Team:St Andrews/project/modelling/models/ODEs

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==Dissociation==
==Dissociation==
The opposite to association is dissociation, which is the breaking apart of substances which are in complex together. Again it can be either positive (i.e. if in the differential for the substances forming the complex) or negative (if in the differential for the complex itself).
The opposite to association is dissociation, which is the breaking apart of substances which are in complex together. Again it can be either positive (i.e. if in the differential for the substances forming the complex) or negative (if in the differential for the complex itself).
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[[Image:DissociationSA.jpg]]
==Translation==
==Translation==

Revision as of 12:57, 23 October 2010


St Andrews from East Sands

University of St Andrews iGEM 2010

Welcome!

The Saints

University of St Andrews iGEM 2010

Our first year at iGEM!

Ordinary Differential Equations (ODEs)

Contents

What is an ODE?

An ordinary differential equation (ODE) is a relation that contains functions of only one independent variable and one or more of their derivatives with respect to that variable. This is in contrast to a partial differential equation which can be defined, a relation involving an unknown function or functions of several independent variables and their partial derivatives with respect to those variables. Of course, in our work we are interested in how all the different components of our quorum sensing system change with time and so will use ODEs where the differentials are with respect to time (dt). Since we have a number of chemicals present at any one time in the system we require a differential equation to describe how each will change in time, thus we develop a system of interlocking ODEs which are all interconnected by shared variables.

Typical ODE elements

Since each chemical participates in different reactions and biological process, there will be great variation in the ODEs describing them. However there are several types of reaction which are common to most of the chemicals and these are discussed below

Natural degradation

Over time, the chemicals within a cell will degrade, whether this be due to use in other processes, being broken down by other chemicals, or simply breaking apart due to their natural instability. This results in a decrease in concentration over time and so is represented by a negative factor in our equations. The rate of degradation is proportional to the concentration of substance present and so in general the term is of the form:

Association

Two or more substances may come together and bind to create a new substance entirely. This process is know as association. The rate at which something associates will clearly be dependent not only upon the concentration of itself but of the other substances which it is associating with. Since a new substance is actually formed, association will be a positive contribution in some equations and negative in others. Typically it will be represented by the relationship:

Dissociation

The opposite to association is dissociation, which is the breaking apart of substances which are in complex together. Again it can be either positive (i.e. if in the differential for the substances forming the complex) or negative (if in the differential for the complex itself).


DissociationSA.jpg

Translation

In a cell proteins are made from sequences of amino acids which are coded for by strands of mRNA which is transcribed from DNA. The process of a protein being produced from the mRNA is translation and has been included in our model by the relationship below.


TranslationSA.jpg

Transcription

The process by which mRNA is produced from DNA is known as transcription. It will more often than not occur at a so-called constitutive rate, caused by the normal processes within the cell, but also can be promoted by the action of a promoter. This causes the mRNA to be produced in greater concentrations than normal, often caused by the binding of a certain substance or complex to an operon which then transcribes a set of mRNAs. The behaviour of these promoters is well-studied, and there is an accepted way in which they are represented mathematically which we have used in our model.


Transcription.jpg


Diffusion

This is the mechanism by which a molecules move around a cell and its surrounding environment, from a high concentration to a low one along a 'concentration gradient'.


The equations

In order to capture the behaviour behaviour mathematically, we developed a system of 8 differential equations which together encapsulate the main behaviour of the LuxR circuit. Each equation represents the change in concentration of either a molecule or piece of mRNA with time, and all are first order.

1. HSLLuxR2.jpg

Eqn. 1: The HSL-LuxR complex is broken apart when either HSL or LuxR degrades, or it may naturally dissociate at a rate kDissHSLLuxR. It is prodcued by the association of HSL and LuxR at a rate kAssHSLLuxR.


2. LuxImRNA2.jpg


3. LuxRmRNA2.jpg

Eqn. 3: The production of LuxRmRNA is promoted by the HSL-LuxR complex. We model this behaviour using a Hill function controlled by the parameters kMaxProductionRNA and kHalfMaxProductionRNA.


4. GFPmRNA2.jpg


5. LuxI2.jpg

Eqn. 5 : LuxI is translated from the mRNA at a reate kTranslation and degrades at a rate kDegRNA


6. LuxR2.jpg

Eqn. 6: LuxR is translated from its mRNA at a constant rate, kTranslation. It can also increase due to the dissociation of the HSL-LuxR complex or the degradation of the HSL or LuxR within the complex, which will result in those molecules which didn't degrade being included in the concentration present in the cell.


7. GFP2.jpg

Eqn. 7: The GFP concentration is our primary indicator of activation of the quorum circuit. Similarly to LuxI it is produced from its respective mRNA at the rate kTranslation and degrades at a rate kDegGFP.


The above equations form the backbone of our model and are the framework on which all of our further work is based. Our next issue was then to develop a method of simulating a change from low to high cell density in order to see if our model displayed the bistability that was theoreticaly predicted.