A galaxy of folds

Many protein classification systems capture homologous relationships by grouping domains into families and superfamilies on the basis of sequence similarity. Superfamilies with similar 3D structures are further grouped into folds. In the absence of discernable sequence similarity, these structural similarities were long thought to have originated independently, by convergent evolution. However, the growth of databases and advances in sequence comparison methods have led to the discovery of many distant evolutionary relationships that transcend the boundaries of superfamilies and folds. To investigate the contributions of convergent versus divergent evolution in the origin of protein folds, we clustered representative domains of known structure by their sequence similarity, treating them as point masses in a virtual 2D space which attract or repel each other depending on their pairwise sequence similarities. As expected, families in the same superfamily form tight clusters. But often, superfamilies of the same fold are linked with each other, suggesting that the entire fold evolved from an ancient prototype. Strikingly, some links connect superfamilies with different folds. They arise from modular peptide fragments of between 20 and 40 residues that co‐occur in the connected folds in disparate structural contexts. These may be descendants of an ancestral pool of peptide modules that evolved as cofactors in the RNA world and from which the first folded proteins arose by amplification and recombination. Our galaxy of folds summarizes, in a single image, most known and many yet undescribed homologous relationships between protein superfamilies, providing new insights into the evolution of protein domains.     

Evolution of Protein Binding Modes in Homooligomers

The evolution of protein interactions cannot be deciphered without a detailed analysis of interaction interfaces and binding modes. We performed a large-scale study of protein homooligomers in terms of their symmetry, interface sizes, and conservation of binding modes. We also focused specifically on the evolution of protein binding modes from nine families of homooligomers and mapped 60 different binding modes and oligomerization states onto the phylogenetic trees of these families. We observed a significant tendency for the same binding modes to be clustered together and conserved within clades on phylogenetic trees; this trend is especially pronounced for close homologs with 70% sequence identity or higher. Some binding modes are conserved among very distant homologs, pointing to their ancient evolutionary origin, while others are very specific for a certain phylogenetic group. Moreover, we found that the most ancient binding modes have a tendency to involve symmetrical (isologous) homodimer binding arrangements with larger interfaces, while recently evolved binding modes more often exhibit asymmetrical arrangements and smaller interfaces.     

Connecting the protein structure universe by using sparse recurring fragments

The quest to order and classify protein structures has lead to various classification schemes, focusing mostly on hierarchical relationships between structural domains. At the coarsest classification level, such schemes typically identify hundreds of types of fundamental units called folds. As a result, we picture protein structure space as a collection of isolated fold islands. It is obvious, however, that many protein folds share structural and functional commonalities. Locating those commonalities is important for our understanding of protein structure, function, and evolution. Here, we present an alternative view of the protein fold space, based on an interfold similarity measure that is related to the frequency of fragments shared between folds. In this view, protein structures form a complicated, crossconnected network with very interesting topology. We show that interfold similarity based on sequence/structure fragments correlates well with similarities of functions between protein populations in different folds.     

Simulating protein evolution in sequence and structure space

Naturally occurring proteins comprise a special subset of all plausible sequences and structures selected through evolution. Simulating protein evolution with simplified and all-atom models has shed light on the evolutionary dynamics of protein populations, the nature of evolved sequences and structures, and the extent to which today's proteins are shaped by selection pressures on folding, structure and function. Extensive mapping of the native structure, stability and folding rate in sequence space using lattice proteins has revealed organizational principles of the sequence/structure map important for evolutionary dynamics. Evolutionary simulations with lattice proteins have highlighted the importance of fitness landscapes, evolutionary mechanisms, population dynamics and sequence space entropy in shaping the generic properties of proteins. Finally, evolutionary-like simulations with all-atom models, in particular computational protein design, have helped identify the dominant selection pressures on naturally occurring protein sequences and structures.     

On the evolution of protein folds: are similar motifs in different protein folds the result of convergence, insertion, or relics of an ancient peptide world?

This paper presents and discusses evidence suggesting how the diversity of domain folds in existence today might have evolved from peptide ancestors. We apply a structure similarity detection method to detect instances where localized regions of different protein folds contain highly similar sequences and structures. Results of performing an all-on-all comparison of known structures are described and compared with other recently published findings. The numerous instances of local sequence and structure similarities within different protein folds, together with evidence from proteins containing sequence and structure repeats, argues in favor of the evolution of modern single polypeptide domains from ancient short peptide ancestors (antecedent domain segments (ADSs)). In this model, ancient protein structures were formed by self-assembling aggregates of short polypeptides. Subsequently, and perhaps concomitantly with the evolution of higher fidelity DNA replication and repair systems, single polypeptide domains arose from the fusion of ADSs genes. Thus modern protein domains may have a polyphyletic origin.     

