Information-Optimal Transcriptional Response to Oscillatory Driving

作     者：Andrew Mugler Aleksandra M. Walczak Chris H. Wiggins 

作者机构：Department of Physics Columbia University New York New York 10027 USA Princeton Center for Theoretical Science Princeton University Princeton New Jersey 08544 USA Department of Applied Physics and Applied Mathematics Center for Computational Biology and Bioinformatics Columbia University New York New York 10027 USA 

出 版 物：《Physical Review Letters》 (Phys Rev Lett)

年 卷 期：2010年第105卷第5期

页      面：058101-058101页

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

基　　金：NEI NIH HHS [PN2 EY016586-08  PN2 EY016586] Funding Source: Medline 

主　　题：Natural frequencies 

摘      要：Intracellular transmission of information via chemical and transcriptional networks is thwarted by a physical limitation: The finite copy number of the constituent chemical species introduces unavoidable intrinsic noise. Here we solve for the complete probabilistic description of the intrinsically noisy response to an oscillatory driving signal. We derive and numerically verify a number of simple scaling laws. Unlike in the case of measuring a static quantity, response to an oscillatory signal can exhibit a resonant frequency which maximizes information transmission. Furthermore, we show that the optimal regulatory design is dependent on biophysical constraints (i.e., the allowed copy number and response time). The resulting phase diagram illustrates under what conditions threshold regulation outperforms linear regulation.