The evolution of protein interaction networks in regulatory proteins

Domain Architecture Based Methods for Comparative Functional Genomics Toward Therapeutic Drug Target Discovery

Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction

Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.

Genome-wide analysis of basic helix-loop-helix transcription factors in papaya (Carica papaya L.)

The basic helix-loop-helix (bHLH) transcription factors (TFs) have been identified and functionally characterized in many plants. However, no comprehensive analysis of the bHLH family in papaya (Carica papaya L.) has been reported previously. Here, a total of 73 CpbHLHs were identified in papaya, and these genes were classified into 18 subfamilies based on phylogenetic analysis. Almost all of the CpbHLHs in the same subfamily shared similar gene structures and protein motifs according to analysis of exon/intron organizations and motif compositions. The number of exons in CpbHLHs varied from one to 10 with an average of five. The amino acid sequences of the bHLH domains were quite conservative, especially Leu-27 and Leu-63. Promoter cis-element analysis revealed that most of the CpbHLHs contained cis-elements that can respond to various biotic/abiotic stress-related events. Gene ontology (GO) analysis revealed that CpbHLHs mainly functions in protein dimerization activity and DNA-binding, and most CpbHLHs were predicted to localize in the nucleus. Abiotic stress treatment and quantitative real-time PCR (qRT-PCR) revealed some important candidate CpbHLHs that might be responsible for abiotic stress responses in papaya. These findings would lay a foundation for further investigate of the molecular functions of CpbHLHs.

Construction, comparison and evolution of networks in life sciences and other disciplines

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through different disciplines, such as social sciences, finance and computational gastronomy, to present commonalities and differences in how networks change and can be analysed. Finally, we envision how borrowing ideas from these disciplines could enrich the future of life science research.

Genome-Wide Identification and Characterization of the Potato bHLH Transcription Factor Family

Plant basic/helix–loop–helix (bHLH) transcription factors participate in a number of biological processes, such as growth, development and abiotic stress responses. The bHLH family has been identified in many plants, and several bHLH transcription factors have been functionally characterized in Arabidopsis. However, no systematic identification of bHLH family members has been reported in potato (Solanum tuberosum). Here, 124 StbHLH genes were identified and named according to their chromosomal locations. The intron numbers varied from zero to seven. Most StbHLH proteins had the highly conserved intron phase 0, which accounted for 86.2% of the introns. According to the Neighbor-joining phylogenetic tree, 259 bHLH proteins acquired from Arabidopsis and potato were divided into 15 groups. All of the StbHLH genes were randomly distributed on 12 chromosomes, and 20 tandem duplicated genes and four pairs of duplicated gene segments were detected in the StbHLH family. The gene ontology (GO) analysis revealed that StbHLH mainly function in protein and DNA binding. Through the RNA-seq and quantitative real time PCR (qRT-PCR) analyses, StbHLH were found to be expressed in various tissues and to respond to abiotic stresses, including salt, drought and heat. StbHLH1, 41 and 60 were highly expressed in flower tissues, and were predicted to be involved in flower development by GO annotation. StbHLH45 was highly expressed in salt, drought and heat stress, which suggested its important role in abiotic stress response. The results provide comprehensive information for further analyses of the molecular functions of the StbHLH gene family.

Functional study of the Hap4-like genes suggests that the key regulators of carbon metabolism HAP4 and oxidative stress response YAP1 in yeast diverged from a common ancestor

