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Team:BostonU/Measurement
From 2014.igem.org
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Below is an example of how we thought about measuring our devices this summer. In the example below, this is how we would measure a gene of interest (blue box in the Measurement Device plasmid) that does not have an inducer molecule associated with it so we need to indirectly induce the expression of the GOI. We also have the GOI shown as a fusion protein with GFP so we can measure the fluorescence. Also, in this example, we are keeping the Measurement Device and Test Device separate on two plasmids. The two devices could also be easily made into one plasmid as well (not shown). | Below is an example of how we thought about measuring our devices this summer. In the example below, this is how we would measure a gene of interest (blue box in the Measurement Device plasmid) that does not have an inducer molecule associated with it so we need to indirectly induce the expression of the GOI. We also have the GOI shown as a fusion protein with GFP so we can measure the fluorescence. Also, in this example, we are keeping the Measurement Device and Test Device separate on two plasmids. The two devices could also be easily made into one plasmid as well (not shown). | ||
<br><br> | <br><br> | ||
| - | <center><img src="https://static.igem.org/mediawiki/2014/9/9e/BU14_Measurement_Update.png" width=" | + | <center><img src="https://static.igem.org/mediawiki/2014/9/9e/BU14_Measurement_Update.png" width="70%"></center><br><br> |
<h3>Why <i>E. coli</i>?</h3> | <h3>Why <i>E. coli</i>?</h3> | ||
| - | We chose to clone all of our genetic parts in <I>E.coli</I> for several reasons. <I>E.coli</I> grows quickly and its genetic manipulation is fairly easy. There are also several different strands of <I>E.coli</I>. | + | We chose to clone all of our genetic parts in <I>E.coli</I> for several reasons. <I>E.coli</I> grows quickly and its genetic manipulation is fairly easy. There are also several different strands of <I>E.coli</I>.<br><br> |
<h3> Strain Selection</h3> | <h3> Strain Selection</h3> | ||
| - | We transformed most of our constructs into the bioline strain. However, for the tandem promoters, we chose to transform them into DH5α Pro strains for testing. The DH5α strain contain <I>araC</I>, <I>tetR</I>, and <I>lacI</I>, which simplifies testing the tandem promoters by preventing us from building additional transcriptional units to express araC, tetR, and lacI. In the Pro strain, the promoters are in their off state by default. Therefore, we can add increasing concentrations of small molecules to induce the promoters and cause increasing fluorescence expression. We also tried using MG1655 Pro strain. However, that soon proved problematic as we use blue-white screening [1] to pick successful colonies from transformed plates. MG1655 strains have a fully functional <i>lacZ</i> sequence, which will always be expressed. Thus, all colonies on transformed plates will appear blue whether the ligation worked or not. | + | We transformed most of our constructs into the bioline strain. However, for the tandem promoters, we chose to transform them into DH5α Pro strains for testing. The DH5α strain contain <I>araC</I>, <I>tetR</I>, and <I>lacI</I>, which simplifies testing the tandem promoters by preventing us from building additional transcriptional units to express araC, tetR, and lacI. In the Pro strain, the promoters are in their off state by default. Therefore, we can add increasing concentrations of small molecules to induce the promoters and cause increasing fluorescence expression. We also tried using MG1655 Pro strain. However, that soon proved problematic as we use blue-white screening [1] to pick successful colonies from transformed plates. MG1655 strains have a fully functional <i>lacZ</i> sequence, which will always be expressed. Thus, all colonies on transformed plates will appear blue whether the ligation worked or not. <br><br> |
<h3> Standardized Data for sharing and reproduction </h3> | <h3> Standardized Data for sharing and reproduction </h3> | ||
Another one of our goals for iGEM was to obtain and present standard characterized data that can then be compared with data in other labs. This goes back to the reason why we wanted to incorporate software tools into the design-build-test cycle. We wanted to achieve predictive design using cost-effective methods. This will only be possible if all labs in the Synthetic Biology community are able to compare each other’s data and that is why we use the TASBE tools, which are available for the entire community and convert arbitrary fluorescent data to standard Molecules of Equivalent Fluorescein (MEFLs). | Another one of our goals for iGEM was to obtain and present standard characterized data that can then be compared with data in other labs. This goes back to the reason why we wanted to incorporate software tools into the design-build-test cycle. We wanted to achieve predictive design using cost-effective methods. This will only be possible if all labs in the Synthetic Biology community are able to compare each other’s data and that is why we use the TASBE tools, which are available for the entire community and convert arbitrary fluorescent data to standard Molecules of Equivalent Fluorescein (MEFLs). | ||
