Inference of predictive phospho-regulatory networks from LC-MS/MS phosphoproteomics data

Sebastian Vlaic, Robert Altwasser, Peter Kupfer, Carol L. Nilsson, Mark Emmett, Anke Meyer-Baese, Reinhard Guthke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the field of transcriptomics data the automated inference of predictive gene regulatory networks from highthroughput data is a common approach for the identification of novel genes with potential therapeutic value. Sophisticated methods have been developed that extensively make use of diverse sources of prior-knowledge to obtain biologically relevant hypotheses. Transferring such concepts to the field of phosphoproteomics data has the potential to reveal new insights into phosphorylation-related signaling mechanisms. In this study we conceptually adapt the TILAR network inference algorithm for the inference of a phospho-regulatory network. Therefore, we use published phosphoproteomics data of WP1193 treated and IL6-stimulated glioblastoma stem cells under normoxic and hypoxic condition. Peptides corresponding to 21 differentially phosphorylated proteins were used for network inference. Topological analysis of the phospho-regulatory network suggests lamin B2 (LMNB2) and spectrin, beta, non-erythrocytic 1 (SPTBN1) as potential hub-proteins associated with the alteration of phosphorylation under the observed conditions. Altogether, our results show that inference of phospho-regulatory networks can aid in the understanding of complex molecular mechanisms and cellular processes of biological systems.

Original languageEnglish (US)
Title of host publicationBIOINFORMATICS 2016 - 7th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
PublisherSciTePress
Pages85-91
Number of pages7
ISBN (Print)9789897581700
StatePublished - 2016
Event7th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 - Rome, Italy
Duration: Feb 21 2016Feb 23 2016

Other

Other7th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
CountryItaly
CityRome
Period2/21/162/23/16

Keywords

  • Glioblastoma cancer stem cells
  • Network inference
  • Phospho-regulatory networks

ASJC Scopus subject areas

  • Biomedical Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Vlaic, S., Altwasser, R., Kupfer, P., Nilsson, C. L., Emmett, M., Meyer-Baese, A., & Guthke, R. (2016). Inference of predictive phospho-regulatory networks from LC-MS/MS phosphoproteomics data. In BIOINFORMATICS 2016 - 7th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 (pp. 85-91). SciTePress.