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Role of interaction network topology in controlling microbial population in consortia

Ren, Xinying and Murray, Richard M. (2018) Role of interaction network topology in controlling microbial population in consortia. In: 2018 IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 2691-2697. ISBN 978-1-5386-1395-5.

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Engineering microbial consortia is an important new frontier for synthetic biology given its efficiency in performing complex tasks and endurance to environmental uncertainty. Most synthetic circuits regulate populational behaviors via cell-to-cell interactions, which are affected by spatially heterogeneous environments. Therefore, it is important to understand the limits on controlling system dynamics and provide a control strategy for engineering consortia under spatial structures. Here, we build a network model for a fractional population control circuit in two-strain consortia, and characterize the cell-to-cell interaction network by topological properties, such as symmetry, locality and connectivity. Using linear network control theory, we relate the network topology to system output's tracking performance. We analytically and numerically demonstrate that the minimum network control cost for good tracking depends on locality difference between two cell population's spatial distributions and how strongly the controller node contributes to interaction strength. To realize a robust consortia, we can manipulate the environment to form a strongly connected network. Our results ground the expected cell population dynamics in its spatially organized interaction network, and inspire directions in cooperative control in microbial consortia.

Item Type:Book Section
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Murray, Richard M.0000-0002-5785-7481
Additional Information:© 2018 IEEE. The authors would like to thank Fangzhou Xiao and Leo Green for their insightful discussion. The authors X. R is partially supported by the Air Force Office of Scientific Research, grant number FA9550-14-1-0060. The project depicted is also sponsored by the 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.
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)FA9550-14-1-0060
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechAUTHORS:20180927-114224927
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Official Citation:X. Ren and R. M. Murray, "Role of interaction network topology in controlling microbial population in consortia," 2018 IEEE Conference on Decision and Control (CDC), FL, USA, 2018, pp. 2691-2697. doi: 10.1109/CDC.2018.8619704
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90010
Deposited By: George Porter
Deposited On:27 Sep 2018 20:52
Last Modified:03 Oct 2019 20:21

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