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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:This study was designed to delineate the functional significance of CCL21 in metabolic reprogramming in experimental arthritis and differentiated rheumatoid arthritis (RA) macrophages (MΦs). To characterize the influence of CCL21 on immunometabolism, its mechanism of action was elucidated by dysregulating glucose uptake in preclinical arthritis and RA MΦs. In CCL21 arthritic joints, the glycolytic intermediates hypoxia-inducible factor 1α (HIF1α), cMYC and GLUT1 were overexpressed compared with oxidative regulators estrogen-related receptor γ and peroxisome proliferator-activated receptor gamma coactivator 1 (PGC1)-α. Interestingly, 2-deoxy-D-glucose (2-DG) therapy mitigated CCL21-induced arthritis by restraining the number of joint F4/80+ iNOS+ MΦs without impacting F4/80+ Arginase+ MΦs. Similar to the preclinical findings, blockade of glycolysis negated CCL21-polarized CD14+ CD86+ GLUT+ MΦ frequency; however, CD14+ CD206+ GLUT+ MΦs were not implicated in this process. In CCL21-induced arthritis and differentiated RA MΦs, the inflammatory imprint was uniquely intercepted by 2-DG via interleukin-6 (IL-6) downregulation. Despite the more expansive inflammatory response of CCL21 in the arthritic joints relative to the differentiated RA MΦs, 2-DG was ineffective in joint tumor necrosis factor-α, IL-1β, CCL2 and CCL5 enrichment. By contrast, disruption of glycolysis markedly impaired CCL21-induced HIF1α and cMYC signaling in arthritic mice. Notably, in RA MΦs, glycolysis interception was directed toward dysregulating CCL21-enhanced HIF1α transcription. Nonetheless, in concurrence with the diminished IL-6 levels, CCL21 differentiation of CD14+ CD86+ GLUT1+ MΦs was reversed by glycolysis and HIIF1α inhibition. Moreover, in the CCL21 experimental arthritis or differentiated RA MΦs, the malfunctioning metabolic machinery was accompanied by impaired oxidative phosphorylation because of reduced PGC1α or peroxisome proliferator-activated receptor-γ expression. CCL21 reconfigures naïve myeloid cells into glycolytic RA CD14+ CD86+ GLUT+ IL-6high HIF1αhigh MΦs. Therefore, inhibiting the CCL21/CCR7 pathway may provide a promising therapeutic strategy.

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.

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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