Characterization of a quorum sensing device for synthetic biology design: Experimental and modeling validation

Saeidi, Nazanin; Arshath, Mohamed; Chang, Matthew Wook; Poh, Chueh Loo

doi:10.1016/j.ces.2012.12.016

Cited by 7 publications

(12 citation statements)

References 30 publications

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“…LuxR binds to AHL to form the LuxR:AHL complex. Then two LuxR:AHL complexes combine together to form the active tetramer complex, LuxR 2 :AHL 2 24 , 25 , which will subsequently bind to the promoter luxpR and induce the expression of the lethal gene to produce the protein CcdB 26 , 27 . In the quorum sensing systems, CcdB is completely artificial, which can inactivate DNA gyrase and kill the host bacteria, thereby regulating bacterial population density 28 , 29 .…”

Section: Resultsmentioning

confidence: 99%

“…As the signaling molecule in the synthetic quorum sensing system, AHL can permeate outside the bacterial cells. A number of models have been developed to evaluate the complex role of AHL in various quorum sensing systems 17 , 26 , 38 . However, a quantitative analysis of whether and how the permeability of AHL can regulate population density is still lacking.…”

Section: Resultsmentioning

confidence: 99%

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Quantifying the optimal strategy of population control of quorum sensing network in Escherichia coli

Jin

Zhang

et al. 2021

npj Syst Biol Appl

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Biological functions of bacteria can be regulated by monitoring their own population density induced by the quorum sensing system. However, quantitative insight into the system’s dynamics and regulatory mechanism remain challenging. Here, we construct a comprehensive mathematical model of the synthetic quorum sensing circuit that controls population density in Escherichia coli. Simulations agree well with experimental results obtained under different ribosome-binding site (RBS) efficiencies. We present a quantitative description of the component dynamics and show how the components respond to isopropyl-β-D-1-thiogalactopyranoside (IPTG) induction. The optimal IPTG-induction range for efficiently controlling population density is quantified. The controllable area of population density by acyl-homoserine lactone (AHL) permeability is quantified as well, indicating that high AHL permeability should be treated with a high dose of IPTG, while low AHL permeability should be induced with low dose for efficiently controlling. Unexpectedly, an oscillatory behavior of the growth curve is observed with proper RBS-binding strengths and the oscillation is greatly restricted by the bacterial death induced by toxic metabolic by-products. Moreover, we identify that the mechanism underlying the emergence of oscillation is determined by the negative feedback loop structure within the signaling. Bifurcation analysis and landscape theory are further employed to study the stochastic dynamic and global stability of the system, revealing two faces of toxic metabolic by-products in controlling oscillatory behavior. Overall, our study presents a quantitative basis for understanding and new insights into the control mechanism of quorum sensing system, providing possible clues to guide the development of more rational control strategy.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Quantifying the optimal strategy of population control of quorum sensing network in Escherichia coli

Jin

Zhang

et al. 2021

npj Syst Biol Appl

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“…Parameter values are obtained from either BioNumber and literature, or by parameter estimation performed in this study (Supporting Information Table S2). Each module is validated using experimental results measured from another genetic circuit(s), or in vitro study provided by other researches. , …”

Section: Methodsmentioning

confidence: 99%

Biosensing Vibrio cholerae with Genetically Engineered Escherichia coli

et al. 2016

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Cholera is a potentially mortal, infectious disease caused by Vibrio cholerae bacterium. Current treatment methods of cholera still have limitations. Beneficial microbes that could sense and kill the V. cholerae could offer potential alternative to preventing and treating cholera. However, such V. cholerae targeting microbe is still not available. This microbe requires a sensing system to be able to detect the presence of V. cholera bacterium. To this end, we designed and created a synthetic genetic sensing system using nonpathogenic Escherichia coli as the host. To achieve the system, we have moved proteins used by V. cholerae for quorum sensing into E. coli. These sensor proteins have been further layered with a genetic inverter based on CRISPRi technology. Our design process was aided by computer models simulating in vivo behavior of the system. Our sensor shows high sensitivity to presence of V. cholerae supernatant with tight control of expression of output GFP protein.

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“…Figure illustrates the quorum sensing device and its corresponding design. The system can be briefly described as follows:…”

Section: Biological Modelsmentioning

confidence: 99%

“…al. 34 The authors designed a quorum sensing device which can sense the pathogenic Pseudomonas aeruginosa bacteria, and upon detection it illuminates green fluorescent protein (GFP). To analyse different aspects of the quorum sensing system, we consider two variations of the model: a rule-based stochastic model and non-deterministic model.…”

Section: Quorum Sensingmentioning

confidence: 99%

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

et al. 2014

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Qualitative and quantitative analysis of systems and synthetic biology constructs using P systems. ACS Synthetic Biology, 4 (1): 83-92. AbstractComputational models are perceived as an attractive alternative to mathematical models, e.g. ordinary differential equations. These models incorporate a set of methods for specifying, modelling, testing and simulating biological systems. In addition, they can be analysed using algorithmic techniques, e.g. formal verification. This paper shows how formal verification is utilised in systems and synthetic biology through qualitative vs quantitative analysis. Here, we choose two well known case studies: quorum sensing in P. aeruginosas and pulse generator. The paper reports verification analysis of two systems carried out using some model checking tools, integrated to the

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Characterization of a quorum sensing device for synthetic biology design: Experimental and modeling validation

Cited by 7 publications

References 30 publications

Quantifying the optimal strategy of population control of quorum sensing network in Escherichia coli

Quantifying the optimal strategy of population control of quorum sensing network in Escherichia coli

Biosensing Vibrio cholerae with Genetically Engineered Escherichia coli

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

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