1
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Chakravarty S, Zhang R, Tian XJ. Noise Reduction in Resource-Coupled Multi-Module Gene Circuits through Antithetic Feedback Control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595570. [PMID: 38826454 PMCID: PMC11142251 DOI: 10.1101/2024.05.24.595570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Gene circuits within the same host cell often experience coupling, stemming from the competition for limited resources during transcriptional and translational processes. This resource competition introduces an additional layer of noise to gene expression. Here we present three multi-module antithetic control strategies: negatively competitive regulation (NCR) controller, alongside local and global controllers, aimed at reducing the gene expression noise within the context of resource competition. Through stochastic simulations and fluctuation-dissipation theorem (FDT) analysis, our findings highlight the superior performance of the NCR antithetic controller in reducing noise levels. Our research provides an effective control strategy for attenuating resource-driven noise and offers insight into the development of robust gene circuits.
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Affiliation(s)
- Suchana Chakravarty
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
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2
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Hamrick GS, Maddamsetti R, Son HI, Wilson ML, Davis HM, You L. Programming Dynamic Division of Labor Using Horizontal Gene Transfer. ACS Synth Biol 2024; 13:1142-1151. [PMID: 38568420 DOI: 10.1021/acssynbio.3c00615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
The metabolic engineering of microbes has broad applications, including biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multistep pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is the division of labor (DOL) in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted interstrain population dynamics. Through modeling, we show that dynamic division of labor (DDOL), which we define as the DOL between indiscrete populations capable of dynamic and reversible interchange, can overcome these limitations and enable the robust maintenance of burdensome, multistep pathways. We propose that DDOL can be mediated by horizontal gene transfer (HGT) and use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.
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Affiliation(s)
- Grayson S Hamrick
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
- Center for Biomolecular and Tissue Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Rohan Maddamsetti
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Hye-In Son
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Maggie L Wilson
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Harris M Davis
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
- Center for Biomolecular and Tissue Engineering, Duke University, Durham, North Carolina 27708, United States
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, North Carolina 27708, United States
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3
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Sechkar K, Steel H, Perrino G, Stan GB. A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits. Nat Commun 2024; 15:1981. [PMID: 38438391 PMCID: PMC10912777 DOI: 10.1038/s41467-024-46410-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 02/27/2024] [Indexed: 03/06/2024] Open
Abstract
Within a cell, synthetic and native genes compete for expression machinery, influencing cellular process dynamics through resource couplings. Models that simplify competitive resource binding kinetics can guide the design of strategies for countering these couplings. However, in bacteria resource availability and cell growth rate are interlinked, which complicates resource-aware biocircuit design. Capturing this interdependence requires coarse-grained bacterial cell models that balance accurate representation of metabolic regulation against simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with appreciation of bacterial growth regulation mechanisms and the processes relevant for biocircuit design. Reliably capturing known growth phenomena, it provides a unifying explanation to disparate empirical relations between growth and synthetic gene expression. Considering a biomolecular controller that makes cell-wide ribosome availability robust to perturbations, we showcase our model's usefulness in numerically prototyping biocircuits and deriving analytical relations for design guidance.
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Affiliation(s)
- Kirill Sechkar
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
| | - Harrison Steel
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
| | - Giansimone Perrino
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
- Imperial College Centre of Excellence in Synthetic Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
| | - Guy-Bart Stan
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
- Imperial College Centre of Excellence in Synthetic Biology, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
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4
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Stone A, Rijal S, Zhang R, Tian XJ. Enhancing circuit stability under growth feedback with supplementary repressive regulation. Nucleic Acids Res 2024; 52:1512-1521. [PMID: 38164993 PMCID: PMC10853785 DOI: 10.1093/nar/gkad1233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/20/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
The field of synthetic biology and biosystems engineering increasingly acknowledges the need for a holistic design approach that incorporates circuit-host interactions into the design process. Engineered circuits are not isolated entities but inherently entwined with the dynamic host environment. One such circuit-host interaction, 'growth feedback', results when modifications in host growth patterns influence the operation of gene circuits. The growth-mediated effects can range from growth-dependent elevation in protein/mRNA dilution rate to changes in resource reallocation within the cell, which can lead to complete functional collapse in complex circuits. To achieve robust circuit performance, synthetic biologists employ a variety of control mechanisms to stabilize and insulate circuit behavior against growth changes. Here we propose a simple strategy by incorporating one repressive edge in a growth-sensitive bistable circuit. Through both simulation and in vitro experimentation, we demonstrate how this additional repressive node stabilizes protein levels and increases the robustness of a bistable circuit in response to growth feedback. We propose the incorporation of repressive links in gene circuits as a control strategy for desensitizing gene circuits against growth fluctuations.
