Difference between revisions of "Team:ETH Zurich/Experiments/Heat Sensor"

 
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<main role="main">
 
<main role="main">
 
<h1 class="headline">Heat Sensor Experiments</h1>
 
<h1 class="headline">Heat Sensor Experiments</h1>
 +
 +
<p><em>This is a detailed experiment page dedicated to an individual function. To access other experiments, go to our <a href="https://2017.igem.org/Team:ETH_Zurich/Experiments">Experiments page</a>. To get a quick glimpse at all of our achievements, check out <a href="https://2017.igem.org/Team:ETH_Zurich/Results">Results</a>.</em></p>
 +
 +
<section class="emphasize">
 +
<h1>Achievements</h1>
 +
<ul>
 +
<li>We <a href="https://2017.igem.org/Team:ETH_Zurich/Experiments/Heat_Sensor#phaseI">characterized</a> our initial design and found that the highest fold-changes in activation can be induced at 45 °C.</li>
 +
<li>We rationally designed an RBS library to tune expression levels of tlpA. By screening for the best variant we were able to dramatically <a href="https://2017.igem.org/Team:ETH_Zurich/Experiments/Heat_Sensor#phaseII">improve our initial design</a>.</li>
 +
<li>Finally, we <a href="https://2017.igem.org/Team:ETH_Zurich/Experiments/Heat_Sensor#phaseII">showed</a> that our thermosensing system is tight enough to put the lysis-inducing protein E under it's control without harming the cells.</li>
 +
</ul>
 +
</section>
  
 
<section>
 
<section>
 
     <h1>Introduction</h1>
 
     <h1>Introduction</h1>
  
−
     <p>We incorporated a module into our system that would allow our engineered bacteria to sense the external toxin release signal of the doctor. The signal is produced with focused ultrasound and increases the temperature in the tumor region to 45 °C. To detect this signal, we needed to fit a naturally occurring heat sensor from <span class="bacterium">Salmonella</span> into our novel genetic circuit. If the heat sensor detects the temperature increase, it should activate the next step (cell lysis), by promoting transcription of protein E.</p>
+
     <p>We incorporated a module into our system that allows our engineered bacteria to sense the external toxin-release signal of the doctor. The signal is produced with focused ultrasound which increases the temperature in the tumor region to 45 °C. To detect this signal, we needed to fit a naturally occurring heat sensor from <span class="bacterium">Salmonella enterica serovar Typhimurium</span> into our novel genetic circuit. <a href="#bib1" class="forward-ref">[1]</a><a href="#bib2" class="forward-ref">[2]</a> Once the heat sensor detects the temperature increase, it activates the next step (<a href="2017.igem.org/Team:ETH_Zurich/Circuit/Fe_Cell_Lysis">Cell Lysis</a>), by promoting expression of protein E.</p>
  
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     <figure class="fig-nonfloat" style="width:700px;">
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     <figure class="fig-nonfloat" style="width:800px;">
−
         <img alt="FIXME"
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         <img alt="Genetic Circuit of Heat Sensor"
 
         src="https://static.igem.org/mediawiki/2017/d/d7/T--ETH_Zurich--TlpA_Heat_Sensor_general.png"/>
 
         src="https://static.igem.org/mediawiki/2017/d/d7/T--ETH_Zurich--TlpA_Heat_Sensor_general.png"/>
−
         <figcaption>Figure 1. The genetic mechanism of our TlpA heat sensor. TlpA dimers bind in the P<sub>TlpA</sub> region and repress transcription of the downstream gene. A temperature of 45 °C shifts the equilibrium of dimerization towards monomers, which don't bind in the P<sub>TlpA</sub> region. Transcription can therefore happen at 45 °C.</figcaption>
+
         <figcaption>Figure 1. The genetic circuit of our <a href="http://parts.igem.org/Part:BBa_K2500003">TlpA heat sensor</a>. TlpA represses the P<sub>TlpA</sub> Promoter. A temperature of 45 °C releases the repression leading to induction of protein E.</figcaption>
 
     </figure>
 
     </figure>
  
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</section>
 
</section>
  
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<section>
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<section id="phaseI">
 
     <h1>Phase I: Initial System Design</h1>
 
     <h1>Phase I: Initial System Design</h1>
  
−
     <p>The TlpA heat sensor consists of two parts: the TlpA coding sequence and the P<sub>TlpA</sub> promotor sequence. We copied the digital sequences from a plasmid used by Piraner et al. and introduced 8 silent mutations to remove forbidden restriction sites inside the coding sequence. We designed test-plasmids to ensure proper function of the system. The initial design of a test system constists of two plasmids, one containing the repressor and the other the promotor and a reporter protein. The first plasmid was designed to have an Anderson Promotor with relative strength of 0.71 that promotes transcription of an RBS (designed with Salis Lab RBS calculator) with a calculated translation initiation rate of 5000 and the TlpA coding sequence.  
+
     <p>The TlpA heat sensor consists of two parts: the TlpA regulator protein and the P<sub>TlpA</sub> promoter. We implemented the digital sequences from a plasmid used by Piraner et al. <a href="#bib2" class="forward-ref">[2]</a>and introduced 8 silent mutations to remove forbidden restriction sites inside the coding sequence. We designed test-plasmids to ensure proper function of the system. The initial design of a test system constists of two plasmids, one containing the repressor and the other the promoter and a reporter protein. The first plasmid was designed to have an <a href="http://parts.igem.org/Part:BBa_J23100">Anderson Promoter</a> with relative strength of 0.71 followed by a RBS (designed with Salis Lab RBS calculator <a href="#bib3" class="forward-ref">[3]</a>) with a calculated translation initiation rate of 5000 and the TlpA coding sequence.  
  
