Stochastic thermodynamic limit with information geometry on E. coli adaptation

Research paper by Keita Ashida, Kotaro Oka

Indexed on: 27 May '18Published on: 27 May '18Published in: arXiv - Quantitative Biology - Molecular Networks


The biological systems have been investigated by stochastic thermodynamic approach, especially for E. coli sensory adaptation model. Recently, using information geometry and stochastic thermo- dynamics, the relationship between speed on information geometry of transition and thermodynamic cost is investigated in biochemical enzymatic reaction model. Here, we introduce the approach to E. coli sensory adaptation model, and investigated the relationship between adaptation speed and rate of thermodynamic cost change and efficiency of the adaptation. For increasing external noise level in stimulation, the efficiency decreased, but for external stimulation strength, the efficiency was highly robust. Using this approach, we succeeded to discuss the relationship between speed of adaptation and rate of thermodynamic cost change in E. coli adaptation. Our quantification could be applied to various biological systems.