Abstract
Growth-mediated feedback between synthetic gene circuits and host organisms leads to diverse emerged behaviors, including growth bistability and enhanced ultrasensitivity. However, the range of possible impacts of growth feedback on gene circuits remains underexplored. Here we mathematically and experimentally demonstrated that growth feedback affects the functions of memory circuits in a network topology-dependent way. Specifically, the memory of the self-activation switch is quickly lost due to the growth-mediated dilution of the circuit products. Decoupling of growth feedback reveals its memory, manifested by its hysteresis property across a broad range of inducer concentration. On the contrary, the toggle switch is more refractory to growth-mediated dilution and can retrieve its memory after the fast-growth phase. The underlying principle lies in the different dependence of active and repressive regulations in these circuits on the growth-mediated dilution. Our results unveil the topology-dependent mechanism on how growth-mediated feedback influences the behaviors of gene circuits.

This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout




Similar content being viewed by others
Data availability
All data produced or analyzed for this study are included in the published article and its supplementary information files or are available from the corresponding authors upon reasonable request.
Code availability
All the equations and parameters of the mathematical models can be found in the Supplementary Note.
References
Brophy, J. A. & Voigt, C. A. Principles of genetic circuit design. Nat. Methods 11, 508–520 (2014).
Liao, C., Blanchard, A. E. & Lu, T. An integrative circuit-host modelling framework for predicting synthetic gene network behaviours. Nat. Microbiol. 2, 1658–1666 (2017).
Boo, A., Ellis, T. & Stan, G.-B. Host-aware synthetic biology. Curr. Opin. Syst. Biol. 14, 66–72 (2019).
Lynch, M. & Marinov, G. K. The bioenergetic costs of a gene. Proc. Natl Acad. Sci. USA 112, 15690–15695 (2015).
Ceroni, F. et al. Burden-driven feedback control of gene expression. Nat. Methods 15, 387–393 (2018).
Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z. & Hwa, T. Interdependence of cell growth and gene expression: origins and consequences. Science 330, 1099–1102 (2010).
Weisse, A. Y., Oyarzun, D. A., Danos, V. & Swain, P. S. Mechanistic links between cellular trade-offs, gene expression, and growth. Proc. Natl Acad. Sci. USA 112, E1038–E1047 (2015).
Klumpp, S., Zhang, Z. & Hwa, T. Growth rate-dependent global effects on gene expression in bacteria. Cell 139, 1366–1375 (2009).
Qian, Y., Huang, H. H., Jimenez, J. I. & Del Vecchio, D. Resource competition shapes the response of genetic circuits. ACS Synth. Biol. 6, 1263–1272 (2017).
Erickson, D. W. et al. A global resource allocation strategy governs growth transition kinetics of Escherichia coli. Nature 551, 119–123 (2017).
Venturelli, O. S. et al. Programming mRNA decay to modulate synthetic circuit resource allocation. Nat. Commun. 8, 15128 (2017).
Klumpp, S. & Hwa, T. Growth-rate-dependent partitioning of RNA polymerases in bacteria. Proc. Natl Acad. Sci. USA 105, 20245–20250 (2008).
Lu, T. K., Khalil, A. S. & Collins, J. J. Next-generation synthetic gene networks. Nat. Biotechnol. 27, 1139–1150 (2009).
Purnick, P. E. & Weiss, R. The second wave of synthetic biology: from modules to systems. Nat. Rev. Mol. Cell Biol. 10, 410–422 (2009).
Kwok, R. Five hard truths for synthetic biology. Nature 463, 288–290 (2010).
Purcell, O., Jain, B., Karr, J. R., Covert, M. W. & Lu, T. K. Towards a whole-cell modeling approach for synthetic biology. Chaos 23, 025112 (2013).
Cardinale, S. & Arkin, A. P. Contextualizing context for synthetic biology–identifying causes of failure of synthetic biological systems. Biotechnol. J. 7, 856–866 (2012).
Zhang, C., Tsoi, R. & You, L. Addressing biological uncertainties in engineering gene circuits. Integr. Biol. Quant. Biosci. Nano Macro 8, 456–464 (2016).
