 A mechanistic integrative computational model of macrophage polarization: Implications in human pathophysiologyChen Zhao, Adam C Mirando, Richard J Sové, Thalyta X Medeiros, Brian H Annex and Aleksander S Popel PLOS Computational Biology, 2019, vol. 15, issue 11, 1-28 Abstract: Macrophages respond to signals in the microenvironment by changing their functional phenotypes, a process known as polarization. Depending on the context, they acquire different patterns of transcriptional activation, cytokine expression and cellular metabolism which collectively constitute a continuous spectrum of phenotypes, of which the two extremes are denoted as classical (M1) and alternative (M2) activation. To quantitatively decode the underlying principles governing macrophage phenotypic polarization and thereby harness its therapeutic potential in human diseases, a systems-level approach is needed given the multitude of signaling pathways and intracellular regulation involved. Here we develop the first mechanism-based, multi-pathway computational model that describes the integrated signal transduction and macrophage programming under M1 (IFN-γ), M2 (IL-4) and cell stress (hypoxia) stimulation. Our model was calibrated extensively against experimental data, and we mechanistically elucidated several signature feedbacks behind the M1-M2 antagonism and investigated the dynamical shaping of macrophage phenotypes within the M1-M2 spectrum. Model sensitivity analysis also revealed key molecular nodes and interactions as targets with potential therapeutic values for the pathophysiology of peripheral arterial disease and cancer. Through simulations that dynamically capture the signal integration and phenotypic marker expression in the differential macrophage polarization responses, our model provides an important computational basis toward a more quantitative and network-centric understanding of the complex physiology and versatile functions of macrophages in human diseases.Author summary: As essential regulators of the immune system, macrophages can be polarized to acquire distinct phenotypes in response to a wide range of signals in the tissue microenvironment, such as bacterial products, endogenous cytokines, cell damage and stress. Decades of research has shown that a number of signaling pathways can regulate this process and determine the functional phenotypes of macrophages in physiology as well as various disease scenarios, and recent studies suggest that macrophage polarization is indeed a dynamic process and that the canonical dichotomous notion with only classical (M1) and alternative (M2) activation states is oversimplifying the continuous spectrum of polarized macrophage phenotypes observed in health and disease. To investigate the mechanistic and therapeutic aspects associated with differentially polarized macrophages, we formulated and calibrated a multi-pathway computational model based on literature knowledge and quantitative experimental datasets to systematically describe the integrative regulation of macrophage transcriptional programs and phenotype markers under different stimuli combinations. Our systems-level model is a key building block of a potential “virtual macrophage” simulation platform that can enable researchers to efficiently generate mechanistic hypotheses and assess macrophage-based therapeutic strategies for human diseases. Date: 2019 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1007468 DOI: 10.1371/journal.pcbi.1007468 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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