Team:XMU-China/Content4

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<h3>Abstract</h3>
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<h3>Gene OS: <small style="font-size:45px">Model of Synchronized Oscillator</small></h3>
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<p>Due to the complexity of our circuit, it is easier to understand the mechanism through modeling. In addition, the suitable modeling gives the results more quickly and correctly. A good mathematic model can also help us compare the affecting strength of different factors.</p><br />
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From July 16th to 17 th, We held a lecture entitled "Contemporary introduction to synthetic biology" with corresponding garden party and exhibition in order to help high school students make a better understanding of synthetic biology and genetic engineering. Thanks to the summer camp hosted by Xiamen University, thousands of high school students from Fujian province took part in our activities related to our theme. On the one hand, we let the high school students have a better understanding of our project and iGEM via the lecture. On the other hand, we expected our elucidation expressed how much genetic engineering contributes to our daily life in food, energy, material and so on. These students are just like seeds we sow to help synthetic biology and genetic engineering well understood by the public. What’s more, we designed a special series of cards with the theme of synthetic biology for the garden party. We plotted and organized the whole HP together with iGEM-XMU software.
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<h4>Software & Function Introduction<br/><br/></h4>
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<p>Based on the DDEs, Gene OS has two main modes of simulations. The basic simulation is designed for the oscillate circuit with <i>LuxI</i>, <i>aiiA</i> and <i>LuxR</i>, while the advanced simulation adds the effect of <i>ndh</i> gene.</p>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 1 shows the first <br/>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;interface of the Gene OS.</small></p><p>
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In each of modes, users can make a series of graphs through setting the different parameters. The numbers of graphs mainly depend on the different parameters and the modes.<br />The advanced simulation is expected to design for the oscillate circuit with <i>LuxI</i>, <i>aiiA</i>, <i>LuxR</i> and <i>ndh</i>, but we have not finished it.
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<img src="https://static.igem.org/mediawiki/2013/2/2d/Xmus-Image005.png" width =350px height=300px class="border alignleft" alt="Figure 2" style="margin-left:70px"/>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 2 shows the basic simulation user interface.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 3 shows the choose dialog box.</small></p>
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<p>This is the interface of the basic simulation where users set the parameters. We added many functions to make Gene OS more user-friendly.<br /><br />
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The meaning of each parameter can be displayed when click each parameter or right-click each input box. For the people first use this software, we designed the “One example” function which can set the parameters suitably in a single time.<br/> <br/>
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To get an idea about the different conditions in which oscillations could occur, we created a function which allows users to enter the range in which the variables should be varied and compare their results in the results. Due to the calculation speed, we finally apply this function in fluid flow speed and cell density, which are the most important parameters in the model. For example, people can set the cell density range from 0.1 to 0.9 with the step 0.2 by not selecting the “Fix the cell density” item.<br/> <br/>
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A white noise system was coded to simulate the noisy environment in the medium. This function makes the model closer to the actual environment. Users can set the strength by clicking “add white noise” box and inputting the decibels.<br/> <br/>
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A script calculates amplify and period of the oscillation is also added as an additional function. This allows our software detect and compare the characteristic of certain oscillation.<br/><br/>
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After setting all the parameters, users can save and output these settings into a standard 2003 excel file through the file menu. Loading is also supported which makes it more convenient for transmitting the parameters.<br/> <br/>
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Before drawing the graphs, users need to choose the plot mode when range parameters exist. For example, when set the cell density the software will ask user to draw separately or put curves with different cell density together. <br/> <br/>
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<p>Then clicking the “Draw” button, the software iterates over the values and plots graphs of all combinations possible for that range of values. After calculating, at most 3 kinds of graphs can be given, (1) concentration alteration of four main protein (2) fluorescence alteration under different cell density and fluid flow speed (3) amplify and period alteration under different cell density and fluid flow speed. </p>
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<img src="https://static.igem.org/mediawiki/2013/b/b9/Xmus-Image007.png" width =300px height=300px class="border alignleft" alt="Figure 4" style="margin-left: 40px;"/>
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<img src="https://static.igem.org/mediawiki/2013/e/e1/Xmus-Image008.png" width =550px height=300px class="border alignleft" alt="Figure 5" style="margin-left: 40px;"/></center>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 4 & 5 show some example output of Gene OS.</small></p>
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<p>To protect the software and computer, we designed an error-stop system which could stop the simulation as soon as one error was detected. This system also is called when users click “Cancel” button to stop the calculation. But different with error happened; this stop process takes about 1 min.
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<br /><br />The calculation speed of this software depends on the complexity of the parameters. Choosing both cell density range and fluid flow range to calculate can sometimes take more than 10 minutes. It is mainly because the large numbers of nested for-loops in the script and the slowly calculation speed about MATLAB core.
