Phosphoproteomic Analysis Reveals Interconnected System-Wide Responses to Perturbations of Kinases and Phosphatases in Yeast

BERND BODENMILLER; STEFANIE WANKA; CLAUDINE KRAFT; JÖRG URBAN; DAVID CAMPBELL; PATRICK PEDRIOLI; BERTRAN GERRITS; PAOLA PICOTTI; HENRY LAM; OLGA VITEK; MI-YOUN BRUSNIAK; BERND ROSCHITZKI; CHAO ZHANG; RALPH SCHLAPBACH; KEVAN SHOKAT; ALEJANDRO COLMAN-LERNER; ALEXEY I. NESVIZHSKII; MATTHIAS PETER; ROBBIE LOEWITH; CHRISTIAN VON MERING; RUEDI AEBERSOLD

SCIENCE SIGNALING

AMER ASSOC ADVANCEMENT SCIENCE

Año: 2010

1937-9145

In eukaryotic cells, the phosphorylation and dephosphorylation of substrate proteins by kinases and phosphatases constitutes an essential regulatory network. This network supports the flow of information from sensors through signaling systems to effector molecules, and ultimately drives the phenotype and function of cells, tissues, and organisms1. Deregulation of this process has severe consequences and is known to be one of the main factors in the emergence and progression of diseases, including cancer2,3. Thus, major efforts have been invested towards developing specific inhibitors that can modulate the activity of individual kinases or phosphatases. However, so far it has been difficult to assess how such pharmacological interventions would impact the cellular signaling network as a whole. Here we use label-free, quantitative phosphoproteomics in a systematically perturbed model organism (S. cerevisiae), to determine in vivo the relationships between 97 kinases, 27 phosphatases and more than 1,000 phosphoproteins. In total, we identified 8,814 perturbed phosphorylation events, describing the first system-wide in vivo protein phosphorylation network. Our results show that, at steady-state, inactivation of most kinases and phosphatases strongly affects large parts of the phosphorylation modulated signal transduction machinery, and not only the immediate downstream targets. Remarkably, the observed cellular phenotype is often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling, and suggest that simple linear representations of signaling pathways might be insufficient for drug development, and for describing organismal homeostasis.