Simple and accurate estimation of ancestral protein sequences

Recent advances in structure-based enzyme engineering for functional reconstruction

Structural information can help engineer enzymes. Usually, specific amino acids in particular regions are targeted for functional reconstruction to enhance the catalytic performance, including activity, stereoselectivity, and thermostability. Appropriate selection of target sites is the key to structure-based design, which requires elucidation of the structure-function relationships. Here, we summarize the mutations of residues in different specific regions, including active center, access tunnels, and flexible loops, on fine-tuning the catalytic performance of enzymes, and discuss the effects of altering the local structural environment on the functions. In addition, we keep up with the recent progress of structure-based approaches for enzyme engineering, aiming to provide some guidance on how to take advantage of the structural information.

Engineering functional thermostable proteins using ancestral sequence reconstruction

Natural proteins are often only slightly more stable in the native state than the denatured state, and an increase in environmental temperature can easily shift the balance towards unfolding. Therefore, the engineering of proteins to improve protein stability is an area of intensive research. Thermostable proteins are required to withstand industrial process conditions, for increased shelf-life of protein therapeutics, for developing robust 'biobricks' for synthetic biology applications, and for research purposes (e.g. structure determination). In addition, thermostability buffers the often destabilizing effects of mutations introduced to improve other properties. Rational design approaches to engineering thermostability require structural information, but even with advanced computational methods, it is challenging to predict or parameterize all the relevant structural factors with sufficient precision to anticipate the results of a given mutation. Directed evolution is an alternative when structures are unavailable but requires extensive screening of mutant libraries. Recently however, bioinspired approaches based on phylogenetic analyses have shown great promise. Leveraging the rapid expansion in sequence data and bioinformatic tools, ancestral sequence reconstruction (ASR) can generate highly stable folds for novel applications in industrial chemistry, medicine, and synthetic biology. This review provides an overview of the factors important for successful inference of thermostable proteins by ASR and what it can reveal about the determinants of stability in proteins.

Mechanochemical Evolution of Disulfide Bonds in Proteins

Disulfide bonds play a pivotal role in the mechanical stability of proteins. Numerous proteins that are known to be exposed to mechanical forces in vivo contain disulfide bonds. The presence of cryptic disulfide bonds in a protein structure may be related to its resistance to an applied mechanical force. Disulfide bonds in proteins tend to be highly conserved but their evolution might be directly related to the evolution of the protein mechanical stability. Hence, tracking the evolution of disulfide bonds in a protein can help to derive crucial stability/function correlations in proteins that are exposed to mechanical forces. Phylogenic analysis and ancestral sequence reconstruction (ASR) allow tracking the evolution of proteins from the past ancestors to our modern days and also establish correlations between proteins from different species. In addition, ASR can be combined with single-molecule force spectroscopy (smFS) to investigate the mechanical properties of proteins including the occurrence and function of disulfide bonds. Here we present a detailed protocol to study the mechanochemical evolution of proteins using a fragment of the giant muscle protein titin as example. The protocol can be easily adapted to AFS studies of any resurrected mechanical force bearing protein of interest.

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.

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.

Ancestral sequence reconstruction - An underused approach to understand the evolution of gene function in plants?

Whilst substantial research effort has been placed on understanding the interactions of plant proteins with their molecular partners, relatively few studies in plants - by contrast to work in other organisms - address how these interactions evolve. It is thought that ancestral proteins were more promiscuous than modern proteins and that specificity often evolved following gene duplication and subsequent functional refining. However, ancestral protein resurrection studies have found that some modern proteins have evolved de novo from ancestors lacking those functions. Intriguingly, the new interactions evolved as a consequence of just a few mutations and, as such, acquisition of new functions appears to be neither difficult nor rare, however, only a few of them are incorporated into biological processes before they are lost to subsequent mutations. Here, we detail the approach of ancestral sequence reconstruction (ASR), providing a primer to reconstruct the sequence of an ancestral gene. We will present case studies from a range of different eukaryotes before discussing the few instances where ancestral reconstructions have been used in plants. As ASR is used to dig into the remote evolutionary past, we will also present some alternative genetic approaches to investigate molecular evolution on shorter timescales. We argue that the study of plant secondary metabolism is particularly well suited for ancestral reconstruction studies. Indeed, its ancient evolutionary roots and highly diverse landscape provide an ideal context in which to address the focal issue around the emergence of evolutionary novelties and how this affects the chemical diversification of plant metabolism.

