The evolution of proteins is one of the fundamental processes that has delivered the diversity and complexity of life we see around ourselves today. While we tend to define protein evolution in terms of sequence level mutations, insertions and deletions, it is hard to translate these processes to a more complete picture incorporating a polypeptide' s structure and function. By considering how protein structures change over time we can gain an entirely new appreciation of their long-term evolutionary dynamics. In this work we seek to identify how populations of proteins at different stages of evolution explore their possible structure space. We use an annotation of superfamily age to this space and explore the relationship between these ages and a diverse set of properties pertaining to a superfamily' s sequence, structure and function. We note several marked differences between the populations of newly evolved and ancient structures, such as in their length distributions, secondary structure content and tertiary packing arrangements. In particular, many of these differences suggest a less elaborate structure for newly evolved superfamilies when compared with their ancient counterparts. We show that the structural preferences we report are not a residual effect of a more fundamental relationship with function. Furthermore, we demonstrate the robustness of our results, using significant variation in the algorithm used to estimate the ages. We present these age estimates as a useful tool to analyse protein populations. In particularly, we apply this in a comparison of domains containing greek key or jelly roll motifs.
The current wealth of freely available genetic sequences offers the potential to uncover the evolutionary history of genes and their products, proteins. While there exist no remains of primitive proteins, extant protein information can be used to estimate a protein family' s history. This approach is particularly well suited to structural information. Protein structures are far more conserved than their sequences and thus preserve a deep phylogenetic signal [1]. Furthermore, for the majority of globular proteins, a stable three-dimensional structure is thought to be a requirement for many aspects of its function. By maintaining the precise positioning of functional residues while also minimising other undesirable interactions a protein' s structure is intimately linked to the role it plays within the cell [2]. Moreover, phylogenetic trees built using the structural content of species' proteomes have been shown to produce more reliable topologies than trees constructed using their protein sequences [3]. These observations support the use of structure as a fundamental molecular unit when studying the evolution of proteins. Furthermore, they suggest that any conversation on the evolution of proteins must first understand the major driving forces behind such changes from a structural perspective. In order to visualise the landscape and diversity of structure space protein structures have been clustered within a hierarchical taxonomy [4], [5]. The SCOP database is one such manual classification scheme which, at the superfamily level, attempts to cluster together protein domains with a common evolutionary origin, based primarily on strong functional and structural similarity [6]. The superfamily classification lies in between the family level, largely defined by a domain' s amino acid sequence, and the fold, a structural consensus of a domain' s topology. In this work we primarily consider sets of structural domains classified as superfamilies in SCOP 1. 75. Despite the potential for rich diversity within the structural universe it is surprising how sparse this space remains [7]. The current repertoire of proteins with known structure fall into less than 1,200 unique SCOP folds and the majority of these contain only one sequence family [8]. While this is unlikely to represent the true diversity of naturally occurring proteins and current projections for the size of protein fold space range from around 2,000 [9] to over 10,000 [10], it is thought that the vast majority of extant proteins will fall into only around 1,000 common folds [11]. Furthermore, the landscape of this core fold space is highly heterogeneous, with a few so called ‘superfolds’ densely populated by sequence families [12]. The unique composition of this space is a consequence of protein evolution through neutral drift and active selection together with a complex interplay of other factors such as genome structure, mutational mechanisms, function and the need for interactions, all of which close off portions of the configuration space. However, little is known about the exact nature by which the range of protein structures we see