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     <figure class="fig-nonfloat" style="width:400px;">
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     <figure class="fig-nonfloat" style="width:500px;">
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         <img alt="FIXME"
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         <img alt="Heat Sensor Test Plamids"
 
         src="https://static.igem.org/mediawiki/2017/b/bb/T--ETH_Zurich--heat_sensor_test_device.png"/>
 
         src="https://static.igem.org/mediawiki/2017/b/bb/T--ETH_Zurich--heat_sensor_test_device.png"/>
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         <figcaption>Figure 2. The heat sensor test plamids. The TlpA coding sequence is placed on the piG17-2-002 (pSEVA361) and the heat inducible gfp is placed on piG17-1-005 (pSEVA291). PF and SF are abbreviations for BioBrick Prefix and BioBrick Suffix restriction sites. RS1-RS4 are restriction sites that we introduced for later cloning.  
+
         <figcaption>Figure 2. The heat sensor test plamids. The TlpA coding sequence is placed on <a href="https://2017.igem.org/Team:ETH_Zurich/Sequences#heatsensor">piG17-2-002</a> (pSEVA361) and the heat inducible gfp is placed on <a href="https://2017.igem.org/Team:ETH_Zurich/Sequences#heatsensor">piG17-1-005</a> (pSEVA291). PF and SF are abbreviations for BioBrick Prefix and BioBrick Suffix restriction sites. RS1-RS4 are restriction sites that we introduced for subsequent cloning steps.  
 
         </figcaption>
 
         </figcaption>
 
     </figure>
 
     </figure>
  
−
     <p>The optimal amount of the TlpA repressor protein in the cytoplasm was not known to us from the beginning, that's why we decided for a medium amount of TlpA expression. The physical DNA sequences were ordered as gBlocks from IDT and inserted to our test plasmids pSEVA361 and pSEVA291 via Ligase Cycling Reactions.</p>
+
     <p>The optimal amount of the TlpA repressor protein in the cytoplasm was not known to us from the beginning, that's why we chose a medium amount of TlpA expression. The physical DNA sequences were ordered as gBlocks from IDT and inserted to our test plasmids pSEVA361 and pSEVA291 via Ligase Cycling Reactions.</p>
  
 
     <h2>Key questions to answer in first experiments</h2>
 
     <h2>Key questions to answer in first experiments</h2>
 
     <ul>
 
     <ul>
−
         <li>Does the heat sensor work in our Lab with our experimental setup?</li>
+
         <li>Does the heat sensor work in our lab with our experimental setup?</li>
−
         <li>Does the heat sensor work despite the changes we made to the coding sequence, the calculated ribosome binding site and the BioBrick promotor?</li>
+
         <li>Does the heat sensor work despite the changes we made to the coding sequence, the synthetic ribosome binding site and the BioBrick promotor?</li>
 
         <li>Which temperature is needed to activate the heat sensor?</li>
 
         <li>Which temperature is needed to activate the heat sensor?</li>
 
         <li>How long does the heat sensor have to be induced for decent expression of the regulated gene?</li>
 
         <li>How long does the heat sensor have to be induced for decent expression of the regulated gene?</li>
 
     </ul>
 
     </ul>
−
</section>
 
  
−
<section>
+
<p>A sequence of experiments was performed to find optimal induction times and experimental setup. <span class="bacterium">E. coli</span> Top10 chemical competent cells or Nissle electrocompetent cells were used. Single colonies of double transformants were inoculated to 12 mL round bottom culture tubes in 5 mL LB and grown for 16 h at 37 °C shaking 230 rpm. After growth to stationary phase, they were diluted to OD 0.1 and grown to exponential phase (OD 0.4). At this point the induction procedure was initiated in different formats, for different times and temperatures.</p>
−
    <h1>Phase II - A: Function test with reporter gene</h1>
+
−
 
+
−
    <p>A sequence of experiments was performed to find optimal induction times and experimental setup. <span class="bacterium">E. Coli</span> Top10 chemical competent cells or Nissle electrocompetent cells were used. Single colonies of double transformants were inoculated to 12 mL round bottom culture tubes in 5 mL LB and grown for 16 h at 37 °C shaking 230 rpm. After growth to stationary phase, they were diluted to OD 0.1 and grown to exponential phase (OD 0.4). At this point the induction procedure was initiated in different formats, for different times and temperatures.</p>
+
 
     <p> Our findings were:</p>
 
     <p> Our findings were:</p>
 
     <ul>
 
     <ul>
−
         <li>Induction times of 1 to 15 minutes don't induce the reporter gene strong enough, even though temperatures above 42 °C lead to slightly higher fluorescence after 15 min induction</li>
+
         <li>Induction times of 1 to 15 minutes don't induce the reporter gene measurably, even though temperatures above 42 °C lead to slightly higher fluorescence after 15 min induction</li>
−
         <li>Strong induction takes place in a timescale of 1-5 hours. (more would not be feasible for our application)</li>
+
         <li>Strong induction takes place in a timescale of 1-5 hours. (more would not be feasible for <a href="https://2017.igem.org/Team:ETH_Zurich/Applied_Design">our application</a>)</li>
−
         <li>Growth in 12 mL culture tubes is best suited and the samples should be diluted before plate reader measurement.</li>
+
         <li>A suitable experiment procedure was found</li>
 