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.

Evolutionary Modes in Protein Observable Space: The Case of Thioredoxins

In this article, we investigated the structural and dynamical evolutionary behaviour of a set of ten thioredoxin proteins as formed by three extant forms and seven resurrected ones in laboratory. Starting from the crystallographic structures, we performed all-atom molecular dynamics simulations and compare the trajectories in terms of structural and dynamical properties. Interestingly, the structural properties related to the protein density (i.e. the number of residues divided by the excluded molecular volume) well describe the protein evolutionary behaviour. Our results also suggest that the changes in sequence as occurred during the evolution have affected the protein essential motions, allowing us to discriminate between ancient and extant proteins in terms of their dynamical behaviour. Such results are yet more evident when the bacterial, archaeal and eukaryotic thioredoxins are separately analysed.

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.

ADP-Dependent Kinases From the Archaeal Order Methanosarcinales Adapt to Salt by a Non-canonical Evolutionarily Conserved Strategy

Halophilic organisms inhabit hypersaline environments where the extreme ionic conditions and osmotic pressure have driven the evolution of molecular adaptation mechanisms. Understanding such mechanisms is limited by the common difficulties encountered in cultivating such organisms. Within the Euryarchaeota, for example, only the Halobacteria and the order Methanosarcinales include readily cultivable halophilic species. Furthermore, only the former have been extensively studied in terms of their component proteins. Here, in order to redress this imbalance, we investigate the halophilic adaptation of glycolytic enzymes from the ADP-dependent phosphofructokinase/glucokinase family (ADP-PFK/GK) derived from organisms of the order Methanosarcinales. Structural analysis of proteins from non-halophilic and halophilic Methanosarcinales shows an almost identical composition and distribution of amino acids on both the surface and within the core. However, these differ from those observed in Halobacteria or Eukarya. Proteins from Methanosarcinales display a remarkable increase in surface lysine content and have no reduction to the hydrophobic core, contrary to the features ubiquitously observed in Halobacteria and which are thought to be the main features responsible for their halophilic properties. Biochemical characterization of recombinant ADP-PFK/GK from M. evestigatum (halophilic) and M. mazei (non-halophilic) shows the activity of both these extant enzymes to be only moderately inhibited by salt. Nonetheless, its activity over time is notoriously stabilized by salt. Furthermore, glycine betaine has a protective effect against KCl inhibition and enhances the thermal stability of both enzymes. The resurrection of the last common ancestor of ADP-PFK/GK from Methanosarcinales shows that the ancestral enzyme displays an extremely high salt tolerance and thermal stability. Structure determination of the ancestral protein reveals unique traits such as an increase in the Lys and Glu content at the protein surface and yet no reduction to the volume of the hydrophobic core. Our results suggest that the halophilic character is an ancient trait in the evolution of this protein family and that proteins from Methanosarcinales have adapted to highly saline environments by a non-canonical strategy, different from that currently proposed for Halobacteria. These results open up new avenues for the search and development of novel salt tolerant biocatalysts.

Unravelling the Carbohydrate-Binding Preferences of the Carbohydrate-Binding Modules of AMP-Activated Protein Kinase

The β subunit of adenosine monophosphate (AMP)-activated protein kinase (AMPK), which exists as two isoforms (β1 and β2) in humans, has a carbohydrate-binding module (CBM) that interacts with glycogen. Although the β1- and β2-CBMs are structurally similar, with strictly conserved ligand-contact residues, they show different carbohydrate affinities. β2-CBM shows the strongest affinity for both branched and unbranched oligosaccharides and it has recently been shown that a Thr insertion into β2-CBM (Thr101) forms a pocket to accommodate branches. This insertion does not explain why β2-CBM binds all carbohydrates with stronger affinity. Herein, it is shown that residue 134 (Val for β2 and Thr for β1), which does not come into contact with a carbohydrate, appears to account for the affinity difference. Characterisation by NMR spectroscopy, however, suggests that mutant β2-Thr101Δ/Val134Thr differs from that of β1-CBM, and mutant β1-Thr101ins/Thr134Val differs from that of β2-CBM. Furthermore, these mutants are less stable to chemical denaturation, relative to that of wild-type β-CBMs, which confounds the affinity analyses. To support the importance of Thr101 and Val134, the ancestral CBM has been constructed. This CBM retains Thr101 and Val134, which suggests that the extant β1-CBM has a modest loss of function in carbohydrate binding. Because the ancestor bound carbohydrate with equal affinity to that of β2-CBM, it is concluded that residue 134 plays an indirect role in carbohydrate binding.

