Identification and analysis of evolutionarily cohesive functional modules in protein networks.

The European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany.
Genome Research (Impact Factor: 13.85). 04/2006; 16(3):374-82. DOI: 10.1101/gr.4336406
Source: PubMed

ABSTRACT The increasing number of sequenced genomes makes it possible to infer the evolutionary history of functional modules, i.e., groups of proteins that contribute jointly to the same cellular function in a given species. Here we identify and analyze those prokaryotic functional modules, whose composition remains largely unchanged during evolution, and study their properties. Such "cohesive" modules have a large number of internal functional connections, encode genes that tend to be in close proximity in prokaryotic genomes, and correspond to physical complexes or complex functional systems like the flagellar apparatus. Cohesive modules are enriched in processes such as energy and amino acid metabolism, cell motility, and intracellular trafficking, or secretion. By grouping genes into modules we achieve a more precise estimate of their age and find that the young modules are often horizontally transferred between species and are enriched in functions involved in interactions with the environment, implying that they play an important role in the adaptation of species to new environments.

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    ABSTRACT: A module is a group of closely related proteins that act in concert to perform specific biological functions through protein-protein interactions (PPIs) that occur in time and space. However, the underlying module organization and variance remain unclear. In this study, we collected module templates to infer respective module families, including 58,041 homologous modules in 1,678 species, and PPI families using searches of complete genomic database. We then derived PPI evolution scores and interface evolution scores to describe the module elements, including core and ring components. Functions of core components were highly correlated with those of essential genes. In comparison with ring components, core proteins/PPIs were conserved across multiple species. Subsequently, protein/module variance of PPI networks confirmed that core components form dynamic network hubs and play key roles in various biological functions. Based on the analyses of gene essentiality, module variance, and gene co-expression, we summarize the observations of module organization and variance as follows: 1) a module consists of core and ring components; 2) core components perform major biological functions and collaborate with ring components to execute certain functions in some cases; 3) core components are more conserved and essential during organizational changes in different biological states or conditions.
    Scientific Reports 03/2015; 5:9386. DOI:10.1038/srep09386 · 5.08 Impact Factor
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    ABSTRACT: One of the crucial steps toward understanding the biological functions of a cellular system is to investigate protein-protein interaction (PPI) networks. As an increasing number of reliable PPIs become available, there is a growing need for discovering PPIs to reconstruct PPI networks of interesting organisms. Some interolog-based methods and homologous PPI families have been proposed for predicting PPIs from the known PPIs of source organisms. Here, we propose a multiple-strategy scoring method to identify reliable PPIs for reconstructing the mouse PPI network from two well-known organisms: human and fly. We firstly identified the PPI candidates of target organisms based on homologous PPIs, sharing significant sequence similarities (joint E-value ≤ 1 × 10-40), from source organisms using generalized interolog mapping. These PPI candidates were evaluated by our multiple-strategy scoring method, combining sequence similarities, normalized ranks, and conservation scores across multiple organisms. According to 106,825 PPI candidates in yeast derived from human and fly, our scoring method can achieve high prediction accuracy and outperform generalized interolog mapping. Experiment results show that our multiple-strategy score can avoid the influence of the protein family size and length to significantly improve PPI prediction accuracy and reflect the biological functions. In addition, the top-ranked and conserved PPIs are often orthologous/essential interactions and share the functional similarity. Based on these reliable predicted PPIs, we reconstructed a comprehensive mouse PPI network, which is a scale-free network and can reflect the biological functions and high connectivity of 292 KEGG modules, including 216 pathways and 76 structural complexes. Experimental results show that our scoring method can improve the predicting accuracy based on the normalized rank and evolutionary conservation from multiple organisms. Our predicted PPIs share similar biological processes and cellular components, and the reconstructed genome-wide PPI network can reflect network topology and modularity. We believe that our method is useful for inferring reliable PPIs and reconstructing a comprehensive PPI network of an interesting organism.
    PLoS ONE 01/2015; 10(1):e0116347. DOI:10.1371/journal.pone.0116347 · 3.53 Impact Factor
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    ABSTRACT: Functional links between genes can be predicted using phylogenetic profiling, by correlating the appearance and loss of homologs in subsets of species. However, effective genome-wide phylogenetic profiling has been hindered by the large fraction of human genes related to each other through historical duplication events. Here, we overcame this challenge by automatically profiling over 30,000 groups of homologous human genes (orthogroups) representing the entire protein-coding genome across 177 eukaryotic species (hOP profiles). By generating a full pairwise orthogroup phylogenetic co-occurrence matrix, we derive unbiased genome-wide predictions of functional modules (hOP modules). Our approach predicts functions for hundreds of poorly characterized genes. The results suggest evolutionary constraints that lead components of protein complexes and metabolic pathways to co-evolve while genes in signaling and transcriptional networks do not. As a proof of principle, we validated two subsets of candidates experimentally for their predicted link to the actin-nucleating WASH complex and cilia/basal body function. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.


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