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<small style="font-size:16px">Figure 6 shows some example output of Gene OS.</small>
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<br /><br />You can download the MATLAB code <a href="https://static.igem.org/mediawiki/2013/8/8c/XMU-China_GeneOS.zip" style="Font-size:19px">here</a>.</p>
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<h3>ImageMe: <small style="font-size:45px">Microfluidic Image Analyser</ small></h3>
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<h4>Background<br/><br/></h4>
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What is synthetic biology on earth? Most people will present a confused expression when hearing this subject. Before the lecture we made a survey, finding that in fact nearly 100% of the respondents didn’t understand the meaning of the term. Fortunately through our lecture, we got our audience across to the basic principle and a general situation of synthetic biology. The lecture was held in the chemistry lecture hall, Xiamen University on July 7th. There was no empty seat in the hall. Lots of students even stood the whole lecture. The lecture has five parts, including introduction of synthetic biology, iGEM, iGEM-XMU , iGEM-HS program and our following activity——garden party.<br/>
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Synthetic biology is a newly-developing subject. Our iGEM-XMU team used simple words with vivid pictures to illustrate the generation and development of this discipline. What’s more, we introduced some basic knowledge of genetic safety in an interesting video. These unfamiliar words such as bacteria and gene got across well in our lecture. <br/>
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In addition, we introduced iGEM, including the start, development and goal of this competition to have the high school students know what we are crazy about. After that we presented some excellent teams, from biosynthesis to software, to stimulate them to enjoy this game. Every program included has its specialty, from bacteria with fluorescence to E.coli that can detect spoiled meat, as well as a kind of automatic LegoTM robot. They were all impressed by the charm synthetic biology shows. iGEM-XMU, a good team with two gold medals in Asia division in the last two years was invited to MIT to compete with the top undergraduates all over the world and achieved a great success. We then introduced our development and our 2013 team, including our project.<br/>
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We usually got a great number of fluorescent images every time when we finished the 8-hour-long microfluidic experiment. However, to get the data we have to calculate each trap in each image though using the software. What’s worse, the software could only process one image each time. Obviously, a more humanized software is needed if we do not want to spend much time on the manual work.<br /><br />
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  We got to know that China had four teams entering the 2012 iGEM-HS competition and made a brilliant achievement. In order to get a better popularization of iGEM-HS in China, we show these high school students some interesting iGEM-HS programs to draw their attention to this competition. Our efforts paid off. Inspired by what they saw, these high school students hoped to popularize synthetic biology and iGEM to make contributions to the development of this interesting project. They believed they can organize a next Chinese iGEM-HS team as well with our help in lab and other aspects. They wished that we can keep a long interaction and cooperation.<br/>
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<small style="font-size:16px">Figure 7 shows the first interface of the ImageMe.</small>
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During the lecture there was a really positive interaction between these high school students and our team. Every student participates in the competition, answering questions related to biological safety and some lucky dogs won our special rewards. In order to have a better and deeper communication, our team members and high school students exchanged E-mail address and telephone number with each other.
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<h4>Coding in MATLAB<br/><br/></h4>
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As we have not found such software on the net, we decided to design our own software. Thus, we used MATLAB coding the script and designed the user interface again for easy use.<br/><br/>
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We called this one “ImageMe” which was related with our team name. The most advantage of ImageMe is that it can analyze all the traps in the all images once.<br/><br/>
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<h4>Algorithm<br/><br/></h4>
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Thanks to the powerful image processing ability of MATLAB, the main algorithm is concise and efficient. First ImageMe changes the 256-color image to gray scale image and then uses edge processing to make the edge of each trap easier to detect. This process also reduces the negative effect of the background. The final step is to calculate the total gray level using numerical integration.
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<h4>Software & function introduction<br/><br/></h4>
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<p>Comparing with the Gene OS, ImageMe has more concise interface arrangement and easier to use. Click “Start” to enter the main interface.<br/></p>
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<img src="https://static.igem.org/mediawiki/2013/2/2d/Xmus-Image011.png" width =450px height=360px class="border alignleft" alt="" style="margin-left:20px"/>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 8 shows the main interface.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 9 shows the input dialog box.</small></p>
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<p>This is the main interface of ImageMe. Here, users can load the images by clicking the “Load” button and then choose the images. Then, ImageMe will pre-read all the images with “.jpg” suffix in this root directory. Make sure that no other .jpg images exist in the same folder. Click “Remove” button before changing the images to be analyzed.<br/><br/>
