<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >Once we confirmed that degradation was working reliably, and that we did in fact have a variety of different strength tags, we then tested whether or not we could change gene expression speed. Using the ATC inducible mScarlet-I constructs from the previous section, we confirmed that we could change the gene expression speed of our constructs. Further, we then compared our observed results to our mathematical predictions based on degradation rate and found that the speed change appeared to be 1/degradation rate, exactly as our model would predict. Together, this represents the first experimental confirmation of the relationship between gene expression speed and degradation rate.
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<div style = 'padding-right: 190px; padding-left: 190px; text-indent: 50px;line-height: 25px;' >Once we confirmed that degradation was working reliably, and that we did in fact have a variety of different strength tags, we then tested whether or not we could change gene expression speed. Using the ATC inducible mScarlet-I constructs from the previous section, we confirmed that we could change the gene expression speed of our constructs. Further, we then compared our observed results to our mathematical predictions based on degradation rate and found that the speed change appeared to be log(2)/degradation rate, exactly as our model would predict (Figure 3). Together, this represents the first experimental confirmation of the relationship between gene expression speed and degradation rate.
<figcaption><div style='padding-left: 5px;padding-top: 15px; color: #808080; width = "80%; font-size: 14px;'>Figure 3: Measurements of the fluorescence (A) or the steady state normalized fluorescence (B) over time of BBa_K2333432 (pTet mScarlet-I pdt E), with and without Lon at 50ng/mL ATC, and with Lon readjusted at 85ng/mL ATC. Each data point represents the geometric mean of 10,000+ cells from each of three biological replicates, with at least 10,000 cells collected for each replicate. Shaded region represents +/- standard deviation. Reporter constructs were used on 1C3 while a 3K3 version of BBa_K2333434 (pLac mf-Lon) was used.
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<center><figcaption><div style='padding-left: 5px;padding-top: 15px; color: #808080; width = "80%; font-size: 14px;'>Figure 4: Measurements of the fluorescence (A) or the steady state normalized fluorescence (B) over time of BBa_K2333432 (pTet mScarlet-I pdt E), with and without Lon at 50ng/mL ATC, and with Lon readjusted at 85ng/mL ATC. Each data point represents the geometric mean of 10,000+ cells from each of three biological replicates, with at least 10,000 cells collected for each replicate. Shaded region represents +/- standard deviation. Reporter constructs were used on 1C3 while a 3K3 version of BBa_K2333434 (pLac mf-Lon) was used.
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Revision as of 04:08, 1 November 2017
Degradation Rates
Although Cameron and Collins already demonstrated the functionality of protein degradation tags (pdt), and the Mesoplasma florum Lon (mf-Lon) protease in E. coli, we noted that they did their work exclusively using genomically integrated constructs. Since the majority of iGEM teams work exclusively or close to exclusively on plasmid constructs, we first wanted to confirm and characterize the parts using iGEM backbones. To do this we assembled constitutive and ATC inducible constructs carrying the red fluorescent protein mScarlet-I, tagged with each of our six different pdts, or left untagged as a control. Further, to ensure that our project will work with a variety of different proteins, we made identical constructs encoding for superfolder GFP (sfGFP), and preformed preliminary characterization.
Text here
Construct schematics here
Results and graphs here.
Speed Control
Once we confirmed that degradation was working reliably, and that we did in fact have a variety of different strength tags, we then tested whether or not we could change gene expression speed. Using the ATC inducible mScarlet-I constructs from the previous section, we confirmed that we could change the gene expression speed of our constructs. Further, we then compared our observed results to our mathematical predictions based on degradation rate and found that the speed change appeared to be log(2)/degradation rate, exactly as our model would predict (Figure 3). Together, this represents the first experimental confirmation of the relationship between gene expression speed and degradation rate.
Figure 2: Measurements of gene expression normalized to steady state using our ATC inducible mScarlet-I constructs. Data is shown for each construct until steady state is reached (at least two consecutive subsequent data points do not increase fluorescence). Each data point represents the geometric mean of 10,000+ cells from each of three biological replicates, with at least 10,000 cells collected for each replicate. Shaded region represents one geometric standard deviation above and below the mean. Reporter constructs were used on 1C3 while a 3K3 version of BBa_K2333434 (pLac mf-Lon) was used.
