Difference between revisions of "Team:TUDelft/ResultsTest"

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                 <div id="CopyNumber">
 
                 <div id="CopyNumber">
 
                     <h2>Copy number</h2>
 
                     <h2>Copy number</h2>
                     Copy number of plasmids vary when used in different bacterial hosts and this significantly alters behaviour of parts. To achieve higher predictability of parts across different bacterial species, we aimed to demonstrate independence to copy number of our iFFL systems, as predicted by our <a href="https://2019.igem.org/Team:TUDelft/Model#PlasmidCopyNumber" ><b> modeling </b></a>. Furthermore, to facilitate the development of portable gene expression systems and reduce host dependency, the iFFL system was successfully expressed along with the Universal Bacterial Expression Resource (UBER) system (Kushwaha & Salis, 2015).
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                     Copy number of plasmids vary when used in different bacterial hosts and this significantly alters behaviour of parts. We used a modeling approach to study the behavior of a genetic implementation of an iFFL. This model shows complete independence to copy number of the steady-state gene expression.  
 
                     <ul class="accordion">
 
                     <ul class="accordion">
 
                         <li>
 
                         <li>
                             <a class="toggle " href="javascript:void(0);" ><b>Experimental design</b><span style="float:right;"><b>&#xfe40;</b></span></a>
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                             <a class="toggle " href="javascript:void(0);" ><b>Results -- Copy number independence</b><span style="float:right;"><b>&#xfe40;</b></span></a>
 
                             <ul class="inner accordion">
 
                             <ul class="inner accordion">
                                 <p> To test the independence to copy number we cloned our <a href="http://parts.igem.org/Part:BBa_K2918010" ><b> T7 promoter based optimized iFFL </b></a> and a control  into low and medium copy number backbones (<a href=”https://www.addgene.org/48073/”>  pICH82113
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                                 <p>  
                                    </a>, and <a href=”https://www.addgene.org/48074/”>  pICH82094
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                                    We have modeled the genetic implementation of the iFFL for a wide range of copy numbers. For all of these simulations the steady-state GFP expression was taken.  
                                    </a> respectively) from the MoClo toolkit. </p> <br> <br>
+
                                      
 
+
                                <p>To reduce dependency on host transcriptional machinery, we co-transformed these constructs with the UBER portable T7 expression system. The UBER system expresses T7 RNAP at a stable level as described on our <a href="https://2019.igem.org/Team:TUDelft/Design" ><b> design page </b></a>.
+
                                     Constructs used: </p>
+
 
+
 
                                 <h3>Results</h3>
 
                                 <h3>Results</h3>
                                 <p>We .... </p>
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                                 <p>As can be seen in figure ..., the system is completely independent to copy number. </p>
 
                             </ul>
 
                             </ul>
 
                         </li>
 
                         </li>
 
                     </ul>
 
                     </ul>
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                 </div>
 
                 </div>
 
                 <div id="Portable">
 
                 <div id="Portable">
 
                     <h2>Portable T7 expression system</h2>
 
                     <h2>Portable T7 expression system</h2>
                     Copy number of plasmids vary when used in different bacterial hosts and this significantly alters behaviour of parts. To achieve higher predictability of parts across different bacterial species, we aimed to demonstrate independence to copy number of our iFFL systems, as predicted by our <a href="https://2019.igem.org/Team:TUDelft/Model#PlasmidCopyNumber" ><b> modeling </b></a>. Furthermore, to facilitate the development of portable gene expression systems and reduce host dependency, the iFFL system was successfully expressed along with the Universal Bacterial Expression Resource (UBER) system (Kushwaha & Salis, 2015).
+
                     To facilitate the development of portable gene expression systems and reduce host dependency, the iFFL system was successfully expressed along with the Universal Bacterial Expression Resource (UBER) system (Kushwaha & Salis, 2015).
 
