Evolution of protein complexes by duplication of homomeric interactions

Mechanisms of protein oligomerization, the critical role of insertions and deletions in maintaining different oligomeric states

The main principles of protein-protein recognition are elucidated by the studies of homooligomers which in turn mediate and regulate gene expression, activity of enzymes, ion channels, receptors, and cell-cell adhesion processes. Here we explore oligomeric states of homologous proteins in various organisms to better understand the functional roles and evolutionary mechanisms of homooligomerization. We observe a great diversity in mechanisms controlling oligomerization and focus in our study on insertions and deletions in homologous proteins and how they enable or disable complex formation. We show that insertions and deletions which differentiate monomers and dimers have a significant tendency to be located on the interaction interfaces and about a quarter of all proteins studied and forty percent of enzymes have regions which mediate or disrupt the formation of oligomers. We suggest that relatively small insertions or deletions may have a profound effect on complex stability and/or specificity. Indeed removal of complex enabling regions from protein structures in many cases resulted in the complete or partial loss of stability. Moreover, we find that insertions and deletions modulating oligomerization have a lower aggregation propensity and contain a larger fraction of polar, charged residues, glycine and proline compared to conventional interfaces and protein surface. Most likely, these regions may mediate specific interactions, prevent nonspecific dysfunctional aggregation and preclude undesired interactions between close paralogs therefore separating their functional pathways. Last, we show how the presence or absence of insertions and deletions on interfaces might be of practical value in annotating protein oligomeric states.

Mosaic origin of the mitochondrial proteome

Although the origin of mitochondria from the endosymbiosis of an α-proteobacterium is well established, the nature of the host cell, the metabolic complexity of the endosymbiont and the subsequent evolution of the proto-mitochondrion into all its current appearances are still the subject of discovery and sometimes debate. Here we review what has been inferred about the original composition and subsequent evolution of the mitochondrial proteome and essential mitochondrial systems. The evolutionary mosaic that currently constitutes mitochondrial proteomes contains (i) endosymbiotic proteins (15-45%), (ii) proteins without detectable orthologs outside the eukaryotic lineage (40%), and (iii) proteins that are derived from non-proteobacterial Bacteria, Bacteriophages and Archaea (15%, specifically multiple tRNA-modification proteins). Protein complexes are of endosymbiotic origin, but have greatly expanded with novel eukaryotic proteins; in contrast to mitochondrial enzymes that are both of proteobacterial and non-proteobacterial origin. This disparity is consistent with the complexity hypothesis, which argues that proteins that are a part of large, multi-subunit complexes are unlikely to undergo horizontal gene transfer. We observe that they neither change their subcellular compartments in the course of evolution, even when their genes do.

Exposing the co-adaptive potential of protein-protein interfaces through computational sequence design

MOTIVATION

In nature, protein-protein interactions are constantly evolving under various selective pressures. Nonetheless, it is expected that crucial interactions are maintained through compensatory mutations between interacting proteins. Thus, many studies have used evolutionary sequence data to extract such occurrences of correlated mutation. However, this research is confounded by other evolutionary pressures that contribute to sequence covariance, such as common ancestry.

RESULTS

Here, we focus exclusively on the compensatory mutations deriving from physical protein interactions, by performing large-scale computational mutagenesis experiments for >260 protein-protein interfaces. We investigate the potential for co-adaptability present in protein pairs that are always found together in nature (obligate) and those that are occasionally in complex (transient). By modeling each complex both in bound and unbound forms, we find that naturally transient complexes possess greater relative capacity for correlated mutation than obligate complexes, even when differences in interface size are taken into account.

An integrated view of molecular coevolution in protein-protein interactions

Protein-protein interactions effectively mediate molecular function. They are the result of specific interactions between protein interfaces and are maintained by the action of evolutionary pressure on the regions of the interacting proteins that contribute to binding. For the most part, selection restricts amino acid replacements, accounting for the conservation of binding interfaces. However, in some cases, change in one protein will be mitigated by compensatory change in its binding partner, maintaining function in the face of evolutionary change. There have been several attempts to use correlations in sequence evolution to predict interactions of proteins. Most commonly, these approaches use the entire sequence to identify correlations and so infer probable binding. However, other factors such as shared evolutionary history and similarities in the rates of evolution confound these whole-sequence-based approaches. Here, we discuss recent work on this topic and argue that both site-specific coevolutionary change and whole-sequence evolution contribute to evolutionary signals in sets of interacting proteins. We discuss the relative effects of both types of selection and how they might be identified. This permits an integrated view of protein-protein interactions, their evolution, and coevolution.

