Literature DB >> 28137890

An Interactive Macrophage Signal Transduction Map Facilitates Comparative Analyses of High-Throughput Data.

Pia Wentker1, Martin Eberhardt1, Florian S Dreyer1, Wilhelm Bertrams2, Martina Cantone1, Kathrin Griss2,3, Bernd Schmeck2,4, Julio Vera5.   

Abstract

Macrophages (Mϕs) are key players in the coordination of the lifesaving or detrimental immune response against infections. The mechanistic understanding of the functional modulation of Mϕs by pathogens and pharmaceutical interventions at the signal transduction level is still far from complete. The complexity of pathways and their cross-talk benefits from holistic computational approaches. In the present study, we reconstructed a comprehensive, validated, and annotated map of signal transduction pathways in inflammatory Mϕs based on the current literature. In a second step, we selectively expanded this curated map with database knowledge. We provide both versions to the scientific community via a Web platform that is designed to facilitate exploration and analysis of high-throughput data. The platform comes preloaded with logarithmic fold changes from 44 data sets on Mϕ stimulation. We exploited three of these data sets-human primary Mϕs infected with the common lung pathogens Streptococcus pneumoniae, Legionella pneumophila, or Mycobacterium tuberculosis-in a case study to show how our map can be customized with expression data to pinpoint regulated subnetworks and druggable molecules. From the three infection scenarios, we extracted a regulatory core of 41 factors, including TNF, CCL5, CXCL10, IL-18, and IL-12 p40, and identified 140 drugs targeting 16 of them. Our approach promotes a comprehensive systems biology strategy for the exploitation of high-throughput data in the context of Mϕ signal transduction. In conclusion, we provide a set of tools to help scientists unravel details of Mϕ signaling. The interactive version of our Mϕ signal transduction map is accessible online at https://vcells.net/macrophage.
Copyright © 2017 by The American Association of Immunologists, Inc.

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Year:  2017        PMID: 28137890     DOI: 10.4049/jimmunol.1502513

Source DB:  PubMed          Journal:  J Immunol        ISSN: 0022-1767            Impact factor:   5.422


  10 in total

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Review 5.  Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

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7.  A data-driven computational model enables integrative and mechanistic characterization of dynamic macrophage polarization.

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8.  Triple-color single-molecule imaging for analysis of the role of receptor oligomers in signal transduction.

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Journal:  Biophys Physicobiol       Date:  2022-03-11

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Authors:  Tinus Schynkel; Matthew A Szaniawski; Adam M Spivak; Alberto Bosque; Vicente Planelles; Linos Vandekerckhove; Wim Trypsteen
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  10 in total

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