Understand the Noise of CI Expression in Phage λ Lysogen
The noisy gene expression is prominent in biology and hot for study these years. However, the cause of noise is still a ‘mysterious thing’. Many scientists have known the importance of noise and it has exact biological meanings, like phenotypic diversity and switch efficiency. The quantitative method to measure noise is stochastic model. But many researchers found it difficult to explain the noise within the existing theoretical framework. Several years ago, Zhu et al stochastically analyzed λ switch and obtained consistency with Little’s experimental result. And they used a new potential construction to analyze SDE and found the existence of extrinsic noise, which is larger than intrinsic noise. In the recent paper by Anderson and Yang, we try to apply the stochastic dynamic model to this new experimental data and justify the existence of extrinsic noise. Our Langevin model shows consistency with the mean level of CI in experimental results of 5 different λ strains. However, there is still variation between theoretical and experimental CI distributions of each strain, which we operationally denote as the extrinsic noise outside the system, corresponding to intrinsic noise inherent to the process itself. Thus we found the extrinsic noise can finally enlarge the variation of distribution remarkably and its impact is more obvious in systems with low copy number of proteins, such as wild type phage. As we extended minimal 1-d Langevin model into 2-d stepwise Langevin model, mRNA acts an important role in making contribution to variation of CI distribution, which could explain 40％ to 70％ of total variation. With more and more biological noise factors discovered and considered, we can better explain the experimental data and the unknown extrinsic noise will never be mysterious.
Phage λ Stochastic Dynamical Analysis SSA Ito Simulation Chemical Langevin Equation Intrinsic Noise Extrinsic Noise Cell Cycle
Hongyuan Zhu Tianqi Chen Xue Lei Wei Tian Youfang Cao Ping Ao
Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, P. R. China Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
7432-7436
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）