title: Comparative analysis reveals conserved protein phosphorylation networks implicated in multiple diseases.
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.
authors.affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada M5G 1X5.
authors.forename: Chris Soon Heng
authors.initials: CS
authors.lastname: Tan
authors.forename: Bernd
authors.initials: B
authors.lastname: Bodenmiller
authors.forename: Adrian
authors.initials: A
authors.lastname: Pasculescu
authors.forename: Marko
authors.initials: M
authors.lastname: Jovanovic
authors.forename: Michael O
authors.initials: MO
authors.lastname: Hengartner
authors.forename: Claus
authors.initials: C
authors.lastname: Jørgensen
authors.forename: Gary D
authors.initials: GD
authors.lastname: Bader
authors.forename: Ruedi
authors.initials: R
authors.lastname: Aebersold
authors.forename: Tony
authors.initials: T
authors.lastname: Pawson
authors.forename: Rune
authors.initials: R
authors.lastname: Linding
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D001665:Binding Sites; D017173:Caenorhabditis elegans / Q000235:genetics / Q000378:metabolism; D016000:Cluster Analysis; D018844:Cyclin-Dependent Kinases / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D004198:Disease Susceptibility / Q000378:metabolism / Q000503:physiopathology*; D004331:Drosophila melanogaster / Q000235:genetics / Q000378:metabolism; D019143:Evolution, Molecular; D006801:Humans; D008969:Molecular Sequence Data; D015394:Molecular Structure; D010750:Phosphoproteins / Q000145:classification / Q000378:metabolism*; D010766:Phosphorylation; D010802:Phylogeny; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000379:methods; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D017386:Sequence Homology, Amino Acid; D015398:Signal Transduction / Q000502:physiology*; D000095043:Cyclin-Dependent Kinase-Activating Kinase
chemical_list: D010750:Phosphoproteins; D011506:Proteins; D018844:Cyclin-Dependent Kinases; D000095043:Cyclin-Dependent Kinase-Activating Kinase