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Transforming growth factor-beta type-II receptor signalling: intrinsic/associated casein kinase activity, receptor interactions and functional effects of blocking antibodies.

ABSTRACT: The transforming growth factor beta (TGF-beta) family of growth factors control proliferation, extracellular matrix synthesis and/ or differentiation in a wide variety of cells. However, the molecular mechanisms governing ligand binding, receptor oligomerization and signal transduction remain incompletely understood. In this study, we utilized a set of antibodies selective for the extracellular and intracellular domains of the TGF-beta type-II receptor as probes to investigate the intrinsic kinase activity of this receptor and its physical association in multimeric complexes with type-I and type-III receptors. The type-II receptor immuno-precipitated from human osteosarcoma cells exhibited autophosphorylation and casein kinase activity that was markedly stimulated by polylysine yet was insensitive to heparin. Affinity cross-linking of 125I-TGF-beta 1 ligand to cellular receptors followed by specific immunoprecipitation demonstrated that type-II receptors form stable complexes with both type-I and type-III receptors expressed on the surfaces of both human osteosarcoma cells and rabbit chondrocytes. Pretreatment of the cultured cells with an antibody directed against a distinct extracellular segment of the type-II receptor (anti-TGF-beta-IIR-NT) effectively blocked the 125I-TGF-beta labelling of type-I receptors without preventing the affinity labelling of type-II or type-III receptors, indicating a selective disruption of the type-I/type-II hetero-oligomers. The anti-TGF-beta-IIR-NT antibodies also blocked the TGF-beta-dependent induction of the plasminogen activator inhibitor (PAI-1) promoter observed in mink lung epithelial cells. However, the same anti-TGF-beta-IIR-NT antibodies did not prevent the characteristic inhibition of cellular proliferation by TGF-beta 1, as determined by [3H]thymidine incorporation into DNA. The selective perturbation of PAI-1 promoter induction versus cell-cycle-negative regulation suggests that strategic disruption of TGF-beta type-I and -II receptor interactions can effectively alter specific cellular responses to TGF-beta signalling.

SUBMITTER: Hall FL

PROVIDER: S-EPMC1217339 | biostudies-other | 1996 May

REPOSITORIES: biostudies-other

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Project description:BACKGROUND: A great deal of data has accumulated on signalling pathways. These large datasets are thought to contain much implicit information on their molecular structure, interaction and activity information, which provides a picture of intricate molecular networks believed to underlie biological functions. While tremendous advances have been made in trying to understand these systems, how information is transmitted within them is still poorly understood. This ever growing amount of data demands we adopt powerful computational techniques that will play a pivotal role in the conversion of mined data to knowledge, and in elucidating the topological and functional properties of protein - protein interactions. RESULTS: A computational framework is presented which allows for the description of embedded networks, and identification of common shared components thought to assist in the transmission of information within the systems studied. By employing the graph theories of network biology - such as degree distribution, clustering coefficient, vertex betweenness and shortest path measures - topological features of protein-protein interactions for published datasets of the p53, nuclear factor kappa B (NF-kappaB) and G1/S phase of the cell cycle systems were ascertained. Highly ranked nodes which in some cases were identified as connecting proteins most likely responsible for propagation of transduction signals across the networks were determined. The functional consequences of these nodes in the context of their network environment were also determined. These findings highlight the usefulness of the framework in identifying possible combination or links as targets for therapeutic responses; and put forward the idea of using retrieved knowledge on the shared components in constructing better organised and structured models of signalling networks. CONCLUSION: It is hoped that through the data mined reconstructed signal transduction networks, well developed models of the published data can be built which in the end would guide the prediction of new targets based on the pathway's environment for further analysis. Source code is available upon request.

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Transforming growth factor-beta type-II receptor signalling: intrinsic/associated casein kinase activity, receptor interactions and functional effects of blocking antibodies.

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