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After clicking the “Begin” button, ImageMe will ask users to input two parameters (which are also the only two need to input through the whole process) to assist the analysis more correctly. The two parameters are very easy to get comparing with those in Gene OS. First one is the lines of the traps and the second one is the rows. To get correct and precise results, please do not change the view or magnification times while taking images.<br/></p>
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<p>It is common that some images are indistinct or the edges are difficult to detect. When these situations occur to one image, ImageMe will use fuzzy calculation to analyze this one and make sure the result has the most correctness. <br/><br/>
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The real time message will be written on the screen when some indistinct images are detected or some errors happened.<br/><br/>
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If the analysis finished successfully, the graphs will show on the screen automatically. At most two kinds of graphs can be given, (1) fluorescence strength change in each trap (2) fluorescence strength change in each line.<br/>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 10 to 12 show the graphs given by ImageMe.</small></p>
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An output function was added to make possible for drawing these graphs through other software. This function generates an excel file including all statistic results about every image and every trap. Thus, users can get the results very easily.</br></br>
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The calculation speed of ImageMe depends on the complexity of the images. Too many lines and rows may lead to less correct results and take more time. However, analyze 80 example images (Figure 8, showed in the main interface) takes less than 70 seconds which is fast enough using MATLAB core.
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<p>You can download the MATLAB code <a href="https://static.igem.org/mediawiki/2013/0/0e/XMU-China_ImageMe.zip" style="Font-size:19px">here</a>. A group of test images is included.
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<h4>Gene OS: Comparing various results with different cell density</h4>
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<p>This example illustrates the importance of the cell density by comparing various results with different cell density.<br />
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Cell density is been normalized so that it is greater than 0 and less than or equal to 1. Thus we vary the cell density from 0.1 to 0.9 with the step-size 0.25 and keep other parameters the same.
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We held a garden party and related exhibition with the theme of synthetic biology and iGEM in the Gui Huashan Building, Xiamen University on July 17th afternoon.  The whole activity included three parts——synthetic biology exhibition, game and the Killers of Three Kingdoms cards presentation. To help the participants learn synthetic biology is a challenging but attractive process. These high school students could enjoy the interests in science and technology, know the knowledge about biology and think over ethics in life science through our activities. <br/>  
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<p><br />Then, choose “Cell density” and start calculation. From the results we can see that under this specific condition too small or too big cell density all cannot lead to a steady oscillation. Only the cell density near 0.35 gives the expected curve. This is mainly because that cell in small density cannot product enough LuxR, AHL, aiiA & GFP to start the oscillation. This can be confirmed by the little fluorescence strength. While too many cells surely lead to high fluorescence strength and slow mass transfer speed which cover up the oscillation.</p>
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We ushered the students to our conference theatre, having them participate in any activities they are interested in and giving them attracting presents. We also gave every participant our badge.<br/>
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The synthetic biology exhibition was composed by some display boards including knowledge of synthetic biology, program display on iGEM, biological safety and genetic engineering. Some information and pictures were from iGEM wiki. We made this exhibition following the lecture to improve our HP effects. <br/>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 13 shows the whole parameters.</small></p>
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Garden party game was the most important parts in order to enhance the interest. It was composed with three parts—Riddles written on lanterns，Foldit computer games and finding the differences between DNA molecules. In the first game, we find some riddles related to gene and biology and wrote them on lanterns. If the participant could find the answer then he would win a prize. Foldit, a computer game liked by the high school students since they can learn from entertainment, folds proteins and tests their stabilities with four people competing in it. Finding the differences between DNA molecules, is to find two or three differences between two analogous DNA pictures. From this game participants could be aware of DNA structure more deeply and practice their precision. We accumulated every students’ points and the final top 10 won the prize.<br/>  
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Our special prize is the cards——Killers of Three Kingdoms, very popular in China. There are abundant role-relationship and mutual promotion and restraint between every cards, just like Bong in America！！！Our team designed this kind of cards particularly for the HP, combining synthetic biology with the cards. Some high school students even play the cards with our plain guidance, making us think it’s an interesting and enjoyable game. Participants hoped that we could  send to them more cards and give them designing pictures. From this game we had a better interaction.<br/>  
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Finally our team organized a special link for these high school students. We show them our culture strains so that they can get an access to germiculture.  <br/>  