Duplicability of self-interacting human genes

Background

There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome.

Results

We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication.

Conclusions

Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

The role of recently derived FT paralogs in sunflower domestication

Gene duplication provides an important source of genetic raw material for phenotypic diversification, but few studies have detailed the mechanisms through which duplications produce evolutionary novelty within species. Here, we investigate how a set of recently duplicated homologs of the floral inducer FLOWERING LOCUS T (FT) has contributed to sunflower domestication. We find that changes in expression of these duplicates are associated with differences in flowering behavior between wild and domesticated sunflower. In addition, we present genetic and functional evidence demonstrating that a frameshift mutation in one paralog, Helianthus annuus FT 1 (HaFT1), underlies a major QTL for flowering time and experienced a selective sweep during early domestication. Notably, this dominant-negative allele delays flowering through interference with action of another paralog, HaFT4. Together, these data reveal that changes affecting the expression, sequence, and gene interactions of HaFT paralogs have played key roles during sunflower domestication. Our findings also illustrate the important role that evolving interactions between new gene family members may play in fostering phenotypic change.

Comparative evolutionary analysis of protein complexes in E. coli and yeast

Background

Proteins do not act in isolation; they frequently act together in protein complexes to carry out concerted cellular functions. The evolution of complexes is poorly understood, especially in organisms other than yeast, where little experimental data has been available.

Results

We generated accurate, high coverage datasets of protein complexes for E. coli and yeast in order to study differences in the evolution of complexes between these two species. We show that substantial differences exist in how complexes have evolved between these organisms. A previously proposed model of complex evolution identified complexes with cores of interacting homologues. We support findings of the relative importance of this mode of evolution in yeast, but find that it is much less common in E. coli. Additionally it is shown that those homologues which do cluster in complexes are involved in eukaryote-specific functions. Furthermore we identify correlated pairs of non-homologous domains which occur in multiple protein complexes. These were identified in both yeast and E. coli and we present evidence that these too may represent complex cores in yeast but not those of E. coli.

Conclusions

Our results suggest that there are differences in the way protein complexes have evolved in E. coli and yeast. Whereas some yeast complexes have evolved by recruiting paralogues, this is not apparent in E. coli. Furthermore, such complexes are involved in eukaryotic-specific functions. This implies that the increase in gene family sizes seen in eukaryotes in part reflects multiple family members being used within complexes. However, in general, in both E. coli and yeast, homologous domains are used in different complexes.

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.

From evidence to inference: probing the evolution of protein interaction networks

The evolutionary mechanisms by which protein interaction networks grow and change are beginning to be appreciated as a major factor shaping their present-day structures and properties. Starting with a consideration of the biases and errors inherent in our current views of these networks, we discuss the dangers of constructing evolutionary arguments from naïve analyses of network topology. We argue that progress in understanding the processes of network evolution is only possible when hypotheses are formulated as plausible evolutionary models and compared against the observed data within the framework of probabilistic modeling. The value of such models is expected to be greatly enhanced as they incorporate more of the details of the biophysical properties of interacting proteins, gene phylogeny, and measurement error and as more advanced methodologies emerge for model comparison and the inference of ancestral network states.

The Modular Organization of Protein Interactions in Escherichia coli

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a 'systems' view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins ( approximately 45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks.

