved, the T-loop associated with binding is substantially less so, with no clear consensus sequence. To further understand the functional role of the binding-associated module, a functional genetic screen of a library of riboswitches with the T-loop and its interacting nucleotides was used to build an experimental phylogeny comprised of sequences that possess a wide range of cobalamin-dependent regulatory activity. Our results reveal conservation patterns of the T-loop and its interaction with the binding core that allow for rapid tertiary structure formation and demonstrate its importance for generating strong ligand-dependent repression of mRNA expression.

Ancestral Function and Diversification of a Horizontally Acquired Oomycete Carboxylic Acid Transporter

Horizontal gene transfer (HGT) can equip organisms with novel genes, expanding the repertoire of genetic material available for evolutionary innovation and allowing recipient lineages to colonize new environments. However, few studies have characterized the functions of HGT genes experimentally or examined postacquisition functional divergence. Here, we report the use of ancestral sequence reconstruction and heterologous expression in Saccharomyces cerevisiae to examine the evolutionary history of an oomycete transporter gene family that was horizontally acquired from fungi. We demonstrate that the inferred ancestral oomycete HGT transporter proteins and their extant descendants transport dicarboxylic acids which are intermediates of the tricarboxylic acid cycle. The substrate specificity profile of the most ancestral protein has largely been retained throughout the radiation of oomycetes, including in both plant and animal pathogens and in a free-living saprotroph, indicating that the ancestral HGT transporter function has been maintained by selection across a range of different lifestyles. No evidence of neofunctionalization in terms of substrate specificity was detected for different HGT transporter paralogues which have different patterns of temporal expression. However, a striking expansion of substrate range was observed for one plant pathogenic oomycete, with a HGT derived paralogue from Pythium aphanidermatum encoding a protein that enables tricarboxylic acid uptake in addition to dicarboxylic acid uptake. This demonstrates that HGT acquisitions can provide functional additions to the recipient proteome as well as the foundation material for the evolution of expanded protein functions.

Alignment Modulates Ancestral Sequence Reconstruction Accuracy

Accurate reconstruction of ancestral states is a critical evolutionary analysis when studying ancient proteins and comparing biochemical properties between parental or extinct species and their extant relatives. It relies on multiple sequence alignment (MSA) which may introduce biases, and it remains unknown how MSA methodological approaches impact ancestral sequence reconstruction (ASR). Here, we investigate how MSA methodology modulates ASR using a simulation study of various evolutionary scenarios. We evaluate the accuracy of ancestral protein sequence reconstruction for simulated data and compare reconstruction outcomes using different alignment methods. Our results reveal biases introduced not only by aligner algorithms and assumptions, but also tree topology and the rate of insertions and deletions. Under many conditions we find no substantial differences between the MSAs. However, increasing the difficulty for the aligners can significantly impact ASR. The MAFFT consistency aligners and PRANK variants exhibit the best performance, whereas FSA displays limited performance. We also discover a bias towards reconstructed sequences longer than the true ancestors, deriving from a preference for inferring insertions, in almost all MSA methodological approaches. In addition, we find measures of MSA quality generally correlate highly with reconstruction accuracy. Thus, we show MSA methodological differences can affect the quality of reconstructions and propose MSA methods should be selected with care to accurately determine ancestral states with confidence.

Following the Evolutionary Track of a Highly Specific l-Arginine Oxidase by Reconstruction and Biochemical Analysis of Ancestral and Native Enzymes

Following the evolutionary track of enzymes can help elucidate how enzymes attain their characteristic functions, such as thermal adaptation and substrate selectivity, during the evolutionary process. Ancestral sequence reconstruction (ASR) is effective for following evolutionary processes if sufficient sequence data are available. Selecting sequences from the data to generate a curated sequence library is necessary for the successful design of artificial proteins by ASR. In this study, we tried to follow the evolutionary track of l-arginine oxidase (AROD), a flavin adenine dinucleotide (FAD)-dependent amino acid oxidase (LAAO) that exhibits high specificity for l-arginine. The library was generated by selecting sequences in which the 15th, 50th, 332nd, and 580th residues are Gly, Ser, Trp, and Thr, respectively. We excluded sequences that are either extremely short or long and those with a low degree of sequence identity. Three ancestral ARODs (AncARODn0, AncARODn1, and AncARODn2) were designed using the library. Subsequently, we expressed the ancestral ARODs as well as native Oceanobacter kriegii AROD (OkAROD) in bacteria. AncARODn0 is phylogenetically most remote from OkAROD, whereas AncARODn2 is most similar to OkAROD. Thermal stability was gradually increased by extending AROD sequences back to the progenitor, while the temperature at which the residual activity is half of the maximum measured activity (T _1/2) of AncARODn0 was >20°C higher than that of OkAROD. Remarkably, only AncARODn0 exhibited broad substrate selectivity similar to that of conventional promiscuous LAAO. Taken together, our findings led us to infer that AROD may have evolved from a highly thermostable and promiscuous LAAO.IMPORTANCE In this study, we attempted to infer the molecular evolution of a recently isolated FAD-dependent l-arginine oxidase (AROD) that oxidizes l-arginine to 2-ketoarginine. Utilizing 10 candidate AROD sequences, we obtained a total of three ancestral ARODs. In addition, one native AROD was obtained by cloning one of the candidate ARODs. The candidate sequences were selected utilizing a curation method defined in this study. All the ARODs were successfully expressed in Escherichia coli for analysis of their biochemical functions. The catalytic activity of our bacterially expressed ancestral ARODs suggests that our ASR was successful. The ancestral AROD that is phylogenetically most remote from a native AROD has the highest thermal stability and substrate promiscuity. Our findings led us to infer that AROD evolved from a highly thermostable and promiscuous LAAO. As an application, we can design artificial ARODs with improved functions compared with those of native ones.

