Limitations to extracellular concentration sensing through signaling cascades

IF 2.2 3区 物理与天体物理 Q2 MECHANICS Journal of Statistical Mechanics: Theory and Experiment Pub Date : 2024-07-09 DOI:10.1088/1742-5468/ad5436
Swoyam Srirupa Biswal and Vaibhav Wasnik
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Abstract

Signaling cascades refer to sequential biochemical reactions that occur in the cytoplasm of living cells in response to the binding of a ligand to a cell surface receptor, triggering a cellular response. Living cells need to sense extracellular concentrations with high precision. In this paper, we study the limitations of extracellular concentration measurement in linear signaling cascades. We find that as long as the cascade is linear and measurement times are much larger or much smaller than the timescales of the cytoplasmic reactions, the error in concentration measurement is independent of cascade length, the nature of the reactions and their rates. Our results can also be extended to generic non-linear signal cascades when the measurement time is much smaller than the timescales of cytoplasmic reactions. We illustrate this by considering the specific example of the accuracy of concentration detection in E. coli.
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通过信号级联传感细胞外浓度的局限性
信号级联是指在配体与细胞表面受体结合后,活细胞的细胞质中会发生连续的生化反应,从而引发细胞反应。活细胞需要高精度地感知细胞外浓度。本文研究了线性信号级联中细胞外浓度测量的局限性。我们发现,只要级联是线性的,测量时间比细胞质反应的时间尺度大得多或小得多,浓度测量误差就与级联长度、反应性质及其速率无关。当测量时间远小于细胞质反应的时间尺度时,我们的结果还可以扩展到一般的非线性信号级联。我们以大肠杆菌浓度检测的准确性为例进行说明。
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来源期刊
CiteScore
4.50
自引率
12.50%
发文量
210
审稿时长
1.0 months
期刊介绍: JSTAT is targeted to a broad community interested in different aspects of statistical physics, which are roughly defined by the fields represented in the conferences called ''Statistical Physics''. Submissions from experimentalists working on all the topics which have some ''connection to statistical physics are also strongly encouraged. The journal covers different topics which correspond to the following keyword sections. 1. Quantum statistical physics, condensed matter, integrable systems Scientific Directors: Eduardo Fradkin and Giuseppe Mussardo 2. Classical statistical mechanics, equilibrium and non-equilibrium Scientific Directors: David Mukamel, Matteo Marsili and Giuseppe Mussardo 3. Disordered systems, classical and quantum Scientific Directors: Eduardo Fradkin and Riccardo Zecchina 4. Interdisciplinary statistical mechanics Scientific Directors: Matteo Marsili and Riccardo Zecchina 5. Biological modelling and information Scientific Directors: Matteo Marsili, William Bialek and Riccardo Zecchina
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