Reconstructed ancestral enzymes reveal that negative selection drove the evolution of substrate specificity in ADP-dependent kinases

One central goal in molecular evolution is to pinpoint the mechanisms and evolutionary forces that cause an enzyme to change its substrate specificity; however, these processes remain largely unexplored. Using the glycolytic ADP-dependent kinases of archaea, including the orders Thermococcales, Methanosarcinales, and Methanococcales, as a model and employing an approach involving paleoenzymology, evolutionary statistics, and protein structural analysis, we could track changes in substrate specificity during ADP-dependent kinase evolution along with the structural determinants of these changes. To do so, we studied five key resurrected ancestral enzymes as well as their extant counterparts. We found that a major shift in function from a bifunctional ancestor that could phosphorylate either glucose or fructose 6-phosphate (fructose-6-P) as a substrate to a fructose 6-P-specific enzyme was started by a single amino acid substitution resulting in negative selection with a ground-state mode against glucose and a subsequent 1,600-fold change in specificity of the ancestral protein. This change rendered the residual phosphorylation of glucose a promiscuous and physiologically irrelevant activity, highlighting how promiscuity may be an evolutionary vestige of ancestral enzyme activities, which have been eliminated over time. We also could reconstruct the evolutionary history of substrate utilization by using an evolutionary model of discrete binary characters, indicating that substrate uses can be discretely lost or acquired during enzyme evolution. These findings exemplify how negative selection and subtle enzyme changes can lead to major evolutionary shifts in function, which can subsequently generate important adaptive advantages, for example, in improving glycolytic efficiency in Thermococcales.

Mechanochemical evolution of the giant muscle protein titin as inferred from resurrected proteins

The sarcomere-based structure of muscles is conserved among vertebrates; however, vertebrate muscle physiology is extremely diverse. A molecular explanation for this diversity and its evolution has not been proposed. We use phylogenetic analyses and single-molecule force spectroscopy (smFS) to investigate the mechanochemical evolution of titin, a giant protein responsible for the elasticity of muscle filaments. We resurrect eight-domain fragments of titin corresponding to the common ancestors to mammals, sauropsids, and tetrapods, which lived 105-356 Myr ago, and compare them with titin fragments from some of their modern descendants. We demonstrate that the resurrected titin molecules are rich in disulfide bonds and display high mechanical stability. These mechanochemical elements have changed over time, creating a paleomechanical trend that seems to correlate with animal body size, allowing us to estimate the sizes of extinct species. We hypothesize that mechanical adjustments in titin contributed to physiological changes that allowed the muscular development and diversity of modern tetrapods.

A simple, high-throughput modeling approach reveals insights into the mechanism of gametophytic self-incompatibility

Specificity in the GSI response results from the S-haplotype-specific molecular interaction of S-locus F-box (SLF/SFB) and SRNase proteins in the self-incompatibility locus (S-locus). The answer to the question of how these two components of the S-locus (SRNase and SLF/SFB) interact has been gathered from several models. Since there is not enough evidence as to which one is the definitive model, none of them can be ruled out. Despite the identification of interacting protein elements, the mechanism by which SLF/SFB and SRNase interact to differently trigger the self-incompatibility among families and subfamilies remain uncertain. The high-throughput modeling approach demonstrates structural visions into the possible existence of a Collaborative Non-Self Recognition model in apple. These findings postulate several prospects for future investigation providing useful information to guide the implementation of breeding strategies.

Biochemical characterization of predicted Precambrian RuBisCO

The antiquity and global abundance of the enzyme, RuBisCO, attests to the crucial and longstanding role it has played in the biogeochemical cycles of Earth over billions of years. The counterproductive oxygenase activity of RuBisCO has persisted over billions of years of evolution, despite its competition with the carboxylase activity necessary for carbon fixation, yet hypotheses regarding the selective pressures governing RuBisCO evolution have been limited to speculation. Here we report the resurrection and biochemical characterization of ancestral RuBisCOs, dating back to over one billion years ago (Gyr ago). Our findings provide an ancient point of reference revealing divergent evolutionary paths taken by eukaryotic homologues towards improved specificity for CO2, versus the evolutionary emphasis on increased rates of carboxylation observed in bacterial homologues. Consistent with these distinctions, in vivo analysis reveals the propensity of ancestral RuBisCO to be encapsulated into modern-day carboxysomes, bacterial organelles central to the cyanobacterial CO2 concentrating mechanism.

