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arXiv 2602.18028physics.bio-phcond-mat.stat-mech
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通过最优传输和信息论解码细胞信号传导

Decoding cell signaling via optimal transport and information theory

Universal Biology Institute, The University of Tokyo（东京大学泛生物研究院）；Department of Physics, The University of Tokyo（东京大学物理系）

Mintu Nandi, Sosuke Ito

备注：
39 pages, 13 figures, includes SI
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AI总结：

针对互信息无法捕捉输入输出分布结构对应性的问题，引入2-Wasserstein距离作为几何保真度，与互信息构成双保真度框架，揭示不同调控拓扑在信息保真度和几何保真度之间的权衡，并通过TNF和RAS-MAPK信号实验验证。

摘要：

尽管存在分子噪声，细胞信号处理仍能可靠进行。互信息（MI）被广泛用于量化信号保真度，捕捉输出区分输入状态的能力。然而，它未能捕捉输出是否保留输入的统计结构，这一特性在形态发生素模式和剂量依赖性信号传导中至关重要。为弥补这一不足，我们引入2-Wasserstein（2-WD）距离，它为比较输入和输出分布提供了几何基础。我们将MI定义为信息保真度（INF），将2-WD的倒数定义为几何保真度（GMF）。将这一双保真度框架应用于高斯信道近似下的典型调控基序，揭示了拓扑依赖的权衡：前馈环路能在两个维度上表现良好，而反馈架构则牺牲INF以增强GMF。肿瘤坏死因子信号传导的实验分析支持了反馈调控的预测作用。对RAS-MAPK信号传导的分析表明，细胞内信号中继更好地由INF和GMF之间的平衡来描述，而非仅由信息传输描述。我们的结果表明，可靠信号传导不一定最大化信息，而是可以源于信息传输与分布对应性之间的平衡。因此，GMF代表了信号保真度的一个独特维度，并为分析自然网络和设计任务特异性合成电路提供了框架。

英文摘要：

Cellular signal processing performs reliably despite molecular noise. Mutual information (MI) is widely used to quantify signaling fidelity, capturing how well outputs discriminate input states. However, it fails to capture whether the output preserves the statistical structure of the input, a property crucial in morphogen patterning and dose-dependent signaling. To address this gap, we introduce the 2-Wasserstein (2-WD) distance, which provides a geometric basis for comparing input and output distributions. We define MI as informational fidelity (INF) and the inverse of the 2-WD as geometric fidelity (GMF). Applying this dual-fidelity framework to canonical regulatory motifs under Gaussian channel approximation reveals topology-dependent trade-offs: coherent feed-forward loops can perform well in both dimensions, whereas feedback architectures reduce INF to enhance GMF. Experimental analysis of tumor necrosis factor signaling reveals dual-fidelity behavior qualitatively consistent with feedback regulation. RAS-MAPK data analysis further shows that jointly considering INF and GMF better characterizes intracellular signal relay than INF alone. Our results thus indicate that these signaling behaviors are not fully characterized by MI alone; instead, distributional correspondence provides a complementary dimension of signaling fidelity. Our study provides a practical framework for analyzing natural networks and guiding the design of task-specific synthetic circuits.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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