CaltechAUTHORS
  A Caltech Library Service

Layered Feedback Control Overcomes Performance Trade-off in Synthetic Biomolecular Networks

Hu, Chelsea Y. and Murray, Richard M. (2021) Layered Feedback Control Overcomes Performance Trade-off in Synthetic Biomolecular Networks. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20210914-194152756

[img] PDF (October 21, 2021) - Submitted Version
See Usage Policy.

5MB
[img] PDF - Supplemental Material
See Usage Policy.

4MB

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20210914-194152756

Abstract

Layered feedback is an optimization strategy in feedback control designs widely used in electrical and mechanical engineering. Layered control theory suggests that the performance of controllers is bound by the universal robustness-efficiency tradeoff limit, which could be overcome by layering two or more feedbacks together. In natural biological networks, genes are often regulated with redundancy and layering to adapt to environmental perturbations. Control theory hypothesizes that this layering architecture is also adopted by nature to overcome this performance trade-off. In this work, we validated this property of layered control with a synthetic network in living E. coli cells. We performed system analysis on a node-based design to confirm the tradeoff properties before proceeding to simulations with an effective mechanistic model, which guided us to the best performing design to engineer in cells. Finally, we interrogated its system dynamics experimentally with eight sets of perturbations on chemical signals, nutrient abundance, and growth temperature. For all cases, we consistently observed that the layered control overcomes the robustness-efficiency trade-off limit. This work experimentally confirmed that layered control could be adopted in synthetic biomolecular networks as a performance optimization strategy. It also provided insights in understanding genetic feedback control architectures in nature.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/2021.09.12.459953DOIDiscussion Paper
https://resolver.caltech.edu/CaltechAUTHORS:20221003-756400000.10Related ItemJournal Article
ORCID:
AuthorORCID
Hu, Chelsea Y.0000-0002-2211-1778
Murray, Richard M.0000-0002-5785-7481
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Version 1 - September 13, 2021; Version 2 - October 21, 2021. The authors would like to thank John Doyle, Fangzhou Xiao, Ayush Pandey, and Xinying Ren for their insightful discussions. The author C. Y. Hu is partially supported by Defense Advanced Research Projects Agency (Agreement HR0011-17-2-0008). The content of the information does not necessarily reflect the position or the policy of the government, and no official endorsement should be inferred. The authors have declared no competing interest.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
DOI:10.1101/2021.09.12.459953
Record Number:CaltechAUTHORS:20210914-194152756
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210914-194152756
Official Citation:Layered Feedback Control Overcomes Performance Trade-off in Synthetic Biomolecular Networks Chelsea Y. Hu, Richard M. Murray bioRxiv 2021.09.12.459953; doi: https://doi.org/10.1101/2021.09.12.459953
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110852
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Sep 2021 19:59
Last Modified:04 Oct 2022 19:55

Repository Staff Only: item control page