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

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Paper

Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data

Topics: Systems Biology

In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSTEC, 85-91, 2016 , Rome, Italy

Authors: Sebastian Vlaic ¹ ; Robert Altwasser ¹ ; Peter Kupfer ¹ ; Carol L. Nilsson ² ; Mark Emmett ³ ; Anke Meyer-Baese ³ and Reinhard Guthke ¹

Affiliations: ¹ Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Germany ; ² The University of Texas Medical Branch, United States ; ³ Florida State University, United States

Keyword(s): Phospho-regulatory networks, Network Inference, Glioblastoma Cancer Stem Cells.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Systems Biology

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. (More)

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Paper citation in several formats:

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 (BIOSTEC 2016) - BIOINFORMATICS; ISBN 978-989-758-170-0; ISSN 2184-4305, SciTePress, pages 85-91. DOI: 10.5220/0005743000850091

@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 (BIOSTEC 2016) - BIOINFORMATICS},
year={2016},
pages={85-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005743000850091},
isbn={978-989-758-170-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - BIOINFORMATICS
TI - Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data
SN - 978-989-758-170-0
IS - 2184-4305
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
PB - SciTePress