Alternative to homo-oligomerisation: the creation of local symmetry in proteins by internal amplification

The biologically active state of many proteins requires their prior homo-oligomerisation. Such complexes are typically symmetrical, a feature that has been proposed to increase their stability and facilitate the evolution of allosteric regulation. We wished to examine the possibility that similar structures and properties could arise from genetic amplifications leading to internal symmetrical repeats. For this, we identified internal structural repeats in a nonredundant Protein Data Bank subset. While testing if repeats in proteins tend to be symmetrical, we found that about half of the large internal repeats are symmetrical, most frequently around a rotation axis of 180 degrees . These repeats were most likely created by genetic amplification processes because they show significant sequence similarity. Symmetrical repeats tend to have a fixed number of copies corresponding to their rotational symmetry order, that is, two for 180 degrees rotation axis, whereas asymmetrical repeats are in longer proteins and show copy number variability. When possible, we confirmed that proteins with symmetrical repeats folding as an n-mer have homologues lacking the repeat with a higher oligomerisation number corresponding to the rotation symmetry order of the repeat. Phylogenetic analyses of these protein families suggest that typically, but not always, symmetrical repeats arise in one single event from proteins that are homo-oligomers. These results suggest that oligomerisation and amplification of internal sequences can interplay in evolutionary terms because they result in functional analogues when the latter exhibit rotational symmetry.

Evolution of phosphoregulation: comparison of phosphorylation patterns across yeast species

Analysis of the phosphoproteomes and the gene interaction networks of divergent yeast species defines the relative contribution of changes in protein phosphorylation pathways to the generation of phenotypic diversity.

The extent by which different cellular components generate phenotypic diversity is an ongoing debate in evolutionary biology that is yet to be addressed by quantitative comparative studies. We conducted an in vivo mass-spectrometry study of the phosphoproteomes of three yeast species (Saccharomyces cerevisiae, Candida albicans, and Schizosaccharomyces pombe) in order to quantify the evolutionary rate of change of phosphorylation. We estimate that kinase–substrate interactions change, at most, two orders of magnitude more slowly than transcription factor (TF)–promoter interactions. Our computational analysis linking kinases to putative substrates recapitulates known phosphoregulation events and provides putative evolutionary histories for the kinase regulation of protein complexes across 11 yeast species. To validate these trends, we used the E-MAP approach to analyze over 2,000 quantitative genetic interactions in S. cerevisiae and Sc. pombe, which demonstrated that protein kinases, and to a greater extent TFs, show lower than average conservation of genetic interactions. We propose therefore that protein kinases are an important source of phenotypic diversity.

Natural selection at a population level requires phenotypic diversity, which at the molecular level arises by mutation of the genome of each individual. What kinds of changes at the level of the DNA are most important for the generation of phenotypic differences remains a fundamental question in evolutionary biology. One well-studied source of phenotypic diversity is mutation in gene regulatory regions that results in changes in gene expression, but what proportion of phenotypic diversity is due to such mutations is not entirely clear. We investigated the relative contribution to phenotypic diversity of mutations in protein-coding regions compared to mutations in gene regulatory sequences. Given the important regulatory role played by phosphorylation across biological systems, we focused on mutations in protein-coding regions that alter protein–protein interactions involved in the binding of kinases to their substrate proteins. We studied the evolution of this “phosphoregulation” by analyzing the in vivo complement of phosphorylated proteins (the “phosphoproteome”) in three highly diverged yeast species—the budding yeast Saccharomyces cerevisiae, the pathogenic yeast Candida albicans, and the fission yeast Schizosaccharomyces pombe—and integrating those data with existing data on thousands of known genetic interactions from S. cerevisiae and Sc. pombe. We show that kinase–substrate interactions are altered at a rate that is at most two orders of magnitude slower than the alteration of transcription factor (TF)–promoter interactions, whereas TFs and kinases both show a faster than average rate of functional divergence estimated by the cross-species analysis of genetic interactions. Our data provide a quantitative estimate of the relative frequencies of different kinds of functionally relevant mutations and demonstrate that, like mutations in gene regulatory regions, mutations that result in changes in kinase–substrate interactions are an important source of phenotypic diversity.

Is protein classification necessary? Toward alternative approaches to function annotation

The current nonredundant protein sequence database contains over seven million entries and the number of individual functional domains is significantly larger than this value. The vast quantity of data associated with these proteins poses enormous challenges to any attempt at function annotation. Classification of proteins into sequence and structural groups has been widely used as an approach to simplifying the problem. In this article we question such strategies. We describe how the multifunctionality and structural diversity of even closely related proteins confounds efforts to assign function on the basis of overall sequence or structural similarity. Rather, we suggest that strategies that avoid classification may offer a more robust approach to protein function annotation.