The transcriptional regulator HAP4, induced by respiratory substrates, is involved in the balance between fermentation and respiration in S. cerevisiae. We identified putative orthologues of the Hap4 protein in all ascomycetes, based only on a conserved sixteen amino acid-long motif. In addition to this motif, some of these proteins contain a DNA-binding motif of the bZIP type, while being nonetheless globally highly divergent. The genome of the yeast Hansenula polymorpha contains two HAP4-like genes encoding the protein HpHap4-A which, like ScHap4, is devoid of a bZIP motif, and HpHap4-B which contains it. This species has been chosen for a detailed examination of their respective properties. Based mostly on global gene expression studies performed in the S. cerevisiae HAP4 disruption mutant (ScΔhap4), we show here that HpHap4-A is functionally equivalent to ScHap4, whereas HpHap4-B is not. Moreover HpHAP4-B is able to complement the H₂O₂ hypersensitivity of the ScYap1 deletant, YAP1 being, in S. cerevisiae, the main regulator of oxidative stress. Finally, a transcriptomic analysis performed in the ScΔyap1 strain overexpressing HpHAP4-B shows that HpHap4-B acts both on oxidative stress response and carbohydrate metabolism in a manner different from both ScYap1 and ScHap4. Deletion of these two genes in their natural host, H. polymorpha, confirms that HpHAP4-A participates in the control of the fermentation/respiration balance, while HpHAP4-B is involved in oxidative stress since its deletion leads to hypersensitivity to H₂O₂. These data, placed in an evolutionary context, raise new questions concerning the evolution of the HAP4 transcriptional regulation function and suggest that Yap1 and Hap4 have diverged from a unique regulatory protein in the fungal ancestor.

A conserved domain in the N-terminus is important for LEAFY dimerization and function in Arabidopsis thaliana

The floral meristem identity gene LEAFY (LFY) of Arabidopsis thaliana is essential for the formation of fertile flowers and has roles in the control of several aspects of floral development, which include phyllotaxy and organ number and identity. This gene encodes a land plant-specific transcription factor and regulates expression of a number of genes that include other floral meristem identity genes and floral homeotic genes. Although the LFY DNA-binding domain has a structure that resembles that of helix-turn-helix proteins, LFY and its orthologs represent a novel family of transcription factors that are characterized by a conserved N-terminus domain of unknown function and a C-terminus DNA-binding domain. Many transcription factors act as dimers. These dimers are essential for the biological activity of the proteins. We demonstrate that LFY forms homodimers or oligomers in solution. This association is mediated through the N-terminus conserved region of the LFY protein. Although mutant LFY proteins that cannot dimerize in solution can bind DNA, the binding is weaker than that of wild type LFY protein. LFY-LFY interactions mediated by the N-terminus domain are essential for the biological activity of this protein, as mutations that abolish the ability to self-associate cannot complement an lfy null allele. Our data indicate: (i) that LFY, and probably its orthologs in other plants, must act in complexes that contain at least two LFY molecules; and (ii) that the N-terminus is essential for stabilization of LFY complexes. This situation is integral to the ability of LFY to regulate gene expression.

Accurate discrimination of bHLH domains in plants, animals, and fungi using biologically meaningful sites

Background

The highly conserved bHLH (basic Helix-Loop-Helix) domain, found in many transcription factors, has been well characterized separately in Plants, Animals, and Fungi. While conserved, even functionally constrained sites have varied since the Eukarya split. Our research identifies those slightly variable sites that were highly characteristic of Plants, Animals, or Fungi.

Results

Through discriminant analysis, we identified five highly discerning DNA-binding amino acid sites. Additionally, by incorporating Kingdom specific HMMs, we were able to construct a tool to quickly and accurately identify and classify bHLH sequences using these sites.

Conclusions

We conclude that highly discerning sites identified through our analysis were likely under functional constraints specific to each Kingdom. We also demonstrated the utility of our tool by identifying and classifying previously unknown bHLH domains in both characterized genomes and from sequences in a large environmental sample.

Evolutionary and comparative analysis of MYB and bHLH plant transcription factors

The expansion of gene families encoding regulatory proteins is typically associated with the increase in complexity characteristic of multi-cellular organisms. The MYB and basic helix-loop-helix (bHLH) families provide excellent examples of how gene duplication and divergence within particular groups of transcription factors are associated with, if not driven by, the morphological and metabolic diversity that characterize the higher plants. These gene families expanded dramatically in higher plants; for example, there are approximately 339 and 162 MYB and bHLH genes, respectively, in Arabidopsis, and approximately 230 and 111, respectively, in rice. In contrast, the Chlamydomonas genome has only 38 MYB genes and eight bHLH genes. In this review, we compare the MYB and bHLH gene families from structural, evolutionary and functional perspectives. The knowledge acquired on the role of many of these factors in Arabidopsis provides an excellent reference to explore sequence-function relationships in crops and other plants. The physical interaction and regulatory synergy between particular sub-classes of MYB and bHLH factors is perhaps one of the best examples of combinatorial plant gene regulation. However, members of the MYB and bHLH families also interact with a number of other regulatory proteins, forming complexes that either activate or repress the expression of sets of target genes that are increasingly being identified through a diversity of high-throughput genomic approaches. The next few years are likely to witness an increasing understanding of the extent to which conserved transcription factors participate at similar positions in gene regulatory networks across plant species.

