Localized network centrality and essentiality in the yeast–protein interaction network

It has been suggested that a close relationship exists between gene essentiality and network centrality in protein–protein interaction networks. However, recent studies have reported somewhat conflicting results on this relationship. In this study, we investigated whether essential proteins could be inferred from network centrality alone. In addition, we determined which centrality measures describe the essentiality well. For this analysis, we devised new local centrality measures based on several well‐known centrality measures to more precisely describe the connection between network topology and essentiality. We examined two recent yeast protein–protein interaction networks using 40 different centrality measures. We discovered a close relationship between the path‐based localized information centrality and gene essentiality, which suggested underlying topological features that represent essentiality. We propose that two important features of the localized information centrality (proper representation of environmental complexity and the consideration of local sub‐networks) are the key factors that reveal essentiality. In addition, a random forest classifier showed reasonable performance at classifying essential proteins. Finally, the results of clustering analysis using centrality measures indicate that some network clusters are closely related with both particular biological processes and essentiality, suggesting that functionally related proteins tend to share similar network properties.     

Understanding gene essentiality by finely characterizing hubs in the yeast protein interaction network

The centrality-lethality rule, i.e., high-degree proteins or hubs tend to be more essential than low-degree proteins in the yeast protein interaction network, reveals that a protein’s central position indicates its important function, but whether and why hubs tend to be more essential have been heavily debated. Here, we integrated gene expression and functional module data to classify hubs into four types: non-co-expressed non-co-cluster hubs, non-co-expressed co-cluster hubs, co-expressed non-co-cluster hubs and co-expressed co-cluster hubs. We found that all the four hub types are more essential than non-hubs, but they also show different enrichments in essential proteins. Non-co-expressed non-co-cluster hubs play key role in organizing different modules formed by the other three hub types, but they are less important to the survival of the yeast cell. Among the four hub types, co-expressed co-cluster hubs, which likely correspond to the core components of stable protein complexes, are the most essential. These results demonstrated that our classification of hubs into four types could better improve the understanding of gene essentiality.     

Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins

Understanding the determinants of the rate of protein sequenceevolution is of fundamental importance in evolutionary biology.Many recent studies have focused on the yeast because of theavailability of many genome-wide expressional and functionaldata. Yeast studies revealed a predominant role of gene expressionlevel and a minor role of gene essentiality in determining therate of protein sequence evolution. Whether these rules applyto complex organisms such as mammals is unclear. Here we assemblea list of 1,138 essential and 2,341 nonessential mouse genesbased on targeted gene deletion experiments and report a significantimpact of gene essentiality on the rate of mammalian proteinevolution. Gene expression level has virtually no effect, althoughtissue specificity in expression pattern has a strong influence.Unexpectedly, gene compactness, measured by average intron sizeand untranslated region length, has the greatest influence.Hence, the relative importance of the various factors in determiningthe rate of mammalian protein evolution is gene compactness> gene essentiality tissue specificity > expression level.Our results suggest a considerable variation in rate determinantsbetween unicellular organisms such as the yeast and multicellularorganisms such as mammals.     

Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality

The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.     

Evolution of gene sequence and gene expression are not correlated in yeast

We show that, in yeast, the divergence rate of gene expression is not correlated with that of its associated coding sequence. Gene essentiality influences both modes of evolution, but other properties related to protein structure or promoter composition are only correlated with coding-sequence divergence or gene expression divergence, respectively. Based on these findings, we discuss the possibilities of neutral evolution of gene expression and of different modes of evolution in unicellular versus multicellular organisms.     

Gene essentiality and the topology of protein interaction networks

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology.     

Thematic review series: lipid posttranslational modifications. GPI anchoring of protein in yeast and mammalian cells, or: how we learned to stop worrying and love glycophospholipids

Glycosylphosphatidylinositol (GPI) anchoring of cell surface proteins is the most complex and metabolically expensive of the lipid posttranslational modifications described to date. The GPI anchor is synthesized via a membrane-bound multistep pathway in the endoplasmic reticulum (ER) requiring >20 gene products. The pathway is initiated on the cytoplasmic side of the ER and completed in the ER lumen, necessitating flipping of a glycolipid intermediate across the membrane. The completed GPI anchor is attached to proteins that have been translocated across the ER membrane and that display a GPI signal anchor sequence at the C terminus. GPI proteins transit the secretory pathway to the cell surface; in yeast, many become covalently attached to the cell wall. Genes encoding proteins involved in all but one of the predicted steps in the assembly of the GPI precursor glycolipid and its transfer to protein in mammals and yeast have now been identified. Most of these genes encode polytopic membrane proteins, some of which are organized in complexes. The steps in GPI assembly, and the enzymes that carry them out, are highly conserved. GPI biosynthesis is essential for viability in yeast and for embryonic development in mammals. In this review, we describe the biosynthesis of mammalian and yeast GPIs, their transfer to protein, and their subsequent processing.     

Characterization of protein hubs by inferring interacting motifs from protein interactions

The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75% at sensitivity of 10%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.     

Gene duplication and hierarchical modularity in intracellular interaction networks

Networks of interactions evolve in many different domains. They tend to have topological characteristics in common, possibly due to common factors in the way the networks grow and develop. It has been recently suggested that one such common characteristic is the presence of a hierarchically modular organization. In this paper, we describe a new algorithm for the detection and quantification of hierarchical modularity, and demonstrate that the yeast protein-protein interaction network does have a hierarchically modular organization. We further show that such organization is evident in artificial networks produced by computational evolution using a gene duplication operator, but not in those developing via preferential attachment of new nodes to highly connected existing nodes.     

