Team:ULB-Brussels/Modeling

From 2012.igem.org

(Difference between revisions)
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interest, it has become crucial to understand and, above all, optimize these pathways. However,
interest, it has become crucial to understand and, above all, optimize these pathways. However,
biological systems are so complex that it is sometimes impossible to have a complete understanding
biological systems are so complex that it is sometimes impossible to have a complete understanding
-
of the reactions and mechanisms of the di�erent pathways. The idea of our project is to solve this
+
of the reactions and mechanisms of the different pathways. The idea of our project is to solve this
optimization problem by using the integron platform { which represents a natural genetic optimiza-
optimization problem by using the integron platform { which represents a natural genetic optimiza-
-
tion tool in bacteria { and putting in competition di�erent populations with di�erent gene orders,
+
tion tool in bacteria { and putting in competition different populations with different gene orders,
so that the population(s) with the optimal order(s) will be naturally selected with time.
so that the population(s) with the optimal order(s) will be naturally selected with time.
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;As a proof of concept, we will try to optimize the order of the genes governing the production of
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;As a proof of concept, we will try to optimize the order of the genes governing the production of
-
two natural antibiotics: Microcin C7 and Microcin B17. The �rst one inhibits a tRNA synthetase
+
two natural antibiotics: Microcin C7 and Microcin B17. The first one inhibits a tRNA synthetase
(thus inhibits protein synthesis and, as a consequence, cell division), and the second inhibits a gyrase
(thus inhibits protein synthesis and, as a consequence, cell division), and the second inhibits a gyrase
(thus provokes inhibition of DNA replication and eventually cell death). We might then expect that
(thus provokes inhibition of DNA replication and eventually cell death). We might then expect that
-
natural selection occurs, so that the optimal gene order(s) �nally emerge.
+
natural selection occurs, so that the optimal gene order(s) finally emerge.
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;In the sequel, we model this competition experiment, and try to see in what sense and in what
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;In the sequel, we model this competition experiment, and try to see in what sense and in what
conditions natural selection could happen.
conditions natural selection could happen.
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<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;In the following, we write Microcins <em>B</em> and <em>C</em> for Microcins <em>B17</em> and <em>C7</em>, respectively. Further,
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;In the following, we write Microcins <em>B</em> and <em>C</em> for Microcins <em>B17</em> and <em>C7</em>, respectively. Further,
the bacterial populations producing these antibiotics will be denoted by <em>Bi</em> and <em>Cj</em> , respectively,
the bacterial populations producing these antibiotics will be denoted by <em>Bi</em> and <em>Cj</em> , respectively,
-
where the indices i and j run through all di�erent gene cassette orders.
+
where the indices i and j run through all different gene cassette orders.
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;We consider the experiment where all these populations are put in competition together. In our
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;We consider the experiment where all these populations are put in competition together. In our
model, for the sake of simplicity, we will simply consider that Microcin <em>B</em> causes the production of
model, for the sake of simplicity, we will simply consider that Microcin <em>B</em> causes the production of
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<br></br>
<br></br>
<h3><A NAME="2.1. Notations and mathematical model"> 2.1. Notations and mathematical model</A></h3>
<h3><A NAME="2.1. Notations and mathematical model"> 2.1. Notations and mathematical model</A></h3>
-
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The study of the di�erent populations will be accomplished through the time evolution of the following dynamical quantities. Notice that subscribed letters will designate the given population, while
+
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The study of the different populations will be accomplished through the time evolution of the following dynamical quantities. Notice that subscribed letters will designate the given population, while
superscripted letters will stand for the corresponding antibiotics.
superscripted letters will stand for the corresponding antibiotics.
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-
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Using these constants and dynamical variables, we can describe the biological competition experiment by the following di�erential equation system (where <em>X = B;C</em> and i runs through all the
+
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Using these constants and dynamical variables, we can describe the biological competition experiment by the following differential equation system (where <em>X = B;C</em> and i runs through all the
-
di�erent possible gene orders for the antibiotics production gene cassettes):
+
different possible gene orders for the antibiotics production gene cassettes):
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img id="logo" src="https://static.igem.org/mediawiki/2012/5/55/Model_2.PNG" height="65%" width="65%">
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img id="logo" src="https://static.igem.org/mediawiki/2012/5/55/Model_2.PNG" height="65%" width="65%">
-
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;This general model can be simpli�ed if we suppose that populations <em>Xi</em> are completely immune to Microcin <em>X</em>, which is a totally reasonable assumption. Further, since bacteria and Microcins have
+
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;This general model can be simplified if we suppose that populations <em>Xi</em> are completely immune to Microcin <em>X</em>, which is a totally reasonable assumption. Further, since bacteria and Microcins have
half-lives that are much larger than the experiment time, we may neglect the corresponding terms.
half-lives that are much larger than the experiment time, we may neglect the corresponding terms.
-
If we also neglect the saturation e�ect in the population growth (which is natural if the experiment
+
If we also neglect the saturation effect in the population growth (which is natural if the experiment
is carried out in exponential phase), we then get the following simpler system:
is carried out in exponential phase), we then get the following simpler system:
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img id="logo" src="https://static.igem.org/mediawiki/2012/6/6f/Model_3.PNG" height="65%" width="65%">
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img id="logo" src="https://static.igem.org/mediawiki/2012/6/6f/Model_3.PNG" height="65%" width="65%">
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<h3><A NAME="2.2. Natural selection?"> 2.2. Natural selection?</A></h3>
<h3><A NAME="2.2. Natural selection?"> 2.2. Natural selection?</A></h3>
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<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;We could hope that putting together bacteria with all the di�erent gene orders leads to a natural
+
<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;We could hope that putting together bacteria with all the different gene orders leads to a natural
-
selection regime, meaning that the subpopulations with the best o�ensive and/or defensive charac-
+
selection regime, meaning that the subpopulations with the best offensive and/or defensive charac-
teristics  
teristics  
<br></br>
<br></br>

