Team:Uppsala/Modeling CellCellInteraction

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document.getElementById("tab1").innerHTML = '<h2>Introduction</h2><p>To facilitate the understanding of our multi-part system, a simulation for cell-cell interaction was developed in Java. Realistic data on movement and reproduction were used, so that our new introduced functions could be evaluated. This resulted in a two dimensional program where bacteria can interact with each other in real time, as if looked at in a microscope. In our scenario we consider the probiotic moving around on the small intestinal wall and reaching the outer surface of a Yersinia enterocolitica colony. By sensing its environment the bacteria can invoke changes in the movement pattern or kill other species in their vicinity. This provides us with a tool to predict how effective our introduced systems will be and add insight to how the systems can be improved. The program can easily be changed and applied to similar systems, hopefully making it useful for understanding and evaluating future projects.</p><h2>Java Design</h2><p>In order to keep track of many bacteria with individual properties we thought it convenient to use an object-oriented language. Since Java also has the advantage of being easily distributed and made executable through a web browser environment, we found it a perfect candidate. Most of the data that has to be visualized are dependent on the programs ability to measure distance. This was made possible by deciding upon a convenient scale and assigning the pixels a suitable size. In our simulation every pixel corresponds to 0.1µm, which makes it easy to visualize the 2x1 µm large bacteria and its movement.</p><h2>Introduced Data</h2><h3>Generation time & Flux</h3><p>Generation time of our bacteria range between 20-40 min and the simulation considers a very limited window of time and space. To work around this issue a flux of bacteria to the visible area has been introduced. Though this will only affect the probiotic since Y. enterocolitica are immobile at gut temperature (De Berardis et al., 2004). In other word, we assume that there are bacteria moving around outside our screen and that they “walk in” at a constant rate. They will still reproduce based on their generation time but to depend solely on this process to drive the simulation would make it very time consuming.
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document.getElementById("tab1").innerHTML = '<h2>Introduction</h2><p>To facilitate the understanding of our multi-part system, a simulation for cell-cell interaction was developed in Java. Realistic data on movement and reproduction were used, so that our new introduced functions could be evaluated. This resulted in a two dimensional program where bacteria can interact with each other in real time, as if looked at in a microscope. In our scenario we consider the probiotic moving around on the small intestinal wall and reaching the outer surface of a Yersinia enterocolitica colony. By sensing its environment the bacteria can invoke changes in the movement pattern or kill other species in their vicinity. This provides us with a tool to predict how effective our introduced systems will be and add insight to how the systems can be improved. The program can easily be changed and applied to similar systems, hopefully making it useful for understanding and evaluating future projects.</p><h2>Java Design</h2><p>In order to keep track of many bacteria with individual properties we thought it convenient to use an object-oriented language. Since Java also has the advantage of being easily distributed and made executable through a web browser environment, we found it a perfect candidate. Most of the data that has to be visualized are dependent on the programs ability to measure distance. This was made possible by deciding upon a convenient scale and assigning the pixels a suitable size. In our simulation every pixel corresponds to 0.1µm, which makes it easy to visualize the 2x1 µm large bacteria and its movement.</p><h2>Introduced Data</h2><h3>Generation time & Flux</h3><p>Generation time of our bacteria range between 20-40 min and the simulation considers a very limited window of time and space. To work around this issue a flux of bacteria to the visible area has been introduced. Though this will only affect the probiotic since Y. enterocolitica are immobile at gut temperature (De Berardis et al., 2004). In other word, we assume that there are bacteria moving around outside our screen and that they “walk in” at a constant rate. They will still reproduce based on their generation time but to depend solely on this process to drive the simulation would make it very time consuming.<br><br>The generation time for the probiotic is based on E. coli data, once every 20 min. The corresponding value for Y. enterocolitica was a bit more tricky. It has been measured to 34 min at 30°C, which is assumed to be their optimal growth temperature (Aswathy Sreedharan, 2012). Since our simulation will take place at 37°C we decided to use 40min as an approximation. However, the simulation is not meant to run for more than a couple of minutes so the generation times have been translated into a chance of occurrence. The reproductions are also limited by available space so that bacteria are not able to stack on top of each other. </p><ul class="reference"><li>[1]Aswathy Sreedharan, C.J., 2012. Preventing Foodborne Illness: Yersiniosis [WWW Document]. URL http://edis.ifas.ufl.edu/fs193 (accessed 8.24.14).</li><li>[2]De Berardis, B., Torresini, G., Brucchi, M., Marinelli, S., Mattucci, S., Schietroma, M., Vecchio, L., Carlei, F., 2004. Yersinia enterocolitica intestinal infection with ileum perforation: report of a clinical observation. Acta Biomed 75, 77–81.</li><li>[3]77–81. H. C. Berg, 2004. E. coli in motion. Biological and medical physics series. (Springer, NewYork)</li><li>[4]Schwartz, S.A., Helinski, D.R., 1971. Purification and characterization of colicin E1. J. Biol. Chem. 246, 6318–6327.</li><li>[5]Spangler, R., Zhang, S.P., Krueger, J., Zubay, G., 1985. Colicin synthesis and cell death. J Bacteriol 163, 167–173.</li></ul>';
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The generation time for the probiotic is based on E. coli data, once every 20 min. The corresponding value for Y. enterocolitica was a bit more tricky. It has been measured to 34 min at 30°C, which is assumed to be their optimal growth temperature (Aswathy Sreedharan, 2012). Since our simulation will take place at 37°C we decided to use 40min as an approximation. However, the simulation is not meant to run for more than a couple of minutes so the generation times have been translated into a chance of occurrence. The reproductions are also limited by available space so that bacteria are not able to stack on top of each other. </p><ul class="reference"><li>[1]Aswathy Sreedharan, C.J., 2012. Preventing Foodborne Illness: Yersiniosis [WWW Document]. URL http://edis.ifas.ufl.edu/fs193 (accessed 8.24.14).</li><li>[2]De Berardis, B., Torresini, G., Brucchi, M., Marinelli, S., Mattucci, S., Schietroma, M., Vecchio, L., Carlei, F., 2004. Yersinia enterocolitica intestinal infection with ileum perforation: report of a clinical observation. Acta Biomed 75, 77–81.</li><li>[3]77–81. H. C. Berg, 2004. E. coli in motion. Biological and medical physics series. (Springer, NewYork)</li><li>[4]Schwartz, S.A., Helinski, D.R., 1971. Purification and characterization of colicin E1. J. Biol. Chem. 246, 6318–6327.</li><li>[5]Spangler, R., Zhang, S.P., Krueger, J., Zubay, G., 1985. Colicin synthesis and cell death. J Bacteriol 163, 167–173.</li></ul>';
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document.getElementById("tab2").innerHTML = '<p>fgdfgfdgd</p></ul></p><ul class="launchlist"><li><a href="#" id="downloadDemo">Download</a></li></ul>';
document.getElementById("tab2").innerHTML = '<p>fgdfgfdgd</p></ul></p><ul class="launchlist"><li><a href="#" id="downloadDemo">Download</a></li></ul>';

Revision as of 15:04, 13 October 2014

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