today have evolved [2]. One way in which we can seek to explore the forces behind such a history is to consider annotating the protein structure universe with an estimate of its evolutionary age [7], [13], [14]. The age of a population of proteins is the estimated node age of its first ancestor across a phylogeny of completely sequenced genomes. This method has been implemented for both structural superfamilies [13], [15] and sequence families [7], [14], although the latter tend to involve a much reduced phylogenetic tree and evolutionary scale. Methods for predicting the internal node of the ancestor for a given family or superfamily also vary. A maximum parsimony model for superfamily evolution has been largely adopted for this step [13], [15], [16], although alternatives include Dollo parsimony: taking the most recent common ancestor [7], [13]. These parsimony models take as input a phylogenetic species tree and the occurrence profile of each structural superfamily across this set of species. The occurrence profile for a superfamily is simply its presence or absence on each of the genomes [16]. Parsimony attempts to reconstruct the most likely series of gain and loss events at internal nodes of the tree which explain the occurrence profile at its leaves. The likelihood of these events is based on simple assumptions relating to the evolution of protein domains. The principle underlying all types of parsimony is that the scenario of events involving the least evolutionary change is preferred. Gain events can represent de novo superfamily gain, lateral gene transfer of a superfamily between genomes, and a false positive assignment of a superfamily to a genome. Loss events can represent the loss of a superfamily and also false negative assignments to a genome. Maximum parsimony methods allow for a weighting of the likelihood of loss events relative to gain events, while Dollo parsimony considers a gain event to be so rare it is most likely to have occurred only once in the evolution of a superfamily. Since lateral gene transfer is rare between Eukaryotes but may be quite common among Prokaryotes it has been suggested that maximum parsimony is an appropriate model for Prokaryotic genomes while Dollo parsimony should be used for Eukaryotes [16], [17]. Previous studies have shown a significant positive correlation between the age of a domain' s structure and its length [7], [14]. These results remain pronounced over different methods for calculating the age of a superfamily or protein sequence. This seemingly fundamental relationship between the age of a structure and its length has supported the idea that the primitive protein universe was populated mainly by small folds [7]. In fact, the recent success in using structural fragments to predict protein structures (see, for example [18]) has further stimulated debate as to whether the evolutionary origins of the current fold space are in fact short peptide fragments that have combined to form larger folds [19]. It has also been reported that class domains tend to be significantly older than superfamilies belonging to other classes [13]. domains also tend to be significantly longer than other classes but they are also distinguishable in other respects [20]. They are unique among the classes in containing a majority of parallel -strands as opposed to the antiparallel structure which characterise all- and classes. folds also contain a large number of the so-called ‘superfolds’: folds containing large numbers of different superfamilies and a high proportion of all determined structures [12]. Such superfolds include P-loop NTPases, Rossmann folds and TIM barrels [11]. In this work we present phylogenetic profiles and evolutionary ages for superfamilies representing the current known structural universe. We show that these age estimates are largely robust to different evolutionary models, datasets and phylogenetic trees. We compare the structural characteristics of two protein populations: new-borns, with biologically recent structural ancestors, and ancients, with ancestors at the root of the tree of life. Our results identify several characteristics that differ between the two populations. These differences support known relationships, such as the propensity of and longer superfamilies to be ancient, and also postulate several previously unseen characteristics which correlate with age. While these structural relationships are marked we considered the possibility that they were the result of an asymmetry in the functional annotation of fold space. Here we show that our structural partitions result in far more dramatic age differences than functional groupings and as such the relationships between structure and age are not a residual effect of functional preferences.
