» Articles » PMID: 29414718

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch

Overview
Journal Biophys J
Publisher Cell Press
Specialty Biophysics
Date 2018 Feb 8
PMID 29414718
Citations 10
Authors
Affiliations
Soon will be listed here.
Abstract

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks.

Citing Articles

How Does Allocate Proteome?.

Liao C, Priyanka P, Lai Y, Rao C, Lu T ACS Synth Biol. 2024; 13(9):2718-2732.

PMID: 39120961 PMC: 11415281. DOI: 10.1021/acssynbio.3c00537.


A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits.

Sechkar K, Steel H, Perrino G, Stan G Nat Commun. 2024; 15(1):1981.

PMID: 38438391 PMC: 10912777. DOI: 10.1038/s41467-024-46410-9.


Context-dependent redesign of robust synthetic gene circuits.

Stone A, Youssef A, Rijal S, Zhang R, Tian X Trends Biotechnol. 2024; 42(7):895-909.

PMID: 38320912 PMC: 11223972. DOI: 10.1016/j.tibtech.2024.01.003.


Emergence of qualitative states in synthetic circuits driven by ultrasensitive growth feedback.

Melendez-Alvarez J, Tian X PLoS Comput Biol. 2022; 18(9):e1010518.

PMID: 36112667 PMC: 9518899. DOI: 10.1371/journal.pcbi.1010518.


Modular, robust, and extendible multicellular circuit design in yeast.

Carignano A, Chen D, Mallory C, Wright R, Seelig G, Klavins E Elife. 2022; 11.

PMID: 35312478 PMC: 9000959. DOI: 10.7554/eLife.74540.


References
1.
Ochab-Marcinek A, Tabaka M . Bimodal gene expression in noncooperative regulatory systems. Proc Natl Acad Sci U S A. 2010; 107(51):22096-101. PMC: 3009792. DOI: 10.1073/pnas.1008965107. View

2.
Scott M, Hwa T, Ingalls B . Deterministic characterization of stochastic genetic circuits. Proc Natl Acad Sci U S A. 2007; 104(18):7402-7. PMC: 1863463. DOI: 10.1073/pnas.0610468104. View

3.
Stricker J, Cookson S, Bennett M, Mather W, Tsimring L, Hasty J . A fast, robust and tunable synthetic gene oscillator. Nature. 2008; 456(7221):516-9. PMC: 6791529. DOI: 10.1038/nature07389. View

4.
Hintsche M, Klumpp S . Dilution and the theoretical description of growth-rate dependent gene expression. J Biol Eng. 2013; 7(1):22. PMC: 3847955. DOI: 10.1186/1754-1611-7-22. View

5.
Scott M, Gunderson C, Mateescu E, Zhang Z, Hwa T . Interdependence of cell growth and gene expression: origins and consequences. Science. 2010; 330(6007):1099-102. DOI: 10.1126/science.1192588. View