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Affiliation(s)
- Austin Stone
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Sadikshya Rijal
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
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5
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Stone A, Youssef A, Rijal S, Zhang R, Tian XJ. Context-dependent redesign of robust synthetic gene circuits. Trends Biotechnol 2024:S0167-7799(24)00003-9. [PMID: 38320912 DOI: 10.1016/j.tibtech.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/08/2024]
Abstract
Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit-host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit-host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.
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Affiliation(s)
- Austin Stone
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Abdelrahaman Youssef
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Sadikshya Rijal
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Rong Zhang
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Xiao-Jun Tian
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA.
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6
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Hamrick GS, Maddamsetti R, Son HI, Wilson ML, Davis HM, You L. Programming dynamic division of labor using horizontal gene transfer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.03.560696. [PMID: 37873187 PMCID: PMC10592921 DOI: 10.1101/2023.10.03.560696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.
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7
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Melendez-Alvarez JR, Zhang R, Tian XJ. Growth Feedback Confers Cooperativity in Resource-Competing Synthetic Gene Circuits. CHAOS, SOLITONS, AND FRACTALS 2023; 173:113713. [PMID: 37485435 PMCID: PMC10361397 DOI: 10.1016/j.chaos.2023.113713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Modularity is a key concept in designing synthetic gene circuits, as it allows for constructing complex molecular systems using well-characterized building blocks. One of the major challenges in this field is that these modular components often do not function as expected when assembled into larger circuits. One of the major issues is caused by resource competition, where multiple genes in the circuit compete for the same limited cellular resources, such as transcription factors and ribosomes. In addition, the mutual inhibition between synthetic gene circuits and cell growth results in growth feedback that significantly impacts its host-circuit dynamics. However, the complexity of the gene circuit dynamics under intertwined resource competition and growth feedback is not fully understood. This study developed a theoretical framework to examine the dynamics of synthetic gene circuits by considering both growth feedback and resource competition. Our results suggest a cooperative behavior between resource-competing gene circuits under growth feedback. Cooperation or competition is non-monotonically determined by the metabolic burden threshold. These two diverse effects could lead to the activation or deactivation of one circuit by the other. Lastly, the cooperativity mediated by growth feedback can attenuate the winner-takes-all resource competition. These findings show that coupling growth feedback and resource competition plays a crucial role in the dynamics of the host-circuit system, and understanding its effects helps control unexpected gene expression behaviors.
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Affiliation(s)
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, USA
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8
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Otero-Muras I, Perez-Carrasco R, Banga JR, Barnes CP. Automated design of gene circuits with optimal mushroom-bifurcation behavior. iScience 2023; 26:106836. [PMID: 37255663 PMCID: PMC10225937 DOI: 10.1016/j.isci.2023.106836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/20/2022] [Accepted: 05/04/2023] [Indexed: 06/01/2023] Open
Abstract
Recent advances in synthetic biology are enabling exciting technologies, including the next generation of biosensors, the rational design of cell memory, modulated synthetic cell differentiation, and generic multifunctional biocircuits. These novel applications require the design of gene circuits leading to sophisticated behaviors and functionalities. At the same time, designs need to be kept minimal to avoid compromising cell viability. Bifurcation theory addresses such challenges by associating circuit dynamical properties with molecular details of its design. Nevertheless, incorporating bifurcation analysis into automated design processes has not been accomplished yet. This work presents an optimization-based method for the automated design of synthetic gene circuits with specified bifurcation diagrams that employ minimal network topologies. Using this approach, we designed circuits exhibiting the mushroom bifurcation, distilled the most robust topologies, and explored its multifunctional behavior. We then outline potential applications in biosensors, memory devices, and synthetic cell differentiation.
