Title :
Understand the noise of CI expression in phage λ lysogen
Author :
Zhu, Hongyuan ; Chen, Tianqi ; Lei, Xue ; Tian, Wei ; Cao, Youfang ; Ao, Ping
Author_Institution :
Shanghai Center for Syst. Biomed., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
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.
Keywords :
RNA; cellular biophysics; genetics; molecular biophysics; proteins; random noise; stochastic processes; 1-d Langevin model; 2-d stepwise Langevin model; CI expression; biological noise factors; biology; extrinsic noise; mRNA; noisy gene expression; phage λ lysogen; phenotypic diversity; proteins; stochastic dynamic model; switch efficiency; Biological system modeling; Mathematical model; Noise; Proteins; Stochastic processes; Strain; Cell Cycle; Chemical Langevin Equation; Extrinsic Noise; Intrinsic Noise; Ito Simulation; Phage λ; SSA; Stochastic Dynamical Analysis;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3