scholarly journals Mitigation of resource competition in synthetic genetic circuits through feedback regulation

2014 ◽  
Author(s):  
Abdullah Hamadeh ◽  
Domitilla Del Vecchio
Keyword(s):  
Resource Competition ◽  
Feedback Regulation ◽  
Genetic Circuits

scholarly journals Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 271
Author(s):  
Chentao Yong ◽  
Andras Gyorgy
Keyword(s):  
Cell Fate ◽  
Rational Design ◽  
Resource Competition ◽  
Dynamic Properties ◽  
Mechanistic Model ◽  
Robustness Analysis ◽  
System Level ◽  
Genetic Circuits ◽  
Scarce Resources ◽  
Genetic Systems

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.

scholarly journals Resource Competition Shapes the Response of Genetic Circuits

2017 ◽  
Vol 6 (7) ◽  
pp. 1263-1272 ◽  
Author(s):  
Yili Qian ◽  
Hsin-Ho Huang ◽  
José I. Jiménez ◽  
Domitilla Del Vecchio
Keyword(s):  
Resource Competition ◽  
Genetic Circuits

scholarly journals The Effects of Ribosome Autocatalysis and Negative Feedback in Resource Competition

2016 ◽  
Author(s):  
Fiona Chandra ◽  
Domitilla Del Vecchio
Keyword(s):  
Steady State ◽  
Negative Feedback ◽  
Resource Competition ◽  
Mrna Level ◽  
Transient Behavior ◽  
Rrna Synthesis ◽  
Qualitative Behavior ◽  
Genetic Circuits ◽  
Synthetic Genes ◽  
State Models

Resource competition, and primarily competition for ribosomes, can lead to unexpected behavior of genetic circuits and has recently gained renewed attention with both experimental and theoretical studies. Current models studying the effects of resource competition assume a constant production of ribosomes and these models describe the experimental results well. However, ribosomes are also autocatalytic since they are partially made of protein and autocatalysis has been shown to have detrimental effects on a system's stability and robustness. Additionally, there are known feedback regulations on ribosome synthesis such as inhibition of rRNA synthesis via ppGpp. Here, we develop two-state models of ribosome and protein synthesis incorporating autocatalysis and feedback to investigate conditions under which these regulatory actions have a significant effect in situations of increased ribosome demand. Our modeling results indicate that for sufficiently low demand, defined by the mRNA level of synthetic genes, autocatalysis has little or no effect. However, beyond a certain demand level, the system goes through a transcritical bifurcation at which the only non-negative steady state is at zero ribosome concentration. The presence of negative feedback, in turn, can shift this point to higher demand values, thus restoring the qualitative behavior observed in a model with a constant ribosome production at low demand. However, autocatalysis affects the dynamics of the system and can lead to an overshoot in the temporal response of the synthetic genes to changes in induction level. Our results show that ribosome autocatalysis has a significant effect on the system robustness to increases in ribosome demand, however the existing negative feedback on ribosome production compensates for the effects of the necessary autocatalytic loop and restores the behavior seen in the system with constant ribosome production. These findings explain why previous models with constant ribosome production reproduce the steady state behavior well, however incorporating autocatalysis and feedback is needed to capture the transient behavior.

Design of Genetic Circuits that are Robust to Resource Competition

2021 ◽  
pp. 100357
Author(s):  
Cameron D. McBride ◽  
Theodore W. Grunberg ◽  
Domitilla Del Vecchio
Keyword(s):  
Resource Competition ◽  
Genetic Circuits

scholarly journals Resource Competition Shapes the Response of Genetic Circuits

2016 ◽  
Author(s):  
Yili Qian ◽  
Hsin-Ho Huang ◽  
José I. Jimenéz ◽  
Domitilla Del Vecchio
Keyword(s):  
Resource Competition ◽  
Hill Function ◽  
Genetic Circuits ◽  
Resource Demand ◽  
E Coli ◽  
Regulatory Interactions ◽  
Ribosome Binding ◽  
Competition Effects ◽  
Activation Cascade ◽  
Competition For Resources

AbstractA common approach to design genetic circuits is to compose gene expression cassettes together. While appealing, this modular approach is challenged by the fact that expression of each gene depends on the availability of transcriptional/translational resources, which is in turn determined by the presence of other genes in the circuit. This raises the question of how competition for resources by different genes affects a circuit’s behavior. Here, we create a library of genetic activation cascades in bacteriaE. coli, where we explicitly tune the resource demand by each gene. We develop a general Hill-function-based model that incorporates resource competition effects through resource demand coefficients. These coefficients lead to non-regulatory interactions among genes that reshape circuit’s behavior. For the activation cascade, such interactions result in surprising biphasic or monotonically decreasing responses. Finally, we use resource demand coefficients to guide the choice of ribosome binding site (RBS) and DNA copy number to restore the cascade’s intended monotonically increasing response. Our results demonstrate how unintended circuit’s behavior arises from resource competition and provide a model-guided methodology to minimize the resulting effects.

scholarly journals Comparison between Effects of Retroactivity and Resource Competition upon Change in Downstream Reporter Genes of Synthetic Genetic Circuits

Life ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 30 ◽  
Author(s):  
Takefumi Moriya ◽  
Tomohiro Yamaoka ◽  
Yuki Wakayama ◽  
Shotaro Ayukawa ◽  
Zicong Zhang ◽  
...  
Keyword(s):  
In Silico ◽  
Fluorescent Protein ◽  
Resource Competition ◽  
Regulatory Protein ◽  
Reporter Genes ◽  
Genetic Circuits ◽  
In Vivo Experiments ◽  
Reporter Promoter ◽  
The Stability

Reporter genes have contributed to advancements in molecular biology. Binding of an upstream regulatory protein to a downstream reporter promoter allows quantification of the activity of the upstream protein produced from the corresponding gene. In studies of synthetic biology, analyses of reporter gene activities ensure control of the cell with synthetic genetic circuits, as achieved using a combination of in silico and in vivo experiments. However, unexpected effects of downstream reporter genes on upstream regulatory genes may interfere with in vivo observations. This phenomenon is termed as retroactivity. Using in silico and in vivo experiments, we found that a different copy number of regulatory protein-binding sites in a downstream gene altered the upstream dynamics, suggesting retroactivity of reporters in this synthetic genetic oscillator. Furthermore, by separating the two sources of retroactivity (titration of the component and competition for degradation), we showed that, in the dual-feedback oscillator, the level of the fluorescent protein reporter competing for degradation with the circuits’ components is important for the stability of the oscillations. Altogether, our results indicate that the selection of reporter promoters using a combination of in silico and in vivo experiments is essential for the advanced design of genetic circuits.

scholarly journals Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity

2021 ◽  
Author(s):  
Cameron D McBride ◽  
Domitilla Del Vecchio
Keyword(s):  
Experimental Approach ◽  
Resource Competition ◽  
Genetic Circuits ◽  
Shared Resources ◽  
Resource Demand ◽  
Sensor Module ◽  
Resource Loading ◽  
Genetic Module

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 multi-module 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, 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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