The evolution of gene regulatory networks controlling Arabidopsis thaliana L. trichome development

BACKGROUND

The variation in structure and function of gene regulatory networks (GRNs) participating in organisms development is a key for understanding species-specific evolutionary strategies. Even the tiniest modification of developmental GRN might result in a substantial change of a complex morphogenetic pattern. Great variety of trichomes and their accessibility makes them a useful model for studying the molecular processes of cell fate determination, cell cycle control and cellular morphogenesis. Nowadays, a large number of genes regulating the morphogenesis of A. thaliana trichomes are described. Here we aimed at a study the evolution of the GRN defining the trichome formation, and evaluation its importance in other developmental processes.

RESULTS

In study of the evolution of trichomes formation GRN we combined classical phylogenetic analysis with information on the GRN topology and composition in major plants taxa. This approach allowed us to estimate both times of evolutionary emergence of the GRN components which are mainly proteins, and the relative rate of their molecular evolution. Various simplifications of protein structure (based on the position of amino acid residues in protein globula, secondary structure type, and structural disorder) allowed us to demonstrate the evolutionary associations between changes in protein globules and speciations/duplications events. We discussed their potential involvement in protein-protein interactions and GRN function.

CONCLUSIONS

We hypothesize that the divergence and/or the specialization of the trichome-forming GRN is linked to the emergence of plant taxa. Information about the structural targets of the protein evolution in the GRN may predict switching points in gene networks functioning in course of evolution. We also propose a list of candidate genes responsible for the development of trichomes in a wide range of plant species.

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.

Whole genome engineering by synthesis

Whole genome engineering is now feasible with the aid of genome editing and synthesis tools. Synthesizing a genome from scratch allows modifications of the genomic structure and function to an extent that was hitherto not possible, which will finally lead to new insights into the basic principles of life and enable valuable applications. With several recent genome synthesis projects as examples, the technical details to synthesize a genome and applications of synthetic genome are addressed in this perspective. A series of ongoing or future synthetic genomics projects, including the different genomes to be synthesized in GP-write, synthetic minimal genome, massively recoded genome, chimeric genome and synthetic genome with expanded genetic alphabet, are also discussed here with a special focus on theoretical and technical impediments in the design and synthesis process. Synthetic genomics will become a commonplace to engineer pathways and genomes according to arbitrary sets of design principles with the development of high-efficient, low-cost genome synthesis and assembly technologies.

Ancient Biomolecules and Evolutionary Inference

Over the past three decades, studies of ancient biomolecules-particularly ancient DNA, proteins, and lipids-have revolutionized our understanding of evolutionary history. Though initially fraught with many challenges, today the field stands on firm foundations. Researchers now successfully retrieve nucleotide and amino acid sequences, as well as lipid signatures, from progressively older samples, originating from geographic areas and depositional environments that, until recently, were regarded as hostile to long-term preservation of biomolecules. Sampling frequencies and the spatial and temporal scope of studies have also increased markedly, and with them the size and quality of the data sets generated. This progress has been made possible by continuous technical innovations in analytical methods, enhanced criteria for the selection of ancient samples, integrated experimental methods, and advanced computational approaches. Here, we discuss the history and current state of ancient biomolecule research, its applications to evolutionary inference, and future directions for this young and exciting field.

Evolution of chalcone isomerase from a noncatalytic ancestor

The emergence of catalysis in a noncatalytic protein scaffold is a rare, unexplored event. Chalcone isomerase (CHI), a key enzyme in plant flavonoid biosynthesis, is presumed to have evolved from a nonenzymatic ancestor related to the widely distributed fatty-acid binding proteins (FAPs) and a plant protein family with no isomerase activity (CHILs). Ancestral inference supported the evolution of CHI from a protein lacking isomerase activity. Further, we identified four alternative founder mutations, i.e., mutations that individually instated activity, including a mutation that is not phylogenetically traceable. Despite strong epistasis in other cases of protein evolution, CHI's laboratory reconstructed mutational trajectory shows weak epistasis. Thus, enantioselective CHI activity could readily emerge despite a catalytically inactive starting point. Accordingly, X-ray crystallography, NMR, and molecular dynamics simulations reveal reshaping of the active site toward a productive substrate-binding mode and repositioning of the catalytic arginine that was inherited from the ancestral fatty-acid binding proteins.