     </ul>
 
     </ul>
  
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     <figure class="fig-nonfloat" style="width:800px;">
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     <figure class="fig-nonfloat" style="width:500px;">
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         <img alt="FIXME"
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         <img alt="Induction Time Comparison for TlpA regulated gfp induction"
 
         src="https://static.igem.org/mediawiki/2017/6/61/T--ETH_Zurich--5h_experiment_data.png"/>
 
         src="https://static.igem.org/mediawiki/2017/6/61/T--ETH_Zurich--5h_experiment_data.png"/>
−
         <figcaption>Figure 3. Fluorescence readouts of the TlpA Heat sensor after induction times from 0.5 to 5 h. Biological triplicates were measured and the standard deviation is depicted. Longer induction times lead to higher fluorescence values. Even though induction is significant, the fold change is very low. Induction was performed in 60 uL cell culture in 100 uL PCR tubes in thermocyclers for the time and temperature indicated and after induction stored at 30 °C until start of the readout (5 h after start of induction).</figcaption>
+
         <figcaption>Figure 3. Fluorescence readouts of the TlpA Heat sensor after induction times from 0.5 to 5 h. Biological triplicates were measured and the standard deviation is depicted as error bars.</figcaption>
 
     </figure>
 
     </figure>
  
−
     <p>The experimental setup was changed from induction in thermocycler to induction in shaking incubators. Shake flasks were used and the same experiment repeated.</p>
+
     <p>Longer induction times lead to higher fluorescence values (Figure 7). Even though induction is significant, the fold change is very low. Induction was performed in 60 uL cell culture in 100 uL PCR tubes in thermocyclers for the time and temperature indicated and after induction stored at 30 °C until start of the readout (5 h after start of induction). The experimental setup was changed from induction in thermocycler to induction in shaking incubators. Shake flasks were used to test whether low oxygen availability could have been an issue for culture growth and induction potency.</p>
  
 
     <figure class="fig-nonfloat" style="width:800px;">
 
     <figure class="fig-nonfloat" style="width:800px;">
 
         <img alt="FIXME"
 
         <img alt="FIXME"
 
         src="https://static.igem.org/mediawiki/2017/6/6e/T--ETH_Zurich--Shake_Flask_xperiment.png"/>
 
         src="https://static.igem.org/mediawiki/2017/6/6e/T--ETH_Zurich--Shake_Flask_xperiment.png"/>
−
         <figcaption>Figure 4. Fluorescence readouts of the TlpA Heat sensor after 3h induction at 45 °C in shake flasks in a shaking incubator. Biological triplicates were measured and the standard deviation is depicted. The fluorescence of the supernatant was also measured to find out if we can use supernatant fluorescence in future cell lysis measurements.</figcaption>
+
         <figcaption>Figure 4. Fluorescence of the TlpA Heat Sensor test device after 3 h induction at 37 °C and 45 °C in shake flasks in a shaking incubator. Biological triplicates were measured and the standard deviation is depicted as error bars. The negative control lacked the gene for gfp (GFP-, TlpA+) and the positive control lacked the TlpA regulator protein (GFP+, TlpA-).</figcaption>
 
     </figure>
 
     </figure>
  
−
     <p>These experiments showed that induction is possible, but the fold change of ~6 is very low. This is either due to a low maximum induction of the promotor compared to a constitutive promotor of gfp, or to a high expression when not induced. We hypothesized that the RBS of TlpA was not inducing translation enough, and low amounts of the TlpA reporessor protein don't inactivate base level expression enough. Double transformations with protein E under the TlpA operator suggested that we need a tighter regulation (they did not yield any transformant colonies due to insufficient inhibition of protein E expression leading to cell lysis). </p>
+
     <p>The fluorescence of the supernatant was also measured to find out if we can use supernatant fluorescence in future cell lysis measurements. These experiments (Figure 3 and 4) showed that induction is possible, but the fold change of ~6 is very low. This is either due to a low maximum induction of the promotor compared to a constitutive promotor of gfp, or to a high leaky expression when not induced. We hypothesized that the RBS of TlpA was not initiating translation enough, and low amounts of the TlpA reporessor protein don't inactivate base level expression enough.  
 +
Since we intend to heat induce protein E mediated cell lysis, a promoter system with high basal expression is useless. Initial trials to clone protein E under P<sub>TlpA</sub> failed, probably due to insufficient inhibition of protein E expression.</p>
  
 +
</section>
  
  
−
<section>
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<section id="phaseII">
−
     <h1>Reducing the heat sensor's leakiness</h1>
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     <h1>Phase II: Optimization of the Heat Sensor</h1>
 +
 
 +
<p><b>Reducing the heat sensor's leakiness</b></p>
 
   <p>
 
   <p>
−
It is very important for proper function of CATE to have a very tightly controlled activation of cell lysis. Only if CATE releases the anti-cancer compound upon the external heat signal an improvement of the precision of toxin delivery is possible. Additionally, it is not possible to transform <span class="bacterium">E. coli</span> with a heat inducible toxic compound with such a leaky expression - the leaky protein E expression already kills all transformants.  
+
It is very important for proper function of CATE to have a very tightly controlled activation of cell lysis. Only if CATE releases the anti-cancer compound upon the external heat signal, an improvement of the control of toxin delivery is possible. Additionally, it is very difficult to introduce the heat inducible protein E expression construct under a leaky promoter, as the basal expression already induces cell death in the successful transformants.
 
