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Team:Sheffield/Modeling
From 2010.igem.org
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The first step in creating the model was to analyse the processes in the system mainly using research literature and the knowledge from the biologists to create the chemical equations for these processes. Next these chemical equations were used to write differential equations for the system, creating a dynamic model. The model was then implemented in matlab to show the changes in the output according to the input and the different parameters in the system. | The first step in creating the model was to analyse the processes in the system mainly using research literature and the knowledge from the biologists to create the chemical equations for these processes. Next these chemical equations were used to write differential equations for the system, creating a dynamic model. The model was then implemented in matlab to show the changes in the output according to the input and the different parameters in the system. | ||
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We would just like to thank Professor Visakan Kadirkamanathan, Dr. Steve Wilkinson, Dr. Paul Dobson and Krishnanathan Kirubakharan for all their help with the modelling work. | We would just like to thank Professor Visakan Kadirkamanathan, Dr. Steve Wilkinson, Dr. Paul Dobson and Krishnanathan Kirubakharan for all their help with the modelling work. | ||
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<td><p><a href="https://2010.igem.org/Team:Sheffield/Modeling" target="_self">Modelling home</a> | | <td><p><a href="https://2010.igem.org/Team:Sheffield/Modeling" target="_self">Modelling home</a> | | ||
Revision as of 15:40, 27 October 2010
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Modelling home | Chimeric protein system | Cholera protein system | Graphical user interface |
In the modelling section of our project we will be implementing mathematical models and computer simulations for the cholera detection biosensor. We have implemented models for the two different systems in our project
1. Chimeric protein system – the quorum sensing receptor from vibrio cholera is fused with histadine kinase BarA in E-coli 2. cholera protein system – the proteins that compile the signal sensing pathway in vibrio cholera is inserted in to E. coli The models can be used to predict how the results would change according to changes in parameters and also how the system could be improved.
How the model was created The first step in creating the model was to analyse the processes in the system mainly using research literature and the knowledge from the biologists to create the chemical equations for these processes. Next these chemical equations were used to write differential equations for the system, creating a dynamic model. The model was then implemented in matlab to show the changes in the output according to the input and the different parameters in the system. To allow easy access to the model and to analyse the output easily for different parameters of the system we have created a graphical user interface (GUI) in matlab. More information on the GUI can be found at the page: Graphical user interface Main principles in the model Both the models are based on the main principles in signal transduction of quorum sensing networks in bacteria and the gene expression. Quorum sensing Quorum sensing is a mechanism by which bacteria controls their population density, through detection of certain signals emitted from the same species. These signals are in the form of chemicals produced by the bacteria and in vibrio cholerae the quorum sensing signalling molecules are called autoinducers, CAI – 1 and AI-2 . When there is a low cell population density there will be less autoinducers leading towards the production of more cells and at high cell population density there will be more autoinducers and thus inhibiting the production of more cells. The signalling molecules CAI-1 and AI-2 are detected by their cognate receptors CqsS and LuxP/Q respectively. For our biosensor we will be using the CAI-1 and CqsS autoinducer/receptor pair. On detection of the autoinducer a signalling pathway consisting of phosphorelays will be activated which ends in a response regulator protein which acts as a transcription factor. This leads to expression of certain genes. Gene expression In response to the E. coli detecting CAI-1 which causes it to initiate the phosphorylation cascade to produce certain transcription factors, the E. Coli system tend to use these transcription factors to bind to a reporter DNA to enable it to produce certain proteins upon which the survival of its cells may depend on; thus there is an expression of particular genes which are translated to proteins that enables the E. Coli to perform some specific functions. These specific proteins produced are controlled by the transcription factors which either increases or decreases RNA polymerase binding to the DNA near gene which therefore affects the level of the mRNA transcript produced and hence the production level of these specific proteins. However, some factors that influence gene expression in E. Coli are; 1. Over – expressing rare tRNAs made for rare codons which can significantly improve gene expression. 2. The type of promoter used, as tight promoters keep expression levels down under non-inducing conditions. 3. The RNA stability 4. The binding interactions of the transcription factors to the DNA The above factors mentioned are the basic principles upon which genes are expressed in eukaryotes and therefore to construct our mathematical model for the gene expression for our two different systems; thus the chimeric protein system and the cholera protein system in E. coli, these factors were taken into consideration. Taking these principles into account we have divided our models in to two sections; signal transduction and gene expression. Next the two sections were combined to simulate the production of the reporter gene in response to the presence of autoinducer. The models for the systems can be accessed from the links below.
Acknowledgements We would just like to thank Professor Visakan Kadirkamanathan, Dr. Steve Wilkinson, Dr. Paul Dobson and Krishnanathan Kirubakharan for all their help with the modelling work. |
Modelling home | Chimeric protein system | Cholera protein system | Graphical user interface |