A catalogue of eukaryotic transcription factor types, their evolutionary origin, and species distribution

Transcription factors (TFs) play key roles in the regulation of gene expression by binding in a sequence-specific manner to genomic DNA. In eukaryotes, DNA binding is achieved by a wide range of structural forms and motifs. TFs are typically classified by their DNA-binding domain (DBD) type. In this chapter, we catalogue and survey 91 different TF DBD types in metazoa, plants, fungi, and protists. We briefly discuss well-characterized TF families representing the major DBD superclasses. We also examine the species distributions and inferred evolutionary histories of the various families, and the potential roles played by TF family expansion and dimerization.

The evolutionary influence of binding site organisation on gene regulatory networks

Gene regulatory networks are shaped by selection for advantageous gene expression patterns. Can we use this fact to predict and explain the structure and properties of gene regulatory networks? Here we address this question with evolutionary simulations of small (two to four genes) transcriptional regulatory networks. Each modeled network is tested for the frequency with which it evolves to produce a bimodal spatial expression pattern of a target gene (the output), in response to a linear trigger gradient (the input). By including network features such as the organisation of binding sites that do not evolve in the model, we can compare the relative chances of evolutionary success between networks differing only in these features. Specifically, we show that networks with competitive binding sites (where binding of one transcription factor excludes another) are more likely to evolve bimodal patterns of gene repression than are networks with independent binding sites (where binding of multiple transcription factors can occur simultaneously). These predictions have implications for the likely structure of gene regulatory networks carrying out bimodal (including bistable) gene expression functions in vivo. The capacity to predict the evolution of structure-function relationships in gene regulatory networks is constrained by gaps in current understanding such as the unknown prior probabilities of the network features, and the quantitative nature of the molecular interactions involved in gene expression. Methods for the circumvention of these constraints, and the potential of the evolutionary modeling approach, are discussed.

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

BACKGROUND

Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example.

RESULTS

Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected.

CONCLUSION

We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network

BACKGROUND

The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved.

RESULTS

Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors.

CONCLUSION

We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Spectral analysis of protein-protein interactions in Drosophila melanogaster

Within a case study on the protein-protein interaction network (PIN) of Drosophila melanogaster we investigate the relation between the network's spectral properties and its structural features. The frequencies of loops of any size within the network can be derived from the spectrum; also the prevalence of specific subgraphs as a result of the network's evolutionary history affects its spectrum. The discrete part of the spectral density shows fingerprints of the PIN's topological features including a preference for loop structures. Duplicate nodes are also characteristic for PINs and we discuss their representation in the PIN's spectrum as well as their biological implications.

Phylogenetic profiling of protein interaction networks in eukaryotic transcription factors reveals focal proteins being ancestral to hubs

The combination of genomic, proteomic and other data, enables to reconstruct the evolution of complex cellular units thus transcending the more reductionistic view of traditional molecular phylogeny. However, most models which try to investigate the evolution of protein interaction networks so far are based on the analysis of their global statistical properties, such as their scale-free behaviour. We have investigated phylogenies of three families of ancient eukaryotic transcription factors for which fairly reliable interaction data are available. For all three families, bZIP, bHLH and NR (nuclear receptors), we find that homo-dimerising proteins were probably the ancestors and that series of single gene duplications, in combination with domain-rearrangements, were the main driving force in establishing the basic network architecture. However, the overall scaling behaviour does not always precisely confer to some theoretical models on network evolution. In conclusion, new models which reflect the biological details of molecular evolution, need to be developed.