   </p>
 
   </p>
 
             <p><b>TlpA RBS library creation</b></p>
 
             <p><b>TlpA RBS library creation</b></p>
 
   <p>
 
   <p>
−
A ribosome binding site library was then created to find variants translating more TlpA RNA. The Red Libs algorithm was used and set to calculate degenerate sequences that produce 12 variants. The variants should all have a rather high expression rate to increase the cytoplasmic amount of TlpA dimers able to repress the promotor. Degenerate primers were ordered at Microsynth and the library was created with a simple PCR and subsequent gel cleanup and transformation.
+
A ribosome binding site library was then created to find variants expressing more TlpA. The RedLibs algorithm <a href="#bib4" class="forward-ref">[4]</a> was used and set to calculate degenerate sequences that produce 12 variants. The variants should all have a rather high expression rate to increase the cytoplasmic amount of TlpA dimers able to repress the promotor. Degenerate primers were used to create the library with a simple PCR and subsequent gel cleanup and transformation.
 
   </p>
 
   </p>
  
−
  <figure class="fig-nonfloat" style="width:300px;">
+
  <figure class="fig-nonfloat" style="width:500px;">
 
         <img src="https://static.igem.org/mediawiki/2017/3/36/T--ETH_Zurich--TlpA_RBS_Library_plate.jpeg">
 
         <img src="https://static.igem.org/mediawiki/2017/3/36/T--ETH_Zurich--TlpA_RBS_Library_plate.jpeg">
−
         <figcaption>Figure 5. TlpA RBS Library. A RBS library of the TlpA RBS was calculated with the Red Libs algorithm. It contained 12 different RBS sequences that should exhibit different strong translation initiation rates. Green colonies have lost the repressor activity of TlpA probably due to very weak TlpA expression. Non-fluorescent colonies might have a strongly repressed gfp, because of a higher amount of TlpA.</figcaption>
+
         <figcaption>Figure 5. TlpA RBS Library. A RBS library of the TlpA RBS was calculated with the RedLibs algorithm. It contained 12 different RBS sequences that should exhibit uniformly distributed translation initiation rates. Green colonies have lost the repressor activity of TlpA probably due to very weak TlpA expression. Non-fluorescent colonies might have a strongly repressed gfp, because of a higher amount of TlpA.</figcaption>
 
     </figure>
 
     </figure>
 
            
 
            
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   <p>
 
   <p>
−
Single colonies were picked and inoculated to a 96 well plate and grown to a stationary phase. Continuing with the 96 well format, the samples were inoculated into a fresh 96 well culture plate and grown to OD 0.4. At this point the cultures were split and induced at 37 °C and 45 °C for 3 h. Samples were diluted in PBS and the fluorescence measured in a plate reader. The eight variants with the highest fold-change were selected for further experiments.
+
Single colonies were picked and inoculated to a 96 well plate and grown to a stationary phase. Continuing with the 96 well format, the samples were inoculated into a fresh 96 well culture plate and grown to OD<sub>600</sub> 0.4. At this point the cultures were split and induced at 37 °C and 45 °C for 3 h. Samples were diluted in PBS and the fluorescence measured in a plate reader. The eight variants with the highest fold-change were selected for further experiments.
 
   </p>
 
   </p>
  
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  <figure class="fig-nonfloat" style="width:800px;">
 
  <figure class="fig-nonfloat" style="width:800px;">
−
         <img src="https://static.igem.org/mediawiki/2017/8/8e/T--ETH_Zurich--TlpA_RBS_Lead_Candidates.png">
+
         <img src="https://static.igem.org/mediawiki/2017/7/77/T--ETH_Zurich--libvar16.png">
−
         <figcaption>Figure 6. TlpA RBS Library variants on/off ratio. Distribution of obtained fluorescence expression of the library variants and their fold change. The fold changes have a high variance from 20 to 7000. This data suggests that different variants of the original RBS were compared. The new variants from the library generation yield higher fold changes than the parent variant which had a RBS with rather low translation initiation rate. The high fold change of H1 is caused by the low leakiness, not by extraordinary high expression.</figcaption>
+
         <figcaption>Figure 6. Distribution of GFP expression of the library variants (A) and their fold change (B).</figcaption>
 
     </figure>
 
     </figure>
  
 +
<p>Our results (Figure 6) suggest that different variants of the original RBS were obtained in the library creation.  The fold changes vary from 20 to 1200. Most of the new variants yield higher fold changes than the parent variant. The high fold change of H1 is caused by a low leakiness, not by high expression.
  
−
<figure class="fig-nonfloat" style="width:800px;">
+
<figure class="fig-nonfloat" style="width:500px;">
 
         <img src="https://static.igem.org/mediawiki/2017/4/49/T--ETH_Zurich--TlpA_best_RBS_variants.png">
 
         <img src="https://static.igem.org/mediawiki/2017/4/49/T--ETH_Zurich--TlpA_best_RBS_variants.png">
 
         <figcaption>Figure 7. The 96 well plate with the four technical replicates of the induction of gfp with the thermosensitive TlpA repressor. On top: 4 wells per column induced for 3 h at 37 °C, bottom: 4 wells per column induced at 45 °C. The positive control did not grow.</figcaption>
 
         <figcaption>Figure 7. The 96 well plate with the four technical replicates of the induction of gfp with the thermosensitive TlpA repressor. On top: 4 wells per column induced for 3 h at 37 °C, bottom: 4 wells per column induced at 45 °C. The positive control did not grow.</figcaption>
 
     </figure>
 
     </figure>
 +
  </p>
 +
<p>The best variants were sequenced and single colonies restreaked for subsequent triplicate measurements. The sequencing results were compared to the predicted translation initiation rates from the RedLibs algorithm:
 +
  </p>
  
 +
<figure class="fig-nonfloat" style="width:500px;">
 +
        <img src="https://static.igem.org/mediawiki/2017/5/59/T--ETH_Zurich--TlpA-RBS-Variant_sequences.png">
 +
    </figure>
 +
<p> The variants A9 and D9 share the same sequence and have the highest predicted translation initiation rate (T.I.R.). Interestingly the T.I.R. of H1 is an order of magnitude lower than the others, but still lead to a high fold change.
 +
</p>
  