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Affiliation(s)
- Irene Otero-Muras
- Computational Synthetic Biology Group. Institute for Integrative Systems Biology (UV, CSIC), Spanish National Research Council, 46980 Valencia, Spain
| | | | - Julio R. Banga
- Computational Biology Lab, MBG-CSIC, Spanish National Research Council, 36143 Pontevedra, Spain
| | - Chris P. Barnes
- Department of Cell and Developmental Biology, University College London, London, UK
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9
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Kong LW, Shi W, Tian XJ, Lai YC. Effects of growth feedback on gene circuits: A dynamical understanding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.06.543915. [PMID: 37333159 PMCID: PMC10274713 DOI: 10.1101/2023.06.06.543915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The successful integration of engineered gene circuits into host cells remains a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback, where the circuit influences cell growth and vice versa. Understanding the dynamics of circuit failures and identifying topologies resilient to growth feedback are crucial for both fundamental and applied research. Utilizing transcriptional regulation circuits with adaptation as a paradigm, we systematically study 435 distinct topological structures and uncover six categories of failures. Three dynamical mechanisms of circuit failures are identified: continuous deformation of the response curve, strengthened or induced oscillations, and sudden switching to coexisting attractors. Our extensive computations also uncover a scaling law between a circuit robustness measure and the strength of growth feedback. Despite the negative effects of growth feedback on the majority of circuit topologies, we identify a few circuits that maintain optimal performance as designed, a feature important for applications.
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10
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Yang P, Zhu X, Ning K. Microbiome-based enrichment pattern mining has enabled a deeper understanding of the biome-species-function relationship. Commun Biol 2023; 6:391. [PMID: 37037946 PMCID: PMC10085995 DOI: 10.1038/s42003-023-04753-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 03/24/2023] [Indexed: 04/12/2023] Open
Abstract
Microbes live in diverse habitats (i.e. biomes), yet their species and genes were biome-specific, forming enrichment patterns. These enrichment patterns have mirrored the biome-species-function relationship, which is shaped by ecological and evolutionary principles. However, a grand picture of these enrichment patterns, as well as the roles of external and internal factors in driving these enrichment patterns, remain largely unexamined. In this work, we have examined the enrichment patterns based on 1705 microbiome samples from four representative biomes (Engineered, Gut, Freshwater, and Soil). Moreover, an "enrichment sphere" model was constructed to elucidate the regulatory principles behind these patterns. The driving factors for this model were revealed based on two case studies: (1) The copper-resistance genes were enriched in Soil biomes, owing to the copper contamination and horizontal gene transfer. (2) The flagellum-related genes were enriched in the Freshwater biome, due to high fluidity and vertical gene accumulation. Furthermore, this enrichment sphere model has valuable applications, such as in biome identification for metagenome samples, and in guiding 3D structure modeling of proteins. In summary, the enrichment sphere model aims towards creating a bluebook of the biome-species-function relationships and be applied in many fields.
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Affiliation(s)
- Pengshuo Yang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
- Institute of Medical Genomics, Biomedical Sciences College, Shandong First Medical University, Shandong, 250117, China
| | - Xue Zhu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
- Institute of Medical Genomics, Biomedical Sciences College, Shandong First Medical University, Shandong, 250117, China.
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11
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Stone A, Ryan J, Tang X, Tian XJ. Negatively Competitive Incoherent Feedforward Loops Mitigate Winner-Take-All Resource Competition. ACS Synth Biol 2022; 11:3986-3995. [PMID: 36355441 DOI: 10.1021/acssynbio.2c00318] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The effects of host resource limitations on the function of synthetic gene circuits have gained significant attention over the past years. Hosts, having evolved resource capacities optimal for their own genome, have been repeatedly demonstrated to suffer from the added burden of synthetic genetic programs, which may in return pose deleterious effects on the circuit's function. Three resource controller archetypes have been proposed previously to mitigate resource distribution problems in dynamic circuits: the local controller, the global controller, and a "negatively competitive" regulatory (NCR) controller that utilizes synthetic competition to combat resource competition. The dynamics of negative feedback forms of these controllers have been previously investigated, and here we extend the analysis of these resource allocation strategies to the incoherent feedforward loop (iFFL) topology. We demonstrate that the three iFFL controllers can attenuate Winner-Take-All resource competition between two bistable switches. We uncover that the parameters associated with the synthetic competition in the NCR iFFL controller are paramount to its increased efficacy over the local controller type, while the global controllers demonstrate to be relatively ineffectual. Interestingly, unlike the negative feedback counterpart topologies, iFFL controllers exhibit a unique coupling of switch activation thresholds which we term the "coactivation threshold shift" effect. Finally, we demonstrate that a nearly fully orthogonal set of bistable switches could be achieved by pairing an NCR controller with an appropriate level of controller resource consumption.