A Comprehensive Study of Molecular Evolution at the Self-Incompatibility Locus of Rosaceae

The family Rosaceae includes a range of important fruit trees, most of which have the S-RNase-based self-incompatibility (SI). Several models have been developed to explain how pollen (SLF) and pistil (S-RNase) components of the S-locus interact. It was discovered in 2010 that additional SLF proteins are involved in pollen specificity, and a Collaborative Non-Self Recognition model has been proposed for SI in Solanaceae; however, the validity of such model remains to be elucidated for other species. The results of this study support the divergent evolution of the S-locus genes from two Rosaceae subfamilies, Prunoideae/Amygdaloideae and Maloideae, The difference identified in the selective pressures between the two lineages provides evidence for positive selection at specific sites in both the S-RNase and the SLF proteins. The evolutionary findings of this study support the role of multiple SLF proteins leading to a Collaborative Non-Self Recognition model for SI in the Maloideae. Furthermore, the identification of the sites responsible for SI specificity determination and the mapping of these sites onto the modelled tertiary structure of ancestor proteins provide useful information for rational functional redesign and protein engineering for the future engineering of new functional alleles providing increased diversity in the SI system in the Maloideae.

Nuclear quantum tunnelling in enzymatic reactions – an enzymologist's perspective

The roles of nuclear quantum tunnelling and dynamics in enzyme reactions are discussed in this perspective on H-transfer reactions.

One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic trees

Bacteria use metallo-β-lactamase enzymes to hydrolyse lactam rings found in many antibiotics, rendering them ineffective. Metallo-β-lactamase activity is thought to be polyphyletic, having arisen on more than one occasion within a single functionally diverse homologous superfamily. Since discovery of multiple origins of enzymatic activity conferring antibiotic resistance has broad implications for the continued clinical use of antibiotics, we test the hypothesis of polyphyly further; if lactamase function has arisen twice independently, the most recent common ancestor (MRCA) is not expected to possess lactam-hydrolysing activity. Two major problems present themselves. Firstly, even with a perfectly known phylogeny, ancestral sequence reconstruction is error prone. Secondly, the phylogeny is not known, and in fact reconstructing a single, unambiguous phylogeny for the superfamily has proven impossible. To obtain a more statistical view of the strength of evidence for or against MRCA lactamase function, we reconstructed a sample of 98 MRCAs of the metallo-β-lactamases, each based on a different tree in a bootstrap sample of reconstructed phylogenies. InterPro sequence signatures and homology modelling were then used to assess our sample of MRCAs for lactamase functionality. Only 5 % of these models conform to our criteria for metallo-β-lactamase functionality, suggesting that the ancestor was unlikely to have been a metallo-β-lactamase. On the other hand, given that ancestral proteins may have had metallo-β-lactamase functionality with variation in sequence and structural properties compared with extant enzymes, our criteria are conservative, estimating a lower bound of evidence for metallo-β-lactamase functionality but not an upper bound.

Emergence of pyridoxal phosphorylation through a promiscuous ancestor during the evolution of hydroxymethyl pyrimidine kinases

In the family of ATP-dependent vitamin kinases, several bifunctional enzymes that phosphorylate hydroxymethyl pyrimidine (HMP) and pyridoxal (PL) have been described besides enzymes specific towards HMP. To determine how bifunctionality emerged, we reconstructed the sequence of three ancestors of HMP kinases, experimentally resurrected, and assayed the enzymatic activity of their last common ancestor. The latter has ∼ 8-fold higher specificity for HMP due to a glutamine residue (Gln44) that is a key determinant of the specificity towards HMP, although it is capable of phosphorylating both substrates. These results show how a specific enzyme with catalytic promiscuity gave rise to current bifunctional enzymes.

Computational tools for the synthetic design of biochemical pathways

As the field of synthetic biology is developing, the prospects for de novo design of biosynthetic pathways are becoming more and more realistic. Hence, there is an increasing need for computational tools that can support these efforts. A range of algorithms has been developed that can be used to identify all possible metabolic pathways and their corresponding enzymatic parts. These can then be ranked according to various properties and modelled in an organism-specific context. Finally, design software can aid the biologist in the integration of a selected pathway into smartly regulated transcriptional units. Here, we review key existing tools and offer suggestions for how informatics can help to shape the future of synthetic microbiology.