−
<p><b>Triplicate measurements of the Best 4 variants</b></p>
+
<section id="phaseIII">
 +
    <h1>Phase III Demonstration of the Heat Sensor Function</h1>
  
 +
    <p><b>Triplicate measurements of the best 3 variants</b></p>
  
−
<p>Experiment was performed according to the protocol with TlpA RBS library variants H1, A9, C12 and D9. They were sequenced and compared to the calculated translation initiation rates:
 
  
−
Sequence T.I.R. Level Variant
+
    <p>A final experiment was performed according to the <a href="https://static.igem.org/mediawiki/2017/9/96/T--ETH_Zurich--protocolfd1.pdf">protocol</a> with the TlpA RBS library variants H1, A9, C12 and D9 in biological triplicates (Figure 8).
−
ATTTAAGG 717'381 A9/D9
+
    </p>
−
ACTTAAGG 638'164   C12
+
−
CCTAAAGG 62'294   H1
+
  
−
</p>
+
<figure class="fig-nonfloat" style="width:800px;">
 +
        <img src="https://static.igem.org/mediawiki/2017/e/e3/T--ETH_Zurich--libvar.png">
 +
        <figcaption>Figure 8. TlpA-regulated GFP expression. <b>A</b> Fluorescence of the variants C12 (C), A9 (A), H1 (H) and the parent variant. <b>B</b> Fold changes of the different variants of the TlpA RBS. The samples were non-induced (37 °C) and induced (45 °C) in biological triplicates.</figcaption>
 +
    </figure>
  
 +
    </p>
  
 +
<p>
 +
The thermoswitch was now tight enough to repress the toxic protein E to enable transformant colonies to grow. In the next step we transformed it together with a protein E RBS library containing plasmid, with the aim to find protein E RBS library variants with enough reduced translation initiation rate to survive.
 +
</p>
 +
  
−
 
+
  <p>We could improve the leakiness of the TlpA promotor by simply enhancing the translation initiation rate of the repressor protein TlpA. High GFP expression fold changes of up to 200 were obtained.</p>
−
    <p>To read more about each of these experiments, click on the buttons below. For a detailed protocol describing each experiment, visit <a href="https://2017.igem.org/Team:ETH_Zurich/Protocols">Protocols.</a></p>
+
</section>
 
</section>
 
</section>
  
  
 +
<section class="references">
 +
    <h1>References</h1>
 +
    <ol>
 +
      <li id="bib1">Hurme, R., Berndt, K.D., Namork, E. & Rhen, M. "DNA binding exerted by a bacterial gene regulator with an extensive coiled-coil domain." <cite>J. Biol. Chem.</cite> 271 (1996): 12626–12631. <a href="https://doi.org/10.1074/jbc.271.21.12626">doi: 10.1074/jbc.271.21.12626</a></li>
  
 +
        <li id="bib2">Piraner, Dan I., et al. "Tunable thermal bioswitches for in vivo control of microbial therapeutics."<cite>Nature chemical biology</cite> 13.1 (2017): 75-80. <a href="https://doi.org/10.1038/nchembio.2233">doi: 10.1038/nchembio.2233</a></li>
 +
<li id="bib3">Espah Borujeni, Amin, Anirudh S. Channarasappa, and Howard M. Salis. "Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites." <cite>Nucleic acids research</cite> 42.4 (2013): 2646-2659. <a href="https://doi.org/10.1093/nar/gkt1139">doi: 10.1093/nar/gkt1139</a></li>
 +
<li id="bib4">Jeschek, Markus, Daniel Gerngross, and Sven Panke. "Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort." <cite>Nature communications</cite> 7 (2016). <a href="https://doi.org/10.1038/ncomms11163">doi: 10.1038/ncomms11163</a></li>
  
 +
    </ol>
  
  
−
 
−
<section>
 
−
    <h1>FIXME--Should these be here?</h1>
 
−
    <div class="multi-summary">
 
−
        <details>
 
−
            <summary>Quorum Sensing End-Point Characterization</summary>
 
−
            <p><b>OBJECTIVE</b></p>
 
−
            <p>Determine the population density at which the quorum system gets activated and provide the modellers with data to infer a<sub>LuxI</sub>, the production rate of LuxI.</p>
 
−
 
−
            <p><b>PROCEDURE</b></p>
 
−
            <p>We transformed <span class="bacterium">E. Coli</span> with a regulator and an actuator plasmid, containing constitutive LuxR and Plux, sfGFP, mCherry and LuxI respectively (Figure 2).</p>
 
−
 
−
            <figure class="fig-nonfloat" style="width:400px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/9/9a/T--ETH_Zurich--WL_TS_figure2.png">
 
−
                <figcaption>Figure 2. Depictions of the two transformed plasmids. One contains the regulator, LuxR. The other one Plux which responds to dimerized LuxR. LuxR dimerizes upon binding to AHL which synthesis is catalyzed by LuxI.</figcaption>
 
−
            </figure>
 
−
 
−
            <p>Subsequently, we let these colonies grow to different final population densities. This was achieved by varying glucose concentrations in a defined medium. <a href="#bib1" class="forward-ref">[1]</a> Population density was assessed by measuring absorbance at 600 nm wavelength. Fluorescence emitted by sfGFP and mCherry served as a read-out of the level of activation. A detailed protocol is available in <a href="https://2017.igem.org/Team:ETH_Zurich/Protocols">Protocols.</a></p>
 
