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Team:Edinburgh/Modelling/Bacterial
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| - | <p>The red light production pathway consists of a red luciferase production gene coupled to lacI promoter ( | + | <p>The red light production pathway consists of a red luciferase production gene coupled to the <i>lacI</i> promoter (<a href="http://partsregistry.org/Part:BBa_R0010">BBa_R0010</a>); the presence of LacI in the system inhibits the production of red luciferase. The assumption is then made that red luciferase translates directly into red light - essentially, that substrates such as luciferin are constitutively expressed, and there's no need to include it within the model.</p> |
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| - | < | + | <p>The red light sensor pathway is a signal transduction pathway involving Cph8 (which can have either 'on' or 'off' state and can bind to OmpR) and OmpR (which can be either phosphorylated or unphosphorylated and can bind to either Cph8 or one of the <a href="http://partsregistry.org/Part:BBa_R0082"><i>ompC</i></a> and <a href="http://partsregistry.org/Part:BBa_R0084"><i>ompF</i></a> promoters). The assumption is made that there is a relatively static amount of Cph8 and OmpR within the system, and that there is no need to model their creation via transcription and translation or their degradation. Assumptions are also made regarding the balance between the concentration of on / off Cph8 and phosphorylated / unphosphorylated OmpR when the system is stable, as well as the fact that OmpR can only change phosphorylation state when not bound to any of Cph8, <i>ompC</i>, or <i>ompF</i>.<p> |
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| - | When red light is not present in the system, | + | <p>When red light is not present in the system, an equilibrium exists between 'on' and 'off' Cph8 and phosphorylated and unphosphorylated OmpR. When the red light sensing pathway is activated by , Cph8 is almost all turned 'off', which leads to OmpR almost fully unphosphorylated. |
OmpC promoter is activated by 'phosphorylated' OmpR, and stimulates the production of TetR. OmpF promoter is activated by small amounts of 'phosphorylated' OmpR, but inhibited by large amounts; when active, it stimulates production of LacI. TetR is also inhibited by presence of LacI in the system, as per standard repressilator. Assumptions regarding mechanism of action of OmpF and OmpC promoters (cumulative, individual) | OmpC promoter is activated by 'phosphorylated' OmpR, and stimulates the production of TetR. OmpF promoter is activated by small amounts of 'phosphorylated' OmpR, but inhibited by large amounts; when active, it stimulates production of LacI. TetR is also inhibited by presence of LacI in the system, as per standard repressilator. Assumptions regarding mechanism of action of OmpF and OmpC promoters (cumulative, individual) | ||
Thus, in standard conditions, large amounts of TetR are produced, while production of LacI is inhibited, due to presence of 'phosphorylated' OmpR. When red light activates the signal transduction pathway, concentration of unphosphorylated OmpR increases, which allows greater amounts of LacI to be produced to inhibit the production of TetR. | Thus, in standard conditions, large amounts of TetR are produced, while production of LacI is inhibited, due to presence of 'phosphorylated' OmpR. When red light activates the signal transduction pathway, concentration of unphosphorylated OmpR increases, which allows greater amounts of LacI to be produced to inhibit the production of TetR. | ||
Revision as of 13:13, 10 September 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. Time units are arbitrary.
For details of Ty Thomson's repressilator model, readers are directed to the aforementioned RuleBase link as well as the actual Kappa model.
