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Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

ABSTRACT: Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.

SUBMITTER: Hill SM

PROVIDER: S-EPMC5279869 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

Hill Steven M SM Nesser Nicole K NK Johnson-Camacho Katie K Jeffress Mara M Johnson Aimee A Boniface Chris C Spencer Simon E F SE Lu Yiling Y Heiser Laura M LM Lawrence Yancey Y Pande Nupur T NT Korkola James E JE Gray Joe W JW Mills Gordon B GB Mukherjee Sach S Spellman Paul T PT

Cell systems 20161222 1

Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on ...[more]

PMID: 28017544

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Project description:Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase's substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A's adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for experimental and computational systems biology.

Project description:A significant consequence of protein phosphorylation is to alter protein-protein interactions, leading to dynamic regulation of the components of protein complexes that direct many core biological processes. Recent proteomic studies have populated databases with extensive compilations of cellular phosphoproteins and phosphorylation sites and a similarly deep coverage of the subunit compositions and interactions in multiprotein complexes. However, considerably less data are available on the dynamics of phosphorylation, composition of multiprotein complexes or that define their interdependence. We describe a method to identify candidate phosphoprotein complexes by combining phosphoprotein affinity chromatography, separation by size, denaturing gel electrophoresis, protein identification by tandem mass spectrometry, and informatics analysis. Toward developing phosphoproteome profiling, we have isolated native phosphoproteins using a phosphoprotein affinity matrix, Pro-Q Diamond resin (Molecular Probes-Invitrogen). This resin quantitatively retains phosphoproteins and associated proteins from cell extracts. Pro-Q Diamond purification of a yeast whole cell extract followed by 1-D PAGE separation, proteolysis and ESI LC-MS/MS, a method we term PA-GeLC-MS/MS, yielded 108 proteins, a majority of which were known phosphoproteins. To identify proteins that were purified as parts of phosphoprotein complexes, the Pro-Q eluate was separated into two fractions by size, <100 kDa and >100 kDa, before analysis by PAGE and ESI LC-MS/MS and the component proteins queried against databases to identify protein-protein interactions. The <100 kDa fraction was enriched in phosphoproteins indicating the presence of monomeric phosphoproteins. The >100 kDa fraction contained 171 proteins of 20-80 kDa, nearly all of which participate in known protein-protein interactions. Of these 171, few are known phosphoproteins, consistent with their purification by participation in protein complexes. By comparing the results of our phosphoprotein profiling with the informational databases on phosphoproteomics, protein-protein interactions and protein complexes, we have developed an approach to examining the correlation between protein interactions and protein phosphorylation.

Dataset Information

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

Publications

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

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