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.

Protein oligomerization in the bacterial outer membrane (Review)

The formation of homo-oligomeric assemblies is a well-established characteristic of many soluble proteins and enzymes. Oligomerization has been shown to increase protein stability, allow allosteric cooperativity, shape reaction compartments and provide multivalent interaction sites in soluble proteins. In comparison, our understanding of the prevalence and reasons behind protein oligomerization in membrane proteins is relatively sparse. Recent progress in structural biology of bacterial outer membrane proteins has suggested that oligomerization may be as common and versatile as in soluble proteins. Here we review the current understanding of oligomerization in the bacterial outer membrane from a structural and functional point of view.

The origin, evolution and structure of the protein world

Contemporary protein architectures can be regarded as molecular fossils, historical imprints that mark important milestones in the history of life. Whereas sequences change at a considerable pace, higher-order structures are constrained by the energetic landscape of protein folding, the exploration of sequence and structure space, and complex interactions mediated by the proteostasis and proteolytic machineries of the cell. The survey of architectures in the living world that was fuelled by recent structural genomic initiatives has been summarized in protein classification schemes, and the overall structure of fold space explored with novel bioinformatic approaches. However, metrics of general structural comparison have not yet unified architectural complexity using the 'shared and derived' tenet of evolutionary analysis. In contrast, a shift of focus from molecules to proteomes and a census of protein structure in fully sequenced genomes were able to uncover global evolutionary patterns in the structure of proteins. Timelines of discovery of architectures and functions unfolded episodes of specialization, reductive evolutionary tendencies of architectural repertoires in proteomes and the rise of modularity in the protein world. They revealed a biologically complex ancestral proteome and the early origin of the archaeal lineage. Studies also identified an origin of the protein world in enzymes of nucleotide metabolism harbouring the P-loop-containing triphosphate hydrolase fold and the explosive discovery of metabolic functions that recapitulated well-defined prebiotic shells and involved the recruitment of structures and functions. These observations have important implications for origins of modern biochemistry and diversification of life.

Questioning the ubiquity of neofunctionalization

Gene duplication provides much of the raw material from which functional diversity evolves. Two evolutionary mechanisms have been proposed that generate functional diversity: neofunctionalization, the de novo acquisition of function by one duplicate, and subfunctionalization, the partitioning of ancestral functions between gene duplicates. With protein interactions as a surrogate for protein functions, evidence of prodigious neofunctionalization and subfunctionalization has been identified in analyses of empirical protein interactions and evolutionary models of protein interactions. However, we have identified three phenomena that have contributed to neofunctionalization being erroneously identified as a significant factor in protein interaction network evolution. First, self-interacting proteins are underreported in interaction data due to biological artifacts and design limitations in the two most common high-throughput protein interaction assays. Second, evolutionary inferences have been drawn from paralog analysis without consideration for concurrent and subsequent duplication events. Third, the theoretical model of prodigious neofunctionalization is unable to reproduce empirical network clustering and relies on untenable parameter requirements. In light of these findings, we believe that protein interaction evolution is more persuasively characterized by subfunctionalization and self-interactions.

An evolutionary and structural characterization of mammalian protein complex organization

Background

We have recently released a comprehensive, manually curated database of mammalian protein complexes called CORUM. Combining CORUM with other resources, we assembled a dataset of over 2700 mammalian complexes. The availability of a rich information resource allows us to search for organizational properties concerning these complexes.

Results

As the complexity of a protein complex in terms of the number of unique subunits increases, we observed that the number of such complexes and the mean non-synonymous to synonymous substitution ratio of associated genes tend to decrease. Similarly, as the number of different complexes a given protein participates in increases, the number of such proteins and the substitution ratio of the associated gene also tends to decrease. These observations provide evidence relating natural selection and the organization of mammalian complexes. We also observed greater homogeneity in terms of predicted protein isoelectric points, secondary structure and substitution ratio in annotated versus randomly generated complexes. A large proportion of the protein content and interactions in the complexes could be predicted from known binary protein-protein and domain-domain interactions. In particular, we found that large proteins interact preferentially with much smaller proteins.

