Noise Propagation and Information Transmission in the Tumor Necrosis Factor Signaling Pathway

Biological Noise;Signal Transduction;Information Theory;TNF;NF-kappaB;Noise Decomposition;Biomedical Engineering

Rhee, Alexander

Johns Hopkins University

关键词: Biological Noise;    Signal Transduction;    Information Theory;    TNF;    NF-kappaB;    Noise Decomposition;    Biomedical Engineering;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/40182/RHEE-DISSERTATION-2014.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

Biological noise is generally defined as the non-genetic variability that arises in populations.For instance, identical twins, although very similar in appearance, will commonly display slightly different phenotypes.Likewise, daughter cells sharing the same genetic material may differentiate along divergent paths.In the past decade, there have been considerable advances in understanding the genetic mechanisms underpinning this variability; however, there still remain unanswered questions surrounding how signaling networks contribute to biological noise and how this noise sets limitations on intracellular information transmission.In the first half of this thesis, we demonstrate that a linear relationship between signal transduction responses allows one to quantify and map the propagation of noise along different parts of a signaling network, even if the network is complex and partially defined.We discover that the JNK pathway generates higher noise than the NF-κB pathway while the activation of c-Jun adds a greater amount of noise than the activation of ATF-2.In addition, by analyzing the negative feedback mechanisms mediated by the protein A20, we find that A20 can suppress noise in the activation of ATF-2 by separately inhibiting the tumor necrosis factor (TNF) receptor complex and JNK pathway.In the second half of this thesis, we will describe an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing TNF signaling, we find that individual TNF signaling pathways transduce information only sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple integrated pathways.In this dissertation, we demonstrate that the application of engineering concepts proves to be of great utility in uncovering novel characteristics of biological noise.We anticipate that these contributions will help move biology closer towards a more predictable and rule-based engineering discipline allowing us to design de novo biological solutions to pressing issues.