Relating protein concentration to cell-type-specific responses is one of the remaining challenges for obtaining a quantitative systems level understanding of mammalian signaling. Here we used mass-spectrometry (MS)- and antibody-based quantitative proteomic approaches to measure protein abundances for 75% of a hand-curated reconstructed ErbB network of 198 proteins, in two established cell types (HEK293 and MCF-7) and in primary keratinocyte cells. Comparison with other quantitative studies allowed building a set of ErbB network proteins expressed in all cells and another which are cell-specific and could impart specific properties to the network. As a proof-of-concept of the importance of protein concentration, we generated a small simplified mathematical model encompassing ligand binding, followed by receptor dimerization, activation, and degradation. The model predicts ErbB phosphorylation in HEK293, MCF-7, and keratinocyte cells simply by incorporating cell-type-specific ErbB1, ErbB2, and caveolin-1 abundances but otherwise contains similar rate constants. Altogether, the data provide a resource for protein abundances and localization to be included in larger mathematical models, enabling the generation of cell-type-specific computational models. MS data have been deposited to the ProteomeXchange via PRIDE (with identifier PXD000623) and PASSEL (with identifier PASS00372).

Quantification of ErbB network proteins in three cell types using complementary approaches identifies cell-general and cell-type-specific signaling proteins

Kiel, Christina;
2014-01-01

Abstract

Relating protein concentration to cell-type-specific responses is one of the remaining challenges for obtaining a quantitative systems level understanding of mammalian signaling. Here we used mass-spectrometry (MS)- and antibody-based quantitative proteomic approaches to measure protein abundances for 75% of a hand-curated reconstructed ErbB network of 198 proteins, in two established cell types (HEK293 and MCF-7) and in primary keratinocyte cells. Comparison with other quantitative studies allowed building a set of ErbB network proteins expressed in all cells and another which are cell-specific and could impart specific properties to the network. As a proof-of-concept of the importance of protein concentration, we generated a small simplified mathematical model encompassing ligand binding, followed by receptor dimerization, activation, and degradation. The model predicts ErbB phosphorylation in HEK293, MCF-7, and keratinocyte cells simply by incorporating cell-type-specific ErbB1, ErbB2, and caveolin-1 abundances but otherwise contains similar rate constants. Altogether, the data provide a resource for protein abundances and localization to be included in larger mathematical models, enabling the generation of cell-type-specific computational models. MS data have been deposited to the ProteomeXchange via PRIDE (with identifier PXD000623) and PASSEL (with identifier PASS00372).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1469172
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