Department of Life Sciences, Imperial College, London, UK.
Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, UK.
Sci Rep. 2019 Nov 15;9(1):16898. doi: 10.1038/s41598-019-53273-4.
Cells are often considered input-output devices that maximize the transmission of information by converting extracellular stimuli (input) via signaling pathways (communication channel) to cell behavior (output). However, in biological systems outputs might feed back into inputs due to cell motility, and the biological channel can change by mutations during evolution. Here, we show that the conventional channel capacity obtained by optimizing the input distribution for a fixed channel may not reflect the global optimum. In a new approach we analytically identify both input distributions and input-output curves that optimally transmit information, given constraints from noise and the dynamic range of the channel. We find a universal optimal input distribution only depending on the input noise, and we generalize our formalism to multiple outputs (or inputs). Applying our formalism to Escherichia coli chemotaxis, we find that its pathway is compatible with optimal information transmission despite the ultrasensitive rotary motors.
细胞通常被认为是输入-输出设备,通过信号通路(通讯信道)将细胞外刺激(输入)转化为细胞行为(输出),从而最大限度地传递信息。然而,在生物系统中,由于细胞的运动性,输出可能会反馈到输入中,并且在进化过程中生物通道可能会发生突变。在这里,我们表明,通过优化固定通道的输入分布获得的传统通道容量可能无法反映全局最优值。在一种新的方法中,我们根据噪声和通道动态范围的约束条件,从分析上确定了最佳的输入分布和输入-输出曲线,以最优地传输信息。我们发现,一个通用的最优输入分布仅取决于输入噪声,并且我们将我们的形式主义推广到多个输出(或输入)。将我们的形式主义应用于大肠杆菌趋化性,我们发现尽管旋转马达非常敏感,但它的途径仍然与最优信息传输兼容。