Conclusion

We observed similar trends in yeast and other data. Our results support the existence of conserved relations associated with the mammalian protein complexes.

Complex fate of paralogs

Background

Thanks to recent high coverage mass-spectrometry studies and reconstructed protein complexes, we are now in an unprecedented position to study the evolution of biological systems. Gene duplications, known to be a major source of innovation in evolution, can now be readily examined in the context of protein complexes.

Results

We observe that paralogs operating in the same complex fulfill different roles: mRNA dosage increase for more than a hundred cytosolic ribosomal proteins, mutually exclusive participation of at least 54 paralogs resulting in alternative forms of complexes, and 24 proteins contributing to bona fide structural growth. Inspection of paralogous proteins participating in two independent complexes shows that an ancient, pre-duplication protein functioned in both multi-protein assemblies and a gene duplication event allowed the respective copies to specialize and split their roles.

Conclusion

Variants with conditionally assembled, paralogous subunits likely have played a role in yeast's adaptation to anaerobic conditions. In a number of cases the gene duplication has given rise to one duplicate that is no longer part of a protein complex and shows an accelerated rate of evolution. Such genes could provide the raw material for the evolution of new functions.

Age-dependent evolution of the yeast protein interaction network suggests a limited role of gene duplication and divergence

Proteins interact in complex protein–protein interaction (PPI) networks whose topological properties—such as scale-free topology, hierarchical modularity, and dissortativity—have suggested models of network evolution. Currently preferred models invoke preferential attachment or gene duplication and divergence to produce networks whose topology matches that observed for real PPIs, thus supporting these as likely models for network evolution. Here, we show that the interaction density and homodimeric frequency are highly protein age–dependent in real PPI networks in a manner which does not agree with these canonical models. In light of these results, we propose an alternative stochastic model, which adds each protein sequentially to a growing network in a manner analogous to protein crystal growth (CG) in solution. The key ideas are (1) interaction probability increases with availability of unoccupied interaction surface, thus following an anti-preferential attachment rule, (2) as a network grows, highly connected sub-networks emerge into protein modules or complexes, and (3) once a new protein is committed to a module, further connections tend to be localized within that module. The CG model produces PPI networks consistent in both topology and age distributions with real PPI networks and is well supported by the spatial arrangement of protein complexes of known 3-D structure, suggesting a plausible physical mechanism for network evolution.

Proteins function together forming stable protein complexes or transient interactions in various cellular processes, such as gene regulation and signaling. Here, we address the basic question of how these networks of interacting proteins evolve. This is an important problem, as the structures of such networks underlie important features of biological systems, such as functional modularity, error-tolerance, and stability. It is not yet known how these network architectures originate or what driving forces underlie the observed network structure. Several models have been proposed over the past decade—in particular, a “rich get richer” model (preferential attachment) and a model based upon gene duplication and divergence—often based only on network topologies. Here, we show that real yeast protein interaction networks show a unique age distribution among interacting proteins, which rules out these canonical models. In light of these results, we developed a simple, alternative model based on well-established physical principles, analogous to the process of growing protein crystals in solution. The model better explains many features of real PPI networks, including the network topologies, their characteristic age distributions, and the spatial distribution of subunits of differing ages within protein complexes, suggesting a plausible physical mechanism of network evolution.

Dynamics of receptor and protein transducer homodimerisation

Background

Signalling pathways are complex systems in which not only simple monomeric molecules interact, but also more complex structures that include constitutive or induced protein assemblies. In particular, the hetero-and homo-dimerisation of proteins is a commonly encountered motif in signalling pathways. Several authors have suggested in recent times that dimerisation relates to a series of physical and biological outcomes used by the cell in the regulation of signal transduction.

Results

In this paper we investigate the role of homodimerisation in receptor-protein transducer interactions. Towards this end, mathematical modelling is used to analyse the features of such kind of interactions and to predict the behaviour of the system under different experimental conditions. A kinetic model in which the interaction between homodimers provokes a dual mechanism of activation (single and double protein transducer activation at the same time) is proposed. In addition, we analyse under which conditions the use of a power-law representation for the system is useful. Furthermore, we investigate the dynamical consequences of this dual mechanism and compare the performance of the system in different simulated experimental conditions.