Latest revision as of 01:11, 18 October 2014
Why is measurement important?Synthetic Biology is a relatively new field of research. It involves the assembly of nucleic acid polymers in many possible arrangements and checking for the range of function that they exhibit. Thus, efficient measurement of genetic devices becomes integral to determining their function. Why is BU in the measurement track?The BU Chimera characterization workflow efficiently combines software with wet lab protocols to yield complex devices. In using this workflow, one goes around the standard design-build-test cycles at least thrice. Testing for any device involves the use of TASBE Tools and flow cytometry. This is used extensively in Phase 2 of the workflow as one multiplexing reaction can potentially yield many possible constructs. Here, measurement can be used to differentiate between a plethora of constructs and to pick the best combinatorial possibility for the assembly of the larger device. Measurement, hence, is an essential part of the Chimera workflow as the results from one phase are necessary as the inputs in the next phase. Considerations in measurement strategyWhen we started thinking about our project this year, we came up with a series of criteria we wanted to take into account when measuring the functionality of our devices. First, we decided to use fluorescent proteins to measure the function for our devices since we had easy access to a flow cytometer. Second, for new parts, we wanted to generate as many transfer curves as possible to obtain data about the dynamic range the new parts may have, which led us to incorporating inducible promoters into our designs. Third, we thought about what transcription units we would need to build to test our devices. For these criteria, we also came up with a series of questions about the design constraints for the testing devices: did we need to include the functional proteins that controlled the promoters? Did we want to use one plasmid or two? Did we want to test these devices in one strain of E. coli or multiple? As we worked through our project this summer, these questions and criteria helped shape our characterization of basic parts. Below is an example of how we thought about measuring our devices this summer. In the example below, this is how we would measure a gene of interest (blue box in the Measurement Device plasmid) that does not have an inducer molecule associated with it so we need to indirectly induce the expression of the GOI. We also have the GOI shown as a fusion protein with GFP so we can measure the fluorescence. Also, in this example, we are keeping the Measurement Device and Test Device separate on two plasmids. The two devices could also be easily made into one plasmid as well (not shown).  Why E. coli?We chose to clone all of our genetic parts in E.coli for several reasons. E.coli grows quickly and its genetic manipulation is fairly easy. There are also several different strands of E.coli.Strain SelectionWe transformed most of our constructs into the bioline strain. However, for the tandem promoters, we chose to transform them into DH5α Pro strains for testing. The DH5α strain contain araC, tetR, and lacI, which simplifies testing the tandem promoters by preventing us from building additional transcriptional units to express araC, tetR, and lacI. In the Pro strain, the promoters are in their off state by default. Therefore, we can add increasing concentrations of small molecules to induce the promoters and cause increasing fluorescence expression. We also tried using MG1655 Pro strain. However, that soon proved problematic as we use blue-white screening [1] to pick successful colonies from transformed plates. MG1655 strains have a fully functional lacZ sequence, which will always be expressed. Thus, all colonies on transformed plates will appear blue whether the ligation worked or not.Standardized Data for sharing and reproductionAnother one of our goals for iGEM was to obtain and present standard characterized data that can then be compared with data in other labs. This goes back to the reason why we wanted to incorporate software tools into the design-build-test cycle. We wanted to achieve predictive design using cost-effective methods. This will only be possible if all labs in the Synthetic Biology community are able to compare each other’s data and that is why we use the TASBE tools, which are available for the entire community and convert arbitrary fluorescent data to standard Molecules of Equivalent Fluorescein (MEFLs). |
References
[1] "Introduction to Blue-White Screening." Sigma-Aldrich. N.p., n.d. Web. 14 Oct. 2014.