                     <ul class="accordion">
 
                     <ul class="accordion">
 
                         <li>
 
                         <li>
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                     </ul>
 
                     </ul>
 
                 </div>
 
                 </div>
               
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                 <div id="Transcription">
 
                 <div id="Transcription">
 
                     <h2>Transcriptional variation</h2>
 
                     <h2>Transcriptional variation</h2>
                     Behavior of promoters (transcriptional rates) significantly changes across different bacterial hosts <a href=”https://www.ncbi.nlm.nih.gov/pubmed/29061047”> (Yang S et al., 2017) </a>. Hence, promoters either need to be re-characterized for each bacterial hosts or promoters specific to the host need to be identified. Using iFFL, we demonstrated gene expression independent of transcriptional rates  when the transcription rate of both genes (TALE and GOI) maintain the same ratio, as predicted by our <a href="https://2019.igem.org/Team:TUDelft/Model#TranscriptionalVariations" ><b> modeling </b></a>.  
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                     Behavior of promoters (transcriptional rates) significantly changes across different bacterial hosts <a href=”https://www.ncbi.nlm.nih.gov/pubmed/29061047”> (Yang S et al., 2017) </a>. Hence, promoters either need to be re-characterized for each bacterial hosts or promoters specific to the host need to be identified. Using iFFL, we demonstrated gene expression independent of transcriptional rates  when the transcription rate of both genes (TALE and GOI) maintain the same ratio, as predicted by <a href="https://2019.igem.org/Team:TUDelft/Model#TranscriptionalVariations" ><b> modeling </b></a>.  
 
                     <br> <br>
 
                     <br> <br>
  
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                             <a class="toggle " href="javascript:void(0);" ><b>Results -- Independence to promoter strengths</b><span style="float:right;"><b>&#xfe40;</b></span></a>
 
                             <a class="toggle " href="javascript:void(0);" ><b>Results -- Independence to promoter strengths</b><span style="float:right;"><b>&#xfe40;</b></span></a>
 
                             <ul class="inner accordion">
 
                             <ul class="inner accordion">
                                 <p> To validate our model prediction, we designed T7 promoters based iFFL systems with varying promoter strengths. We compared our <a href="http://parts.igem.org/Part:BBa_K2918040">wild-type T7 promoter based iFFL system</a> to a iFFL system based on a T7 promoter variant with 50% strength compared to the wild-type (Ryo Komura et al., 2018) (<a href="http://parts.igem.org/Part:BBa_K2918048">medium T7 based iFFL system</a>). Two negative controls were used: </p>
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                                 <p> To validate our model prediction, we designed T7 promoters based iFFL systems with varying promoter strengths. We compared our <a href="http://parts.igem.org/Part:BBa_K2918040">wild-type T7 promoter based iFFL system</a> (figure 1) to a iFFL system based on a T7 promoter variant with 50% strength compared to the wild-type (figure 2) (Ryo Komura et al., 2018) (<a href="http://parts.igem.org/Part:BBa_K2918048">medium T7 based iFFL system</a>).  
                                 <ol>
+
                                    As a control we express GFP without any TALE (figure 3). </p>
                                    <li>Control 1: T7 based iFFL system without a binding site for TALE protein in the promoter controlling GFP.</li>
+
 
                                    <li>Control 2: A promoter controlling GFP without any TALE expressed.</li>
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                                 <img src="https://static.igem.org/mediawiki/2019/d/d7/T--TUDelft--T7iFFL.png" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
                                 </ol>
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                                    alt="TALE system">
                                 <p>In figure ..., an overview of all the constructs is depicted. </p>
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                                <figcaption class="centermodel"><b>Figure 1</b>: T7 based iFFL. Both genes are controlled by a T7 promoter. </figcaption>
                                [insert images]
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                                <br>
 +
                                <img src="https://static.igem.org/mediawiki/2019/6/6f/T--TUDelft--mediumt7.png" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
 +
                                    alt="TALE system">
 +
                                <figcaption class="centermodel"><b>Figure 2</b>: Medium T7 based iFFL. Both genes are controlled by a medium strength version of a T7 promoter. </figcaption>
 +
                                 <br>
 +
                                 <img src="https://static.igem.org/mediawiki/2019/4/4e/T--TUDelft--notale.png#00a6d6;" class="centermodel"
 +
                                    alt="TALE system">
 +
                                <figcaption class="centermodel"><b>Figure 3</b>: Negative control, T7 promoter controlling GFP. </figcaption>
  
  
 
