Team:Toulouse/Modelling

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   <p style="margin:0 auto; color:#696969; width:960px; padding-top:20px; font-size:16px;"><a href="https://2014.igem.org/Team:Toulouse/Result/experimental-results">Results</a>&nbsp;&nbsp;&nbsp;>&nbsp;&nbsp;&nbsp;<a href="https://2014.igem.org/Team:Toulouse/Modelling">Modeling</a>&nbsp;&nbsp;&nbsp;>&nbsp;&nbsp;
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   <p style="margin:0 auto; color:#696969; width:960px; padding-top:20px; font-size:16px;">Results&nbsp;&nbsp;&nbsp;>&nbsp;&nbsp;&nbsp;Modeling
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<i>Bacillus subtilis</i> is a tree endophyte strain. A study showed that <i>Bacillus subtilis</i> could develop and fully colonize a tree, reaching a concentration of 10<sup>5</sup> cells per gram of fresh plant. We need to know in which conditions the growth of <i>B. subtilis</i> is optimum in a tree and if the weather can stop its development during winter. Therefore we decided to work on the growthof <i>Bacillus subtilis'</i> in function of the temperature during the year.  
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<i>Bacillus subtilis</i> is a tree endophyte strain. A study showed that <i>B. subtilis</i> could develop and fully colonize a tree, reaching a concentration of 10<sup>5</sup> cells per gram of fresh plant. We need to know in which conditions the growth of <i>B. subtilis</i> is optimum in a tree and if the weather can stop its development during winter. Therefore we decided to work on the growthof <i>B. subtilis'</i> in function of the temperature during the year.  
<br>Modeling bacterial growth in a tree section generates some difficulties. We need to know the distance between two tree extremities (treetops and root) or the speed sap flow. However the flow of speed sap can vary with temperature during the day. The composition of sap also varies due to seasons and type of container (phloem, xylem). Furthermore a tree is not an homogeneous system: its roots, trunk and branches do not contain the same amount of sap and wood. <br>The average speed of the plane tree sap is 2.4 m/h, which means that in a day the sap of a 30 m tree will flow from one extremity to the other. We thus reduced the tree to a bioreactor.
<br>Modeling bacterial growth in a tree section generates some difficulties. We need to know the distance between two tree extremities (treetops and root) or the speed sap flow. However the flow of speed sap can vary with temperature during the day. The composition of sap also varies due to seasons and type of container (phloem, xylem). Furthermore a tree is not an homogeneous system: its roots, trunk and branches do not contain the same amount of sap and wood. <br>The average speed of the plane tree sap is 2.4 m/h, which means that in a day the sap of a 30 m tree will flow from one extremity to the other. We thus reduced the tree to a bioreactor.
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According to the publication of <b>Xianling Ji</b> (See References), after six months of <i>Bacillus subtilis</i> growth in a tree, bacteria cells reach a concentration of 10<sup>5</sup> cells per gram of fresh plant. We assume that 10<sup>5</sup> cells/g is the maximum concentration.
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According to the publication of <b>Xianling Ji</b> (See References), after six months of <i>B. subtilis</i> growth in a tree, bacteria cells reach a concentration of 10<sup>5</sup> cells per gram of fresh plant. We assume that 10<sup>5</sup> cells/g is the maximum concentration.
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An assessment of the <i>Bacillus subtilis</i> growth in a similar sap was performed in laboratory conditions with optimum growth medium for <i>Bacillus subtilis</i>. The composition sap used was the one from birch sap.<br>
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An assessment of the <i>B. subtilis</i> growth in a similar sap was performed in laboratory conditions with optimum growth medium for <i>B. subtilis</i>. The composition sap used was the one from birch sap.<br>
In these conditions, the growth rate µ is optimal. From this value we can extrapolate a growth curve as a function of temperature. We used the <b>cardinal temperature model</b>: </p>
In these conditions, the growth rate µ is optimal. From this value we can extrapolate a growth curve as a function of temperature. We used the <b>cardinal temperature model</b>: </p>
   
   
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<center style="margin-top: -52px;"><img style="" src="https://static.igem.org/mediawiki/2014/b/b1/Plot_growth_rate.png" alt="Figure1"></center>
<center style="margin-top: -52px;"><img style="" src="https://static.igem.org/mediawiki/2014/b/b1/Plot_growth_rate.png" alt="Figure1"></center>
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<p class="legend">Figure 1: bacterial growth (µ) as a function of temperature</p>
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<p class="legend">Figure 1: Bacterial growth (µ) as a function of temperature</p>
<p class="texte"> A logistic model developed by <b>Hiroshi Fujikawa</b> (See References) is used to study bacterial growth.</p>
<p class="texte"> A logistic model developed by <b>Hiroshi Fujikawa</b> (See References) is used to study bacterial growth.</p>
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In practice, temperature variations are certainly lower in trees than outside, especially if roots extend very deep. Composition of the tree sap must also intervene in the growth rate and nutrient content of sap is also temperature dependent. The effects of the decrease of the temperature in winter also induces a fall of the sap and this must also be involved in the disappearance of our strain in the tree. The period of <i>Bacillus subtilis</i> growth is certainly affected by the change of temperature, the rise of sap in the trunk and sap composition variations. All these parameters can consequently slow-down or boost the growth rate.
