Team:Alberta/Project/Modeling

From 2009.igem.org

(Difference between revisions)
Line 1: Line 1:
-
{{:Team:Alberta/Template3}}
+
{{:Team:Alberta/TemplateSc}}
<html>
<html>
<head>
<head>
Line 26: Line 26:
     <div class="Outreach">
     <div class="Outreach">
     <div style="height: 400; background:#FFFFFF; colorou line-height:100% padding: 3px 0px;">
     <div style="height: 400; background:#FFFFFF; colorou line-height:100% padding: 3px 0px;">
-
     <h1>Why build a minimal genome?</h1>
+
     <h1>Modeling</h1>
<!-- <div align="justify" style="padding-left:20px; padding-right:20px"> -->
<!-- <div align="justify" style="padding-left:20px; padding-right:20px"> -->
Line 32: Line 32:
<font size="2">
<font size="2">
-
<P>Genomes are complex! Determining how simplified a genome can become enriches our understanding of the function and interactions of cellular components. Simplified cells can be used as a well characterized chasses for synthetic biology. Moreover, a simplified cell can be used to study cellular processes in a controlled, characterized genetic background. Finally, developing a minimal genome requires us to develop and optimize molecular methods of genome assembly. These methods can be then applied to other high through put biology. </P>
+
<P>Metabolic modeling allows for computational analysis of entire genomes which would be impossible to accomplish any other way. The various sources and methods used to collect data has allowed for an unique gene list which has the best possible chance of producing a minimal genome. This has been produced through a series of multiple gene deletions and media change in silico experiments. The MatLab protocols demonstrated in the modeling section can be used to identify any organism’s essential genes provided a model is available.</P>
</font></div>
</font></div>
Line 46: Line 46:
     <div class="Why We Need Bioinformatics">
     <div class="Why We Need Bioinformatics">
     <div style="height: 400; background:#FFFFFF; colorou line-height:100% padding: 3px 0px;">
     <div style="height: 400; background:#FFFFFF; colorou line-height:100% padding: 3px 0px;">
-
     <h1>Why We Need Bioinformatics</h1>
+
     <h1>Constraint Based Flux Analysis – Cobra Toolbox and SBML</h1>
<!-- <div align="justify" style="padding-left:20px; padding-right:20px"> -->
<!-- <div align="justify" style="padding-left:20px; padding-right:20px"> -->
Line 53: Line 53:
<font size="2">
<font size="2">
-
<b> The size and complexity of the genome make bioinformatics analysis essential. We used bioinformatics to accomplish the following: </b>
 
-
<P> - review lists of essential genes in the literature and existing databases and compile a preliminary essential gene list </P>
+
<P>Constraint Based Flux Analysis is a mathematical way of representing biological system information and allows for easy manipulation of this data. It is based on a stoichiometric matrix of reactions which correspond to individual enzymatic or transport reactions which have been characterized inside of the organism. In other words, it computationally represents each reaction using a linear array of numbers (see Figure 1).  
-
<P> - model the metabolic reactions and net growth rate of E.coli with given gene sets. This identified additional metabolic genes essential to a minimal genome. </P>
+
-
<P> - identify knock out combinations that could be tested in the wet lab, to verify the accuracy of our metabolic model. </P>
+
-
<P> - select standardized promoters and terminators that would replace the natural promoters and terminators of essential genes. </P>
+
-
<P> - determine which promoter should be used with which gene, by analyzing expression level data. </P>
+
-
<P> - design primers to amplify all essential genes from genomic DNA. </P>
+
-
<b> These steps have all been completed, and are described on the following pages. </b>
+
The flux can be defined as the amount of substrate moving to product for each individual reaction.  The model assumes that the system is at steady state therefore, the overall flux is zero since each product becomes a substrate of another reaction. All substrates entering the system will have the same amount leaving the system.  The products leaving the system can be removed by changing the boundary condition of the compound (that is making it unavailable to the system) or by using it to produce growth of the organism.  A master growth equation determines which products are required for the cell to grow and this represented in units of DW/unit time.  Systems Biology Markup Language (SBML) and the Cobra Toolbox (both produced from System’s Biology Research Group) allows for flux analysis to be performed in the MatLab program.
-
<P>
 
</font></div>
</font></div>

Revision as of 18:54, 14 September 2009

University of Alberta - BioBytes










































































































Modeling

Metabolic modeling allows for computational analysis of entire genomes which would be impossible to accomplish any other way. The various sources and methods used to collect data has allowed for an unique gene list which has the best possible chance of producing a minimal genome. This has been produced through a series of multiple gene deletions and media change in silico experiments. The MatLab protocols demonstrated in the modeling section can be used to identify any organism’s essential genes provided a model is available.

Constraint Based Flux Analysis – Cobra Toolbox and SBML

Constraint Based Flux Analysis is a mathematical way of representing biological system information and allows for easy manipulation of this data. It is based on a stoichiometric matrix of reactions which correspond to individual enzymatic or transport reactions which have been characterized inside of the organism. In other words, it computationally represents each reaction using a linear array of numbers (see Figure 1). The flux can be defined as the amount of substrate moving to product for each individual reaction. The model assumes that the system is at steady state therefore, the overall flux is zero since each product becomes a substrate of another reaction. All substrates entering the system will have the same amount leaving the system. The products leaving the system can be removed by changing the boundary condition of the compound (that is making it unavailable to the system) or by using it to produce growth of the organism. A master growth equation determines which products are required for the cell to grow and this represented in units of DW/unit time. Systems Biology Markup Language (SBML) and the Cobra Toolbox (both produced from System’s Biology Research Group) allows for flux analysis to be performed in the MatLab program.

Constraint Based Flux Analysis – Cobra Toolbox and SBML