−
 
−
            <p><b>RESULTS</b></p>
 
−
            <figure class="fig-nonfloat" style="width:700px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/3/3b/T--ETH_Zurich--QS_Trigger_Analysis.png">
 
−
                <figcaption>Figure 3. A) Fluorescense per A600 in response to population density. Colonies were grown over night in media with varying glucose concentrations that lead to different final population denisities. With increasing absorbances at 600 nm, increasing fluorescence levels are observed. B) Proof of concept that final population densities can be modulated with the amount of glucose in a defined medium. </figcaption>
 
−
            </figure>
 
−
 
−
            <p><b>CONCLUSION</b></p>
 
−
            <ul>
 
−
                <li>We can modulate the density a bacterial population reaches in defined medium by varying the amount of glucose.</li>
 
−
                <li>The quorum sensing system shows a response to increasing population densities.</li>
 
−
            </ul>
 
−
        </details>
 
−
 
−
        <details>
 
−
            <summary>AND-gate without Quorum Sensing</summary>
 
−
 
−
            <p><b>OBJECTIVE</b><br>
 
−
            Determine expression levels of GFP production under the control of the AND-gate with different inducer concentrations. In this experiment we wanted to assess whether our designs would be capable to distinguish healthy and tumor tissue based on lactate and expected AHL concentrations.</p>
 
−
 
−
            <p><b>PROCEDURE</b><br>
 
−
            Two plasmids required for the AND-gate were transformed into <span class="bacterium">E. coli</span> Top 10 (Figure 4). Cultures were grown in microtiter plates under combinations of 8 different AHL and 8 different lactate concentrations and measured after 5.5 hours. A detailed protocol is available in <a href="https://2017.igem.org/Team:ETH_Zurich/Protocols">Protocols.</a></p>
 
−
 
−
            <figure class="fig-nonfloat" style="width:400px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/5/56/T--ETH_Zurich--WL_TS_ANDgate_wo_LuxI.png">
 
−
                <figcaption>Figure 4. Schematic depiction of the two plasmids that were transformed for this experiment. Both lactate and AHL were manually provided in this experiment.</figcaption>
 
−
            </figure>
 
−
 
−
            <p><b>RESULTS</b></p>
 
−
            <p>The different conditions cleary have an impact on expression levels of sfGFP under control of the AND-gate promoter. All three designs show increasing activation with increasing inducer concentration, even if the second inducer is not present. The highest fold-change for all designs however, is observed if both inducers are present in high amounts.</p>
 
−
 
−
            <figure class="fig-nonfloat" style="width:700px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/a/a1/T--ETH_Zurich--AHL_Dose_Response.png">
 
−
                <figcaption>Figure 5. AHL Dose-Response Curve obtained by measuring fluorescence.</figcaption>
 
−
            </figure>
 
−
 
−
            <p><b>CONCLUSION</b></p>
 
−
            <ul>
 
−
                <li>Leakiness of the synthetic promoter increases with increasing amounts of either inducer in the absence of the other.</li>
 
−
                <li>Increasing AHL amounts have a greater influence on the leakiness in absence of lactate.</li>
 
−
                <li>All three AND-gates exhibit highest inductions in presence of both inducers.</li>
 
−
                <li>At lactate levels found in healthy tissue and low AHL concentrations, all designs are only weakly activated.</li>
 
−
                <li>Design B performed best at distinguishing “healthy tissue lactate”, low AHL vs. “tumor tissue lactate”, high AHL. Design C, on the other hand, performed worst.</li>
 
−
            </ul>
 
−
        </details>
 
−
 
−
        <details>
 
−
            <summary>AND-gate with Quorum Sensing</summary>
 
−
 
−
            <p><b>OBJECTIVE</b><br>
 
−
            Verify the findings of the AND-gate characterization without quorum sensing with strains of <span class="bacterium">E. Coli</span> that contain additionally to the AND-gate also LuxI, the enzyme that catalzyes AHL production.</p>
 
−
 
−
            <p><b>PROCEDURE</b><br>
 
−
            Two plasmids required for the AND-gate were transformed into <span class="bacterium">E. coli</span> Top 10 (Figure 6). Cultures were grown in microtiter plates in media with varying lactate concentrations. Density and fluorescence measurements were taken every 15 minutes to ensure a high enough time-resolution. A detailed protocol is available in <a href="https://2017.igem.org/Team:ETH_Zurich/Protocols">Protocols.</a>
 
−
 
−
            <figure class="fig-nonfloat" style="width:400px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/2/21/T--ETH_Zurich--ANDgate_w_LuxI.png">
 
−
                <figcaption>Figure 6. Schematic depiction of the two plasmids that were transformed for this experiment. Lactate is provided to the system in this experiment, AHL is synthesized by the cells themselves.</figcaption>
 
−
            </figure>
 
−
 
−
 
−
            <p><b>RESULTS</b><br>
 
−
            The data is very noisy and it’s hard to make general statements about this systems behaviour. Despite this, a clear trend is visible for GFP to be higher expressed under lactate concentrations similar to tumor tissue than under those resembling healthy tissue or no lactate at all. With increasing population densities this effect becomes less pronounced (Figure 7).</p>
 
−
 
−
            <figure class="fig-nonfloat" style="width:700px;">
 
−
                <img src="https://static.igem.org/mediawiki/2017/1/1b/T--ETH_Zurich--AND_vsLuxI_B_norm.png">
 
