Khanum Sana, Gupta Shakti, Maurya Mano R, Raja Rubesh, Aboulmouna Lina, Subramaniam Shankar, Ramkrishna Doraiswami
The Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, USA.
Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
J Lipid Res. 2024 Dec;65(12):100666. doi: 10.1016/j.jlr.2024.100666. Epub 2024 Oct 11.
Cellular metabolism is a complex process involving the consumption and production of metabolites, as well as the regulation of enzyme synthesis and activity. Modeling of metabolic processes is important to understand the underlying mechanisms, with a wide range of applications in metabolic engineering and health sciences. Cybernetic modeling is a powerful technique that accounts for unknown intricate regulatory mechanisms in complex cellular processes. It models regulation as goal-oriented, where the levels and activities of enzymes are modulated by the cybernetic control variables to achieve the cybernetic objective. This study used cybernetic model to study the enzyme competition between arachidonic acid (AA) and eicosapentaenoic acid (EPA) metabolism in murine macrophages. AA and EPA compete for the shared enzyme cyclooxygenase. Upon external stimuli, AA produces proinflammatory 2-series prostaglandins and EPA metabolizes to antiinflammatory 3-series prostaglandins, where proinflammatory and antiinflammatory responses are necessary for homeostasis. The cybernetic model adequately captured the experimental data for control and EPA-supplemented conditions. The model is validated by performing an F-test, conducting leave-one-out-metabolite cross-validation, and predicting an unseen experimental condition. The cybernetic variables provide insights into the competition between AA and EPA for the cyclooxygenase enzyme. Predictions from our model suggest that the system undergoes a switch from a predominantly proinflammatory state in the control to an antiinflammatory state with EPA-supplementation. The model can also be used to analytically determine the AA and EPA concentrations required for the switch to occur. The quantitative outcomes enhance understanding of proinflammatory and antiinflammatory metabolism in RAW 264.7 macrophages.
细胞代谢是一个复杂的过程,涉及代谢物的消耗和产生,以及酶合成和活性的调节。代谢过程的建模对于理解其潜在机制很重要,在代谢工程和健康科学中有广泛应用。控制论建模是一种强大的技术,它考虑了复杂细胞过程中未知的复杂调节机制。它将调节建模为目标导向的,其中酶的水平和活性由控制论控制变量调节以实现控制论目标。本研究使用控制论模型研究小鼠巨噬细胞中花生四烯酸(AA)和二十碳五烯酸(EPA)代谢之间的酶竞争。AA和EPA竞争共享的酶环氧化酶。在外部刺激下,AA产生促炎的2-系列前列腺素,而EPA代谢为抗炎的3-系列前列腺素,其中促炎和抗炎反应对于体内平衡是必要的。控制论模型充分捕捉了对照和EPA补充条件下的实验数据。通过进行F检验、进行留一法代谢物交叉验证和预测一个未见过的实验条件来验证该模型。控制论变量为AA和EPA竞争环氧化酶提供了见解。我们模型的预测表明,该系统经历了从对照中主要的促炎状态到补充EPA后的抗炎状态的转变。该模型还可用于分析确定发生转变所需的AA和EPA浓度。这些定量结果增强了对RAW 264.7巨噬细胞中促炎和抗炎代谢的理解。