Evolutionary flexibility of protein complexes.
BACKGROUND
Proteins play a key role in cellular life. They do not act alone but are organised in complexes. Throughout the life of a cell, complexes are dynamic in their composition due to attachments and shared components. Experimental and computational evidence indicate that consecutive addition and secondary losses of components played a major role in the evolution of some complexes, mostly without affecting the core function. Here, we analysed in a large scale approach whether this flexibility in evolution is only limited to a distinct number of complexes or represents a more general trend.


RESULTS
Focussing on human protein complexes, we based our analysis on a manually curated dataset from HPRD. In total, 1,060 complexes with 6,136 proteins from 2,187 unique genes were considered. We computed interologs in 25 different species and predicted the composition of complexes. Over the analysed species, the composition of most complexes was highly flexible and only 25% of all genes were never lost. Even if one component was lost at a particular point in time, the fraction of observed second, independent losses of additional components was high (75% of all complexes affected). Still, loss of whole complexes happened rarely. This biological signal deviated significantly from random models. We exemplified this trend on the anaphase promoting complex (APC) where a core is highly conserved throughout all metazoans, but flexibility in certain components is observable.


CONCLUSIONS
Consecutive additions and losses of distinct units is a fundamental process in the evolution of protein complexes. These evolutionary events affecting genes coding for units in human protein complexes showed a significantly different phylogenetic pattern compared to randomly selected genes. Determination of taxon specific attachments or losses might be linked to specific cellular or morphological features. Thus, protein complexes contain not only structural and functional, but also evolutionary cores.
Seidl
Michael F
MF
Department of Bioinformatics, Biozentrum, University Würzburg, Am Hubland, 97074 Würzburg, Germany.
Schultz
Jörg
J
D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D030562:Databases, Protein; D019143:Evolution, Molecular; D006801:Humans; D008957:Models, Genetic; D010802:Phylogeny; D011506:Proteins / Q000235:genetics*; D020539:Sequence Analysis, Protein
D011506:Proteins