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Coupled Reaction Networks for Noise Suppression

Xiao, Fangzhou and Fang, Meichen and Doyle, John C. (2018) Coupled Reaction Networks for Noise Suppression. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20181030-075417310

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Abstract

Noise is intrinsic to many important regulatory processes in living cells, and often forms obstacles to be overcome for reliable biological functions. However, due to stochastic birth and death events of all components in biomolecular systems, suppression of noise of one component by another is fundamentally hard and costly. Quantitatively, a widely-cited severe lower bound on noise suppression in biomolecular systems was established by Lestas et. al. in 2010, assuming that the plant and the controller have separate birth and death reactions. This makes the precision observed in several biological phenomena, e.g. cell fate decision making and cell cycle time ordering, seem impossible. We demonstrate that coupling, a mechanism widely observed in biology, could suppress noise lower than the bound of Lestas et. al. with moderate energy cost. Furthermore, we systematically investigate the coupling mechanism in all two-node reaction networks, showing that negative feedback suppresses noise better than incoherent feedforward achitectures, coupled systems have less noise than their decoupled version for a large class of networks, and coupling has its own fundamental limitations in noise suppression. Results in this work have implications for noise suppression in biological control and provide insight for a new efficient mechanism of noise suppression in biology.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/440453DOIDiscussion Paper
ORCID:
AuthorORCID
Xiao, Fangzhou0000-0002-5001-5644
Doyle, John C.0000-0002-1828-2486
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license. bioRxiv preprint first posted online Oct. 11, 2018. The authors would like to thank Jiawei Yan and Noah Olsman for constructive discussions. F. X. and J. C. D. are partially funded by the Defense Advanced Research Projects Agency (Agreement HR0011-16-2-0049). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-16-2-0049
Record Number:CaltechAUTHORS:20181030-075417310
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181030-075417310
Official Citation:Coupled Reaction Networks for Noise Suppression. Fangzhou Xiao, Meichen Fang, John C. Doyle. bioRxiv 440453; doi: https://doi.org/10.1101/440453
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90486
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 Oct 2018 17:12
Last Modified:30 Oct 2018 17:12

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