Literature DB >> 26199343

Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing.

Nathan P Manes1, Bastian R Angermann1, Marijke Koppenol-Raab1, Eunkyung An1, Virginie H Sjoelund1, Jing Sun1, Masaru Ishii2, Ronald N Germain1, Martin Meier-Schellersheim1, Aleksandra Nita-Lazar3.   

Abstract

Osteoclasts are monocyte-derived multinuclear cells that directly attach to and resorb bone. Sphingosine-1-phosphate (S1P)(1) regulates bone resorption by functioning as both a chemoattractant and chemorepellent of osteoclast precursors through two G-protein coupled receptors that antagonize each other in an S1P-concentration-dependent manner. To quantitatively explore the behavior of this chemosensing pathway, we applied targeted proteomics, transcriptomics, and rule-based pathway modeling using the Simmune toolset. RAW264.7 cells (a mouse monocyte/macrophage cell line) were used as model osteoclast precursors, RNA-seq was used to identify expressed target proteins, and selected reaction monitoring (SRM) mass spectrometry using internal peptide standards was used to perform absolute abundance measurements of pathway proteins. The resulting transcript and protein abundance values were strongly correlated. Measured protein abundance values, used as simulation input parameters, led to in silico pathway behavior matching in vitro measurements. Moreover, once model parameters were established, even simulated responses toward stimuli that were not used for parameterization were consistent with experimental findings. These findings demonstrate the feasibility and value of combining targeted mass spectrometry with pathway modeling for advancing biological insight.
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 26199343      PMCID: PMC4597143          DOI: 10.1074/mcp.M115.048918

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  93 in total

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