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Affiliation(s)
- Austin Stone
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona85281, United States
| | - Jordan Ryan
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana70803, United States
| | - Xun Tang
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana70803, United States
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona85281, United States
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12
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Toward predictive engineering of gene circuits. Trends Biotechnol 2022; 41:760-768. [PMID: 36435671 DOI: 10.1016/j.tibtech.2022.11.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/26/2022] [Accepted: 11/02/2022] [Indexed: 11/25/2022]
Abstract
Many synthetic biology applications rely on programming living cells using gene circuits - the assembly and wiring of genetic elements to control cellular behaviors. Extensive progress has been made in constructing gene circuits with diverse functions and applications. For many circuit functions, however, it remains challenging to ensure that the circuits operate in a predictable manner. Although the notion of predictability may appear intuitive, close inspection suggests that it is not always clear what constitutes predictability. We dissect this concept and how it can be confounded by the complexity of a circuit, the complexity of the context, and the interplay between the two. We discuss circuit engineering strategies, in both computation and experiment, that have been used to improve the predictability of gene circuits.
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13
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Lee TA, Steel H. Cybergenetic control of microbial community composition. Front Bioeng Biotechnol 2022; 10:957140. [PMID: 36277404 PMCID: PMC9582452 DOI: 10.3389/fbioe.2022.957140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The use of bacterial communities in bioproduction instead of monocultures has potential advantages including increased productivity through division of labour, ability to utilise cheaper substrates, and robustness against perturbations. A key challenge in the application of engineered bacterial communities is the ability to reliably control the composition of the community in terms of its constituent species. This is crucial to prevent faster growing species from outcompeting others with a lower relative fitness, and to ensure that all species are present at an optimal ratio during different steps in a biotechnological process. In contrast to purely biological approaches such as synthetic quorum sensing circuits or paired auxotrophies, cybergenetic control techniques - those in which computers interface with living cells-are emerging as an alternative approach with many advantages. The community composition is measured through methods such as fluorescence intensity or flow cytometry, with measured data fed real-time into a computer. A control action is computed using a variety of possible control algorithms and then applied to the system, with actuation taking the form of chemical (e.g., inducers, nutrients) or physical (e.g., optogenetic, mechanical) inputs. Subsequent changes in composition are then measured and the cycle repeated, maintaining or driving the system to a desired state. This review discusses recent and future developments in methods for implementing cybergenetic control systems, contrasts their capabilities with those of traditional biological methods of population control, and discusses future directions and outstanding challenges for the field.
