TY - GEN
T1 - How Cell-to-Cell Heterogeneity and Scarce Resources Shape the Population-Level Stability Profile of Toggle Switches
AU - Gyorgy, Andras
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - The lack of modularity in synthetic biology presents one of the major bottlenecks in the scalability of complex gene circuits. One source of this context-dependent behavior is the scarcity of shared transcriptional and translational resources. To overcome this issue, predictive computational tools must account for the resulting competition phenomenon both when studying individual cells and at the population-level considering cell-to-cell heterogeneity. Since toggle switches are one of the most widely used genetic modules, here we focus on how shared resources affect the stability profile of toggle switches even in the presence of loading from their context. Modeling the parameters of the toggle switch as random variables reveals how cellular context, noise and correlation between key parameters shape the population-level stability distribution. To demonstrate the relevance of our results, we illustrate that detrimental effects of even unknown contexts can be bounded, thus enabling the design of genetic modules that are robust to disturbances due to unknown loading effects.
AB - The lack of modularity in synthetic biology presents one of the major bottlenecks in the scalability of complex gene circuits. One source of this context-dependent behavior is the scarcity of shared transcriptional and translational resources. To overcome this issue, predictive computational tools must account for the resulting competition phenomenon both when studying individual cells and at the population-level considering cell-to-cell heterogeneity. Since toggle switches are one of the most widely used genetic modules, here we focus on how shared resources affect the stability profile of toggle switches even in the presence of loading from their context. Modeling the parameters of the toggle switch as random variables reveals how cellular context, noise and correlation between key parameters shape the population-level stability distribution. To demonstrate the relevance of our results, we illustrate that detrimental effects of even unknown contexts can be bounded, thus enabling the design of genetic modules that are robust to disturbances due to unknown loading effects.
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U2 - 10.1109/CDC40024.2019.9030266
DO - 10.1109/CDC40024.2019.9030266
M3 - Conference contribution
AN - SCOPUS:85082491696
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 6622
EP - 6627
BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Conference on Decision and Control, CDC 2019
Y2 - 11 December 2019 through 13 December 2019
ER -