Isocost Lines Describe the Cellular Economy of Genetic Circuits
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Weiss_Isocost lines.pdf
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Author(s)
Yazbek, John
Huang, Hsin-Ho
Chung, Hattie
Weiss, Ron
Del Vecchio, Domitilla
Gyoergy, Andras
Jimenez Zarco, Jose I.
Del Vecchio, Domitilla
Date Issued
August 2015
Journal
Biophysical Journal
Publisher
Elsevier
Citation
Gyorgy, Andras, Jose I. Jimenez, John Yazbek, Hsin-Ho Huang, Hattie Chung, Ron Weiss, and Domitilla Del Vecchio. “Isocost Lines Describe the Cellular Economy of Genetic Circuits.” Biophysical Journal 109, no. 3 (August 2015): 639–646.
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Final published version
Abstract
Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Synthetic Biology Center
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DOI of Published Version
https://doi.org/10.1016/j.bpj.2015.06.034
