Dimitrova Elena, Caromile Leslie A, Laubenbacher Reinhard, Shapiro Linda H
Department of Mathematical Sciences, Clemson University, Clemson, SC, USA.
Center for Vascular Biology, Department of Cell Biology, University of Connecticut School of Medicine, Farmington, 06030, CT, USA.
BMC Syst Biol. 2018 Apr 10;12(1):50. doi: 10.1186/s12918-018-0580-z.
Cell death as a result of ischemic injury triggers powerful mechanisms regulated by germline-encoded Pattern Recognition Receptors (PRRs) with shared specificity that recognize invading pathogens and endogenous ligands released from dying cells, and as such are essential to human health. Alternatively, dysregulation of these mechanisms contributes to extreme inflammation, deleterious tissue damage and impaired healing in various diseases. The Toll-like receptors (TLRs) are a prototypical family of PRRs that may be powerful anti-inflammatory targets if agents can be designed that antagonize their harmful effects while preserving host defense functions. This requires an understanding of the complex interactions and consequences of targeting the TLR-mediated pathways as well as technologies to analyze and interpret these, which will then allow the simulation of perturbations targeting specific pathway components, predict potential outcomes and identify safe and effective therapeutic targets.
We constructed a multiscale mathematical model that spans the tissue and intracellular scales, and captures the consequences of targeting various regulatory components of injury-induced TLR4 signal transduction on potential pro-inflammatory or pro-healing outcomes. We applied known interactions to simulate how inactivation of specific regulatory nodes affects dynamics in the context of injury and to predict phenotypes of potential therapeutic interventions. We propose rules to link model behavior to qualitative estimates of pro-inflammatory signal activation, macrophage infiltration, production of reactive oxygen species and resolution. We tested the validity of the model by assessing its ability to reproduce published data not used in its construction.
These studies will enable us to form a conceptual framework focusing on TLR4-mediated ischemic repair to assess potential molecular targets that can be utilized therapeutically to improve efficacy and safety in treating ischemic/inflammatory injury.
缺血性损伤导致的细胞死亡触发了由种系编码的模式识别受体(PRR)调控的强大机制,这些受体具有共同的特异性,可识别入侵病原体和死亡细胞释放的内源性配体,因此对人类健康至关重要。另外,这些机制的失调会导致各种疾病中出现极端炎症、有害的组织损伤和愈合受损。Toll样受体(TLR)是PRR的一个典型家族,如果能够设计出在保留宿主防御功能的同时拮抗其有害作用的药物,它们可能成为强大的抗炎靶点。这需要了解靶向TLR介导的信号通路的复杂相互作用和后果,以及分析和解释这些相互作用的技术,进而能够模拟针对特定通路成分的扰动,预测潜在结果并确定安全有效的治疗靶点。
我们构建了一个跨越组织和细胞内尺度的多尺度数学模型,该模型捕捉了针对损伤诱导的TLR4信号转导的各种调控成分对潜在促炎或促愈合结果的影响。我们应用已知的相互作用来模拟特定调控节点的失活如何在损伤背景下影响动力学,并预测潜在治疗干预的表型。我们提出了将模型行为与促炎信号激活、巨噬细胞浸润、活性氧产生和消退的定性估计联系起来的规则。我们通过评估模型再现未用于其构建的已发表数据的能力来测试模型的有效性。
这些研究将使我们能够形成一个聚焦于TLR4介导的缺血修复的概念框架,以评估可用于治疗的潜在分子靶点,从而提高治疗缺血/炎症性损伤的疗效和安全性。