Revision as of 17:29, 26 September 2012

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Sommaire

1. Introduction

     Since complex biological pathways are used in an industrial way in order to produce molecules of interest, it has become crucial to understand and, above all, optimize these pathways. However, biological systems are so complex that it is sometimes impossible to have a complete understanding of the reactions and mechanisms of the different pathways. The idea of our project is to solve this optimization problem by using the integron platform { which represents a natural genetic optimiza- tion tool in bacteria { and putting in competition different populations with different gene orders, so that the population(s) with the optimal order(s) will be naturally selected with time.

     As a proof of concept, we will try to optimize the order of the genes governing the production of two natural antibiotics: Microcin C7 and Microcin B17. The first one inhibits a tRNA synthetase (thus inhibits protein synthesis and, as a consequence, cell division), and the second inhibits a gyrase (thus provokes inhibition of DNA replication and eventually cell death). We might then expect that natural selection occurs, so that the optimal gene order(s) finally emerge.

     In the sequel, we model this competition experiment, and try to see in what sense and in what conditions natural selection could happen.

2. Modeling the competition experiment

     In the following, we write Microcins B and C for Microcins B17 and C7, respectively. Further, the bacterial populations producing these antibiotics will be denoted by Bi and Cj , respectively, where the indices i and j run through all different gene cassette orders.

     We consider the experiment where all these populations are put in competition together. In our model, for the sake of simplicity, we will simply consider that Microcin B causes the production of some protein complexes that provoke cell death (bactericidal), while Microcin C inhibits cell division of the protein complexes that allow the cellular division process. (bacteriostatic). Thus note that the quantities AXi and DXi have no biological meaning, but are used phenomenologically to better describe the situation.

2.1. Notations and mathematical model

     The study of the different populations will be accomplished through the time evolution of the following dynamical quantities. Notice that subscribed letters will designate the given population, while superscripted letters will stand for the corresponding antibiotics.           

     Using these constants and dynamical variables, we can describe the biological competition experiment by the following differential equation system (where X = B;C and i runs through all the different possible gene orders for the antibiotics production gene cassettes):           

     This general model can be simplified if we suppose that populations Xi are completely immune to Microcin X, which is a totally reasonable assumption. Further, since bacteria and Microcins have half-lives that are much larger than the experiment time, we may neglect the corresponding terms. If we also neglect the saturation effect in the population growth (which is natural if the experiment is carried out in exponential phase), we then get the following simpler system:           

2.2. Natural selection?

     We could hope that putting together bacteria with all the different gene orders leads to a natural selection regime, meaning that the subpopulations with the best offensive and/or defensive charac- teristics

4. Appendix



4.1. Determining analytically the asymptotical behaviour of the solutions of (1)



4.2. Parameter estimation