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Proc Natl Acad Sci U S A. 2014 Dec 2;111(48):17330-5. doi: 10.1073/pnas.1411932111. Epub 2014 Nov 17.

Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.

Author information

1
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218; and.
2
Yale Systems Biology Institute and Department of Biomedical Engineering, Yale University, New Haven, CT 06520 andre.levchenko@yale.edu.

Abstract

Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic-intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.

KEYWORDS:

analysis of variance; extrinsic noise; intrinsic noise; noise decomposition; signal transduction

PMID:
25404303
PMCID:
PMC4260601
DOI:
10.1073/pnas.1411932111
[Indexed for MEDLINE]
Free PMC Article

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