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After the garden party as well as the exhibition, these senior high school students signed on our whiteboard and had a group photo taken with us at our request. We made informal interviews with some of them and get a satisfactory feedback. They wished we could hold the activities next year and they would try their best to popularize synthetic biology and iGEM. A student, from Shaowu No.1 Middle School Of Fujian, expressed his hope that we could come to their hometown to help people in the countryside to get a correct understanding of genetic engineering. As I know, some people even regard transgenosis as poisons. This is also our hope that more and more people can learn something about transgenic products via this competition and have a better understanding of genetic engineering. After all, we, as iGEMers, not only need to do experiments in laboratory, but also help synthetic biology understood by the public. <br/>
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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 15&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 16
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<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 14 & 15 show the results given by Gene OS. Figure 16 shows the results when cell density equal to 0.35 and choose “Separate all”.</small></p>
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<h4>ImageMe: Comparing the results with manual calculation</h4>
 +
<p>To confirm the accuracy of ImageMe, we compared the two group results with manual calculated data. Due to the different algorithm, the fluorescence strength is not equal, but the tendency indicated in the each graph is comparable.
 +
<br /><br />
 +
First we compare them under the weak fluorescence situation.
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<img src="https://static.igem.org/mediawiki/2013/3/3e/XMU-China_s1.jpg" width =400px height=200px class="border alignleft" alt="Figure 2" style="margin-left:50px"/>
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<img src="https://static.igem.org/mediawiki/2013/e/e0/XMU-China_s2.png" width =400px height=200px class="border alignleft" alt="Figure 2" style="margin-left:70px"/></center>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 17 shows the results line 1 given by ImageMe.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 18 shows the results of line 1 given by manual calculation.</small></p>
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<p>From above, we can see that the general trend of each graph is both decreasing. However, ImageMe shows that the fluorescence strength of the last image is almost half of the first one while the manual calculation results only indicate a 15 percent decrease. The results are more amazing when we compare the 44th image (middle of the group) and the last one. ImageMe shows a 40 percent decrease while manual calculation results even implies a small increase in the fluorescence strength.<br />Now we compare these results with some of the images.<br /><br /></p>
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<p>Thus, from these images we can conclude that the fluorescence strength is decreasing significantly from the first one to the last. In addition, it is obviously that fluorescence strength of the last image is less than the middle one which </p><div class="clear"></div>
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<p>means a great computation error exists in the manual calculation.</p><div class="clear"></div>
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<img src="https://static.igem.org/mediawiki/2013/0/0a/XMU-China_s5.png" width =450px height=100px class="border alignleft" alt="Figure 2" />
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<a name="Surveys"></a>
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<p><small style="font-size:16px">Figure 19 is the first image of line 1 in the group.<br />Figure 20 is the 44<sup>th</sup> image of line 1 in the group.<br />Figure 21 is the 84<sup>th</sup> (last one) image of line 1 in the group.</small></p>
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<p>Second, we compare them under the strong fluorescence situation.</p><br />
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<h4>Surveys on The Popularization of Synthetic Biology and iGEM
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<img src="https://static.igem.org/mediawiki/2013/8/8a/XMU-China_s6.png" width =400px height=200px class="border alignleft" alt="Figure 2" style="margin-left:40px"/>
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in high school students of Fujian Province<br/>
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<img src="https://static.igem.org/mediawiki/2013/e/e8/XMU-China_s7.png" width =400px height=200px class="border alignleft" alt="Figure 2" style="margin-left:70px"/>
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<p><small style="font-size:16px">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 22 shows the results of line 2 given by ImageMe.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Figure 23 shows the results of line 2 given by manual calculation.</small></p>
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<p>In the second group, ImageMe shows a total 13 percent fluorescence strength increase while manual calculation indicates 10 percent. Comparing the 58th image (minimum of fluorescence strength) with the last one, ImageMe shows a 29 percent increase while manual calculation shows 32 percent. From the analysis, we can see the general trends of the two graphs match better than the first group.<br /><br />Now we compare these results with some of the images again.
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Our team conducted a synthetic biology survey before our lecture entitled "Contemporary introduction to synthetic biology". hWe wanted to compare how much they knew about synthetic biology and iGEM before the lecture with what their knowledge about them after our presentation in order to assess our work. We’ve prepared 300 questionnaires and handed out 227 of them. Among these drew-back questionnaires, 180 of them are valid. We put 12 questions on the questionnaire as below.<br/>  
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<br />
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1. Have you ever heard about synthetic biology before our lecture? <br/>  
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We choose the 54<sup>th</sup> and 58<sup>th</sup> (time 270 & 290) image because ImageMe shows a strange peak at 54<sup>th</sup> and a following valley at 58<sup>th</sup>.
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2. If you have, in which way it was accessible to you?<br/>  
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3. Which parts do you think are the most intriguing about synthetic biology after our lecture?<br/>  
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4. Have you ever heard about iGEM before our lecture? <br/>  
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5. If you have, in which way it was accessible to you? <br/>
