Network evolution: rewiring and signatures of conservation in signaling.

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constru...

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Main Authors: Mark G F Sun, Martin Sikora, Michael Costanzo, Charles Boone, Philip M Kim
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3305342?pdf=render
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spelling doaj-366119c6c05e4a4cb0cff7a10089fc4e2020-11-25T01:13:57ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582012-01-0183e100241110.1371/journal.pcbi.1002411Network evolution: rewiring and signatures of conservation in signaling.Mark G F SunMartin SikoraMichael CostanzoCharles BoonePhilip M KimThe analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.http://europepmc.org/articles/PMC3305342?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Mark G F Sun
Martin Sikora
Michael Costanzo
Charles Boone
Philip M Kim
spellingShingle Mark G F Sun
Martin Sikora
Michael Costanzo
Charles Boone
Philip M Kim
Network evolution: rewiring and signatures of conservation in signaling.
PLoS Computational Biology
author_facet Mark G F Sun
Martin Sikora
Michael Costanzo
Charles Boone
Philip M Kim
author_sort Mark G F Sun
title Network evolution: rewiring and signatures of conservation in signaling.
title_short Network evolution: rewiring and signatures of conservation in signaling.
title_full Network evolution: rewiring and signatures of conservation in signaling.
title_fullStr Network evolution: rewiring and signatures of conservation in signaling.
title_full_unstemmed Network evolution: rewiring and signatures of conservation in signaling.
title_sort network evolution: rewiring and signatures of conservation in signaling.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2012-01-01
description The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.
url http://europepmc.org/articles/PMC3305342?pdf=render
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