Coiled-Coil Proteins Facilitated the Functional Expansion of the Centrosome

Repurposing existing proteins for new cellular functions is recognized as a main mechanism of evolutionary innovation, but its role in organelle evolution is unclear. Here, we explore the mechanisms that led to the evolution of the centrosome, an ancestral eukaryotic organelle that expanded its functional repertoire through the course of evolution. We developed a refined sequence alignment technique that is more sensitive to coiled coil proteins, which are abundant in the centrosome. For proteins with high coiled-coil content, our algorithm identified 17% more reciprocal best hits than BLAST. Analyzing 108 eukaryotic genomes, we traced the evolutionary history of centrosome proteins. In order to assess how these proteins formed the centrosome and adopted new functions, we computationally emulated evolution by iteratively removing the most recently evolved proteins from the centrosomal protein interaction network. Coiled-coil proteins that first appeared in the animal–fungi ancestor act as scaffolds and recruit ancestral eukaryotic proteins such as kinases and phosphatases to the centrosome. This process created a signaling hub that is crucial for multicellular development. Our results demonstrate how ancient proteins can be co-opted to different cellular localizations, thereby becoming involved in novel functions.     

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to normal populations evolving on neutral networks.     

Genetic Structure of Earthworm Populations at a Regional Scale: Inferences from Mitochondrial and Microsatellite Molecular Markers in Aporrectodea icterica (Savigny 1826)

Despite the fundamental role that soil invertebrates (e.g. earthworms) play in soil ecosystems, the magnitude of their spatial genetic variation is still largely unknown and only a few studies have investigated the population genetic structure of these organisms. Here, we investigated the genetic structure of seven populations of a common endogeic earthworm (Aporrectodea icterica) sampled in northern France to explore how historical species range changes, microevolutionary processes and human activities interact in shaping genetic variation at a regional scale. Because combining markers with distinct modes of inheritance can provide extra, complementary information on gene flow, we compared the patterns of genetic structure revealed using nuclear (7 microsatellite loci) and mitochondrial markers (COI). Both types of markers indicated low genetic polymorphism compared to other earthworm species, a result that can be attributed to ancient bottlenecks, for instance due to species isolation in southern refugia during the ice ages with subsequent expansion toward northern Europe. Historical events can also be responsible for the existence of two divergent, but randomly interbreeding mitochondrial lineages within all study populations. In addition, the comparison of observed heterozygosity among microsatellite loci and heterozygosity expected under mutation-drift equilibrium suggested a recent decrease in effective size in some populations that could be due to contemporary events such as habitat fragmentation. The absence of relationship between geographic and genetic distances estimated from microsatellite allele frequency data also suggested that dispersal is haphazard and that human activities favour passive dispersal among geographically distant populations.     

Ribonuclease P: the evolution of an ancient RNA enzyme

Ribonuclease P (RNase P) is an ancient and essential endonuclease that catalyses the cleavage of the 5' leader sequence from precursor tRNAs (pre-tRNAs). The enzyme is one of only two ribozymes which can be found in all kingdoms of life (Bacteria, Archaea, and Eukarya). Most forms of RNase P are ribonucleoproteins; the bacterial enzyme possesses a single catalytic RNA and one small protein. However, in archaea and eukarya the enzyme has evolved an increasingly more complex protein composition, whilst retaining a structurally related RNA subunit. The reasons for this additional complexity are not currently understood. Furthermore, the eukaryotic RNase P has evolved into several different enzymes including a nuclear activity, organellar activities, and the evolution of a distinct but closely related enzyme, RNase MRP, which has different substrate specificities, primarily involved in ribosomal RNA biogenesis. Here we examine the relationship between the bacterial and archaeal RNase P with the eukaryotic enzyme, and summarize recent progress in characterizing the archaeal enzyme. We review current information regarding the nuclear RNase P and RNase MRP enzymes in the eukaryotes, focusing on the relationship between these enzymes by examining their composition, structure and functions.     

Replicability and recurrence in the experimental evolution of a group I ribozyme

In order to explore the variety of possible responses available to a ribozyme population evolving a novel phenotype, five Tetrahymena thermophila group I intron ribozyme pools were evolved in parallel for cleavage of a DNA oligonucleotide. These ribozyme populations were propagated under identical conditions and characterized when they reached apparent phenotypic plateaus; the populations that reached the highest plateau showed a near 100-fold improvement in DNA cleavage activity. A detailed characterization of the evolved response in these populations reveals at least two distinct phenotypic trajectories emerging as a result of the imposed selection. Not only do these distinct solutions exhibit differential DNA cleavage activity, but they also exhibit a very different correlation with a related, but unselected, phenotype: RNA cleavage activity. In turn, each of these trajectories is underwritten by differing genotypic profiles. This study underscores the complex network of possible trajectories through sequence space available to an evolving population and uncovers the diversity of solutions that result when the process of experimental evolution is repeated multiple times in a simple, engineered system.     