Mineralocorticoid receptors: evolutionary and pathophysiological considerations

Mineralocorticoid receptors (MR), glucocorticoid receptors (GR), progesterone receptors (PR), and androgen receptors (AR) comprise a closely related subfamily within the human 49-member nuclear receptor family. These receptors and their cognate ligands play major roles in homeostasis, reproduction, growth, and development, despite which their evolution and diversification remains incompletely understood. Several conflicting models have been advanced for the evolution of this subfamily. We have thus undertaken Bayesian and maximum likelihood phylogenetic analyses of this subfamily. The Bayesian consensus and maximum likelihood trees support a basal position for MR, with the PR and AR forming a sister clade. We next performed analyses using topological constraints to directly contrast the likelihood of seven phylogenetic models. In these analyses, three models have similar support: one proposes two sister clades (MR and GR, PR and AR); the other two propose a different subfamily member (MR or GR) to be the first to have diverged. Ancestral state reconstructions at sites critical for physiological function show that the S810L mutation in the MR, which results in the MR being similar to estrogen receptors and the more distantly related retinoic acid receptor-α is likely to reflect the ancestral receptor sequence before the divergence of this subfamily and provides further support for MR having been the first of the subfamily to diverge. Finally, we drew on pathophysiological comparisons to help to distinguish the different models. On the basis of our phylogenetic analyses and pathophysiological considerations, we propose that the MR was the first to diverge from the ancestral gene lineage from which this subfamily derived.

Single-molecule paleoenzymology probes the chemistry of resurrected enzymes

A journey back in time is possible at the molecular level by reconstructing proteins from extinct organisms. Here we report the reconstruction, based on sequence predicted by phylogenetic analysis, of seven Precambrian thioredoxin enzymes (Trx), dating back between ~1.4 and ~4 billion years (Gyr). The reconstructed enzymes are up to 32° C more stable than modern enzymes and the oldest show significantly higher activity than extant ones at pH 5. We probed their mechanisms of reduction using single-molecule force spectroscopy. From the force-dependency of the rate of reduction of an engineered substrate, we conclude that ancient Trxs utilize chemical mechanisms of reduction similar to those of modern enzymes. While Trx enzymes have maintained their reductase chemistry unchanged, they have adapted over a 4 Gyr time span to the changes in temperature and ocean acidity that characterize the evolution of the global environment from ancient to modern Earth.

Reconstructed ancestral sequences improve pathogen identification using resequencing DNA microarrays

We describe the benefit of using reconstructed ancestral sequences (RAS) on resequencing microarrays for rapid pathogen identification, with Enterobacteriaceae rpoB sequences as a model. Our results demonstrate a sharp improvement of call rate and accuracy when using RASs as compared to extant sequences. This improvement was attributed to the lower sequence divergence of RASs, which also expanded the sequence space covered by the microarray. Extension of this novel microarray design strategy to viruses, antimicrobial resistance elements or toxins is straightforward.

Deep phylogeny--how a tree can help characterize early life on Earth

The Darwinian concept of biological evolution assumes that life on Earth shares a common ancestor. The diversification of this common ancestor through speciation events and vertical transmission of genetic material implies that the classification of life can be illustrated in a tree-like manner, commonly referred to as the Tree of Life. This article describes features of the Tree of Life, such as how the tree has been both pruned and become bushier throughout the past century as our knowledge of biology has expanded. We present current views that the classification of life may be best illustrated as a ring or even a coral with tree-like characteristics. This article also discusses how the organization of the Tree of Life offers clues about ancient life on Earth. In particular, we focus on the environmental conditions and temperature history of Precambrian life and show how chemical, biological, and geological data can converge to better understand this history."You know, a tree is a tree. How many more do you need to look at?"--Ronald Reagan (Governor of California), quoted in the Sacramento Bee, opposing expansion of Redwood National Park, March 3, 1966.