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14
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Melendez-Alvarez JR, Tian XJ. Emergence of qualitative states in synthetic circuits driven by ultrasensitive growth feedback. PLoS Comput Biol 2022; 18:e1010518. [PMID: 36112667 PMCID: PMC9518899 DOI: 10.1371/journal.pcbi.1010518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/28/2022] [Accepted: 08/26/2022] [Indexed: 11/24/2022] Open
Abstract
The mutual interactions between the synthetic gene circuits and the host growth could cause unexpected outcomes in the dynamical behaviors of the circuits. However, how the steady states and the stabilities of the gene circuits are affected by host cell growth is not fully understood. Here, we developed a mathematical model for nonlinear growth feedback based on published experimental data. The model analysis predicts that growth feedback could significantly change the qualitative states of the system. Bistability could emerge in a circuit without positive feedback, and high-order multistability (three or more steady states) arises in the self-activation and toggle switch circuits. Our results provide insight into the potential effects of ultrasensitive growth feedback on the emergence of qualitative states in synthetic circuits and the corresponding underlying mechanism. The mutual inhibitory effect between synthetic gene circuits and cell growth produces growth feedback in the host-circuit system. Previous studies have demonstrated that the growth feedback could significantly impact the dynamics of the host-circuit system. However, the complexity of the growth feedback impact is not fully understood. Here, our data analysis displays ultrasensitive growth feedback between the cells and synthetic gene circuits under different growth conditions. To study the effect of ultrasensitive growth feedback on the host-circuit system, we develop a mathematical modeling framework. Our results reveal the emergence of qualitative states on the host-circuit system induced by ultrasensitive growth feedback. We found an emergence of bistability in a simple synthetic gene circuit with a constitutive promoter. Also, tristability could be seen in self-activation and toggle switch circuits. Our research uncovered the effect of ultrasensitive growth feedback in synthetic gene circuits and host interactions. Understanding the effects of ultrasensitive growth feedback could help scientists and engineers identify unexpected outcomes in gene circuits and formulate control strategies.
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Affiliation(s)
- Juan Ramon Melendez-Alvarez
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
- * E-mail:
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15
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Lewis DD, Gong T, Xu Y, Tan C. Frequency dependent growth of bacteria in living materials. Front Bioeng Biotechnol 2022; 10:948483. [PMID: 36159663 PMCID: PMC9493075 DOI: 10.3389/fbioe.2022.948483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
The fusion of living bacteria and man-made materials represents a new frontier in medical and biosynthetic technology. However, the principles of bacterial signal processing inside synthetic materials with three-dimensional and fluctuating environments remain elusive. Here, we study bacterial growth in a three-dimensional hydrogel. We find that bacteria expressing an antibiotic resistance module can take advantage of ambient kinetic disturbances to improve growth while encapsulated. We show that these changes in bacterial growth are specific to disturbance frequency and hydrogel density. This remarkable specificity demonstrates that periodic disturbance frequency is a new input that engineers may leverage to control bacterial growth in synthetic materials. This research provides a systematic framework for understanding and controlling bacterial information processing in three-dimensional living materials.
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Affiliation(s)
- Daniel D. Lewis
- Department of Biomedical Engineering, University of California, Davis, CA, United States
- Integrative Genetics and Genomics, University of California, Davis, CA, United States
| | - Ting Gong
- Department of Biomedical Engineering, University of California, Davis, CA, United States
| | - Yuanwei Xu
- Department of Biomedical Engineering, Peking University, Beijing, China
| | - Cheemeng Tan
- Department of Biomedical Engineering, University of California, Davis, CA, United States
- *Correspondence: Cheemeng Tan,
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16
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Ryan J, Hong S, Foo M, Kim J, Tang X. Model-Based Investigation of the Relationship between Regulation Level and Pulse Property of I1-FFL Gene Circuits. ACS Synth Biol 2022; 11:2417-2428. [PMID: 35729788 PMCID: PMC9295143 DOI: 10.1021/acssynbio.2c00109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Mathematical models are powerful tools in guiding the construction of synthetic biological circuits, given their capability of accurately capturing and predicting circuit dynamics. Recent innovations in RNA technology have enabled the development of a variety of new tools for regulating gene expression at both the transcription and translation levels. However, the effects of different regulation levels on the circuit dynamics remain largely unexplored. In this study, we focus on the type 1 incoherent feed-forward loop (I1-FFL) gene circuit with four different variations (TX, TL, HY-1, HY-2), to investigate how regulation at the transcription and translation levels affect the circuit dynamics. We develop a mechanistic model for each of the four circuits and deploy sensitivity analysis to investigate the circuits' dynamics in terms of pulse generation. Based on the analysis, we observe that the repression regulation mechanism dominates the characteristics of the pulse as compared to the activation regulation mechanism and find that the I1-FFL with transcription repression has a higher chance of generating a pulse meeting the desired criteria. The experimental results in Escherichia coli also confirm our findings from the computational analysis. We expect our findings to facilitate future experimental construction of gene circuits with insights on the selection of appropriate transcription and translation regulation tools.
