NDLI: Understand the noise of CI expression in phage λ lysogen

Content Provider	IEEE Xplore Digital Library
Author	Hongyuan Zhu Tianqi Chen Xue Lei Wei Tian Youfang Cao Ping Ao
Copyright Year	2012
Description	Author affiliation: Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, P.R. China (Hongyuan Zhu; Xue Lei; Ping Ao) \|\| Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R. China (Tianqi Chen) \|\| Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA (Wei Tian; Youfang Cao)
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.
Starting Page	7432
Ending Page	7436
File Size	267754
Page Count	5
File Format	PDF
ISBN	9781467325813
ISSN	21612927
e-ISBN	9789881563811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	SSA Biological system modeling Noise Stochastic processes Ito Simulation Strain Intrinsic Noise Proteins Stochastic Dynamical Analysis Phage λ Cell Cycle Mathematical model Extrinsic Noise Chemical Langevin Equation
Content Type	Text
Resource Type	Article

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