Information-optimal transcriptional response to oscillatory driving.

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.

[1]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[2]  A. Goldbeter,et al.  Control of oscillating glycolysis of yeast by stochastic, periodic, and steady source of substrate: a model and experimental study. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[3]  H. Berg,et al.  Physics of chemoreception. , 1977, Biophysical journal.

[4]  N. Kampen,et al.  Stochastic processes in physics and chemistry , 1981 .

[5]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[6]  S. Golden,et al.  Circadian Rhythms in Rapidly Dividing Cyanobacteria , 1997, Science.

[7]  M. Elowitz,et al.  A synthetic oscillatory network of transcriptional regulators , 2000, Nature.

[8]  Tetsuya Mori,et al.  Cyanobacterial circadian clockwork: roles of KaiA, KaiB and the kaiBC promoter in regulating KaiC , 2003, The EMBO journal.

[9]  宁北芳,et al.  疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A , 2005 .

[10]  W. Bialek,et al.  Physical limits to biochemical signaling. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Attila Csikász-Nagy,et al.  Analysis of a generic model of eukaryotic cell-cycle regulation. , 2006, Biophysical journal.

[12]  P. R. ten Wolde,et al.  Signal detection, modularity, and the correlation between extrinsic and intrinsic noise in biochemical networks. , 2005, Physical review letters.

[13]  W. Bialek,et al.  Information flow and optimization in transcriptional regulation , 2007, Proceedings of the National Academy of Sciences.

[14]  Jerome T. Mettetal,et al.  The Frequency Dependence of Osmo-Adaptation in Saccharomyces cerevisiae , 2008, Science.

[15]  Andrew Mugler,et al.  A stochastic spectral analysis of transcriptional regulatory cascades , 2008, Proceedings of the National Academy of Sciences.

[16]  Jeff Hasty,et al.  The pedestrian watchmaker: Genetic clocks from engineered oscillators , 2009, FEBS letters.

[17]  A. Walczak,et al.  Spectral solutions to stochastic models of gene expression with bursts and regulation. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  F. Tostevin,et al.  Mutual information between input and output trajectories of biochemical networks. , 2009, Physical review letters.