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Reprogramming of macrophages employing gene regulatory and metabolic network models.

ABSTRACT: Upon exposure to different stimuli, resting macrophages undergo classical or alternative polarization into distinct phenotypes that can cause fatal dysfunction in a large range of diseases, such as systemic infection leading to sepsis or the generation of an immunosuppressive tumor microenvironment. Investigating gene regulatory and metabolic networks, we observed two metabolic switches during polarization. Most prominently, anaerobic glycolysis was utilized by M1-polarized macrophages, while the biosynthesis of inosine monophosphate was upregulated in M2-polarized macrophages. Moreover, we observed a switch in the urea cycle. Gene regulatory network models revealed E2F1, MYC, PPAR? and STAT6 to be the major players in the distinct signatures of these polarization events. Employing functional assays targeting these regulators, we observed the repolarization of M2-like cells into M1-like cells, as evidenced by their specific gene expression signatures and cytokine secretion profiles. The predicted regulators are essential to maintaining the M2-like phenotype and function and thus represent potential targets for the therapeutic reprogramming of immunosuppressive M2-like macrophages.

SUBMITTER: Horhold F

PROVIDER: S-EPMC7059956 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Reprogramming of macrophages employing gene regulatory and metabolic network models.

Hörhold Franziska F Eisel David D Oswald Marcus M Kolte Amol A Röll Daniela D Osen Wolfram W Eichmüller Stefan B SB König Rainer R

PLoS computational biology 20200225 2

Upon exposure to different stimuli, resting macrophages undergo classical or alternative polarization into distinct phenotypes that can cause fatal dysfunction in a large range of diseases, such as systemic infection leading to sepsis or the generation of an immunosuppressive tumor microenvironment. Investigating gene regulatory and metabolic networks, we observed two metabolic switches during polarization. Most prominently, anaerobic glycolysis was utilized by M1-polarized macrophages, while th ...[more]

PMID: 32097424

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Project description:Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Project description:Reticuloendothelial macrophages engulf ?0.2 trillion senescent erythrocytes daily in a process called erythrophagocytosis (EP). This critical mechanism preserves systemic heme-iron homeostasis by regulating red blood cell (RBC) catabolism and iron recycling. Although extensive work has demonstrated the various effects on macrophage metabolic reprogramming by stimulation with proinflammatory cytokines, little is known about the impact of EP on the macrophage metabolome and proteome. Thus, we performed mass spectrometry-based metabolomics and proteomics analyses of mouse bone marrow-derived macrophages (BMDMs) before and after EP of IgG-coated RBCs. Further, metabolomics was performed on BMDMs incubated with free IgG to ensure that changes to macrophage metabolism were due to opsonized RBCs and not to free IgG binding. Uniformly labeled tracing experiments were conducted on BMDMs in the presence and absence of IgG-coated RBCs to assess the flux of glucose through the pentose phosphate pathway (PPP). In this study, we demonstrate that EP significantly alters amino acid and fatty acid metabolism, the Krebs cycle, OXPHOS, and arachidonate-linoleate metabolism. Increases in levels of amino acids, lipids and oxylipins, heme products, and RBC-derived proteins are noted in BMDMs following EP. Tracing experiments with U-13C6 glucose indicated a slower flux through glycolysis and enhanced PPP activation. Notably, we show that it is fueled by glucose derived from the macrophages themselves or from the extracellular media prior to EP, but not from opsonized RBCs. The PPP-derived NADPH can then fuel the oxidative burst, leading to the generation of reactive oxygen species necessary to promote digestion of phagocytosed RBC proteins via radical attack. Results were confirmed by redox proteomics experiments, demonstrating the oxidation of Cys152 and Cys94 of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and hemoglobin-?, respectively. Significant increases in early Krebs cycle and C5-branched dibasic acid metabolites (?-ketoglutarate and 2-hydroxyglutarate, respectively) indicate that EP promotes the dysregulation of mitochondrial metabolism. Lastly, EP stimulated aminolevulinic acid (ALA) synthase and arginase activity as indicated by significant accumulations of ALA and ornithine after IgG-mediated RBC ingestion. Importantly, EP-mediated metabolic reprogramming of BMDMs does not occur following exposure to IgG alone. In conclusion, we show that EP reprograms macrophage metabolism and modifies macrophage polarization.

Dataset Information

Reprogramming of macrophages employing gene regulatory and metabolic network models.

Publications

Reprogramming of macrophages employing gene regulatory and metabolic network models.

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