Regulation of metabolism in mammalian cells is achieved through a complex interplay between cellular signaling, metabolic reactions, and transcriptional changes. The modeling of metabolic fluxes in a cell requires the knowledge of all these mechanisms, some of which may be unknown. A cybernetic approach provides a framework to model these complex interactions through implicit accounting of such regulatory mechanisms, assuming a biological ‘goal’. The premise underlying the cybernetic framework is that the regulatory processes affecting metabolism can be mathematically formulated as a cybernetic objective through variables that constrain the metabolic reaction network to achieve a specified biological ‘goal’. Here, we highlight the utility of the cybernetic framework in modeling of prostaglandin metabolism in murine macrophage cells during inflammation. We present a perspective for future use of the cybernetic framework for modeling complex cellular processes using multiple objectives, which can represent distinct subprocesses within the metabolic reaction network.

哺乳动物细胞中新陈代谢的调节是通过细胞信号传导，代谢反应和转录变化之间的复杂相互作用来实现的。细胞中代谢通量的建模需要所有这些机制的知识，其中一些可能是未知的。控制论方法提供了一个框架，可以通过对这种调节机制的隐式说明来对这些复杂的相互作用进行建模，并假设它们是生物学上的“目标”。控制论框架的前提是，可以通过限制代谢反应网络实现特定生物学“目标”的变量，将影响代谢的调节过程数学上化为控制论目标。这里，我们强调了控制论框架在炎症过程中鼠巨噬细胞中前列腺素代谢建模中的效用。我们提出了未来的控制论框架，用于使用多个目标对复杂的细胞过程进行建模的观点，这可以代表代谢反应网络中不同的子过程。