Superfamily ages are sensitive to the phylogenetic tree of life used, the prediction of superfamilies on genome sequences for the occurrence profiles, and to the parsimony method and parameters used to estimate events. In order to investigate the robustness of our age estimates to these assumptions we undertook our analysis across several phylogenetic trees and multiple parsimony models. We also explored the effect on our results of using different datasets: changing both the occurrence profiles and the set of genomes considered. Representative domains for these superfamilies were taken from the ASTRAL database [22]. A number of different properties pertaining to the sequences, structures and functions of these domains were then used to compare the ancient and new-born populations. The enrichment of disulphide bonds among new-born superfamilies indicated a potential over-representation of cysteine residues among these superfamilies. We investigated whether there were further relationships with other amino acids. Very little is known about the evolution of early life but it is a common theory that the twenty amino acids we see today did not appear simultaneously. It is likely therefore that the earliest peptides consisted of only a subset of these amino acids: the first to evolve. Trifonov suggests a chronological order for the evolution of these amino acids: Gly, Ala, Asp, Val, Pro, Ser, Glu, Leu, Thr, Arg, Ile, Gln, Asn, His, Lys, Cys, Phe, Tyr, Met, Trp [27]. We looked here at the sequence composition of different domains and the propensity for different amino acids for ancient or new-born superfamilies. Since sequence change is rapid compared to structural change it is unlikely that the composition of the earliest peptides could be detected from their extant descendants. However, the propensities calculated here may still hold some signal of preference for certain amino acids. Propensities were calculated for all 20 amino acids across the two age groups and are shown in Table 1. While amino acids predicted by Trifonov to occur early during protein evolution were more likely to be enriched in ancient superfamilies this relationship was by no means strict. Amino acids significantly over-represented in ancient superfamilies are Arg, Gly, and Val, which are hydrophobic, non-polar residues, with the exception of Arg, which is polar and positively charged. Residues over-represented in new-born superfamilies are Asn, Cys, Gln, Ser, Thr, Trp and Tyr. These residues are mostly polar and uncharged. Trp and Tyr also contain large, aromatic side chains. The propensities in new-born superfamilies for polar residues further supports our previous observation that newly evolving structures may have a larger surface area to volume ratio. In this study we have primarily focussed on the structural properties characterising superfamilies rather than on their functional roles. We performed enrichment analysis of GO functions for populations of superfamilies in the different age groups. We compared three different age groups: new-born, ancient and middle-aged superfamilies (those superfamilies in neither the new-born or ancient groups). A list of all terms which were significantly enriched can be found in Table S1. It has been observed in a study of the protein interaction network of yeast that older proteins tend to have more interaction partners than either middle-aged or young proteins [28]. This would appear to indicate that older superfamilies will tend to have more enriched functional terms than younger superfamilies, since partners in the interaction network will tend to share functional annotations. Indeed we find this to be the case. Of 189 GO terms found to be enriched in any one of the three age groups (ancient, middle-aged or new-born), none were enriched in new-born superfamilies, 8 in middle-aged superfamilies and the remaining 181 were enriched in ancient superfamilies. The terms enriched in middle-aged superfamilies refer mostly to the regulation of developmental growth unique to Eukaryotes. The majority of terms enriched in ancient superfamilies correspond to fundamental cellular processes common to the vast majority of the tree of life. Interestingly, while RNA synthesis is enriched in ancient superfamilies, terms relating specifically to DNA synthesis are not. This supports the RNA world hypothesis, that during early evolution genetic material was stored as RNA as opposed to DNA [29]. For full details of the functional terms enriched in our age groups see Table S1. We considered the possibility that the structural biases of ancient and new-born superfamilies we report here might be a residual effect of a more fundamental relationship with function. For example, we observe a strong relationship between ancient superfamilies and parallel strands. But, as mentioned before, folds are often superfolds, and are known to be associated with a large repertoire of fundamental functions. Perhaps it is the enrichment of these functions in the class that drives the preference for ancient superfamilies to have parallel strands. We compared our structural ages (Figure 2c) with ages for populations of superfamilies annotated with functional terms enriched in either parallel or antiparallel superfamilies. In order to do this we constructed lists of parallel/antiparallel functions: GO terms significantly enriched in the subset of parallel/antiparallel superfamilies. We then compared the ages of the superfamilies annotated with these terms. The results of this comparison are shown in Figure S4. We found that the structural partition resulted in a much more dramatic age difference than the functional groupings. In particular, the functional annotations failed to divide the space efficiently, with many superfamilies annotated with both ‘parallel’ terms and ‘antiparallel’ terms. Even when considering superfamilies unique to a directional functional annotation, there was a less marked distinction than seen in superfamilies distinguished by structural features alone. Not only can these ages be related to general properties of proteins but they also provide a framework for examining more specific questions. For example, we present here a case study for analysing the evolutionary dynamics of certain structural motifs common in domains in a number of different folds. As was discussed earlier, antiparallel -sheet structures appear to be significantly younger than parallel sheets. Antiparallel topologies are, however, more common and more varied than parallel motifs. The most common topology in antiparallel sheets is the hairpin meander where neighbouring strands in a sheet are consecutive in the amino acid sequence. Apart from the simple meander the next two most common topological motifs are the greek key and the jelly roll. Around of all- folds in SCOP are annotated as containing either a greek key or a jelly roll and these motifs form a considerable role in their classification. Proteins containing these motifs rarely share either sequence similarity or a common function [30]. The topological architecture of these two common motifs is very similar, with the jelly roll containing a greek key at its core. While some papers treat the jelly roll motif as a special case of the greek key [31], others argue that they occupy a unique portion of fold space [32]. In this study the age distributions of superfamilies classified as containing a greek key or a jelly roll were compared. Greek keys were significantly older than jelly rolls (, Figure 3). Moreover, we could find no other disparity (for example, in the lengths of these populations) that helped explain this difference.