Arkin, A. P. A wise consistency: engineering biology for conformity, reliability, predictability. Curr. Opin. Chem. Biol. 17, 893–901 (2013).
Klumpp, S. & Hwa, T. Bacterial growth: global effects on gene expression, growth feedback and proteome partition. Curr. Opin. Biotechnol. 28, 96–102 (2014).
Tan, C., Marguet, P. & You, L. Emergent bistability by a growth-modulating positive feedback circuit. Nat. Chem. Biol. 5, 842–848 (2009).
Nevozhay, D., Adams, R. M., Van Itallie, E., Bennett, M. R. & Balazsi, G. Mapping the environmental fitness landscape of a synthetic gene circuit. PLoS Comput. Biol. 8, e1002480 (2012).
Deris, J. B. et al. The innate growth bistability and fitness landscapes of antibiotic-resistant bacteria. Science 342, 1237435 (2013).
Feng, J., Kessler, D. A., Ben-Jacob, E. & Levine, H. Growth feedback as a basis for persister bistability. Proc. Natl Acad. Sci. USA 111, 544–549 (2014).
Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342 (2000).
Lou, C. et al. Synthesizing a novel genetic sequential logic circuit: a push-on push-off switch. Mol. Syst. Biol. 6, 350–350 (2010).
Isaacs, F. J., Hasty, J., Cantor, C. R. & Collins, J. J. Prediction and measurement of an autoregulatory genetic module. Proc. Natl Acad. Sci. USA 100, 7714–7719 (2003).
Wu, F., Su, R. Q., Lai, Y. C. & Wang, X. Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination. eLife 6, e23702 (2017).
Zeng, W. et al. Rational design of an ultrasensitive quorum-sensing switch. ACS Synth. Biol. 6, 1445–1452 (2017).
Li, T. et al. Engineering of a genetic circuit with regulatable multistability. Integr. Biol. Quant. Biosci. Nano Macro 10, 474–482 (2018).
Wu, F., Menn, D. J. & Wang, X. Quorum-sensing crosstalk-driven synthetic circuits: from unimodality to trimodality. Chem. Biol. 21, 1629–1638 (2014).
Dong, H., Nilsson, L. & Kurland, C. G. Gratuitous overexpression of genes in Escherichia coli leads to growth inhibition and ribosome destruction. J. Bacteriol. 177, 1497–1504 (1995).
Blanchard, A. E., Liao, C. & Lu, T. Circuit-host coupling induces multifaceted behavioral modulations of a gene switch. Biophys. J. 114, 737–746 (2018).
Andersen, J. B. et al. New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria. Appl Environ. Microbiol. 64, 2240–2246 (1998).
Gefen, O., Fridman, O., Ronin, I. & Balaban, N. Q. Direct observation of single stationary-phase bacteria reveals a surprisingly long period of constant protein production activity. Proc. Natl Acad. Sci. USA 111, 556–561 (2014).
Litcofsky, K. D., Afeyan, R. B., Krom, R. J., Khalil, A. S. & Collins, J. J. Iterative plug-and-play methodology for constructing and modifying synthetic gene networks. Nat. Methods 9, 1077–1080 (2012).
Menn, D., Sochor, P., Goetz, H., Tian, X. J. & Wang, X. Intracellular noise level determines ratio control strategy confined by speed-accuracy trade-off. ACS Synth. Biol. 8, 1352–1360 (2019).
Wu, M. et al. Engineering of regulated stochastic cell fate determination. Proc. Natl Acad. Sci. USA 110, 10610–10615 (2013).
Keren, L. et al. Noise in gene expression is coupled to growth rate. Genome Res. 25, 1893–1902 (2015).
Wang, L., Xin, J. & Nie, Q. A critical quantity for noise attenuation in feedback systems. PLoS Comput. Biol. 6, e1000764 (2010).
Chen, M., Wang, L., Liu, C. C. & Nie, Q. Noise attenuation in the ON and OFF states of biological switches. ACS Synth. Biol. 2, 587–593 (2013).
