Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, TX, USA.
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
NPJ Syst Biol Appl. 2024 Sep 14;10(1):103. doi: 10.1038/s41540-024-00430-9.
Throughout development, complex networks of cell signaling pathways drive cellular decision-making across different tissues and contexts. The transforming growth factor β (TGF-β) pathways, including the BMP/Smad pathway, play crucial roles in determining cellular responses. However, as the Smad pathway is used reiteratively throughout the life cycle of all animals, its systems-level behavior varies from one context to another, despite the pathway connectivity remaining nearly constant. For instance, some cellular systems require a rapid response, while others require high noise filtering. In this paper, we examine how the BMP-Smad pathway balances trade-offs among three such systems-level behaviors, or "Performance Objectives (POs)": response speed, noise amplification, and the sensitivity of pathway output to receptor input. Using a Smad pathway model fit to human cell data, we show that varying non-conserved parameters (NCPs) such as protein concentrations, the Smad pathway can be tuned to emphasize any of the three POs and that the concentration of nuclear phosphatase has the greatest effect on tuning the POs. However, due to competition among the POs, the pathway cannot simultaneously optimize all three, but at best must balance trade-offs among the POs. We applied the multi-objective optimization concept of the Pareto Front, a widely used concept in economics to identify optimal trade-offs among various requirements. We show that the BMP pathway efficiently balances competing POs across species and is largely Pareto optimal. Our findings reveal that varying the concentration of NCPs allows the Smad signaling pathway to generate a diverse range of POs. This insight identifies how signaling pathways can be optimally tuned for each context.
在整个发育过程中，细胞信号通路的复杂网络在不同的组织和环境中驱动细胞决策。转化生长因子β（TGF-β）途径，包括 BMP/Smad 途径，在决定细胞反应方面起着至关重要的作用。然而，由于 Smad 途径在所有动物的生命周期中被反复使用，尽管途径连接性几乎保持不变，但它的系统级行为在不同的情况下会有所不同。例如，一些细胞系统需要快速响应，而另一些系统需要高噪声过滤。在本文中，我们研究了 BMP-Smad 途径如何在三个系统级行为（或“性能目标（POs）”）之间平衡权衡：响应速度、噪声放大和途径输出对受体输入的敏感性。我们使用适合人类细胞数据的 Smad 途径模型表明，通过改变非保守参数（NCPs），如蛋白质浓度，Smad 途径可以调整以强调三个 POs 中的任何一个，并且核磷酸酶的浓度对调整 POs 有最大的影响。然而，由于 POs 之间的竞争，途径不能同时优化所有三个 POs，而是必须在 POs 之间进行权衡。我们应用了 Pareto 前沿的多目标优化概念，这是经济学中广泛使用的概念，用于在各种要求之间识别最优权衡。我们表明，BMP 途径在不同物种中有效地平衡了竞争的 POs，并且在很大程度上是 Pareto 最优的。我们的研究结果表明，改变 NCPs 的浓度可以使 Smad 信号通路在不同的情况下产生多样化的 POs。这一发现确定了信号通路如何针对每个上下文进行最佳调整。