In this work we estimate the evolutionary age of structural superfamilies. Our results are highly robust to different evolutionary assumptions in estimating ages, as well as alternative topologies and a smaller number of species in the phylogenetic trees. The results presented here indicate that newly evolving superfamilies tend to be, in general, shorter and structurally more simple than ancient structures. They appear, on average, to have a less hydrophobic core and a greater surface area to volume ratio. They differ from ancient superfamilies in terms of their amino acid composition, containing more polar residues, and tend to contain more additional stabilising features such as disulphide bonds and aromatic residues. Ancient superfamilies on the other hand are dominated by superfamilies and are enriched for many fundamental cellular functions. In particular, the still extant LUCA folds contain a comprehensive repertoire of proteins relating to RNA synthesis and maintenance rather than those used in DNA synthesis, and thus LUCA may have contained a ribosome mechanism for protein synthesis. The age of a superfamily could also be described as the depth at which it can be traced back through evolution. As such, there are several interpretations of our results, in particular in the case of what we have termed new-born superfamilies. Firstly, it could be that an entirely new domain was formed at some point in evolution. This could indicate that the evolution of a new superfamily as a transition from an already existing structure is a rare event, or that evolutionary transitions through fold space, when they occur, are more often reductive. It could also suggest that, through evolutionary drift, there is a tendency towards an increasingly elaborate structure. Secondly, a superfamily with a low age estimate might have originated earlier in evolution but the family recognition profiles have failed to identify homologues in distantly related species. In this case, such a superfamily may lack a representative deposition of solved structures, or be rapidly evolving and highly divergent. Certainly, characteristics such as a high solvent accessibility are correlated with the rate of sequence evolution [33]. Nevertheless, by using multiple profiles to build their Hidden Markov Models, SUPERFAMILY improves detection of sequence-divergent families compared to pairwise comparison and single profile searches [34]. As a greater coverage of proteins in such superfamilies are solved structurally, the likelihood of an incorrect low age estimate will decrease. Thirdly, a young superfamily may be the result of an unfound evolutionary link between superfamilies. As such the structural ancestor of these superfamilies may be earlier than their given age estimates. In order to address this possibility we have shown that the preferences are preserved at both the superfamily and fold level of the SCOP hierarchy. Finally, what appears to be a young superfamily may actually be ancient but has been lost at several more internal nodes than a parsimonious scenario suggests. This could be the result of functional specialisation within a superfamily. At present our understanding of the evolutionary history of individual superfamilies is not advanced enough to alter the evolutionary model behind age estimation for each superfamily. Our work concerning the robustness of the dataset overall to differing gain weights suggest that our results will be upheld within a moderate level of variation between different superfamilies. In this study we consider the structural universe of proteins and show that the age preferences of structural characteristics are not a residual effect derived from functional preferences. This result alone justifies the use of protein structures as a fundamental evolutionary unit. Using our age estimates we examined the specific case of greek key and jelly roll motifs, and identified a significant difference between their ages of origin. Given their similarity in topology it is possible that some superfamilies containing these motifs were involved in evolutionary transitions, where a greek key acted as a scaffold during the innovation of a jelly roll topology. This example demonstrates that these ages can be used to examine specific properties or motifs of interest, as well as explore more general fold space preferences for proteins at different stages in their evolution.