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In practice, temperature variations are certainly lower in trees than outside, especially if roots extend very deep. Composition of the tree sap must also intervene in the growth rate and nutrient content of sap is also temperature dependent. The effects of the decrease of the temperature in winter also induces a fall of the sap and this must also be involved in the disappearance of our strain in the tree. The period of <i>B. subtilis</i> growth is certainly affected by the change of temperature, the rise of sap in the trunk and sap composition variations. All these parameters can consequently slow-down or boost the growth rate.
The modeling work is done with the programming language 'R' script attached (See Annexe).
The modeling work is done with the programming language 'R' script attached (See Annexe).
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Xianling Ji, Guobing Lu, Yingping Gai, Chengchao Zheng & Zhimei Mu (2008) <b>Biological control against bacterial wilt and colonization of mulberry by an endophytic Bacillus subtilis strain.</b> FEMS Microbiol Ecol 65: 565–573
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Xianling Ji, Guobing Lu, Yingping Gai, Chengchao Zheng,and Zhimei Mu. (2008) <b>Biological control against bacterial wilt and colonization of mulberry by an endophytic <i>Bacillus subtilis</i> strain.</b> FEMS Microbiol Ecol 65: 565–573.
</li></p>
</li></p>
<li class="tree"><p class="texte">
<li class="tree"><p class="texte">
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A. Garnier(1977) <b>Transfert de sève brute dans le tronc des arbres aspects méthodologiques et physiologiques.</b> Ann. Sci. Foresi. 34 (1): 17-45
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A. Garnier. (1977) <b>Transfert de sève brute dans le tronc des arbres aspects méthodologiques et physiologiques.</b> Ann. Sci. Foresi. 34 (1): 17-45.
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<li class="tree"><p class="texte">
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Heikki Kallio , Tuija Teerinen , Seija Ahtonen , Meri Suihko , Reino R. Linko (1989) <b>Composition and properties of birch syrup (Betula pubescens).</b> J. Agric. Food Chem 37 (1): 51–54
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Heikki Kallio, Tuija Teerinen, Seija Ahtonen, Meri Suihko, and Reino R. Linko. (1989) <b>Composition and properties of birch syrup (<i>Betula pubescens</i>).</b> J. Agric. Food Chem 37 (1): 51–54.
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</li></p>
<li class="tree"><p class="texte">
<li class="tree"><p class="texte">
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L. Rosso, J. R. Lobry & J. P. Flandrois (1992) AN <b>Unexpected Correlation between Cardinal Temperatures of Microbial Growth Highlighted by a New Model.</b> J. theor. Biol. 162 : 447-463
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L. Rosso, J. R. Lobry, and J. P. Flandrois. (1992) AN <b>Unexpected Correlation between Cardinal Temperatures of Microbial Growth Highlighted by a New Model.</b> J. theor. Biol. 162 : 447-463.
</li></p>
</li></p>
<li class="tree"><p class="texte">
<li class="tree"><p class="texte">
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Hiroshi Fujikawa (2010), <b>Development of a New Logistic Model for Microbial Growth in Foods.</b> Biocontrol of Science Vol 15: 75-80
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Hiroshi Fujikawa. (2010) <b>Development of a New Logistic Model for Microbial Growth in Foods.</b> Biocontrol of Science Vol 15: 75-80.
</li></p>
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Latest revision as of 03:17, 18 October 2014