−
                <figcaption>Figure 7. Fluorescence normalized to population density vs. population density. Blue circles correspond to media lacking lactate, green to media containing 1 mM lactate, and red to 5 mM lactate. Circle styles correspond to three different biological replicates. It becomes apparent that with higher densities comes higher activation and that for lower population densities, lactate has a positive influence on GFP expression levels.</figcaption>
 
−
            </figure>
 
−
 
−
            <p><b>CONCLUSION</b></p>
 
−
            <ul>
 
−
                <li>Due to a lot of noise in the data, conclusions have to be drawn with caution</li>
 
−
                <li>Under lactate concentration mimicking tumor tissue, GFP gets stronger expressed than under lactate levels associated with healthy tissue.</li>
 
−
                <li>Fold-changes are around 4 for design B and 2 for design A which is considerably less than observed in Figure 5. This might be due to a somewhat different experimental setup.</li>
 
−
            </ul>
 
−
        </details>
 
−
    </div>
 
−
</section>
 
−
 
−
<section class="references">
 
−
    <h1>References</h1>
 
−
    <ol>
 
−
        <li id="bib1">Contois, D. E. "Kinetics of bacterial growth: relationship between population density and specific growth rate of continuous cultures." <cite>Microbiology</cite> 21.1 (1959): 40-50. <a href="https://doi.org/10.1099/00221287-21-1-40">doi: 10.1099/00221287-21-1-40</a></li>
 
−
    </ol>
 
 
</section>
 
</section>
 
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</main>
 
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Latest revision as of 01:38, 2 November 2017

Heat Sensor Experiments

This is a detailed experiment page dedicated to an individual function. To access other experiments, go to our Experiments page. To get a quick glimpse at all of our achievements, check out Results.

Achievements

  • We characterized our initial design and found that the highest fold-changes in activation can be induced at 45 °C.
  • We rationally designed an RBS library to tune expression levels of tlpA. By screening for the best variant we were able to dramatically improve our initial design.
  • Finally, we showed that our thermosensing system is tight enough to put the lysis-inducing protein E under it's control without harming the cells.

Introduction

We incorporated a module into our system that allows our engineered bacteria to sense the external toxin-release signal of the doctor. The signal is produced with focused ultrasound which increases the temperature in the tumor region to 45 °C. To detect this signal, we needed to fit a naturally occurring heat sensor from Salmonella enterica serovar Typhimurium into our novel genetic circuit. [1][2] Once the heat sensor detects the temperature increase, it activates the next step (Cell Lysis), by promoting expression of protein E.

Genetic Circuit of Heat Sensor
Figure 1. The genetic circuit of our TlpA heat sensor. TlpA represses the PTlpA Promoter. A temperature of 45 °C releases the repression leading to induction of protein E.

For more details about the mechanism, go to Heat Sensor.

Phase I: Initial System Design

The TlpA heat sensor consists of two parts: the TlpA regulator protein and the PTlpA promoter. We implemented the digital sequences from a plasmid used by Piraner et al. [2]and introduced 8 silent mutations to remove forbidden restriction sites inside the coding sequence. We designed test-plasmids to ensure proper function of the system. The initial design of a test system constists of two plasmids, one containing the repressor and the other the promoter and a reporter protein. The first plasmid was designed to have an Anderson Promoter with relative strength of 0.71 followed by a RBS (designed with Salis Lab RBS calculator [3]) with a calculated translation initiation rate of 5000 and the TlpA coding sequence.

Heat Sensor Test Plamids
Figure 2. The heat sensor test plamids. The TlpA coding sequence is placed on piG17-2-002 (pSEVA361) and the heat inducible gfp is placed on piG17-1-005 (pSEVA291). PF and SF are abbreviations for BioBrick Prefix and BioBrick Suffix restriction sites. RS1-RS4 are restriction sites that we introduced for subsequent cloning steps.

The optimal amount of the TlpA repressor protein in the cytoplasm was not known to us from the beginning, that's why we chose a medium amount of TlpA expression. The physical DNA sequences were ordered as gBlocks from IDT and inserted to our test plasmids pSEVA361 and pSEVA291 via Ligase Cycling Reactions.

Key questions to answer in first experiments

  • Does the heat sensor work in our lab with our experimental setup?
  • Does the heat sensor work despite the changes we made to the coding sequence, the synthetic ribosome binding site and the BioBrick promotor?
  • Which temperature is needed to activate the heat sensor?
  • How long does the heat sensor have to be induced for decent expression of the regulated gene?

A sequence of experiments was performed to find optimal induction times and experimental setup. E. coli Top10 chemical competent cells or Nissle electrocompetent cells were used. Single colonies of double transformants were inoculated to 12 mL round bottom culture tubes in 5 mL LB and grown for 16 h at 37 °C shaking 230 rpm. After growth to stationary phase, they were diluted to OD 0.1 and grown to exponential phase (OD 0.4). At this point the induction procedure was initiated in different formats, for different times and temperatures.

Our findings were:

  • Induction times of 1 to 15 minutes don't induce the reporter gene measurably, even though temperatures above 42 °C lead to slightly higher fluorescence after 15 min induction
  • Strong induction takes place in a timescale of 1-5 hours. (more would not be feasible for our application)
  • A suitable experiment procedure was found
Induction Time Comparison for TlpA regulated gfp induction
Figure 3. Fluorescence readouts of the TlpA Heat sensor after induction times from 0.5 to 5 h. Biological triplicates were measured and the standard deviation is depicted as error bars.

Longer induction times lead to higher fluorescence values (Figure 7). Even though induction is significant, the fold change is very low. Induction was performed in 60 uL cell culture in 100 uL PCR tubes in thermocyclers for the time and temperature indicated and after induction stored at 30 °C until start of the readout (5 h after start of induction). The experimental setup was changed from induction in thermocycler to induction in shaking incubators. Shake flasks were used to test whether low oxygen availability could have been an issue for culture growth and induction potency.

