A complex-centric view of protein network evolution

The recent availability of protein–protein interaction networks for several species makes it possible to study protein complexes in an evolutionary context. In this article, we present a novel network-based framework for reconstructing the evolutionary history of protein complexes. Our analysis is based on generalizing evolutionary measures for single proteins to the level of whole subnetworks, comprehensively considering a broad set of computationally derived complexes and accounting for both sequence and interaction changes. Specifically, we compute sets of orthologous complexes across species, and use these to derive evolutionary rate and age measures for protein complexes. We observe significant correlations between the evolutionary properties of a complex and those of its member proteins, suggesting that protein complexes form early in evolution and evolve as coherent units. Additionally, our approach enables us to directly quantify the extent to which gene duplication has played a role in the evolution of complexes. We find that about one quarter of the sets of orthologous complexes have originated from evolutionary cores of homodimers that underwent duplication and divergence, testifying to the important role of gene duplication in protein complex evolution.     

The nature of protein domain evolution: shaping the interaction network

The proteomes that make up the collection of proteins in contemporary organisms evolved through recombination and duplication of a limited set of domains. These protein domains are essentially the main components of globular proteins and are the most principal level at which protein function and protein interactions can be understood. An important aspect of domain evolution is their atomic structure and biochemical function, which are both specified by the information in the amino acid sequence. Changes in this information may bring about new folds, functions and protein architectures. With the present and still increasing wealth of sequences and annotation data brought about by genomics, new evolutionary relationships are constantly being revealed, unknown structures modeled and phylogenies inferred. Such investigations not only help predict the function of newly discovered proteins, but also assist in mapping unforeseen pathways of evolution and reveal crucial, co-evolving inter- and intra-molecular interactions. In turn this will help us describe how protein domains shaped cellular interaction networks and the dynamics with which they are regulated in the cell. Additionally, these studies can be used for the design of new and optimized protein domains for therapy. In this review, we aim to describe the basic concepts of protein domain evolution and illustrate recent developments in molecular evolution that have provided valuable new insights in the field of comparative genomics and protein interaction networks.     

Identification of conserved protein complexes based on a model of protein network evolution

MOTIVATION: Data on protein-protein interactions (PPIs) are increasing exponentially. To date, large-scale protein interaction networks are available for human and most model species. The arising challenge is to organize these networks into models of cellular machinery. As in other biological domains, a comparative approach provides a powerful basis for addressing this challenge. RESULTS: We develop a probabilistic model for protein complexes that are conserved across two species. The model describes the evolution of conserved protein complexes from an ancestral species by protein interaction attachment and detachment and gene duplication events. We apply our model to search for conserved protein complexes within the PPI networks of yeast and fly, which are the largest networks in public databases. We detect 150 conserved complexes that match well-known complexes in yeast and are coherent in their functional annotations both in yeast and in fly. In comparison with two previous approaches, our model yields higher specificity and sensitivity levels in protein complex detection. AVAILABILITY: The program is available upon request.     

Functional evolution of the yeast protein interaction network

Protein interactions are central to most biological processes. We investigated the dynamics of emergence of the protein interaction network of Saccharomyces cerevisiae by mapping origins of proteins on an evolutionary tree. We demonstrate that evolutionary periods are characterized by distinct connectivity levels of the emerging proteins. We found that the most-connected group of proteins dates to the eukaryotic radiation, and the more ancient group of pre-eukaryotic proteins is less connected. We show that functional classes have different average connectivity levels and that the time of emergence of these functional classes parallels the observed connectivity variation in evolution. We take these findings as evidence that the evolution of function might be the reason for the differences in connectivity throughout evolutionary time. We propose that the understanding of the mechanisms that generate the scale-free protein interaction network, and possibly other biological networks, requires consideration of protein function.     

The role of peptide motifs in the evolution of a protein network

Naturally occurring proteins in cellular networks often share peptide motifs. These motifs have been known to play a pivotal role in protein interactions among the components of a network. However, it remains unknown how these motifs have contributed to the evolution of the protein network. Here we addressed this issue by a synthetic biology approach. Through the motif programming method, we have constructed an artificial protein library by mixing four peptide motifs shared among the Bcl-2 family proteins that positively or negatively regulate the apoptosis networks. We found one strong pro-apoptotic protein, d29, and two proteins having moderate, but unambiguous anti-apoptotic functions, a10 and d16, from the 28 tested clones. Thus both the pro- and anti-apoptotic modulators were present in the library, demonstrating that functional proteins with opposing effects can emerge from a single pool prepared from common motifs. Motif programming studies have exhibited that the annotated function of the motifs were significantly influenced by the context that the motifs embedded. The results further revealed that reshuffling of a set of motifs realized the promiscuous state of protein, from which disparate functions could emerge. Our finding suggests that motifs contributed to the plastic evolvability of the protein network.     