Greedy selection of species for ancestral state reconstruction on phylogenies: elimination is better than insertion

Accurate reconstruction of ancestral character states on a phylogeny is crucial in many genomics studies. We study how to select species to achieve the best reconstruction of ancestral character states on a phylogeny. We first show that the marginal maximum likelihood has the monotonicity property that more taxa give better reconstruction, but the Fitch method does not have it even on an ultrametric phylogeny. We further validate a greedy approach for species selection using simulation. The validation tests indicate that backward greedy selection outperforms forward greedy selection. In addition, by applying our selection strategy, we obtain a set of the ten most informative species for the reconstruction of the genomic sequence of the so-called boreoeutherian ancestor of placental mammals. This study has broad relevance in comparative genomics and paleogenomics since limited research resources do not allow researchers to sequence the large number of descendant species required to reconstruct an ancestral sequence.

The effect of recombination on the reconstruction of ancestral sequences

While a variety of methods exist to reconstruct ancestral sequences, all of them assume that a single phylogeny underlies all the positions in the alignment and therefore that recombination has not taken place. Using computer simulations we show that recombination can severely bias ancestral sequence reconstruction (ASR), and quantify this effect. If recombination is ignored, the ancestral sequences recovered can be quite distinct from the grand most recent common ancestor (GMRCA) of the sample and better resemble the concatenate of partial most recent common ancestors (MRCAs) at each recombination fragment. When independent phylogenetic trees are assumed for the different recombinant segments, the estimation of the fragment MRCAs improves significantly. Importantly, we show that recombination can change the biological predictions derived from ASRs carried out with real data. Given that recombination is widespread on nuclear genes and in particular in RNA viruses and some bacteria, the reconstruction of ancestral sequences in these cases should consider the potential impact of recombination and ideally be carried out using approaches that accommodate recombination.

Comparative and evolutionary genomics of globin genes in fish

Sequencing genomes of model organisms is a great challenge for biological sciences. In the past decade, scientists have developed a large number of methods to align and compare sequenced genomes. The analysis of a given sequence provides much information on the genome structure but to a lesser extent on the function. Comparative genomics are a useful tool for functional and evolutionary annotation of genomes. In principle, comparison of genomic sequences may allow for identification of the evolutionary selection (negative or positive) that the functional sequences have been subjected to over time. Positively selected genome regions are the most important ones for evolution, because most changes are adaptive and often induce biological differences in organisms. The draft genomes of five fish species have recently become available. We herewith review and discuss some new insights into comparative genomics in fish globin genes. Special attention will be given to a complementary methodological approach to comparative genomics, fluorescence in situ hybridization (FISH). Internet resources for analyzing sequence alignments and annotations and new bioinformatic tools to address critical problems are thoroughly discussed.

Bayesian methods for proteomics

Biological and medical data have been growing exponentially over the past several years [1, 2]. In particular, proteomics has seen automation dramatically change the rate at which data are generated [3]. Analysis that systemically incorporates prior information is becoming essential to making inferences about the myriad, complex data [4-6]. A Bayesian approach can help capture such information and incorporate it seamlessly through a rigorous, probabilistic framework. This paper starts with a review of the background mathematics behind the Bayesian methodology: from parameter estimation to Bayesian networks. The article then goes on to discuss how emerging Bayesian approaches have already been successfully applied to research across proteomics, a field for which Bayesian methods are particularly well suited [7-9]. After reviewing the literature on the subject of Bayesian methods in biological contexts, the article discusses some of the recent applications in proteomics and emerging directions in the field.

Measures of clade confidence do not correlate with accuracy of phylogenetic trees

Metrics of phylogenetic tree reliability, such as parametric bootstrap percentages or Bayesian posterior probabilities, represent internal measures of the topological reproducibility of a phylogenetic tree, while the recently introduced aLRT (approximate likelihood ratio test) assesses the likelihood that a branch exists on a maximum-likelihood tree. Although those values are often equated with phylogenetic tree accuracy, they do not necessarily estimate how well a reconstructed phylogeny represents cladistic relationships that actually exist in nature. The authors have therefore attempted to quantify how well bootstrap percentages, posterior probabilities, and aLRT measures reflect the probability that a deduced phylogenetic clade is present in a known phylogeny. The authors simulated the evolution of bacterial genes of varying lengths under biologically realistic conditions, and reconstructed those known phylogenies using both maximum likelihood and Bayesian methods. Then, they measured how frequently clades in the reconstructed trees exhibiting particular bootstrap percentages, aLRT values, or posterior probabilities were found in the true trees. The authors have observed that none of these values correlate with the probability that a given clade is present in the known phylogeny. The major conclusion is that none of the measures provide any information about the likelihood that an individual clade actually exists. It is also found that the mean of all clade support values on a tree closely reflects the average proportion of all clades that have been assigned correctly, and is thus a good representation of the overall accuracy of a phylogenetic tree.

