Targeted Proteomics-Driven Computational Modeling of Macrophage Microbial Sensing Pathways

Authors

• NP Manes
• JM Calzola
• PR Kaplan
• M Meier-Schellersheim
• IDC Fraser
• RN Germain
• A Nita-Lazar

Abstract

The Toll-like receptor (TLR) and chemotaxis pathways in macrophages are essential for generating effective immune responses. Subtle variations in the concentration and timing of stimuli affect signaling within these pathways and cell function. Pathway modeling is needed to understand how these signaling networks function in time and space. RNA-seq was performed to identify expressed transcripts, and targeted mass spectrometry was used to measure the absolute abundance of the pathway proteins. The resulting values were used as pathway model parameters. Rule-based computational modeling of the chemotaxis pathway was performed using the Simmune software suite. Molecular reaction rates were not measured directly, but instead were constrained using in vitro microscopy data. The model produced in silico results consistent with experimental data that was not used to train the model. Phosphoprotein quantification is being performed using parallel reaction monitoring, a recently developed targeted mass spectrometry technology, to produce data for model training, testing, and validation. These findings demonstrate the feasibility and value of combining mass spectrometry-based measurements with pathway modeling for advancing biological insight. This research was supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases, NIH.

Scientific Focus Area: Systems Biology

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