Conclusion

The analysis of our mathematical model suggests that in receptor-protein interacting systems with dual mechanism there may be a shift between double and single activation in a way that intense double protein transducer activation could initiate and dominate the signal in the short term (getting a fast intense signal), while single protein activation could control the system in the medium and long term (when input signal is weaker and decreases slowly). Our investigation suggests that homodimerisation and oligomerisation are mechanisms used to enhance and regulate the dynamic properties of the initial steps in signalling pathways.

Comparative genomic analysis of the odorant-binding protein family in 12 Drosophila genomes: purifying selection and birth-and-death evolution

The comparative analysis of the odorant binding protein family in 12 Drosophila genomes allowed the identification of 595 putative family member genes and revealed insights into the evolution of this family in these species.

Background

Chemoreception is a widespread mechanism that is involved in critical biologic processes, including individual and social behavior. The insect peripheral olfactory system comprises three major multigene families: the olfactory receptor (Or), the gustatory receptor (Gr), and the odorant-binding protein (OBP) families. Members of the latter family establish the first contact with the odorants, and thus constitute the first step in the chemosensory transduction pathway.

Results

Comparative analysis of the OBP family in 12 Drosophila genomes allowed the identification of 595 genes that encode putative functional and nonfunctional members in extant species, with 43 gene gains and 28 gene losses (15 deletions and 13 pseudogenization events). The evolution of this family shows tandem gene duplication events, progressive divergence in DNA and amino acid sequence, and prevalence of pseudogenization events in external branches of the phylogenetic tree. We observed that the OBP arrangement in clusters is maintained across the Drosophila species and that purifying selection governs the evolution of the family; nevertheless, OBP genes differ in their functional constraints levels. Finally, we detect that the OBP repertoire evolves more rapidly in the specialist lineages of the Drosophila melanogaster group (D. sechellia and D. erecta) than in their closest generalists.

Conclusion

Overall, the evolution of the OBP multigene family is consistent with the birth-and-death model. We also found that members of this family exhibit different functional constraints, which is indicative of some functional divergence, and that they might be involved in some of the specialization processes that occurred through the diversification of the Drosophila genus.

Interacting gene clusters and the evolution of the vertebrate immune system

Unraveling the "code" of genome structure is an important goal of genomics research. Colocalization of genes in eukaryotic genomes may facilitate preservation of favorable allele combinations between epistasic loci or coregulation of functionally related genes. However, the presence of interacting gene clusters in the human genome has remained unclear. We systematically searched the human genome for evidence of closely linked genes whose protein products interact. We find 83 pairs of interacting genes that are located within 1 Mbp in the human genome or 37 if we exclude hub proteins. This number of interacting gene clusters is significantly more than expected by chance and is not the result of tandem duplications. Furthermore, we find that these clusters are significantly more conserved across vertebrate (but not chordate) genomes than other pairs of genes located within 1 Mbp in the human genome. In many cases, the genes are both present but not clustered in older vertebrate lineages. These results suggest gene cluster creation along the human lineage. These clusters are not enriched for housekeeping genes, but we find a significant contribution from genes involved in "response to stimulus." Many of these genes are involved in the immune response, including, but not limited to, known clusters such as the major histocompatibility complex. That these clusters were formed contemporaneously with the origin of adaptive immunity within the vertebrate lineage suggests that novel evolutionary and regulatory constraints were associated with the operation of the immune system.