                                 <br> <br>
 
                                 <br> <br>
                                 <p>We measure GFP fluorescence using flow cytometry. As a reference for background fluorescence we use <i>E. coli</i> BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the <i>E. coli</i> BL21DE(3) cells without any plasmid.</p> <br>
+
                                 <p>The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use <i>E. coli</i> BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the <i>E. coli</i> BL21DE(3) cells without any plasmid.</p> <br>
                                 <p>The median of the background is subtracted from the median of the samples. </p>
+
                                 <p>The median of the background is subtracted from the median of the samples and the resulting values are plotted (figure ...). </p>
 +
 
  
 
                                 <h3>Results</h3>
 
                                 <h3>Results</h3>
                                 <p>Unexpectedly low fluorescence was observed for control 1. However, when comparing the unrepressed iFFL system forward and side-scatter to <i>E. coli</i> BL21DE(3) cells without any plasmid they were smaller in size and had. The difference in cell morphology suggests that over expression of TALE and GFP could be burdensome to the cells. Hence, for further data analysis, only control 2 was used.</p> <br>
+
                                 <p>
                                <img src="https://static.igem.org/mediawiki/2019/5/5c/T--TUDelft--promoter_variation_wetlab_model.svg" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
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                                    <img src="https://static.igem.org/mediawiki/2019/5/5c/T--TUDelft--promoter_variation_wetlab_model.svg" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
                                    alt="TALE system">
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                                        alt="TALE system">
                                <figcaption class="centermodel"><b>Figure 6</b>: Steady-state GFP fluorescence measurement of promoter variation using flow cytometry. The graph depicts T7 and medium T7 iFFL systems, expected to give the same fluorescence according to the model. As a control, GFP under control of an unrepressed T7 promoter was used. </figcaption>
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                                    <figcaption class="centermodel"><b>Figure 6</b>: Steady-state GFP fluorescence measurement of promoter variation using flow cytometry. The graph depicts T7 and medium T7 iFFL systems, expected to give the same fluorescence according to the model. As a control, GFP under control of an unrepressed T7 promoter was used. </figcaption>
                                <br>
+
                                    <br>
                                 <p>In figure ..., we can clearly see that the stabilized systems are very close in fluorescence while the unrepressed system is higher, as predicted.</p>
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                                 <p>In figure ..., similar GFP fluorescence can be observed for the iFFL systems while the unrepressed control system shows high fluorescence. This suggests successful insulation of gene expression from change in promoter strengths.</p>
 
                             </ul>
 
                             </ul>
  
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                         <ul class="inner accordion">
 
                         <ul class="inner accordion">
 
                             <p>  
 
                             <p>  
                                 Aside from transcriptional variation through changing the promoters in the construct, we also tested the effect of different concentrations of IPTG. In unrepressed systems the expression of the GOI increases when more IPTG concentrations are increased.  
+
                                 Aside from testing gene expression independent of transcriptional variation by using promoters of different strengths, the effect of different concentrations of IPTG on the iFFL loop was tested. Change in IPTG concentrations, changes in-vivo concentrations of T7 RNAP and this contributes to variations in transcriptional rates.
                                Since both the promoter of the TALE and the promoter of the GFP are variants of T7 they will both increase in the same way and should result in the same level of expression, as predicted by <a href="https://2019.igem.org/Team:TUDelft/Model#TranscriptionalVariations"> modeling</a>. As a control we expressed GFP under the control of our <a href="http://parts.igem.org/Part:BBa_K2918010">T7sp1 promoter</a> without any expression of TALE protein.                          
+
                                In unrepressed systems, the expression of the GOI is a function of IPTG concentrations. However, in iFFL systems, since the transcriptional rates of TALE and GFP are under control of T7 promoters, similar GOI expression is expected (figure 1).  As a control we expressed GFP under the control of T7sp1 promoter was used (figure 2).
 +
                                <img src="https://static.igem.org/mediawiki/2019/6/6b/T--TUDelft--weakt7.png" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
 +
                                    alt="TALE system">
 +
                                <figcaption class="centermodel"><b>Figure 1</b>: Optimized T7 based iFFL. TALE is under cotntrol of weak T7 promtoer. GFP is controlled by a T7 promoter. </figcaption>
 +
                                <br>
 +
                               