Modularity in the evolution of yeast protein interaction network

Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.     

Plant neighbours mediate bird predation effects on arthropod abundance and herbivory

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The structure of protein evolution and the evolution of protein structure

The observed distribution of protein structures can give us important clues about the underlying evolutionary process, imposing important constraints on possible models. The availability of results from an increasing number of genome projects has made the development of these models an active area of research. Models explaining the observed distribution of structures have focused on the inherent functional capabilities and structural properties of different folds and on the evolutionary dynamics. Increasingly, these elements are being combined.     

Modification of gene duplicability during the evolution of protein interaction network

Duplications of genes encoding highly connected and essential proteins are selected against in several species but not in human, where duplicated genes encode highly connected proteins. To understand when and how gene duplicability changed in evolution, we compare gene and network properties in four species (Escherichia coli, yeast, fly, and human) that are representative of the increase in evolutionary complexity, defined as progressive growth in the number of genes, cells, and cell types. We find that the origin and conservation of a gene significantly correlates with the properties of the encoded protein in the protein-protein interaction network. All four species preserve a core of singleton and central hubs that originated early in evolution, are highly conserved, and accomplish basic biological functions. Another group of hubs appeared in metazoans and duplicated in vertebrates, mostly through vertebrate-specific whole genome duplication. Such recent and duplicated hubs are frequently targets of microRNAs and show tissue-selective expression, suggesting that these are alternative mechanisms to control their dosage. Our study shows how networks modified during evolution and contributes to explaining the occurrence of somatic genetic diseases, such as cancer, in terms of network perturbations.     

Modeling protein network evolution under genome duplication and domain shuffling

Background  

Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI) networks by outweighing, in particular, all time-linear network growths modeled so far.     

The protein folding network

The conformation space of a 20 residue antiparallel beta-sheet peptide, sampled by molecular dynamics simulations, is mapped to a network. Snapshots saved along the trajectory are grouped according to secondary structure into nodes of the network and the transitions between them are links. The conformation space network describes the significant free energy minima and their dynamic connectivity without requiring arbitrarily chosen reaction coordinates. As previously found for the Internet and the World-Wide Web as well as for social and biological networks, the conformation space network is scale-free and contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the native basin exhibits a hierarchical organization, which is not found for a random heteropolymer lacking a predominant free-energy minimum. The network topology is used to identify conformations in the folding transition state (TS) ensemble, and provides a basis for understanding the heterogeneity of the TS and denatured state ensemble as well as the existence of multiple pathways.     

The combined effects of amino acid substitutions and indels on the evolution of structure within protein families

Background

In the process of protein evolution, sequence variations within protein families can cause changes in protein structures and functions. However, structures tend to be more conserved than sequences and functions. This leads to an intriguing question: what is the evolutionary mechanism by which sequence variations produce structural changes? To investigate this question, we focused on the most common types of sequence variations: amino acid substitutions and insertions/deletions (indels). Here their combined effects on protein structure evolution within protein families are studied.

Results

Sequence-structure correlation analysis on 75 homologous structure families (from SCOP) that contain 20 or more non-redundant structures shows that in most of these families there is, statistically, a bilinear correlation between the amount of substitutions and indels versus the degree of structure variations. Bilinear regression of percent sequence non-identity (PNI) and standardized number of gaps (SNG) versus RMSD was performed. The coefficients from the regression analysis could be used to estimate the structure changes caused by each unit of substitution (structural substitution sensitivity, SSS) and by each unit of indel (structural indel sensitivity, SIDS). An analysis on 52 families with high bilinear fitting multiple correlation coefficients and statistically significant regression coefficients showed that SSS is mainly constrained by disulfide bonds, which almost have no effects on SIDS.

Conclusions

Structural changes in homologous protein families could be rationally explained by a bilinear model combining amino acid substitutions and indels. These results may further improve our understanding of the evolutionary mechanisms of protein structures.     

