Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada.
Department of Chemical and Physical Sciences, University of Toronto, Mississauga, ON L5L 1C6, Canada.
Proc Natl Acad Sci U S A. 2023 Sep 19;120(38):e2302016120. doi: 10.1073/pnas.2302016120. Epub 2023 Sep 11.
A key goal of synthetic biology is to develop functional biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently developed control module in which two control species perfectly annihilate each other's biological activity. The AIF module confers robust perfect adaptation to the steady-state average level of a controlled intracellular component when subjected to sustained perturbations. Recent work has suggested that such robustness comes at the unavoidable price of increased stochastic fluctuations around average levels. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the idealized limit with perfect annihilation. However, we also show that this trade-off is a singular limit of the control module: Even minute deviations from perfect adaptation allow systems to achieve effective noise suppression as long as cells can pay the corresponding energetic cost. We further show that a variant of the AIF control module can achieve significant noise suppression even in the idealized limit with perfect adaptation. This atypical configuration may thus be preferable in synthetic biology applications.
合成生物学的一个主要目标是开发具有独立网络特性的功能生化模块。对偶积分反馈（AIF）是最近开发的一种控制模块，其中两种控制物质能够完美地消除彼此的生物活性。当受到持续干扰时，AIF 模块能够赋予对受控细胞内成分稳态平均水平的稳健完美适应。最近的研究表明，这种鲁棒性是以增加平均水平周围的随机波动为不可避免的代价换来的。我们提出了理论结果，支持并量化了这种权衡，针对理想化极限中常见的分析 AIF 变体以及完美消除的情况。然而，我们还表明，这种权衡是控制模块的奇异极限：只要细胞能够支付相应的能量成本，即使微小的偏离完美适应也能使系统实现有效的噪声抑制。我们进一步表明，AIF 控制模块的变体即使在理想化极限中也能实现显著的噪声抑制，即使是完美适应的情况。因此，这种非典型的配置在合成生物学应用中可能更为可取。