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6. Are you willing to participate in iGEM after our lecture? <br/>
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7. If your answer is no, why? <br/>
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8. What’s your reason for participation, why? <br/>
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9. If you participate in iGEM in which aspects do to want to get supports? <br/>
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10. How much time can you spend on iGEM?<br/>
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11. If you participate, you and your family are willing to afford in which aspects? Some survey results are shown as below:<br/>
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<img src="https://static.igem.org/mediawiki/2013/8/87/Xmu-Image001.png" width =300px height=200px class="border alignleft" alt="" />
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<img src="https://static.igem.org/mediawiki/2013/8/89/Xmu-Image002.png" width =300px height=200px class="border alignleft" alt="" />
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<img src="https://static.igem.org/mediawiki/2013/6/60/Xmu-Image003.png" width =300px height=200px class="border alignleft" alt="" />
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<img src="https://static.igem.org/mediawiki/2013/0/05/Xmu-Image004.png" width =300px height=200px class="border alignleft" alt="" />
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<img src="https://static.igem.org/mediawiki/2013/a/a2/Xmu-Image005.png" width =300px height=200px class="border alignleft" alt="" />
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<img src="https://static.igem.org/mediawiki/2013/6/68/XMU-China_s8.png" width =450px height=100px class="border alignleft" alt="Figure 2" />
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Discussion<br/>  
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<p>From these images we can observe that the fluorescence strength is increasing a little from the first one to the last. In addition, the fluorescence of 58<sup>th</sup> seems the weakest in the</p>
-
Two major findings have been obtained from this analysis.<br/>  
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First of all, we drew a conclusion that almost everyone learned a lot from our lecture although they tended to be unfamiliar about the details of synthetic biology. Comparing the number of people who know about iGEM and the number of people who are willing to participate in iGEM we think the number of people who are interested in iGEM increases nearly 60%. Just look at the reasons why they don’t want to participate, most people chose no time and no supports. Only few people claimed that they were not interested in it and far less people said they didn’t like biology at all. Considering that our high school students are under so much pressure from National College Entrance Examination and some high school are too poor to afford technologies and apparatus, our results indicated a really good reality that almost everyone was willing to accept this new science and technology. <br/>  
+
<img src="https://static.igem.org/mediawiki/2013/8/89/XMU-China_s9.png" width =450px height=100px class="border alignleft" alt="Figure 2" />
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Second, as for how to popularize iGEM and synthetic biology, we summarize two points. <br/>  
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<p>four and the 54<sup>th</sup> obviously stronger than 58<sup>th</sup>. This result confirms ImageMe is sbetter again.<br />Therefore, ImageMe adapts the both situation while manual</p>
-
On the one hand, popularizing iGEM and synthetic biology via internet can reach a good effect because nearly half of these high school students said they heard iGEM and synthetic biology from the internet. We all think wiki is really a good platform to popularize synthetic biology and communicate with other iGEMers. What’s more, publishing more books relating to synthetic biology and iGEM is also a good conduit to let synthetic biology and iGEM known by other people, especially the young. <br/>  
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   On the other hand, teacher and parents seem to have difficulties in accepting a new technology in China or in the whole world so that students can’t learn some interesting and impressive new science and technologies from adults. It’s very common in China but we, as a new generation, should try our best to realize the rapid changing of our society.<br/>  
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<img src="https://static.igem.org/mediawiki/2013/8/8e/XMU-China_s10.png" width =450px height=100px class="border alignleft" alt="Figure 2" />
-
Future plans<br/>  
+
<p>calculation has significant computation error when the total fluorescence strength is weak which means only gives reliable results under strong fluorescence.</p>
-
Finally we drew some conclusion to improve our survey next time. In order to obtain results that are more valid we should launch a more widely circulated survey. In addition, perhaps more copies can be distributed at random to the general public. On the other hand, it’s really important to make an effective and smart questionnaire to get a more cogent result. Maybe we can make two kinds of questionnaire to hand out before and after the lecture to compare to get a better conclusion. <br/>  
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   <div class="clear"></div>
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<img src="https://static.igem.org/mediawiki/2013/3/38/XMU-China_s11.png" width =450px height=100px class="border alignleft" alt="Figure 2" />
 +
<p><small style="font-size:16px">Figure 24 is the first image of line 1 in the group.<br />Figure 25 is the 54<sup>th</sup> image of line 1 in the group.<br />Figure 26 is the 58<sup>th</sup> image of line 1 in the group.<br />Figure 27 is the 84<sup>th</sup> (last one) image of line 1 in the group.</small></p>
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We collaborated with Purdue iGEM team to create a definitive characterization standard for the parts registry. All the teams participated required to fill out a survey which about the important items in the registry page. Purdue iGEM team worked out a standard protocol which contains all of the details. The other teams need to complete it better or put forward some questions and problems. To make this work easy, we had a video meeting with the Purdue iGEM team and USP Brazil team though the GOOGLE HANGOUTS. It really helped us to exchange the opinions just like face to face.<br/>
 