Preserving Steady State Protein Concentration
While we have demonstrated that we can see a real speed change, you might remember that in our math section we noted that the steady state value is given as the production rate divided by the degradation rate. This means that though we are increasing the speed of gene expression, we are also decreasing the steady-state value. While some applications may only care about a gene’s expression an on or off signal, and not about the magnitude of expression, we wanted our system to be usable in any system. Since in our model gene expression speed is only regulated by degradation, it should be possible to readjust our steady-state value back up to its original expression. Using pdt E as an example, we measured the time to steady state with and without mf-Lon at a given ATC induction level. We then showed that by increasing the ATC concentration (increasing production rate), we can return the steady state of the protease condition to the no protease condition while maintaining the same speed change, exactly as our model predicts.
Figure 4: Measurements of the fluorescence (A) or the steady state normalized fluorescence (B) over time of BBa_K2333432 (pTet mScarlet-I pdt E), with and without Lon at 50ng/mL ATC, and with Lon readjusted at 85ng/mL ATC. Each data point represents the geometric mean of 10,000+ cells from each of three biological replicates, with at least 10,000 cells collected for each replicate. Shaded region represents +/- standard deviation. Reporter constructs were used on 1C3 while a 3K3 version of BBa_K2333434 (pLac mf-Lon) was used.
Enabling Future iGEM Teams
Once we felt that we could understand and control gene expression speed using our system, we next wanted to make it accessible to future iGEM teams. While our system is inherently easy to clone and implement, as it only consists of only a 27 amino acid residue pdt and the associated mf-Lon protease, we wanted to make it even easier to implement. So we created a suite of ready to clone pdt constructs and placed them on the registry. Each part contains one of our six different strength E. coli optimized protein degradation tags, as well as a double stop codon and a double terminator. Combining all these parts together into one construct prevents extra cloning steps, saving time, money and aggravation. In addition to the functional elements above, each construct also contains two BsaI restriction sites for Golden Gate Assembly, two Universal Nucleotide Sequences for Gibson Assembly, as well as a number of well-tested primer sequences that can be used for any other type of cloning. We also made it easy to swap and design large libraries of constructs with different speeds, by making sure that the only difference between each ready cloning construct was a small unique region in the pdt. That means there is no need to switch primers to use a different strength pdt. Alongside our well-characterized construct K2333434 (pLac mf-Lon), these ready to clone parts should make it cheap and easy for future teams to test their constructs with a wide variety of different gene expression speeds, either by changing the pdt or the concentration of mf-Lon.
Figure 4: Schematic of generic cloning ready part. UNS sites can be used for easy cloning and backbone transfers, while BsaI sites enable Golden Gate Assembly
Proof of Concept
After demonstrating that our pdt system can be used to increase gene expression speed, we wanted to ensure that they could actually be used by future teams. So we developed a set of parts and associated primers that easily enable Gibson, Golden Gate and other forms of restriction enzyme-based cloning. Further, we collaborated with the University of Maryland iGEM team to create a practical proof of concept where increasing the speed of a circuit would be valuable. To that end, we created and characterized the speed of pdt tagged version of their copper detecting circuit, and then sent it back to them for future use. Though we did not get to do the full range of characterization we wanted due to time concerns, we found that we were able to increase speed in the same manner as with our test circuits. This serves as a practical proof of concept, as we were successfully able to show that with our cloning parts, and with minimal time we were able to increase the speed of an arbitrary genetic circuit.
Figure 5: Normalized fluorescence of three different pdt modified versions of copper parts, contrasted against a no Lon control. Each data point represents the geometric mean of 10,000+ cells from each of three biological replicates. Shaded region represents one geometric standard deviation above and below the mean. Reporter constructs were used on 1C3 while a 3K3 version of BBa_K2333434 (pLac mf-Lon) was used. Note that the no Lon control did not reach steady state, so its true expression speed may be even slower