Rapid evolution of adaptive niche construction in experimental microbial populations

Many species engage in adaptive niche construction: modification of the local environment that increases the modifying organism's competitive fitness. Adaptive niche construction provides an alternative pathway to higher fitness, shaping the environment rather than conforming to it. Yet, experimental evidence for the evolutionary emergence of adaptive niche construction is lacking, leaving its role in evolution uncertain. Here we report a direct observation of the de novo evolution of adaptive niche construction in populations of the bacteria Pseudomonas fluorescens. In a laboratory experiment, we allowed several bacterial populations to adapt to a novel environment and assessed whether niche construction evolved over time. We found that adaptive niche construction emerged rapidly, within approximately 100 generations, and became ubiquitous after approximately 400 generations. The large fitness effect of this niche construction was dominated by the low fitness of evolved strains in the ancestrally modified environment: evolved niche constructors were highly dependent on their specific environmental modifications. Populations were subjected to frequent resetting of environmental conditions and severe reduction of spatial habitat structure, both of which are thought to make adaptive niche construction difficult to evolve. Our finding that adaptive niche construction nevertheless evolved repeatably suggests that it may play a more important role in evolution than generally thought.     

A Correspondence Between Solution-State Dynamics of an Individual Protein and the Sequence and Conformational Diversity of its Family

Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using “Backrub” motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.     

Nonlinearities in protein space limit the utility of informatics in protein biophysics

We examine the utility of informatic‐based methods in computational protein biophysics. To do so, we use newly developed metric functions to define completely independent sequence and structure spaces for a large database of proteins. By investigating the relationship between these spaces, we demonstrate quantitatively the limits of knowledge‐based correlation between the sequences and structures of proteins. It is shown that there are well‐defined, nonlinear regions of protein space in which dissimilar structures map onto similar sequences (the conformational switch), and dissimilar sequences map onto similar structures (remote homology). These nonlinearities are shown to be quite common—almost half the proteins in our database fall into one or the other of these two regions. They are not anomalies, but rather intrinsic properties of structural encoding in amino acid sequences. It follows that extreme care must be exercised in using bioinformatic data as a basis for computational structure prediction. The implications of these results for protein evolution are examined. Proteins 2015; 83:1923–1928. © 2015 Wiley Periodicals, Inc.     

Lake Baikal: a unique place to study evolution of sponges and their stress response in an environment nearly unimpaired by anthropogenic perturbation.

Lake Baikal is considered as a unique place to study evolution. In this review, we report on recent data on the evolution of endemic freshwater sponges of this ancient lake. Nucleotide sequence data support the idea that these sponges are of monophyletic origin and evolved from Spongillidae. Baikalian sponges form the dominating biomass in the benthos of the lake. Data on the expression of the biomarker heat shock protein 70, revealed that the endemic sponge species of Lake Baikal are useful as bioindicators to assess the anthropogenic impact on the lake.     

Modular evolution and the origins of symmetry: reconstruction of a three-fold symmetric globular protein

The high frequency of internal structural symmetry in common protein folds is presumed to reflect their evolutionary origins from the repetition and fusion of ancient peptide modules, but little is known about the primary sequence and physical determinants of this process. Unexpectedly, a sequence and structural analysis of symmetric subdomain modules within an abundant and ancient globular fold, the β-trefoil, reveals that modular evolution is not simply a relic of the ancient past, but is an ongoing and recurring mechanism for regenerating symmetry, having occurred independently in numerous existing β-trefoil proteins. We performed a computational reconstruction of a β-trefoil subdomain module and repeated it to form a newly three-fold symmetric globular protein, ThreeFoil. In addition to its near perfect structural identity between symmetric modules, ThreeFoil is highly soluble, performs multivalent carbohydrate binding, and has remarkably high thermal stability. These findings have far-reaching implications for understanding the evolution and design of proteins via subdomain modules.     

Prior evolution in stochastic versus constant temperatures affects RNA virus evolvability at a thermal extreme

It is unclear how historical adaptation versus maladaptation in a prior environment affects population evolvability in a novel habitat. Prior work showed that vesicular stomatitis virus (VSV) populations evolved at constant 37°C improved in cellular infection at both 29°C and 37°C; in contrast, those evolved under random changing temperatures between 29°C and 37°C failed to improve. Here, we tested whether prior evolution affected the rate of adaptation at the thermal‐niche edge: 40°C. After 40 virus generations in the new environment, we observed that populations historically evolved at random temperatures showed greater adaptability. Deep sequencing revealed that most of the newly evolved mutations were de novo. Also, two novel evolved mutations in the VSV glycoprotein and replicase genes tended to co‐occur in the populations previously evolved at constant 37°C, whereas this parallelism was not seen in populations with prior random temperature evolution. These results suggest that prior adaptation under constant versus random temperatures constrained the mutation landscape that could improve fitness in the novel 40°C environment, perhaps owing to differing epistatic effects of new mutations entering genetic architectures that earlier diverged. We concluded that RNA viruses maladapted to their previous environment could “leapfrog” over counterparts of higher fitness, to achieve faster adaptability in a novel environment.