Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression

被引:27
作者
Agrawal, Deepak K. [1 ]
Tang, Xun [2 ]
Westbrook, Alexandra [3 ]
Marshall, Ryan [4 ]
Maxwell, Colin S. [5 ]
Lucks, Julius [7 ]
Noireaux, Vincent [4 ]
Beisel, Chase L. [5 ,6 ]
Dunlop, Mary J. [1 ]
Franco, Elisa [2 ]
机构
[1] Boston Univ, Dept Biomed Engn, Boston, MA 02215 USA
[2] Univ Calif Riverside, Dept Mech Engn, Riverside, CA 92521 USA
[3] Cornell Univ, Robert F Smith Sch Chem & Biomol Engn, Ithaca, NY 14853 USA
[4] Univ Minnesota, Sch Phys & Astron, Minneapolis, MN 55455 USA
[5] North Carolina State Univ, Dept Chem & Biomol Engn, Raleigh, NC 27695 USA
[6] Helmholtz Inst RNA Based Infect Res HIRI, Josef Schneider Str 2-D15, D-97080 Wurzburg, Germany
[7] Northwestern Univ, Dept Chem & Biol Engn, Evanston, IL 60208 USA
来源
ACS SYNTHETIC BIOLOGY | 2018年 / 7卷 / 05期
关键词
RNA; feedback; gene expression; mathematical modeling; control; sensitivity analysis; GREEN FLUORESCENT PROTEIN; SYNTHETIC BIOLOGY; ESCHERICHIA-COLI; GUIDE RNA; CRISPR; ACTIVATION; NETWORKS; DESIGN; SYSTEM; IMPLEMENTATION;
D O I
10.1021/acssynbio.8b00040
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.
引用
收藏
页码:1219 / 1228
页数:19
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