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As we know, the members of this collaboration are currently over 50 teams so that it is the biggest collaboration in the iGEM history. We feel awesome about what we did!<br/>
 
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We provided parts BBa_C0061 and BBa_I0462 to the Toulouse iGEM team due to the high transform difficulty they described using this year’s distribution. Toulouse could directly use them for their cloning and we got some useful feedback about our parts.<br/> 
 
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<p style="font-size:20px;line-height:30px">
 
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We had a short meeting with 4 members of NJU iGEM team that visited us. During it, we introduced this year’s project to each other and exchanged the opinions. We welcome all other visitors as well.<br/>
 
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In the summer vacation, we drew a doodle about 2013 iGEM in Furong tunnel in the camp with the member of software team of our university. This tunnel is not only a main stem but also a famous scenic spots, so that more than 30,000 people per day will pass by and look our doodle. In addition, the doodle is a quite novel approach to introduce synthetic biology and we believe that no team did it before.<br/>
 
-
We also held a garden party with software team where introduced iGEM and synthetic biology to 200 students of senior high school from the whole Fujian Province. Go to page…to see more<br/>
 
-
In the wet lab, we helped them to structure their plasmids, such as teaching how to ligation and digestion.<br/>
 
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We’ve also had a really good communication with the iGEM team of Peking University. From August 11th to August 19th ,one of our team members went to Peking University to get a deep cooperation with them. Firstly we introduced our own project in this year and exchanged the opinions .They gave us some good suggestions in experiments and models. What’s more, they gave us one BioBrick of sfGFP (BBa_...), which gave a great help to our structure. This sfGFP allowed our circuit to generated a brighter fluorescence and made easier to obverse in the microfluidics.<br/>
 
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We very much appreciate the work you’ve done in the HP. Last but not least, we’re really grateful to the high school students for their joy in the HP.<br/>
 
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Latest revision as of 13:29, 26 October 2013

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Gene OS: Model of Synchronized Oscillator

Figure 1

Due to the complexity of our circuit, it is easier to understand the mechanism through modeling. In addition, the suitable modeling gives the results more quickly and correctly. A good mathematic model can also help us compare the affecting strength of different factors.


Software & Function Introduction

Based on the DDEs, Gene OS has two main modes of simulations. The basic simulation is designed for the oscillate circuit with LuxI, aiiA and LuxR, while the advanced simulation adds the effect of ndh gene.

        Figure 1 shows the first
       interface of the Gene OS.

In each of modes, users can make a series of graphs through setting the different parameters. The numbers of graphs mainly depend on the different parameters and the modes.
The advanced simulation is expected to design for the oscillate circuit with LuxI, aiiA, LuxR and ndh, but we have not finished it.

