Title: Approaches to defining the ancestral eukaryotic protein complexome
Authors: Ceulemans, Hugo ×
Beke, Lijs
Bollen, Mathieu #
Issue Date: Feb-2006
Series Title: BioEssays : news and reviews in molecular, cellular and developmental biology. vol:28 issue:3 pages:316-24
Abstract: In this paper, we integrate and summarize the currently available information on the ancestral eukaryotic protein complexome, which is defined as the set of protein complexes that extant eukaryotes inherited from their last common ancestor. From the literature, we compiled lists of complexes with three or more distinct protein components from well-studied eukaryotic model organisms. Combinatorial complexes of membrane-associated signalling proteins and specific transcription factors were disregarded. A stringent but sensitive novel orthology detection algorithm, complemented with manual sequence similarity searches and with published data on whole genome or segmental and tandem gene duplications, enabled us to map the vast majority of these complexes to a virtual primitive eukaryote termed Eukaryotic Virtual Ancestor (EVA). EVA is intended to resemble the last common eukaryotic ancestor and to emulate the biological common denominator of the major extent eukaryotic lineages at the molecular level. The dataset was then used for the functional and domain annotation of the ancestral eukaryotic complexome. Furthermore, we illustrate its usefulness for inferring complexes of poorly studied eukaryotes and for the recognition of highly divergent orthologs. We also discuss the evolution of the circa 1,400 complex-associated ancestral proteins. As about 90% of these proteins have been conserved in all thirteen studied free-living eukaryotes, the evolutionary reduction and loss of complexes seems minimal. Moreover, the available data suggest that, in general, the acquisition of stable complexes of novel design occurs too slowly to be a major contributor to evolutionary innovation. Finally, given the stability of the ancestral eukarotic complexome we propose its use in the formulation of the mathematical systems that aim to simulate biological processes. Our data suggest that these simplified formulations can apply to most free-living model eukaryotes.
ISSN: 0265-9247
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Biochemistry Section (Medicine) (-)
Laboratory of Biosignaling & Therapeutics
× corresponding author
# (joint) last author

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