Occurrence profiles of superfamilies across whole genome trees were analysed using the principles of parsimony to estimate when their structural ancestor first evolved. The method described here is based on the the formulation developed by Winstanley et al. [13]. In subsequent sections we outline the process as it is used in this work. The data we use in this study were taken primarily from the SUPERFAMILY (v1. 75) database. SUPERFAMILY uses families of HMMs to identify homologues of 2,019 SCOP superfamilies. The database comprises protein sequences taken from completely sequenced and annotated genomes and assignments of these sequences to SCOP superfamilies. We downloaded predicted superfamilies for all 1,496 species available in the SUPERFAMILY database on September 11th 2012. This set was then filtered as follows: This left 649 Bacteria, 265 Eukaryotes and 100 Archaea. We called this set the ALLgenomes and it was intended to represent the diversity in the currently known tree of life as accurately as possible. A second set (MULTIgenomes) was created that contained 211 multi-cellular Eukaryotes, a subset of ALLgenomes. The list of all these species including those removed from the original data are included in Table S2. These predictions of superfamilies on genome sequences were then collapsed to a binary occurrence matrix where each element represents the presence or absence of a superfamily on a genome. A similar occurrence matrix was constructed at the fold level of the SCOP hierarchy. Multiple species trees were considered as the underlying phylogeny for the completely sequenced genomes. Using numerous trees helps to ensure that the results presented here are robust to inaccuracies in estimating the tree of life. We considered both the NCBI common taxonomy tree [37], [38] as well as phylogenies constructed using the superfamily and fold occurrence profiles calculated above. For completeness the constructed trees were estimated using both parsimony and distance-based algorithms. All the trees were inferred using the PHYLIP package [39]. A total of 8 different trees were constructed for each of the genome sets (ALLgenomes, MULTIgenomes). For each tree, the age of a superfamily is the result of a parsimony analysis on potential gain and loss events of the superfamily. Structural properties of 1,279 superfamilies were obtained using domains from the ASTRAL (1. 75) database [22] with an aerospaci score and filtered to sequence identity. This set of 5,493 domains will be referred to as the ASTRAL40 set. The number of representative ASTRAL40 domains for each superfamily is included in Table S3. Comparisons between the properties of new-born and ancient superfamilies were carried out using the Mann-Whitney U test [40]. Since multiple superfamilies shared the same age and therefore tied in rank the standard deviation of the distribution for the test statistic was appropriately adjusted [41]. While age distributions from all trees were considered in the analysis, for simplicity the p-values reported in the Results section derive from the ages calculated by maximum parsimony on the NCBI tree with branch lengths added using superfamily annotations. However, the results are only reported as significant if they gave significant p-values on ages from all the trees.
Proteins are the molecular workers of the cell. They are formed from a string of amino acids which folds into an elaborate three-dimensional structure. While there is a relationship between a protein' s sequence and its structure this relationship is highly complex and not fully understood. Protein structures tend to evolve differently to their sequences. They are far more conserved so tend to change slower. The aim of this paper was to identify trends in the way that protein structures evolve, rather than adapting models of sequence evolution. To do this we have provided a database of ages for structural superfamilies. These ages are robust to drastic differences in the evolutionary assumptions underlying their estimation and can be used to study differences between populations of proteins. For example, we have compared newly evolved structures against those with a long evolutionary history and found that, overall, a shorter evolutionary history corresponds to a less elaborate structure. We have also demonstrated here how these ages can be used to compare particular structural motifs present in a large number of protein structures and have shown that the jelly roll motif is significantly younger than the greek key.
Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies