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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-28711

Tan, C S H; Bodenmiller, B; Pasculescu, A; Jovanovic, M; Hengartner, M O; Jørgensen, C; Bader, G D; Aebersold, R; Pawson, T; Linding, R (2009). Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases. Science Signaling, 2(81):ra39.

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Abstract

Protein kinases enable cellular information processing. Although numerous human phosphorylation sites and their dynamics have been characterized, the evolutionary history and physiological importance of many signaling events remain unknown. Using target phosphoproteomes determined with a similar experimental and computational pipeline, we investigated the conservation of human phosphorylation events in distantly related model organisms (fly, worm, and yeast). With a sequence-alignment approach, we identified 479 phosphorylation events in 344 human proteins that appear to be positionally conserved over approximately 600 million years of evolution and hence are likely to be involved in fundamental cellular processes. This sequence-alignment analysis suggested that many phosphorylation sites evolve rapidly and therefore do not display strong evolutionary conservation in terms of sequence position in distantly related organisms. Thus, we devised a network-alignment approach to reconstruct conserved kinase-substrate networks, which identified 778 phosphorylation events in 698 human proteins. Both methods identified proteins tightly regulated by phosphorylation as well as signal integration hubs, and both types of phosphoproteins were enriched in proteins encoded by disease-associated genes. We analyzed the cellular functions and structural relationships for these conserved signaling events, noting the incomplete nature of current phosphoproteomes. Assessing phosphorylation conservation at both site and network levels proved useful for exploring both fast-evolving and ancient signaling events. We reveal that multiple complex diseases seem to converge within the conserved networks, suggesting that disease development might rely on common molecular networks.

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
08 University Research Priority Programs > Systems Biology / Functional Genomics
DDC:570 Life sciences; biology
Language:English
Date:28 July 2009
Deposited On:31 Jan 2010 17:36
Last Modified:27 Nov 2013 18:14
Publisher:American Association for the Advancement of Science (AAAS)
ISSN:1945-0877
Publisher DOI:10.1126/scisignal.2000316
PubMed ID:19638616
Citations:Web of Science®. Times Cited: 85
Google Scholar™
Scopus®. Citation Count: 90

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