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Affiliation(s)
- Jordan Ryan
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States
| | - Seongho Hong
- Department of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk 37673, South Korea
| | - Mathias Foo
- School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Jongmin Kim
- Department of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk 37673, South Korea
| | - Xun Tang
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States
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17
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Carignano A, Chen DH, Mallory C, Wright RC, Seelig G, Klavins E. Modular, robust and extendible multicellular circuit design in yeast. eLife 2022; 11:74540. [PMID: 35312478 PMCID: PMC9000959 DOI: 10.7554/elife.74540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 03/20/2022] [Indexed: 11/13/2022] Open
Abstract
Division of labor between cells is ubiquitous in biology but the use of multi-cellular consortia for engineering applications is only beginning to be explored. A significant advantage of multi-cellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their input-output relationships. We then compose these strains into two- and three-strain cascades as well as a four-strain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two-, three- and four-strain consortia to identify combinations that realize target behaviors including logic gates, band-pass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.
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Affiliation(s)
- Alberto Carignano
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Dai Hua Chen
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Cannon Mallory
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | | | - Georg Seelig
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Eric Klavins
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
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18
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Goetz H, Stone A, Zhang R, Lai Y, Tian X. Double-edged role of resource competition in gene expression noise and control. ADVANCED GENETICS (HOBOKEN, N.J.) 2022; 3:2100050. [PMID: 35989723 PMCID: PMC9390979 DOI: 10.1002/ggn2.202100050] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Despite extensive investigation demonstrating that resource competition can significantly alter the deterministic behaviors of synthetic gene circuits, it remains unclear how resource competition contributes to the gene expression noise and how this noise can be controlled. Utilizing a two-gene circuit as a prototypical system, we uncover a surprising double-edged role of resource competition in gene expression noise: competition decreases noise through introducing a resource constraint but generates its own type of noise which we name as "resource competitive noise." Utilization of orthogonal resources enables retainment of the noise reduction conferred by resource constraint while removing the added resource competitive noise. The noise reduction effects are studied using three negative feedback types: negatively competitive regulation (NCR), local, and global controllers, each having four placement architectures in the protein biosynthesis pathway (mRNA or protein inhibition on transcription or translation). Our results show that both local and NCR controllers with mRNA-mediated inhibition are efficacious at reducing noise, with NCR controllers demonstrating a superior noise-reduction capability. We also find that combining feedback controllers with orthogonal resources can improve the local controllers. This work provides deep insights into the origin of stochasticity in gene circuits with resource competition and guidance for developing effective noise control strategies.
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Affiliation(s)
- Hanah Goetz
- School for Engineering of Matter, Transport and EnergyArizona State UniversityTempeAZ85287USA
| | - Austin Stone
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
| | - Rong Zhang
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
| | - Ying‐Cheng Lai
- School of Electrical, Computer and Energy EngineeringArizona State UniversityTempeAZ85287USA
- Department of PhysicsArizona State UniversityTempeAZ85287USA
| | - Xiao‐Jun Tian
- School of Biological and Health Systems EngineeringArizona State UniversityTempeAZ85287USA
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19
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Sun Z, Wei W, Zhang M, Shi W, Zong Y, Chen Y, Yang X, Yu B, Tang C, Lou C. Synthetic robust perfect adaptation achieved by negative feedback coupling with linear weak positive feedback. Nucleic Acids Res 2022; 50:2377-2386. [PMID: 35166832 PMCID: PMC8887471 DOI: 10.1093/nar/gkac066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 01/15/2022] [Accepted: 01/25/2022] [Indexed: 12/21/2022] Open
Abstract
Unlike their natural counterparts, synthetic genetic circuits are usually fragile in the face of environmental perturbations and genetic mutations. Several theoretical robust genetic circuits have been designed, but their performance under real-world conditions has not yet been carefully evaluated. Here, we designed and synthesized a new robust perfect adaptation circuit composed of two-node negative feedback coupling with linear positive feedback on the buffer node. As a key feature, the linear positive feedback was fine-tuned to evaluate its necessity. We found that the desired function was robustly achieved when genetic parameters were varied by systematically perturbing all interacting parts within the topology, and the necessity of the completeness of the topological structures was evaluated by destroying key circuit features. Furthermore, different environmental perturbances were imposed onto the circuit by changing growth rates, carbon metabolic strategies and even chassis cells, and the designed perfect adaptation function was still achieved under all conditions. The successful design of a robust perfect adaptation circuit indicated that the top-down design strategy is capable of predictably guiding bottom-up engineering for robust genetic circuits. This robust adaptation circuit could be integrated as a motif into more complex circuits to robustly implement more sophisticated and critical biological functions.
