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Saeidi2012 - Quorum sensing device that produces GFP

ABSTRACT: Saeidi2012 - Quorum sensing device that produces GFP Saeidi et al. (2012) has modelled a quorum sensing device that produces green fluorescent protein (GFP) as reporter in the presence of Acyl Homoserine Lactone (AHL). This model is described in the article: Characterization of a quorum sensing device for synthetic biology design: Experimental and modeling validation Nazanin Saeidi, Mohamed Arshath, Matthew Wook Chang, Chueh Loo Poh Chemical Engineering Science. December 2012. Abstract: Modeling of biological parts is of crucial importance as it enables the in silico study of synthetic biological systems prior to the actual construction of genetic circuits, which can be time consuming and costly. Because standard biological parts are utilized to build the synthetic systems, it is important that each of these standard parts is well characterized and has a corresponding mathematical model that could simulate the characteristics of the part. These models could be used in computer aided design (CAD) tools during the design stage to facilitate the building of the model of biological systems. This paper describes the development of a mathematical model that is able to simulate both the dynamic and static performance of a biological device created using standard parts. We modeled an example quorum sensing device that produces green fluorescent protein (GFP) as reporter in the presence of Acyl Homoserine Lactone (AHL). The parameters of the model were estimated using experimental results. The simulation results show that the model was able to simulate behavior similar to experimental results. Since it is important that these models and the content in the models can be searchable and readable by machines, standard SBML (system biology markup language) format was used to store the models. All parts and reactions are fully annotated to enable easy searching, and the models follow the Minimum Information Requested In the Annotation of Models (MIRIAM) compliance as well as the Minimum Information About a Simulation Experiment (MIASE). Figure 4a of the reference publication has been reproduced as curation figure. The plot shows the performance of the model at different concentrations of the inducer (3OC12HSL=5E-10, 5E-07, 5E-07). This model is hosted on BioModels Database and identified by: MODEL1301110000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Nazanin Saeidi

PROVIDER: BIOMD0000000438 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000438?filename=BIOMD0000000438-biopax2.owl	Owl
	BIOMD0000000438?filename=BIOMD0000000438-biopax3.owl	Owl
	BIOMD0000000438?filename=BIOMD0000000438-matlab.m	Other
	BIOMD0000000438?filename=BIOMD0000000438-octave.m	Other
	BIOMD0000000438?filename=BIOMD0000000438.m	Other

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Project description:Boada2016 - Incoherent type 1 feed-forward loop (I1-FFL) A synthetic-biology mathematical modelling framework that was constructed to provide guidelines for experimental implementation and parameter optimisation resulted in a biological device demonstrating desired behaviour. This model is described in the article: Multi-objective optimization framework to obtain model-based guidelines for tuning biological synthetic devices: an adaptive network case. Boada Y, Reynoso-Meza G, Picó J, Vignoni A. BMC Syst Biol 2016 Mar; 10: 27 Abstract: Model based design plays a fundamental role in synthetic biology. Exploiting modularity, i.e. using biological parts and interconnecting them to build new and more complex biological circuits is one of the key issues. In this context, mathematical models have been used to generate predictions of the behavior of the designed device. Designers not only want the ability to predict the circuit behavior once all its components have been determined, but also to help on the design and selection of its biological parts, i.e. to provide guidelines for the experimental implementation. This is tantamount to obtaining proper values of the model parameters, for the circuit behavior results from the interplay between model structure and parameters tuning. However, determining crisp values for parameters of the involved parts is not a realistic approach. Uncertainty is ubiquitous to biology, and the characterization of biological parts is not exempt from it. Moreover, the desired dynamical behavior for the designed circuit usually results from a trade-off among several goals to be optimized.We propose the use of a multi-objective optimization tuning framework to get a model-based set of guidelines for the selection of the kinetic parameters required to build a biological device with desired behavior. The design criteria are encoded in the formulation of the objectives and optimization problem itself. As a result, on the one hand the designer obtains qualitative regions/intervals of values of the circuit parameters giving rise to the predefined circuit behavior; on the other hand, he obtains useful information for its guidance in the implementation process. These parameters are chosen so that they can effectively be tuned at the wet-lab, i.e. they are effective biological tuning knobs. To show the proposed approach, the methodology is applied to the design of a well known biological circuit: a genetic incoherent feed-forward circuit showing adaptive behavior.The proposed multi-objective optimization design framework is able to provide effective guidelines to tune biological parameters so as to achieve a desired circuit behavior. Moreover, it is easy to analyze the impact of the context on the synthetic device to be designed. That is, one can analyze how the presence of a downstream load influences the performance of the designed circuit, and take it into account. This model is hosted on BioModels Database and identified by: BIOMD0000000696. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Saeidi2012 - Quorum sensing device that produces GFP

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