The construction of phylogenetic trees, which depict past relationships between groups of DNA or protein sequences, has valuable application in many fields of study, most commonly evolutionary and population biology. Before drawing conclusions from phylogenetic trees, it is important to assess how accurate those reconstructions are. This is typically accomplished by examining measures of “clade credibility” (such as bootstrap or posterior probability values), which represent how reproducible relationships are within the tree based on the parameters of the phylogenetic analysis. However, such measures do not necessarily reflect how likely inferred relationships are to have actually occurred in nature. Therefore, using simulated data where relationships are known, we have determined how well several measures of clade credibility correlate with the likelihood that a deduced phylogenetic grouping actually exists in reality. Surprisingly, we found no such correlation, and that the inferred relationships were correctly assigned about as often in cases where clade credibility values were very low as where they were high. This finding suggests that current measures of phylogenetic tree reliability are not useful in predicting whether specific inferred relationships have actually occurred.

ProteinParser--a community based tool for the generation of a detailed protein consensus and FASTA output

Comparison of bioinformatic data is a common application in the life sciences and beyond. In this communication, a novel Java based software tool, ProteinParser, is outlined. This software tool calculates a detailed consensus, or most common, amino acid at a given position in an aligned protein set, whilst also generating a full consensus protein FASTA output. A second application of this software tool, computing a consensus amino acid given a tolerance threshold, is also demonstrated. The phytase and the common bacterial beta-lactamase proteins are analysed as 'proof of concept' examples. Consensus proteins, as generated by ProteinParser, are regularly utilised in the selection of residues for protein stabilisation mutagenesis; however, this widely applicable software tool will find many alternative applications in areas such as protein homology modelling.

Exploring genomic dark matter: a critical assessment of the performance of homology search methods on noncoding RNA

Homology search is one of the most ubiquitous bioinformatic tasks, yet it is unknown how effective the currently available tools are for identifying noncoding RNAs (ncRNAs). In this work, we use reliable ncRNA data sets to assess the effectiveness of methods such as BLAST, FASTA, HMMer, and Infernal. Surprisingly, the most popular homology search methods are often the least accurate. As a result, many studies have used inappropriate tools for their analyses. On the basis of our results, we suggest homology search strategies using the currently available tools and some directions for future development.

Assessing the accuracy of ancestral protein reconstruction methods

The phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence, resulting in potentially misleading estimates of the ancestral protein's properties. To assess the accuracy of ancestral protein reconstruction methods, we performed computational population evolution simulations featuring near-neutral evolution under purifying selection, speciation, and divergence using an off-lattice protein model where fitness depends on the ability to be stable in a specified target structure. We were thus able to compare the thermodynamic properties of the true ancestral sequences with the properties of “ancestral sequences” inferred by maximum parsimony, maximum likelihood, and Bayesian methods. Surprisingly, we found that methods such as maximum parsimony and maximum likelihood that reconstruct a “best guess” amino acid at each position overestimate thermostability, while a Bayesian method that sometimes chooses less-probable residues from the posterior probability distribution does not. Maximum likelihood and maximum parsimony apparently tend to eliminate variants at a position that are slightly detrimental to structural stability simply because such detrimental variants are less frequent. Other properties of ancestral proteins might be similarly overestimated. This suggests that ancestral reconstruction studies require greater care to come to credible conclusions regarding functional evolution. Inferred functional patterns that mimic reconstruction bias should be reevaluated.

It is now possible to apply computational methods to known current protein sequences to recreate the sequences of ancestral proteins. By synthesising these proteins and measuring their properties in the laboratory, we can gain much information about the nature of evolution, better understand how proteins change and adapt over time, and develop insights into the environments of ancient organisms. Unfortunately, the accuracy of these reconstructions is difficult to evaluate. We simulate protein evolution using a simplified computational model and apply the various reconstruction methods to the sequences that arise from our simulations. Because we have the complete record of the evolutionary history, we can evaluate the reconstruction accuracy directly. We demonstrate that the reconstruction procedures in common use may have a bias toward overestimating the properties of these ancestral proteins, opposite to what has been assumed previously. An alternative method of creating these sequences is presented, Bayesian sampling, that can eliminate this bias and provide more robust conclusions.