Assembly reflects evolution of protein complexes

A homomer is formed by self-interacting copies of a protein unit. This is functionally important, as in allostery, and structurally crucial because mis-assembly of homomers is implicated in disease. Homomers are widespread, with 50-70% of proteins with a known quaternary state assembling into such structures. Despite their prevalence, their role in the evolution of cellular machinery and the potential for their use in the design of new molecular machines, little is known about the mechanisms that drive formation of homomers at the level of evolution and assembly in the cell. Here we present an analysis of over 5,000 unique atomic structures and show that the quaternary structure of homomers is conserved in over 70% of protein pairs sharing as little as 30% sequence identity. Where quaternary structure is not conserved among the members of a protein family, a detailed investigation revealed well-defined evolutionary pathways by which proteins transit between different quaternary structure types. Furthermore, we show by perturbing subunit interfaces within complexes and by mass spectrometry analysis, that the (dis)assembly pathway mimics the evolutionary pathway. These data represent a molecular analogy to Haeckel's evolutionary paradigm of embryonic development, where an intermediate in the assembly of a complex represents a form that appeared in its own evolutionary history. Our model of self-assembly allows reliable prediction of evolution and assembly of a complex solely from its crystal structure.

Subunit architecture of intact protein complexes from mass spectrometry and homology modeling

Proteomic studies have yielded detailed lists of protein components. Relatively little is known, however, of interactions between proteins or of their spatial arrangement. To bridge this gap, we are developing a mass spectrometry approach based on intact protein complexes. By studying intact complexes, we show that we are able to not only determine the stoichiometry of all subunits present but also deduce interaction maps and topological arrangements of subunits. To construct an interaction network, we use tandem mass spectrometry to define peripheral subunits and partial denaturation in solution to generate series of subcomplexes. These subcomplexes are subsequently assigned using tandem mass spectrometry. To facilitate this assignment process, we have developed an iterative search algorithm (SUMMIT) to both assign protein subcomplexes and generate protein interaction networks. This software package not only allows us to construct the subunit architecture of protein assemblies but also allows us to explore the limitations and potential of our approach. Using series of hypothetical complexes, generated at random from protein assemblies containing between six and fourteen subunits, we highlight the significance of tandem mass spectrometry for defining subunits present. We also demonstrate the importance of pairwise interactions and the optimal numbers of subcomplexes required to assign networks with up to fourteen subunits. To illustrate application of our approach, we describe the overall architecture of two endogenous protein assemblies isolated from yeast at natural expression levels, the 19S proteasome lid and the RNA exosome. In constructing our models, we did not consider previous electron microscopy images but rather deduced the subunit architecture from series of subcomplexes and our network algorithm. The results show that the proteasome lid complex consists of a bicluster with two tetrameric lobes. The exosome lid, by contrast, is a six-membered ring with three additional bridging subunits that confer stability to the ring and with a large subunit located at the base. Significantly, by combining data from MS and homology modeling, we were able to construct an atomic model of the yeast exosome. In summary, the architectural and atomic models of both protein complexes described here have been produced in advance of high-resolution structural data and as such provide an initial model for testing hypotheses and planning future experiments. In the case of the yeast exosome, the atomic model is validated by comparison with the atomic structure from X-ray diffraction of crystals of the reconstituted human exosome, which is homologous to that of the yeast. Overall therefore this mass spectrometry and homology modeling approach has given significant insight into the structure of two previously intractable protein complexes and as such has broad application in structural biology.

Choose your partners: dimerization in eukaryotic transcription factors

In many eukaryotic transcription factor gene families, proteins require a physical interaction with an identical molecule or with another molecule within the same family to form a functional dimer and bind DNA. Depending on the choice of partner and the cellular context, each dimer triggers a sequence of regulatory events that lead to a particular cellular fate, for example, proliferation or differentiation. Recent syntheses of genomic and functional data reveal that partner choice is not random; instead, dimerization specificities, which are strongly linked to the evolution of the protein family, apply. Our focus is on understanding these interaction specificities, their functional consequences and how they evolved. This knowledge is essential for understanding gene regulation and designing a new generation of drugs.

