Predicting Chemical Environments of Bacteria from Receptor Signaling
Predicting Chemical Environments of Bacteria from Receptor Signaling
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DOI：
10.1371/journal.pcbi.1003870
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发表时间：
2014-10-01
影响因子：
4.3
通讯作者：
Endres, Robert G.
中科院分区：
文献类型：
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作者：
Clausznitzer, Diana;Micali, Gabriele;Endres, Robert G.
感觉系统已经进化到能够响应某些统计特性的输入刺激，并通过生化途径可靠地传输这些信息。因此，对于一个经过实验充分表征的感觉系统，人们应该能够提取有关刺激统计数据的有价值的信息。根据细菌趋化感觉系统体内荧光共振能量转移（FRET）实验的剂量反应曲线，我们预测趋化大肠杆菌细胞在自然环境中通常遇到的化学梯度。为了预测细胞经历的平均梯度，我们重新评估现象学韦伯定律及其对韦伯-费希纳定律和倍数变化检测的推广。为了获得梯度的完整分布，我们使用信息论和模拟，考虑到细胞外部和内部噪声的信息传输的局限性。我们确定了指数梯度的广泛分布，这导致了对数正态刺激和最大漂移速度。因此，我们的结果为破译复杂的、实验上无法访问的细胞微环境（例如人类肠道）的化学性质迈出了第一步。
Sensory systems have evolved to respond to input stimuli of certain statistical properties, and to reliably transmit this information through biochemical pathways. Hence, for an experimentally well-characterized sensory system, one ought to be able to extract valuable information about the statistics of the stimuli. Based on dose-response curves from in vivo fluorescence resonance energy transfer (FRET) experiments of the bacterial chemotaxis sensory system, we predict the chemical gradients chemotactic Escherichia coli cells typically encounter in their natural environment. To predict average gradients cells experience, we revaluate the phenomenological Weber's law and its generalizations to the Weber-Fechner law and fold-change detection. To obtain full distributions of gradients we use information theory and simulations, considering limitations of information transmission from both cell-external and internal noise. We identify broad distributions of exponential gradients, which lead to log-normal stimuli and maximal drift velocity. Our results thus provide a first step towards deciphering the chemical nature of complex, experimentally inaccessible cellular microenvironments, such as the human intestine.