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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; 42:895-909. [PMID: 38320912 PMCID: PMC11223972 DOI: 10.1016/j.tibtech.2024.01.003] [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: 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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2
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Abstract
Microbial communities are complex living systems that populate the planet with diverse functions and are increasingly harnessed for practical human needs. To deepen the fundamental understanding of their organization and functioning as well as to facilitate their engineering for applications, mathematical modeling has played an increasingly important role. Agent-based models represent a class of powerful quantitative frameworks for investigating microbial communities because of their individualistic nature in describing cells, mechanistic characterization of molecular and cellular processes, and intrinsic ability to produce emergent system properties. This review presents a comprehensive overview of recent advances in agent-based modeling of microbial communities. It surveys the state-of-the-art algorithms employed to simulate intracellular biomolecular events, single-cell behaviors, intercellular interactions, and interactions between cells and their environments that collectively serve as the driving forces of community behaviors. It also highlights three lines of applications of agent-based modeling, namely, the elucidation of microbial range expansion and colony ecology, the design of synthetic gene circuits and microbial populations for desired behaviors, and the characterization of biofilm formation and dispersal. The review concludes with a discussion of existing challenges, including the computational cost of the modeling, and potential mitigation strategies.
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Affiliation(s)
- Karthik Nagarajan
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Congjian Ni
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Ting Lu
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,National Center for Supercomputing Applications, Urbana, Illinois 61801, United States
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3
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Atkinson E, Tuza Z, Perrino G, Stan GB, Ledesma-Amaro R. Resource-aware whole-cell model of division of labour in a microbial consortium for complex-substrate degradation. Microb Cell Fact 2022; 21:115. [PMID: 35698129 PMCID: PMC9195437 DOI: 10.1186/s12934-022-01842-0] [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] [Received: 01/28/2022] [Accepted: 05/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Low-cost sustainable feedstocks are essential for commercially viable biotechnologies. These feedstocks, often derived from plant or food waste, contain a multitude of different complex biomolecules which require multiple enzymes to hydrolyse and metabolise. Current standard biotechnology uses monocultures in which a single host expresses all the proteins required for the consolidated bioprocess. However, these hosts have limited capacity for expressing proteins before growth is impacted. This limitation may be overcome by utilising division of labour (DOL) in a consortium, where each member expresses a single protein of a longer degradation pathway. RESULTS Here, we model a two-strain consortium, with one strain expressing an endohydrolase and a second strain expressing an exohydrolase, for cooperative degradation of a complex substrate. Our results suggest that there is a balance between increasing expression to enhance degradation versus the burden that higher expression causes. Once a threshold of burden is reached, the consortium will consistently perform better than an equivalent single-cell monoculture. CONCLUSIONS We demonstrate that resource-aware whole-cell models can be used to predict the benefits and limitations of using consortia systems to overcome burden. Our model predicts the region of expression where DOL would be beneficial for growth on starch, which will assist in making informed design choices for this, and other, complex-substrate degradation pathways.
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Affiliation(s)
- Eliza Atkinson
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Zoltan Tuza
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Giansimone Perrino
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Guy-Bart Stan
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK.
| | - Rodrigo Ledesma-Amaro
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK.
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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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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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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: 9] [Impact Index Per Article: 3.0] [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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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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Gómez-Schiavon M, Dods G, El-Samad H, Ng AH. Multidimensional Characterization of Parts Enhances Modeling Accuracy in Genetic Circuits. ACS Synth Biol 2020; 9:2917-2926. [PMID: 33166452 DOI: 10.1021/acssynbio.0c00288] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Mathematical models can aid the design of genetic circuits, but may yield inaccurate results if individual parts are not modeled at the appropriate resolution. To illustrate the importance of this concept, we study transcriptional cascades consisting of two inducible synthetic transcription factors connected in series. Despite the simplicity of this design, we find that accurate prediction of circuit behavior requires mapping the dose responses of each circuit component along the dimensions of both its expression level and its inducer concentration. Using this multidimensional characterization, we were able to computationally explore the behavior of 16 different circuit designs. We experimentally verified a subset of these predictions and found substantial agreement. This method of biological part characterization enables the use of models to identify (un)desired circuit behaviors prior to experimental implementation, thus shortening the design-build-test cycle for more complex circuits.
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Affiliation(s)
- Mariana Gómez-Schiavon
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California 94158, United States
| | - Galen Dods
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California 94158, United States
| | - Hana El-Samad
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California 94158, United States
- Chan−Zuckerberg Biohub, San Francisco, California 94158, United States
- Cell Design Institute, University of California, San Francisco, San Francisco, California 94158, United States
| | - Andrew H. Ng
- Cell Design Institute, University of California, San Francisco, San Francisco, California 94158, United States
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California 94158, United States
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9
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Yáñez Feliú G, Vidal G, Muñoz Silva M, Rudge TJ. Novel Tunable Spatio-Temporal Patterns From a Simple Genetic Oscillator Circuit. Front Bioeng Biotechnol 2020; 8:893. [PMID: 33014996 PMCID: PMC7509427 DOI: 10.3389/fbioe.2020.00893] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 07/13/2020] [Indexed: 11/13/2022] Open
Abstract
Multicellularity, the coordinated collective behavior of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviors at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates traveling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the traveling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.
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Affiliation(s)
- Guillermo Yáñez Feliú
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Gonzalo Vidal
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Macarena Muñoz Silva
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Timothy J. Rudge
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
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