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Team:Edinburgh/Modelling/Bacterial
From 2010.igem.org
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| - | Use of arbitrary rates for creation of red light, etc., how to balance them off against one another such that the desired interactions occur at the desired frequency. Fine-tuning of response was an integral part of the model-building process. | + | Use of arbitrary rates for creation of red light, etc., how to balance them off against one another such that the desired interactions occur at the desired frequency. Fine-tuning of response was an integral part of the model-building process. Especially difficult since this is a two-stage pathway (as modelled) and hence the response to the stimulus is more complex, and there are two different actions with hopefully the same effect at work here. Analysis of which one is more powerful, whether or not both of them are required, etc. |
Assumptions and justifications thereof. Not enough is fully understood and clearly documented of the action of these systems, and individual interpretations cloud the issue even further. | Assumptions and justifications thereof. Not enough is fully understood and clearly documented of the action of these systems, and individual interpretations cloud the issue even further. | ||
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<p><b>Figure 5:</b> The same pathway without introducing a burst of blue light into the system.</p><br><br></center> --> | <p><b>Figure 5:</b> The same pathway without introducing a burst of blue light into the system.</p><br><br></center> --> | ||
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| + | The graph in Figure 4 shows the results of simulating the blue light sensing pathway, after inducing a short period of red light expression at t=100. This blue light then represses the production of lambda-CI within the system for a short period of time (in comparison to the control simulation in Figure 5), before the effect wears off and transcription / translation are allowed to occur once more. | ||
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| + | Similar problems to the above, except the pathway as a whole has a simpler response (single-step, only one effect). | ||
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Revision as of 15:06, 31 August 2010
Overview: Modelling bacterial BRIDGEs
The second Kappa model created for the project attempted to realise the original vision we held for the system: a composite device based on the tried and tested Elowitz repressilator, combined with three different light-producing and light-sensing pathways. The primary objective of the modelling would then be to confirm that the three systems interacted with one another in roughly the manner we expect, without undue interference or trouble. We would also try to use the model to analyse the structure of the system and possibly to compare different proposed subsystems against one another, to analyse which one would work better.
The following sections describe, in turn: the repressilator model that forms the core of the system, the red light production and signal transduction pathways, the blue light production and signal transduction pathways, the green light production and signal transduction pathways, the results obtained by running the simulation, and finally the analysis of the results obtained.
The Repressilator
The core of the model is formed by the Elowitz repressilator designed by Ty Thomson in 2009 (available to view here). This was one of the first to incorporate the concept of standardised biological parts (i.e. BioBricks) into a modelling context, attempting to "introduce a modular framework for modelling BioBrick parts and systems using rule-based modelling". The idea was to model at the level of individual parts, such that systems could be constructed using different components by paying a cost upfront with the construction of models of the parts, and thus making modular construction of specific models practically effort free - similar, in fact, to the idea of characterised and composable BioBricks used in the design and construction of synthetic circuits.
The framework as described by Thomson establishes a concise set of Kappa rules necessary to incorporate new BioBricks into such a model, by dividing them into four wide-ranging categories - promoter sequences, coding sequences, ribosome binding sites, and terminators. For example, a promoter sequence must define how repressor proteins and RNA polymerases bind with it, how transcription is initiated, and what happens when readthrough occurs and the promoter sequence is transcribed. A coding sequence must define its transcription, translation initiation and actual translation, and degradation of the translated protein (the action of the protein itself is not necessary, with the exception of its repressor activity which would be described in the corresponding promoter sequence). Finally, a ribosome binding site must define how a ribosome may bind with the site and how the RBS is transcribed, and a terminator must define how termination occurs, and what happens if termination fails (i.e. terminator readthrough).
The framework also describes what rates are necessary for the complete characterisation of the model. These roughly correspond to the rules given above, and include: promoter binding affinities and rate of RNAP recruitment; rate of transcription and rate of recruitment for ribosome binding sites; rates of transcription, translation, and degradation for protein coding sequences; and terminator percentage of successful termination. Although very few, if any, of the BioBricks in the Registry are characterised to this extent of modelling utility, such a framework at least provides something that we can be aiming for.
Thomson's model of the Elowitz repressilator was created as a working example of this framework, and is capable of fully simulating the interactions that occur within the system. The rules within fully satisfy the above framework for the repressilating reactions involving lacI, lambda-cI, and tetR and their associated BioBricks: BBa_B0034, BBa_R0051, BBa_R0040, BBa_R0010, BBa_C0051, BBa_C0040, BBa_C0012, and BBa_B0011.
Figure 1: Results of simulating Ty Thomson's repressilator model.
For details of Ty Thomson's repressilator model, readers are directed to the aforementioned RuleBase link as well as the actual Kappa model.