Large-scale screening for novel low-affinity extracellular protein interactions

Extracellular protein-protein interactions are essential for both intercellular communication and cohesion within multicellular organisms. Approximately a fifth of human genes encode membrane-tethered or secreted proteins, but they are largely absent from recent large-scale protein interaction datasets, making current interaction networks biased and incomplete. This discrepancy is due to the unsuitability of popular high-throughput methods to detect extracellular interactions because of the biochemical intractability of membrane proteins and their interactions. For example, cell surface proteins contain insoluble hydrophobic transmembrane regions, and their extracellular interactions are often highly transient, having half-lives of less than a second. To detect transient extracellular interactions on a large scale, we developed AVEXIS (avidity-based extracellular interaction screen), a high-throughput assay that overcomes these technical issues and can detect very transient interactions (half-lives <or= 0.1 sec) with a low false-positive rate. We used it to systematically screen for receptor-ligand pairs within the zebrafish immunoglobulin superfamily and identified novel ligands for both well-known and orphan receptors. Genes encoding receptor-ligand pairs were often clustered phylogenetically and expressed in the same or adjacent tissues, immediately implying their involvement in similar biological processes. Using AVEXIS, we have determined the first systematic low-affinity extracellular protein interaction network, supported by independent biological data. This technique will now allow large-scale extracellular protein interaction mapping in a broad range of experimental contexts.

The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins.

A large scale analysis of protein-protein interactions in the nitrogen-fixing bacterium Mesorhizobium loti

Global viewing of protein–protein interactions (PPIs) is a useful way to assign biological roles to large numbers of proteins predicted by complete genome sequence. Here, we systematically analyzed PPIs in the nitrogen-fixing soil bacterium Mesorhizobium loti using a modified high-throughput yeast two-hybrid system. The aims of this study are primarily on the providing functional clues to M. loti proteins that are relevant to symbiotic nitrogen fixation and conserved in other rhizobium species, especially proteins with regulatory functions and unannotated proteins. By the screening of 1542 genes as bait, 3121 independent interactions involving 1804 proteins (24% of the total protein coding genes) were identified and each interaction was evaluated using an interaction generality (IG) measure and the general features of the interacting partners. Most PPIs detected in this study are novel interactions revealing potential functional relationships between genes for symbiotic nitrogen fixation and signal transduction. Furthermore, we have predicted the putative functions of unannotated proteins through their interactions with known proteins. The results described here represent new insight into protein network of M. loti and provide useful experimental clues to elucidate the biological function of rhizobial genes that can not be assigned directly from their genomic sequence.

A simple principle concerning the robustness of protein complex activity to changes in gene expression

Background

The functions of a eukaryotic cell are largely performed by multi-subunit protein complexes that act as molecular machines or information processing modules in cellular networks. An important problem in systems biology is to understand how, in general, these molecular machines respond to perturbations.

Results

In yeast, genes that inhibit growth when their expression is reduced are strongly enriched amongst the subunits of multi-subunit protein complexes. This applies to both the core and peripheral subunits of protein complexes, and the subunits of each complex normally have the same loss-of-function phenotypes. In contrast, genes that inhibit growth when their expression is increased are not enriched amongst the core or peripheral subunits of protein complexes, and the behaviour of one subunit of a complex is not predictive for the other subunits with respect to over-expression phenotypes.

Conclusion

We propose the principle that the overall activity of a protein complex is in general robust to an increase, but not to a decrease in the expression of its subunits. This means that whereas phenotypes resulting from a decrease in gene expression can be predicted because they cluster on networks of protein complexes, over-expression phenotypes cannot be predicted in this way. We discuss the implications of these findings for understanding how cells are regulated, how they evolve, and how genetic perturbations connect to disease in humans.

Multiple domain insertions and losses in the evolution of the Rab prenylation complex

BACKGROUND

Rab proteins are regulators of vesicular trafficking, requiring a lipid modification for proper function, prenylation of C-terminal cysteines. This is catalysed by a complex of a catalytic heterodimer (Rab Geranylgeranyl Transferase - RabGGTase) and an accessory protein (Rab Escort Protein. REP). Components of this complex display domain insertions relative to paralogous proteins. The function of these inserted domains is unclear.

RESULTS

We profiled the domain architecture of the components of the Rab prenylation complex in evolution. We identified the orthologues of the components of the Rab prenylation machinery in 43 organisms, representing the crown eukaryotic groups. We characterize in detail the domain structure of all these components and the phylogenetic relationships between the individual domains.

CONCLUSION

We found different domain insertions in different taxa, in alpha-subunits of RGGTase and REP. Our results suggest that there were multiple insertions, expansions and contractions in the evolution of this prenylation complex.