Figure 2 Figure 3

                       Figure 2 shows the basic simulation user interface.                                            Figure 3 shows the choose dialog box.

This is the interface of the basic simulation where users set the parameters. We added many functions to make Gene OS more user-friendly.

The meaning of each parameter can be displayed when click each parameter or right-click each input box. For the people first use this software, we designed the “One example” function which can set the parameters suitably in a single time.

To get an idea about the different conditions in which oscillations could occur, we created a function which allows users to enter the range in which the variables should be varied and compare their results in the results. Due to the calculation speed, we finally apply this function in fluid flow speed and cell density, which are the most important parameters in the model. For example, people can set the cell density range from 0.1 to 0.9 with the step 0.2 by not selecting the “Fix the cell density” item.

A white noise system was coded to simulate the noisy environment in the medium. This function makes the model closer to the actual environment. Users can set the strength by clicking “add white noise” box and inputting the decibels.

A script calculates amplify and period of the oscillation is also added as an additional function. This allows our software detect and compare the characteristic of certain oscillation.

After setting all the parameters, users can save and output these settings into a standard 2003 excel file through the file menu. Loading is also supported which makes it more convenient for transmitting the parameters.

Before drawing the graphs, users need to choose the plot mode when range parameters exist. For example, when set the cell density the software will ask user to draw separately or put curves with different cell density together.

Then clicking the “Draw” button, the software iterates over the values and plots graphs of all combinations possible for that range of values. After calculating, at most 3 kinds of graphs can be given, (1) concentration alteration of four main protein (2) fluorescence alteration under different cell density and fluid flow speed (3) amplify and period alteration under different cell density and fluid flow speed.

Figure 4 Figure 5

                                                                                   Figure 4 & 5 show some example output of Gene OS.

To protect the software and computer, we designed an error-stop system which could stop the simulation as soon as one error was detected. This system also is called when users click “Cancel” button to stop the calculation. But different with error happened; this stop process takes about 1 min.

The calculation speed of this software depends on the complexity of the parameters. Choosing both cell density range and fluid flow range to calculate can sometimes take more than 10 minutes. It is mainly because the large numbers of nested for-loops in the script and the slowly calculation speed about MATLAB core.

Figure 6 shows some example output of Gene OS.

You can download the MATLAB code here.

ImageMe: Microfluidic Image Analyser

Background

We usually got a great number of fluorescent images every time when we finished the 8-hour-long microfluidic experiment. However, to get the data we have to calculate each trap in each image though using the software. What’s worse, the software could only process one image each time. Obviously, a more humanized software is needed if we do not want to spend much time on the manual work.

Figure 7 shows the first interface of the ImageMe.

Coding in MATLAB

As we have not found such software on the net, we decided to design our own software. Thus, we used MATLAB coding the script and designed the user interface again for easy use.

We called this one “ImageMe” which was related with our team name. The most advantage of ImageMe is that it can analyze all the traps in the all images once.

Algorithm

Thanks to the powerful image processing ability of MATLAB, the main algorithm is concise and efficient. First ImageMe changes the 256-color image to gray scale image and then uses edge processing to make the edge of each trap easier to detect. This process also reduces the negative effect of the background. The final step is to calculate the total gray level using numerical integration.


Software & function introduction

Comparing with the Gene OS, ImageMe has more concise interface arrangement and easier to use. Click “Start” to enter the main interface.

                                Figure 8 shows the main interface.                                                                         Figure 9 shows the input dialog box.

This is the main interface of ImageMe. Here, users can load the images by clicking the “Load” button and then choose the images. Then, ImageMe will pre-read all the images with “.jpg” suffix in this root directory. Make sure that no other .jpg images exist in the same folder. Click “Remove” button before changing the images to be analyzed.

After clicking the “Begin” button, ImageMe will ask users to input two parameters (which are also the only two need to input through the whole process) to assist the analysis more correctly. The two parameters are very easy to get comparing with those in Gene OS. First one is the lines of the traps and the second one is the rows. To get correct and precise results, please do not change the view or magnification times while taking images.

It is common that some images are indistinct or the edges are difficult to detect. When these situations occur to one image, ImageMe will use fuzzy calculation to analyze this one and make sure the result has the most correctness.

The real time message will be written on the screen when some indistinct images are detected or some errors happened.