The effects of sex-biased gene expression and X-linkage on rates of adaptive protein sequence evolution in Drosophila

A faster rate of adaptive evolution of X-linked genes compared with autosomal genes may be caused by the fixation of new recessive or partially recessive advantageous mutations (the Faster-X effect). This effect is expected to be largest for mutations that affect only male fitness and absent for mutations that affect only female fitness. We tested these predictions in Drosophila melanogaster by using genes with different levels of sex-biased expression and by estimating the extent of adaptive evolution of non-synonymous mutations from polymorphism and divergence data. We detected both a Faster-X effect and an effect of male-biased gene expression. There was no evidence for a strong association between the two effects—modest levels of male-biased gene expression increased the rate of adaptive evolution on both the autosomes and the X chromosome, but a Faster-X effect occurred for both unbiased genes and female-biased genes. The rate of genetic recombination did not influence the magnitude of the Faster-X effect, ruling out the possibility that it reflects less Hill–Robertson interference for X-linked genes.     

The evolution of multimeric protein assemblages

Although the mechanisms by which complex cellular features evolve constitute one of the great unsolved problems of evolutionary biology, it is clear that the emergence of new protein-protein interactions, often accompanied by the diversification of duplicate genes, is involved. Using information on the levels of protein multimerization in major phylogenetic groups as a guide to the patterns that must be explained and relying on results from population-genetic theory to define the relative plausibility of alternative evolutionary pathways, a framework for understanding the evolution of dimers is developed. The resultant theory demonstrates that the likelihoods of alternative pathways for the emergence of protein complexes depend strongly on the effective population size. Nonetheless, it is equally clear that further advancements in this area will require comparative studies on the fitness consequences of alternative monomeric and dimeric proteins.     

The effect of neighbours on the mortality of harvester ant colonies

1. This study investigates how the density and size of conspecific neighbours affected the mortality of established colonies. Data were from a population of 250–300 colonies of the red harvester ant [ Pogonomyrmex barbatus (F. Smith)], on a 10-ha site, from 1988 to 1995.
2. Colonies are more likely to die as they grow older.
3. Small neighbours tend to lower the probability of dying.
4. The probability of dying varied significantly from year to year.
5. There was little effect of crowding on mortality.
6. There appeared to be no spatial effects, on the scale of 25. m, on the probability of dying.
7. Previous work shows effects of density on the founding of new colonies and on the reproductive output of established ones. The results presented here indicate that competition with neighbours rarely causes the death of established colonies.     

The protein network of HIV budding

HIV release requires TSG101, a cellular factor that sorts proteins into vesicles that bud into multivesicular bodies (MVB). To test whether other proteins involved in MVB biogenesis (the class E proteins) also participate in HIV release, we identified 22 candidate human class E proteins. These proteins were connected into a coherent network by 43 different protein-protein interactions, with AIP1 playing a key role in linking complexes that act early (TSG101/ESCRT-I) and late (CHMP4/ESCRT-III) in the pathway. AIP1 also binds the HIV-1 p6(Gag) and EIAV p9(Gag) proteins, indicating that it can function directly in virus budding. Human class E proteins were found in HIV-1 particles, and dominant-negative mutants of late-acting human class E proteins arrested HIV-1 budding through plasmal and endosomal membranes. These studies define a protein network required for human MVB biogenesis and indicate that the entire network participates in the release of HIV and probably many other viruses.     

The designability hypothesis and protein evolution

The usage of protein folds in nature is known to be non-uniform: a few folds are used often, while most others are used relatively rarely. What makes one fold more successful than another? The designability explanation, which posits that successful folds have an exponentially larger number of compatible sequences, is critically reviewed, and compared with other structural and functional explanations. It is argued that designability is one component of fold fitness, but most likely not a dominant one.     

The evolution of the protein synthesis system

An evolutionary picture of the early protein synthesis was presented in relation to the problem of the origin and the evolution of life. A model of an autocatalytic system was studied in this connection. The system in this model included a template nucleotide and two activated amino acid polymerases with or without a nucleotide polymerase. Variables defining the system were: (1) Catalytic activity of the polymerases, (2) Number of amino acid residues at the activity site of the polymerases, (3) Number of amino acid residues at the selectivity site of the polymerases, (4) Number of the polymerases, (5) Accuracy of polymerization and activity of the polymerases, (6) Number of evolutionary improvements, and (7) The probability of an occurrence of beneficial mutations. The population changes of the systems were obtained by computer calculations. The simulation results indicated that even a very small enzymic activity and specificity of the polymerases could eventually lead the system to the most accurate protein synthesis, as far as transitions to systems with higher accuracy were allowed. The model study would encourage further quantiative investigations on catalytic activities of synthetic peptides, and on interactions between nucleotides and amino acids, and constructions of autocatalytic systems from a chemical evolutionary point of view.This is a part of a dissertation of HM to be presented to the Graduate School of the University of Maryland in partial fulfilment of the requirements for the Ph.D.