Team:BCCS-Bristol/Modelling

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==Modelling Strategy==
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=Modelling Strategy=
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===Overall Aims===
 
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Our modelling strategy needs to tie in with our larger plan for this year’s project. We are working on a soil analysis system for use in agriculture, based on an E. coli chassis. Our bacteria will need to be able to:
 
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* Reliably detect nitrate levels in soil
 
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* Signal using GFP
 
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Additionally, our bacteria need to be:
 
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* Detectable
 
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* Contained
 
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We need to be able to detect the signal from our bacteria using equipment that can feasibly used on a farm. Containing our bacteria means they cannot interfere with the outside world in undesirable ways.
 
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===Modelling aims===
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Modelling has a key role in synthetic biology. Synthetic biologists use mathematical models to predict how new genetic networks will act, which is crucial when designing a BioBrick construct. It is also important to be able to predict how groups of bacteria will interact with one another and their environment. The primary function of our modelling team is to use computational simulations to assist and inform the work of our biologists.
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The primary function of our modelling team is to use computational simulations to assist and inform the work of our biologists.  
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Currently, we plan to achieve this by working on these areas:
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* GRN models
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** Simple GRN model (Nitrate Detector → GFP)
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** Composite GRN (Detect several nutrients → Respond with a combination of signals)
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* Behaviour of Capsules compared to direct application to soil (spray)
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** Nitrate Diffusion into capsules and cells
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*** '''Modify BSim to allow for irregular boundaries:''' ''Currently, BSim divides space into discrete cubic blocks. This makes defining curved or spherical boundaries difficult. We are working on an algorithm to approximate curved surfaces in a cubic environment.''
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** Analyse data from microscope experiments
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** Detectability of Capsules
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*** '''Quorum Sensing to amplify signal:''' ''The outermost bacteria in a capsule may be able to detect nitrates much more effectively than those buried deep within the capsule. If the outer bacteria signalled that they detect nitrates, the inner bacteria could detect this and express GFP. This would effectively amplify GFP expression in the capsule.''
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*** '''Multiple populations & sensitivity:''' ''By using populations of different sensitivities, we can use the total GFP expression as a more accurate measure of the concentration of nitrates in the soil.''
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*** '''Constant expression of RFP, detect ratio of GFP to RFP:''' ''If our bacteria express one colour constantly, and express another colour in response to nitrate detection, the ratio of the two colours can be used to quantify the level of nitrate detection.''
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==Current activity==
 
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We have been working on these areas in the last few weeks:
 
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* Implementing boundaries and chemical fields in BSim
 
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* Diffusion through capsules
 
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* Fitting parameters to GRN
 
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* Soil analysis
 
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* GUI
 
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* Collaborations
 
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==Summary==
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==[[Team:BCCS-Bristol/Modelling/BSIM|BSim Modelling Framework]]==
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The modelling team should have two main outputs. These are:
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* Modelling Capsules
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<html><center><a href="https://2010.igem.org/Team:BCCS-Bristol/Modelling/BSIM">
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* Developing BSim GUI and encouraging collaboration
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<img width="200" src="https://static.igem.org/mediawiki/2010/f/f2/Bsim2010logo.png" border="0">
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===Modelling Capsules===
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Containing our bacteria within a semi-permeable capsule is one of the more unique aspects of our project. We can use our models to inform the design of these capsules; the size of the capsule and thickness of its coating are dependent on our estimates of diffusion through them, and the detectability of the GFP within them.
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===BSim GUI===
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BSim is BCCS Bristol's award winning modelling package. It is an agent-based modelling framework written in Java. BSim's agents operate on the level of individual bacteria, vesicles and particles. The internal state of bacteria can be modelled with ODE's which are solved numerically by BSim. We hope that BSim can be used as a 'virtual microscope', a tool that all biologists can use to investigate almost any microbiological system, from the level of GRN's to multicelluar interaction to environmental interaction.
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BSim is currently an excellent modelling tool, but not widely used. By giving it a Graphical User Interface (GUI), we can make it more accessible to the wider synthetic biology community, who may lack JAVA knowledge. To help test and improve our GUI, we will make it available to several other IGEM teams. This will also constitute a modelling collaboration, which is a sufficient criterion for a gold medal.
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==[[Team:BCCS-Bristol/Modelling/GRN|Modelling the GRN]]==
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<html><center><a href="https://2010.igem.org/Team:BCCS-Bristol/Modelling/GRN">
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<img width="200" src="https://static.igem.org/mediawiki/2010/6/6d/Grnicon.png" border="0">
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</a></center></html>
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Being able to predict how a novel gene regulatory network (GRN) will behave is crucial. Before one commits the time and resources to actually constructing such a network out of BioBricks (or other pieces of genetic material) it is important to know if it is stable, if the time-scales that it operates on are relevant and if it will produce the responses that one is looking for. Many approaches exist to model GRNs, the most popular being coupled ordinary differential equations (ODEs), stochastic networks and graphical models. For the levels of expression considered in this project the coupled ODE approach is the most valid, since it assumes that quantities of repressors, promoters, proteins etc. are high enough to be represented as being well mixed and continuous.
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==[https://2010.igem.org/Team:UCL_London/Genetic_Circuit Collaboration]==
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<html><center><a href="https://2010.igem.org/Team:UCL_London/Genetic_Circuit">
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<img width="200" src="https://static.igem.org/mediawiki/2010/f/fa/BCCS_Collaboration_Icon.png">
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</a></center></html>
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Our team helped to model the UCL team's system this year. Using BSim, we created simulations and visualisations to show that UCL's new 'Feedback Loop' system works faster than the existing IPTG based system. Check out the UCL website for more details.
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During the course of our collaboration, feedback from working on the UCL system helped to inform our Graphical User Interface (GUI) design.

Latest revision as of 20:47, 27 October 2010

Modelling Strategy

Contents


Modelling has a key role in synthetic biology. Synthetic biologists use mathematical models to predict how new genetic networks will act, which is crucial when designing a BioBrick construct. It is also important to be able to predict how groups of bacteria will interact with one another and their environment. The primary function of our modelling team is to use computational simulations to assist and inform the work of our biologists.


BSim Modelling Framework

BSim is BCCS Bristol's award winning modelling package. It is an agent-based modelling framework written in Java. BSim's agents operate on the level of individual bacteria, vesicles and particles. The internal state of bacteria can be modelled with ODE's which are solved numerically by BSim. We hope that BSim can be used as a 'virtual microscope', a tool that all biologists can use to investigate almost any microbiological system, from the level of GRN's to multicelluar interaction to environmental interaction.


Modelling the GRN

Being able to predict how a novel gene regulatory network (GRN) will behave is crucial. Before one commits the time and resources to actually constructing such a network out of BioBricks (or other pieces of genetic material) it is important to know if it is stable, if the time-scales that it operates on are relevant and if it will produce the responses that one is looking for. Many approaches exist to model GRNs, the most popular being coupled ordinary differential equations (ODEs), stochastic networks and graphical models. For the levels of expression considered in this project the coupled ODE approach is the most valid, since it assumes that quantities of repressors, promoters, proteins etc. are high enough to be represented as being well mixed and continuous.

Collaboration

Our team helped to model the UCL team's system this year. Using BSim, we created simulations and visualisations to show that UCL's new 'Feedback Loop' system works faster than the existing IPTG based system. Check out the UCL website for more details.

During the course of our collaboration, feedback from working on the UCL system helped to inform our Graphical User Interface (GUI) design.

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