If the analysis finished successfully, the graphs will show on the screen automatically. At most two kinds of graphs can be given, (1) fluorescence strength change in each trap (2) fluorescence strength change in each line.

                                                                                        Figure 10 to 12 show the graphs given by ImageMe.

An output function was added to make possible for drawing these graphs through other software. This function generates an excel file including all statistic results about every image and every trap. Thus, users can get the results very easily.

The calculation speed of ImageMe depends on the complexity of the images. Too many lines and rows may lead to less correct results and take more time. However, analyze 80 example images (Figure 8, showed in the main interface) takes less than 70 seconds which is fast enough using MATLAB core.

You can download the MATLAB code here. A group of test images is included.

Examples & Confirmation

Gene OS: Comparing various results with different cell density

This example illustrates the importance of the cell density by comparing various results with different cell density.
Cell density is been normalized so that it is greater than 0 and less than or equal to 1. Thus we vary the cell density from 0.1 to 0.9 with the step-size 0.25 and keep other parameters the same.


Then, choose “Cell density” and start calculation. From the results we can see that under this specific condition too small or too big cell density all cannot lead to a steady oscillation. Only the cell density near 0.35 gives the expected curve. This is mainly because that cell in small density cannot product enough LuxR, AHL, aiiA & GFP to start the oscillation. This can be confirmed by the little fluorescence strength. While too many cells surely lead to high fluorescence strength and slow mass transfer speed which cover up the oscillation.

             Figure 13 shows the whole parameters.

Figure 3

                                                                                                                    Figure 14

Figure 2 Figure 3

                                                                         Figure 15                                                                                 Figure 16
            Figure 14 & 15 show the results given by Gene OS. Figure 16 shows the results when cell density equal to 0.35 and choose “Separate all”.



ImageMe: Comparing the results with manual calculation

To confirm the accuracy of ImageMe, we compared the two group results with manual calculated data. Due to the different algorithm, the fluorescence strength is not equal, but the tendency indicated in the each graph is comparable.

First we compare them under the weak fluorescence situation.

Figure 2 Figure 2

                     Figure 17 shows the results line 1 given by ImageMe.                             Figure 18 shows the results of line 1 given by manual calculation.

From above, we can see that the general trend of each graph is both decreasing. However, ImageMe shows that the fluorescence strength of the last image is almost half of the first one while the manual calculation results only indicate a 15 percent decrease. The results are more amazing when we compare the 44th image (middle of the group) and the last one. ImageMe shows a 40 percent decrease while manual calculation results even implies a small increase in the fluorescence strength.
Now we compare these results with some of the images.

Figure 2

Thus, from these images we can conclude that the fluorescence strength is decreasing significantly from the first one to the last. In addition, it is obviously that fluorescence strength of the last image is less than the middle one which

Figure 2

means a great computation error exists in the manual calculation.

Figure 2

Figure 19 is the first image of line 1 in the group.
Figure 20 is the 44th image of line 1 in the group.
Figure 21 is the 84th (last one) image of line 1 in the group.


Second, we compare them under the strong fluorescence situation.


Figure 2 Figure 2

                  Figure 22 shows the results of line 2 given by ImageMe.                         Figure 23 shows the results of line 2 given by manual calculation.

In the second group, ImageMe shows a total 13 percent fluorescence strength increase while manual calculation indicates 10 percent. Comparing the 58th image (minimum of fluorescence strength) with the last one, ImageMe shows a 29 percent increase while manual calculation shows 32 percent. From the analysis, we can see the general trends of the two graphs match better than the first group.

Now we compare these results with some of the images again.
We choose the 54th and 58th (time 270 & 290) image because ImageMe shows a strange peak at 54th and a following valley at 58th.

Figure 2

From these images we can observe that the fluorescence strength is increasing a little from the first one to the last. In addition, the fluorescence of 58th seems the weakest in the

Figure 2

four and the 54th obviously stronger than 58th. This result confirms ImageMe is sbetter again.
Therefore, ImageMe adapts the both situation while manual

Figure 2

calculation has significant computation error when the total fluorescence strength is weak which means only gives reliable results under strong fluorescence.

Figure 2

Figure 24 is the first image of line 1 in the group.
Figure 25 is the 54th image of line 1 in the group.
Figure 26 is the 58th image of line 1 in the group.
Figure 27 is the 84th (last one) image of line 1 in the group.


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