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Team:Calgary/21 August 2009
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| - | + | Wiki Wrap up / Team Meeting / Question Period | |
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| - | + | Scholarships , Posters , Presentations , timelines , future conferences and much more was discussed in the team meetings. | |
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Today I spent the entire morning updating both the Wiki as well as my lab notebook. My lab Notebook is now up-to-date. Yay! And my section of the Wiki is almost completely updated. This afternoon we had an important team meeting to talk about or plans for the upcoming months in respect to the completion of our project. | Today I spent the entire morning updating both the Wiki as well as my lab notebook. My lab Notebook is now up-to-date. Yay! And my section of the Wiki is almost completely updated. This afternoon we had an important team meeting to talk about or plans for the upcoming months in respect to the completion of our project. | ||
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| - | + | Paper Writing: | |
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| - | + | First of all today is my birthday. | |
| + | It is about the time that we have to write about what we have been doing over this summer. In order to do so, we have planned to cover the following sections in the paper: | ||
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| + | -Abstract | ||
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| + | -Introduction to quorum sensing | ||
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| + | -Introduction to MC (membrane computing): | ||
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| + | a -P systems in general | ||
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| + | b-P system in this framework | ||
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| + | -membrane structure, objects (agents), and interaction rules | ||
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| + | -Gillespie's Algorithm : | ||
| + | a- Modifications and Implementations | ||
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| + | b-Rate of reactions (reactions' constant) | ||
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| + | c-Time (global clock) | ||
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| + | -Results | ||
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| + | -Conclusion | ||
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| + | -References | ||
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| + | To give you an idea how would be the content of this paper, I post the abstract: | ||
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| + | In this article, we present a membrane computing model of the quorum sensing system in genetically engineered Escherichia coli (E.coli) bacteria. Quorum sensing is a way of communication between unicellular bacteria. In this way of communication, bacteria release signaling molecules to their environment. Other bacteria are able to receive and recognize the signals. Measuring the accumulation of signals in the environment of a bacterium, enables it to sense the number of cells (cell density) around it. Many species of bacteria use the information obtained to coordinate their gene expression in response to the size of their population. The regulation of genes according to the cell density is called Quorum Sensing. Moreover, membrane computing is a powerful model for computation of some features of living cells. MC is inspired by biological membranes structures and functions. In this model, Each bacterium has two membranes, where one of them is enclosed by the other one and therefore each bacterium has to enclosed regions. Each region is associated with a multiset of objects and a set of evolution rules is assigned to each membrane as well. The application of the rules is computed by a compartmentalized version of Gillespie's algorithm in a way that in each time step,only one rule is applied to the system. This model allows us to observe the behavior of each individual bacterium as well as the emergent properties of the whole population. It also enables us to manipulate some factors involved in the simulation to understand the effects of them in individual behaviors as well as colony behavior. Our simulation demonstrates that at low bacteria densities all the bacteria produce GFP protein which emits light but as the population grows by division, they regulate their gene expression and they do not produce GFP longer and after a while they turn dark. | ||
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| + | This is what I have been doing this week and I will be busy doing it for next couple of weeks. | ||
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| - | + | Analyzing AI-2 Isolation Data and Lab Cleanup | |
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| - | + | Lab cleanup! Lots of gruelling work but worth it. The lab looked really clean and spiffy after we were done with it. | |
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| + | Beyond that I also sat around and played with Excel to see what kind of graphs I could generate with my data and what use it would be. Data was re-arrayed with a macro donated by Margot from the Surette lab (''MANY'' thanks with everything you have helped us with!!). | ||
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| + | [[Image:Calgary_AI2-(1).jpg | 600px]] | ||
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| + | 'Figure 1.'Luminescence readings from an autoinducer bioassay using cell-free supernatants from overnights of various bacterial strains with Vibrio harveyi MM32 as the reporter strain. MM32 is responsive (i.e. luminescent) to the AI-2 present in the supernatant of V. harveyi BB120, a wildtype strain, and BB152 (BB120 luxLM::Tn5)2, a strain deficient in AHL production. Salmonella typhimurium 14028 produces AI-2 but due to differences in boration1, specificity to the V. harveyi reporter strain, and therefore luminescence, decreases. S. typhimurium SS007 (14028 luxS::T-POP)3 is incapable of producing AI-2 and serves as a negative control. E. coli DH5α has been reported as lacking the ability to produce AI-24. The lack of a peak in luminescence for MM32 grown with DH5α supernatant validates using DH5α as the chassis for our system. Our signalling system in DH5α will be responsive solely to exogenously added AI-2 derived from BB152 as it only produces AI-2. Cell-free supernatants were made by centrifugation of overnight cultures and filtering it with a 0.2μm (indicated by an ‘F’). Controls indicate the importance of filtering the supernatant (data not shown). The graph indicates an average obtained from 3 trials. | ||
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Latest revision as of 21:12, 1 October 2009
UNIVERSITY OF CALGARY
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