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Affiliation(s)
- Zhi Sun
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Weijia Wei
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Mingyue Zhang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,School of Physics, Peking University, Beijing 100871, China
| | - Wenjia Shi
- Department of Applied Physics, School of Sciences, Xi'an University of Technology, Xi'an 710048, China
| | | | - Yihua Chen
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Xiaojing Yang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Bo Yu
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chao Tang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,School of Physics, Peking University, Beijing 100871, China
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
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20
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McBride CD, Del Vecchio D. Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity. ACS Synth Biol 2021; 10:3330-3342. [PMID: 34780149 DOI: 10.1021/acssynbio.1c00281] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared resources. In order to engineer multimodule circuits that behave as intended, it is thus necessary to predict changes in the behavior of a genetic module when other modules load cellular resources. Here, we introduce two characteristics of circuit modules: the demand for cellular resources and the sensitivity to resource loading. When both are known for every genetic module in a circuit library, they can be used to predict any module's behavior upon addition of any other module to the cell. We develop an experimental approach to measure both characteristics for any circuit module using a resource sensor module. Using the measured resource demand and sensitivity for each module in a library, the outputs of the modules can be accurately predicted when they are inserted in the cell in arbitrary combinations. These resource competition characteristics may be used to inform the design of genetic circuits that perform as predicted despite resource competition.
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Affiliation(s)
- Cameron D. McBride
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02142, United States
| | - Domitilla Del Vecchio
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02142, United States
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21
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Duncker KE, Holmes ZA, You L. Engineered microbial consortia: strategies and applications. Microb Cell Fact 2021; 20:211. [PMID: 34784924 PMCID: PMC8597270 DOI: 10.1186/s12934-021-01699-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/23/2021] [Indexed: 11/10/2022] Open
Abstract
Many applications of microbial synthetic biology, such as metabolic engineering and biocomputing, are increasing in design complexity. Implementing complex tasks in single populations can be a challenge because large genetic circuits can be burdensome and difficult to optimize. To overcome these limitations, microbial consortia can be engineered to distribute complex tasks among multiple populations. Recent studies have made substantial progress in programming microbial consortia for both basic understanding and potential applications. Microbial consortia have been designed through diverse strategies, including programming mutualistic interactions, using programmed population control to prevent overgrowth of individual populations, and spatial segregation to reduce competition. Here, we highlight the role of microbial consortia in the advances of metabolic engineering, biofilm production for engineered living materials, biocomputing, and biosensing. Additionally, we discuss the challenges for future research in microbial consortia.
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Affiliation(s)
- Katherine E Duncker
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA
| | - Zachary A Holmes
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA.
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22
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Gyorgy A. Context-Dependent Stability and Robustness of Genetic Toggle Switches with Leaky Promoters. Life (Basel) 2021; 11:life11111150. [PMID: 34833026 PMCID: PMC8624834 DOI: 10.3390/life11111150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/21/2021] [Accepted: 10/26/2021] [Indexed: 01/22/2023] Open
Abstract
Multistable switches are ubiquitous building blocks in both systems and synthetic biology. Given their central role, it is thus imperative to understand how their fundamental properties depend not only on the tunable biophysical properties of the switches themselves, but also on their genetic context. To this end, we reveal in this article how these factors shape the essential characteristics of toggle switches implemented using leaky promoters such as their stability and robustness to noise, both at single-cell and population levels. In particular, our results expose the roles that competition for scarce transcriptional and translational resources, promoter leakiness, and cell-to-cell heterogeneity collectively play. For instance, the interplay between protein expression from leaky promoters and the associated cost of relying on shared cellular resources can give rise to tristable dynamics even in the absence of positive feedback. Similarly, we demonstrate that while promoter leakiness always acts against multistability, resource competition can be leveraged to counteract this undesirable phenomenon. Underpinned by a mechanistic model, our results thus enable the context-aware rational design of multistable genetic switches that are directly translatable to experimental considerations, and can be further leveraged during the synthesis of large-scale genetic systems using computer-aided biodesign automation platforms.
