The impact of plasmid copy number on leaky gene expression and on the behavior of an activator-based genetic switch

Chentao Yong, Yiren Zhou, Andras Gyorgy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Plasmid copy number (PCN) is traditionally considered a static design parameter in synthetic biology applications. However, recent tools enable its dynamic regulation, thus opening up a novel dimension of gene expression control that complements well-established transcriptional and translational techniques. Therefore, here we characterize how tuning this crucial parameter impacts promoter leakiness both when relying on positive and negative regulation. We demonstrate both analytically and experimentally that in the former case, greater PCN yields elevated leakiness in protein expression, whereas this basal level can surprisingly decrease as PCN increases in repressor-based regulation, and that multi-level gene expression control can amplify this effect. Considering a genetic switch as a concrete application example, we further characterize how the interplay of PCN and promoter leakiness together determine the number of stable fixed points and their robustness to noise. Finally, we reveal how the metabolic burden that originates within the switch and its context shapes the dynamics and behavior of this ubiquitous gene circuit.

Original languageEnglish (US)
Title of host publication2024 IEEE 63rd Conference on Decision and Control, CDC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5592-5597
Number of pages6
ISBN (Electronic)9798350316339
DOIs
StatePublished - 2024
Event63rd IEEE Conference on Decision and Control, CDC 2024 - Milan, Italy
Duration: Dec 16 2024Dec 19 2024

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference63rd IEEE Conference on Decision and Control, CDC 2024
Country/TerritoryItaly
CityMilan
Period12/16/2412/19/24

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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