Mathematical Modeling of Pro- and Anti-Inflammatory Signaling in Macrophages

Abstract

Inflammation is a beneficial mechanism that is usually triggered by injury or infection and is designed to return the body to homeostasis. However, uncontrolled or sustained inflammation can be deleterious and has been shown to be involved in the etiology of several diseases, including inflammatory bowel disorder and asthma. Therefore, effective anti-inflammatory signaling is important in the maintenance of homeostasis in the body. However, the inter-play between pro-and anti-inflammatory signaling is not fully understood. In the present study, we develop a mathematical model to describe integrated pro-and anti-inflammatory signaling in macrophages. The model incorporates the feedback effects of de novo synthesized pro-inflammatory (tumor necrosis factor α; TNF-α) and anti-inflammatory (interleukin-10; IL-10) cytokines on the activation of the transcription factor nuclear factor κB (NF-κB) under continuous lipopolysaccharide (LPS) stimulation (mimicking bacterial infection). In the model, IL-10 upregulates its own production (positive feedback) and also downregulates TNF-α production through NF-κB (negative feedback). In addition, TNF-α upregulates its own production through NF-κB (positive feedback). Eight model parameters are selected for estimation involving sensitivity analysis and clustering techniques. We validate the mathematical model predictions by measuring phosphorylated OPEN ACCESSProcesses 2015, 3 2 NF-κB, de novo synthesized TNF-α and IL-10 in RAW 264.7 macrophages exposed to LPS. This integrated model represents a first step towards modeling the interaction between proand anti-inflammatory signaling.

Mathematical Modeling and Parameter Estimation of Intracellular Signaling Pathway: Application to LPS-induced NFκB Activation and TNFα Production in Macrophages

“…In order to further assess the predictive capability of the newly calibrated model, the simulated dynamics of nuclear NFκB levels (i.e., activated NFκB) in the absence of Golgiplug ™ were computed and plotted in Figure 5a. The maximum NFκB translocation to the nucleus occurred within 2 h of LPS addition, which was consistent with previous experimental studies [15,55,56]. Moreover, as the LPS concentration increased, the nuclear NFκB levels reached their maximum value earlier (i.e., at 50, 60, 75 and 105 min after adding LPS), and the areas under the curves in Figure 5a, which were computed as indicators of the signal strength, were around 20 µM·min for different concentrations of LPS.…”

“…Motivated by the above considerations, we developed a deterministic model that can accurately predict the average signaling dynamics of single cells. We chose lipopolysaccharide (LPS)-induced nuclear factor κB (NFκB) signaling in mouse macrophages for our model system as it is an extensively studied and characterized signaling pathway [8,15,16]. In order to address the issues discussed above, both computational and experimental approaches have been implemented.…”

Mathematical modeling of ventilator-induced lung inflammation

“…Additionally, models related to smoking and asthma (Brown et al, 2011;Chernyavsky et al, 2014;Golov et al, 2017;Pothen et al, 2015), mechanical ventilation (Hickling, 1998;Marini et al, 1989;Pidaparti et al, 2013), and general inflammatory stress (Reynolds et al, 2010) have been developed, but these models generally deal with the mechanics of the airways, including airflow, pressure, and gas exchange, and how these mechanics respond to inflammation and particle inhalation without accounting for the various cells types involved in the immune response. Models have also been developed to understand and analyze the molecular mechanisms that govern the phenotype switch that macrophages undergo from pro-inflammatory to anti-inflammatory, as well as other important subcellular pathways (Anderson et al, 2016;Braun et al, 2013;Maiti et al, 2014).…”

“…M1 macrophages produce PIM, which upregulate the activation and migration of macrophages to the site of injury; see the second term in Equations (11) and (12) (Herold et al, 2011;Mosser and Edwards, 2008). The macrophage population self-regulates by releasing anti-inflammatory mediators (AIM) such as IL-10, thus inhibiting further production of PIM (Maiti et al, 2014). Therefore the term includes the same inhibiting multiplier as in Equation (9), through which the rate of PIM production by M1 macrophages decreases with increased concentrations of a b .…”

“…Using the same inhibition multiplier as previously, AIM inhibit differentiation to M1 as part of their regulatory role in the inflammatory process, although a complete understanding of these mechanisms is yet to be uncovered (Gardner et al, 2010;Maiti et al, 2014;Mosser and Edwards, 2008). In the absence of injury, lungs contain a low number of undifferentiated macrophages which patrol the surrounding area (Crosby and Waters, 2010).…”