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Affiliation(s)
- Andras Gyorgy
- Division of Engineering, New York University Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab Emirates
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23
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Melendez-Alvarez J, He C, Zhang R, Kuang Y, Tian XJ. Emergent Damped Oscillation Induced by Nutrient-Modulating Growth Feedback. ACS Synth Biol 2021; 10:1227-1236. [PMID: 33915046 PMCID: PMC10893968 DOI: 10.1021/acssynbio.1c00041] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Growth feedback, the inherent coupling between the synthetic gene circuit and the host cell growth, could significantly change the circuit behaviors. Previously, a diverse array of emergent behaviors, such as growth bistability, enhanced ultrasensitivity, and topology-dependent memory loss, were reported to be induced by growth feedback. However, the influence of the growth feedback on the circuit functions remains underexplored. Here, we reported an unexpected damped oscillatory behavior of a self-activation gene circuit induced by nutrient-modulating growth feedback. Specifically, after dilution of the activated self-activation switch into the fresh medium with moderate nutrients, its gene expression first decreases as the cell grows and then shows a significant overshoot before it reaches the steady state, leading to damped oscillation dynamics. Fitting the data with a coarse-grained model suggests a nonmonotonic growth-rate regulation on gene production rate. The underlying mechanism of the oscillation was demonstrated by a molecular mathematical model, which includes the ribosome allocation toward gene production, cell growth, and cell maintenance. Interestingly, the model predicted a counterintuitive dependence of oscillation amplitude on the nutrition level, where the highest peak was found in the medium with moderate nutrients, but was not observed in rich nutrients. We experimentally verified this prediction by tuning the nutrient level in the culture medium. We did not observe significant oscillatory behavior for the toggle switch, suggesting that the emergence of damped oscillatory behavior depends on circuit network topology. Our results demonstrated a new nonlinear emergent behavior mediated by growth feedback, which depends on the ribosome allocation between gene circuit and cell growth.
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Affiliation(s)
- Juan Melendez-Alvarez
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Changhan He
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85281, United States
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85281, United States
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States
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24
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Yong C, Gyorgy A. Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources. Life (Basel) 2021; 11:271. [PMID: 33805212 PMCID: PMC8064337 DOI: 10.3390/life11040271] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 03/17/2021] [Accepted: 03/19/2021] [Indexed: 12/24/2022] Open
Abstract
While the vision of synthetic biology is to create complex genetic systems in a rational fashion, system-level behaviors are often perplexing due to the context-dependent dynamics of modules. One major source of context-dependence emerges due to the limited availability of shared resources, coupling the behavior of disconnected components. Motivated by the ubiquitous role of toggle switches in genetic circuits ranging from controlling cell fate differentiation to optimizing cellular performance, here we reveal how their fundamental dynamic properties are affected by competition for scarce resources. Combining a mechanistic model with nullcline-based stability analysis and potential landscape-based robustness analysis, we uncover not only the detrimental impacts of resource competition, but also how the unbalancedness of the switch further exacerbates them. While in general both of these factors undermine the performance of the switch (by pushing the dynamics toward monostability and increased sensitivity to noise), we also demonstrate that some of the unwanted effects can be alleviated by strategically optimized resource competition. Our results provide explicit guidelines for the context-aware rational design of toggle switches to mitigate our reliance on lengthy and expensive trial-and-error processes, and can be seamlessly integrated into the computer-aided synthesis of complex genetic systems.
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Affiliation(s)
- Chentao Yong
- Department of Chemical and Biological Engineering, New York University, New York, NY 10003, USA;
| | - Andras Gyorgy
- Department of Electrical and Computer Engineering, New York University Abu Dhabi, Abu Dhabi 129188, United Arab Emirates
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