Identification of functional signatures in the metabolism of the three cellular domains of life.

Pedro Escobar-Turriza,Katya Rodríguez-Vázquez,Ernesto Pérez-Rueda,Rafael Hernandez-Guerrero,Augusto Cesar Poot-Hernández,Jorge Ramírez-Prado,Andreas Hofmann

doi:10.1371/journal.pone.0217083

Abstract

In order to identify common and specific enzymatic activities associated with the metabolism of the three cellular domains of life, the conservation and variations between the enzyme contents of Bacteria, Archaea, and Eukarya organisms were evaluated. To this end, the content of enzymes belonging to a particular pathway and their abundance and distribution in 1507 organisms that have been annotated and deposited in the KEGG database were assessed. In addition, we evaluated the consecutive enzymatic reaction pairs obtained from metabolic pathway reactions and transformed into sequences of enzymatic reactions, with catalytic activities encoded in the Enzyme Commission numbers, which are linked by a substrate. Both analyses are complementary: the first considers individual reactions associated with each organism and metabolic map, and the second evaluates the functional associations between pairs of consecutive reactions. From these comparisons, we found a set of five enzymatic reactions that were widely distributed in all the organisms and considered here as universal to Bacteria, Archaea, and Eukarya; whereas 132 pairs out of 3151 reactions were identified as significant, only 5 of them were found to be widely distributed in all the taxonomic divisions. However, these universal reactions are not widely distributed along the metabolic maps, suggesting their dispensability to all metabolic processes. Finally, we found that universal reactions are also associated with ancestral domains, such as those related to phosphorus-containing groups with a phosphate group as acceptor or those related to the ribulose-phosphate binding barrel, triosephosphate isomerase, and D-ribose-5-phosphate isomerase (RpiA) lid domain, among others. Therefore, we consider that this analysis provides clues about the functional constraints associated with the repertoire of enzymatic functions per organism.

Highlights

In recent years, the organization and construction of metabolic databases, such as KEGG [1] and MetaCyc [2], has allowed the understanding of adaptive process of cellular life, the diversity of cellular organization, and the complexity of the cellular systems [3]
In order to evaluate the abundance of enzymatic reactions, the metabolism information for 1264 Bacteria, 105 Archaea, and 138 Eukarya organisms was downloaded from the KEGG database and exhaustively scrutinized
This distribution suggests that enzyme-catalyzed transfer and oxidoreduction reactions are highly abundant in metabolism, probably because metabolic processes can be seen as the movement of electrons between molecules, often capturing some of the energy released as the electrons move from high-energy to lower-energy states, as occurs in glycolysis or respiration [15]

Summary

Introduction

The organization and construction of metabolic databases, such as KEGG [1] and MetaCyc [2], has allowed the understanding of adaptive process of cellular life, the diversity of cellular organization, and the complexity of the cellular systems [3]. Metabolism is considered a biological network, where enzymes or substrates are represented as nodes and edges represent their relationships [4,5,6] In this context, two possible scenarios have been suggested to explain the emergence and evolution of metabolic pathways, based on the fact that gene duplication, followed by divergence, lead to the origin of new metabolic reactions. The Patchwork scenario [8] proposes that duplication of genes encoding promiscuous enzymes (capable of catalyzing multiple reactions) allows each descendant enzyme to specialize in one of the ancestral reactions Based on these hypotheses, it is plausible that a small number of enzymes with broad specificity existed in early stages of metabolic evolution. Genes encoding these enzymes would have been duplicated, generating enzymes that, through sequence divergence, became more specialized [9]

Methods

Results

Conclusion