FIXME
Figure 4. Fluorescence of the TlpA Heat Sensor test device after 3 h induction at 37 °C and 45 °C in shake flasks in a shaking incubator. Biological triplicates were measured and the standard deviation is depicted as error bars. The negative control lacked the gene for gfp (GFP-, TlpA+) and the positive control lacked the TlpA regulator protein (GFP+, TlpA-).

The fluorescence of the supernatant was also measured to find out if we can use supernatant fluorescence in future cell lysis measurements. These experiments (Figure 3 and 4) showed that induction is possible, but the fold change of ~6 is very low. This is either due to a low maximum induction of the promotor compared to a constitutive promotor of gfp, or to a high leaky expression when not induced. We hypothesized that the RBS of TlpA was not initiating translation enough, and low amounts of the TlpA reporessor protein don't inactivate base level expression enough. Since we intend to heat induce protein E mediated cell lysis, a promoter system with high basal expression is useless. Initial trials to clone protein E under PTlpA failed, probably due to insufficient inhibition of protein E expression.

Phase II: Optimization of the Heat Sensor

Reducing the heat sensor's leakiness

It is very important for proper function of CATE to have a very tightly controlled activation of cell lysis. Only if CATE releases the anti-cancer compound upon the external heat signal, an improvement of the control of toxin delivery is possible. Additionally, it is very difficult to introduce the heat inducible protein E expression construct under a leaky promoter, as the basal expression already induces cell death in the successful transformants.

TlpA RBS library creation

A ribosome binding site library was then created to find variants expressing more TlpA. The RedLibs algorithm [4] was used and set to calculate degenerate sequences that produce 12 variants. The variants should all have a rather high expression rate to increase the cytoplasmic amount of TlpA dimers able to repress the promotor. Degenerate primers were used to create the library with a simple PCR and subsequent gel cleanup and transformation.

Figure 5. TlpA RBS Library. A RBS library of the TlpA RBS was calculated with the RedLibs algorithm. It contained 12 different RBS sequences that should exhibit uniformly distributed translation initiation rates. Green colonies have lost the repressor activity of TlpA probably due to very weak TlpA expression. Non-fluorescent colonies might have a strongly repressed gfp, because of a higher amount of TlpA.

TlpA RBS library variant selection

Single colonies were picked and inoculated to a 96 well plate and grown to a stationary phase. Continuing with the 96 well format, the samples were inoculated into a fresh 96 well culture plate and grown to OD600 0.4. At this point the cultures were split and induced at 37 °C and 45 °C for 3 h. Samples were diluted in PBS and the fluorescence measured in a plate reader. The eight variants with the highest fold-change were selected for further experiments.

The best eight TlpA RBS variants were tested for fluorescence induction according to the protocol.

Figure 6. Distribution of GFP expression of the library variants (A) and their fold change (B).

Our results (Figure 6) suggest that different variants of the original RBS were obtained in the library creation. The fold changes vary from 20 to 1200. Most of the new variants yield higher fold changes than the parent variant. The high fold change of H1 is caused by a low leakiness, not by high expression.

Figure 7. The 96 well plate with the four technical replicates of the induction of gfp with the thermosensitive TlpA repressor. On top: 4 wells per column induced for 3 h at 37 °C, bottom: 4 wells per column induced at 45 °C. The positive control did not grow.

The best variants were sequenced and single colonies restreaked for subsequent triplicate measurements. The sequencing results were compared to the predicted translation initiation rates from the RedLibs algorithm:

The variants A9 and D9 share the same sequence and have the highest predicted translation initiation rate (T.I.R.). Interestingly the T.I.R. of H1 is an order of magnitude lower than the others, but still lead to a high fold change.

Phase III Demonstration of the Heat Sensor Function

Triplicate measurements of the best 3 variants

A final experiment was performed according to the protocol with the TlpA RBS library variants H1, A9, C12 and D9 in biological triplicates (Figure 8).

Figure 8. TlpA-regulated GFP expression. A Fluorescence of the variants C12 (C), A9 (A), H1 (H) and the parent variant. B Fold changes of the different variants of the TlpA RBS. The samples were non-induced (37 °C) and induced (45 °C) in biological triplicates.

The thermoswitch was now tight enough to repress the toxic protein E to enable transformant colonies to grow. In the next step we transformed it together with a protein E RBS library containing plasmid, with the aim to find protein E RBS library variants with enough reduced translation initiation rate to survive.

We could improve the leakiness of the TlpA promotor by simply enhancing the translation initiation rate of the repressor protein TlpA. High GFP expression fold changes of up to 200 were obtained.

References

  1. Hurme, R., Berndt, K.D., Namork, E. & Rhen, M. "DNA binding exerted by a bacterial gene regulator with an extensive coiled-coil domain." J. Biol. Chem. 271 (1996): 12626–12631. doi: 10.1074/jbc.271.21.12626
  2. Piraner, Dan I., et al. "Tunable thermal bioswitches for in vivo control of microbial therapeutics."Nature chemical biology 13.1 (2017): 75-80. doi: 10.1038/nchembio.2233
  3. Espah Borujeni, Amin, Anirudh S. Channarasappa, and Howard M. Salis. "Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites." Nucleic acids research 42.4 (2013): 2646-2659. doi: 10.1093/nar/gkt1139
  4. Jeschek, Markus, Daniel Gerngross, and Sven Panke. "Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort." Nature communications 7 (2016). doi: 10.1038/ncomms11163