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

Abstract

In the field of transcriptomics data the automated inference of predictive gene regulatory networks from high-throughput 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.

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Paper Citation


in Harvard Style

Vlaic S., Altwasser R., Kupfer P., Nilsson C., Emmett M., Meyer-Baese A. and Guthke R. (2016). Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 85-91. DOI: 10.5220/0005743000850091


in Bibtex Style

@conference{bioinformatics16,
author={Sebastian Vlaic and Robert Altwasser and Peter Kupfer and Carol L. Nilsson and Mark Emmett and Anke Meyer-Baese and Reinhard Guthke},
title={Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={85-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005743000850091},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data
SN - 978-989-758-170-0
AU - Vlaic S.
AU - Altwasser R.
AU - Kupfer P.
AU - Nilsson C.
AU - Emmett M.
AU - Meyer-Baese A.
AU - Guthke R.
PY - 2016
SP - 85
EP - 91
DO - 10.5220/0005743000850091