Slager, J. & Veening, J. W. Hard-wired control of bacterial processes by chromosomal gene location. Trends Microbiol 24, 788–800 (2016).
Moon, T. S., Lou, C., Tamsir, A., Stanton, B. C. & Voigt, C. A. Genetic programs constructed from layered logic gates in single cells. Nature 491, 249 (2012).
Zhong, Z., Ravikumar, A. & Liu, C. C. Tunable expression systems for orthogonal DNA replication. ACS Synth. Biol. 7, 2930–2934 (2018).
Liu, C. C., Jewett, M. C., Chin, J. W. & Voigt, C. A. Toward an orthogonal central dogma. Nat. Chem. Biol. 14, 103–106 (2018).
Arzumanyan, G. A., Gabriel, K. N., Ravikumar, A., Javanpour, A. A. & Liu, C. C. Mutually orthogonal DNA replication systems in vivo. ACS Synth. Biol. 7, 1722–1729 (2018).
Darlington, A. P. S., Kim, J., Jimenez, J. I. & Bates, D. G. Dynamic allocation of orthogonal ribosomes facilitates uncoupling of co-expressed genes. Nat. Commun. 9, 695 (2018).
An, W. & Chin, J. W. Synthesis of orthogonal transcription-translation networks. Proc. Natl Acad. Sci. USA 106, 8477–8482 (2009).
Zong, Y. et al. Insulated transcriptional elements enable precise design of genetic circuits. Nat. Commun. 8, 52 (2017).
Ferry, M. S., Razinkov, I. A. & Hasty, J. in Methods in Enzymology Vol. 497 (ed. Voigt, C.) 295–372 (Academic Press, 2011).
Acknowledgements
We thank X. Fu, T. Hong, G. Yao, J. Xing, W. Shou and T. Hwa for valuable comments. This project was supported by the ASU School of Biological and Health Systems Engineering, NSF grant (no. EF-1921412 to X-J.T.) and NIH grant (no. GM106081 to X.W.). H.G. and J.M.-A. were also supported by the Arizona State University Dean’s Fellowship.
Author information
Authors and Affiliations
Contributions
X.-J.T. conceived the study. X.-J.T., R.Z. and X.W. designed the study. R.Z., J.L., P.S. and X.C. performed experiments. J.M.-A., H.G., and X.-J.T. performed model studies. R.Z., X.-J.T., Q.Z., T.D. and X.W. analyzed the data. R.Z. and X.-J.T. wrote the manuscript. H.G. and X.W. edited the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary Figs. 1–15 and Note.
Supplementary Video 1
A time-lapse video showing the dynamics of GFP in the AraC self-activation circuit under the condition without l-ara and fresh medium for 14 h and conditioned medium for 7 h thereafter.
Supplementary Video 2
A time-lapse video showing the dynamics of GFP in the AraC self-activation circuit under the condition with a high dose of l-ara and fresh medium condition for 14 h and conditioned medium for 7 h thereafter.
Supplementary Video 3
A time-lapse video showing the dynamics of GFP in the toggle switch circuit under the condition without aTc and fresh medium for 16 h and conditioned medium for 10 h thereafter.
Supplementary Video 4
A time-lapse video showing the dynamics of GFP in the toggle switch circuit under the condition with 2 ng ml−1 aTc and fresh medium for 16 h and conditioned medium for 10 h thereafter.
Rights and permissions
About this article
Cite this article
Zhang, R., Li, J., Melendez-Alvarez, J. et al. Topology-dependent interference of synthetic gene circuit function by growth feedback. Nat Chem Biol 16, 695–701 (2020). https://doi.org/10.1038/s41589-020-0509-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41589-020-0509-x
This article is cited by
-
Unbalanced response to growth variations reshapes the cell fate decision landscape
Nature Chemical Biology (2023)
-
Feedforward growth rate control mitigates gene activation burden
Nature Communications (2022)
-
Winner-takes-all resource competition redirects cascading cell fate transitions
Nature Communications (2021)
-
Predictable control of RNA lifetime using engineered degradation-tuning RNAs
Nature Chemical Biology (2021)