Systems biology approach reveals possible evolutionarily conserved moonlighting functions for enolase. (October 2015)

• Record Type: Journal Article
• Authors: Paludo, Gabriela Prado; Lorenzatto, Karina Rodrigues; Bonatto, Diego; Ferreira, Henrique Bunselmeyer
• Is Part Of: Computational biology and chemistry. Volume 58(2015)
• Page Start: 1
• Page End: 8
• Publication Date: 2015-10
• Subjects: Enolase -- Glycolytic enzyme -- Moonlighting functions -- Systems biology -- Protein–protein interaction network; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2015.04.010
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Enolase interaction networks were designed for four distantly related organisms. Enolase was identified as a bottleneck node in all designed networks. Enolase non glycolic partners indicate several moonlighting functions. Enolase connectivity patterns indicate partial conservation in its interactions. Some enolase moonlighting functions seem to be evolutionary conserved. Abstract: Glycolytic enzymes, such as enolase, have been described as multifunctional complex proteins that also display non-glycolytic activities, termed moonlighting functions. Although enolase multifunctionality has been described for several organisms, the conservation of enolase alternative functions through different phyla has not been explored with more details. A useful strategy to investigate moonlighting functions is the use of systems biology tools, which allow the prediction of protein functions/interactions by graph design and analysis. In this work, available information from protein–protein interaction (PPI) databases were used to design enolase PPI networks for four eukaryotic organisms, namely Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae, covering a wide spectrum of this domain of life. PPI networks with number of nodes ranging from 140 to 411 and up to 15, 855 connections were generated, and modularity and centrality analyses, and functional enrichment were performed for all of them. The performed analyses showed that enolase is a central node within the networks, and that, in addition to its canonical interactions with proteins related to glycolysis and energetic metabolism, it is also part of protein clusters related to different biological processes, like transcription, development, and apoptosis, among others. Some of these non-glycolytic clusters, are partially conserved between networks, in terms of overall sharing of orthologs, overall cluster structure, and/or at the levels of key regulatory proteins within clusters. Overall, our results provided evidences of enolase multifunctionality and evolutionary conservation of enolase PPIs at all these levels.