Protein bipartivity and essentiality in the yeast protein-protein interaction network

Protein-protein interaction networks (PINs) are structured by means of a few highly connected proteins linked to a large number of less-connected ones. Essential proteins have been found to be more abundant among these highly connected proteins. Here we demonstrate that the likelihood that removal of a protein in a PIN will prove lethal to yeast correlates with the lack of bipartivity of the protein. A protein is bipartite if it can be partitioned in such a way that there are two groups of proteins with intergroup, but not intragroup, interactions. The abundance of essential proteins found among the least bipartite proteins clearly exceeds that found among the most connected ones. For instance, among the top 50 proteins ranked by their lack of bipartivity 62% are essential proteins. However, this percentage is only 38% for proteins ranked according to their number of interactions. Protein bipartivity also surpasses another 5 measures of protein centrality in yeast PIN in identifying essential proteins and doubles the number of essential proteins selected at random. We propose a possible mechanism for the evolution of essential proteins in yeast PIN based on the duplication-divergence scheme. We conclude that a replica protein evolving from a nonbipartite target will also be nonbipartite with high probability. Consequently, these new replicas evolving from nonbipartite (essential) targets will with high probability be essential.     

Quantitative assessment of the structural bias in protein-protein interaction assays

With recent publications of several large-scale protein-protein interaction (PPI) studies, the realization of the full yeast interaction network is getting closer. Here, we have analysed several yeast protein interaction datasets to understand their strengths and weaknesses. In particular, we investigate the effect of experimental biases on some of the protein properties suggested to be enriched in highly connected proteins. Finally, we use support vector machines (SVM) to assess the contribution of these properties to protein interactivity. We find that protein abundance is the most important factor for detecting interactions in tandem affinity purifications (TAP), while it is of less importance for Yeast Two Hybrid (Y2H) screens. Consequently, sequence conservation and/or essentiality of hubs may be related to their high abundance. Further, proteins with disordered structure are over-represented in Y2H screens and in one, but not the other, large-scale TAP assay. Hence, disordered regions may be important both in transient interactions and interactions in complexes. Finally, a few domain families seem to be responsible for a large part of all interactions. Most importantly, we show that there are method-specific biases in PPI experiments. Thus, care should be taken before drawing strong conclusions based on a single dataset.     

Highly divergent amino termini of the homologous human ALR and yeast scERV1 gene products define species specific differences in cellular localization.

The yeast scERV1 gene product is involved in the biogenesis of mitochondria and is indispensable for viability and regulation of the cell cycle. Recently the general importance of this gene for the eukaryotic cell was shown by the identification of a structural and functional human homologue. The homologous mammalian ALR (Augmenter of Liver Regeneration) genes from man, mouse and rat are involved in the phenomenon of liver regeneration. A low expression rate of the genes is found in all investigated cells and mammalian tissues but it is specifically induced after damage of liver organs and is especially high during spermatogenesis. The alignment of the different proteins identifies a highly conserved carboxy terminus with more than 40% identical amino acids between yeast and mammals. The conserved carboxy terminus is functionally interchangeable between distantly related species like yeast and man. In contrast, the amino terminal parts of the proteins display a high degree of variability and significant differences even among closely related species. This finding leads to the problem whether the amino termini have comparable or divergent functions in different species. In this study we demonstrate by heterologous complementation experiments in yeast that the complete human ALR protein with its own amino terminus is not able to substitute for the yeast scERV1 protein. Fusion proteins of Alrp and scErv1p with the green fluorescence protein were created to investigate the respective subcellular localizations of these homologous proteins in yeast and human cells. In yeast cells human Alrp accumulates in the cytoplasm in contrast to yeast scErv1p that is preferentially associated with yeast mitochondria. Comparable studies with human cells clearly show that the homologous human Alrp is located in the cytosol of these cells. Fractionation experiments and antibody tests with yeast and human mitochondria and cellular extracts verify these findings.     

Cloning and characterization of two mouse genes with homology to the yeast Sir2 gene

The yeast Sir2 gene encodes a protein (Sir2p) that plays an essential role in silencing regulation at mating-type loci, rDNA, and telomeres. Recent studies have also shown that the protein participates in cell cycle regulation, DNA double-strand break repair, meiotic checkpoint control, and histone deacetylation. Overexpression of wildtype Sir2p in yeast resulted in an extended life span but mutant Sir2p shortened the life span, suggesting its function in aging processes. Sir2p is evolutionarily conserved from prokaryotes to higher eukaryotes. However, its function(s) in mammals remains unknown. To investigate Sir2p function(s) in mice, we cloned and characterized two mouse Sir2-like genes. Our results revealed that the two mouse Sir2-like proteins (mSIR2L2 and mSIR2L3) are most similar to the human Sir2-like proteins SIR2L2 and SIR2L3, respectively. Sir2 core domains are highly conserved in the two proteins and yeast Sir2p; however, the intracellular localizations of both mSIR2L2 and mSIR2L3 differ from that of yeast Sir2p and from one another. The two mouse genes have completely different genomic structures but were mapped on the same chromosome. It seems that the two mouse proteins, though they have Sir2 conserved domains, may function differently than yeast Sir2p.     

Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology

Background  

In many protein-protein interaction (PPI) networks, densely connected hub proteins are more likely to be essential proteins. This is referred to as the "centrality-lethality rule", which indicates that the topological placement of a protein in PPI network is connected with its biological essentiality. Though such connections are observed in many PPI networks, the underlying topological properties for these connections are not yet clearly understood. Some suggested putative connections are the involvement of essential proteins in the maintenance of overall network connections, or that they play a role in essential protein clusters. In this work, we have attempted to examine the placement of essential proteins and the network topology from a different perspective by determining the correlation of protein essentiality and reverse nearest neighbor topology (RNN).