 +
                                <img src="https://static.igem.org/mediawiki/2019/4/4e/T--TUDelft--notale.png#00a6d6;" class="centermodel"
 +
                                    alt="TALE system">
 +
                                <figcaption class="centermodel"><b>Figure 2</b>: Negative control, T7 promoter controlling GFP. </figcaption>
 +
 
 
                             </p>
 
                             </p>
  
                             <p>We measure GFP fluorescence using flow cytometry. As a reference for background fluorescence we use <i>E. coli</i> BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the <i>E. coli</i> BL21DE(3) cells without any plasmid. </p> <br>
+
                             <p>The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use <i>E. coli</i> BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the <i>E. coli</i> BL21DE(3) cells without any plasmid. </p> <br>
 
                             <p>The median of the background is subtracted from the samples and are compared. </p>
 
                             <p>The median of the background is subtracted from the samples and are compared. </p>
  
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                             <h3>Results</h3>
 
                             <h3>Results</h3>
 
                             <p>
 
                             <p>
                             <p> Figure ... clearly shows a strong increase in fluorescence when no repression is used. However, when our iFFL is implemented the levels of GFP are constant. </p>
+
                             <p> Figure ... the GFP fluorescence of the unrepressed control changes with changing concentrations of IPTG while the iFFL system shows the same GFP expression across different IPTG concentrations. Thus, the iFFL system has been shown to insulate gene expression against changes in transcription rates (achieved by varying IPTG concentrations). 
 +
. </p>
 
                             <img src="https://static.igem.org/mediawiki/2019/a/a9/T--TUDelft--IPTGtitration.svg" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
 
                             <img src="https://static.igem.org/mediawiki/2019/a/a9/T--TUDelft--IPTGtitration.svg" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
 
                                 alt="TALE system">
 
                                 alt="TALE system">
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                 </ul>
 
                 </ul>
 
                 <h3>Conclusion</h3>
 
                 <h3>Conclusion</h3>
                    <p>Results above indicate successful implementation of the iFFL system to insulate from transcriptional variations. Transcriptional variations were achieved by using T7 promoters of different strengths and by induction at different IPTG concentrations. Furthermore, we demonstrated the tunability of the iFFL system to achieve different levels of gene expression. As predicted by our model, we achieved gene expression independent of changes in transcriptional rates by maintaining constant ratios of transcriptional rates of TALE and GFP genes.</p>
+
                <p>Results above indicate successful implementation of the iFFL system to insulate from transcriptional variations. Transcriptional variations were achieved by using T7 promoters of different strengths and by induction at different IPTG concentrations. Furthermore, we demonstrated the tunability of the iFFL system to achieve different levels of gene expression. As predicted by our model, we achieved gene expression independent of changes in transcriptional rates by maintaining constant ratios of transcriptional rates of TALE and GFP genes.</p>
 
                 <div id="Translation">
 
                 <div id="Translation">
 
                     <h2>Translational variation</h2>
 
                     <h2>Translational variation</h2>
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                                 Broad host range promoter (P<sub>BHR</sub>) was designed by combining the conserved -10 and -35 regions from <i> E.coli</i> and <i> B.subtilis </i> <cite><a href=""> (Yang S et al., 2018) </a></cite> and the promoter was engineered to contain a binding site for TALE repressor (P<sub>BHRsp1</sub>). Using the P<sub>BHR</sub> and P<sub>BHRsp1</sub>, we constructed an iFFL genetic circuit driving GFP expression.  
 
                                 Broad host range promoter (P<sub>BHR</sub>) was designed by combining the conserved -10 and -35 regions from <i> E.coli</i> and <i> B.subtilis </i> <cite><a href=""> (Yang S et al., 2018) </a></cite> and the promoter was engineered to contain a binding site for TALE repressor (P<sub>BHRsp1</sub>). Using the P<sub>BHR</sub> and P<sub>BHRsp1</sub>, we constructed an iFFL genetic circuit driving GFP expression.  
 
                                 The circuit was transformed in <i>E.coli</i> and <i> P.putida</i> and, output fluorescence was measured by flow cytometry during logarithmic growth phase. To correct for background fluorescence, <i>E.coli</i> and <i> P.putida</i>  without plasmids were used as blanks. GFP under the control of P<sub>BHRsp1</sub> was used as a positive (unrepressed) control. As the cell morphologies of <i>E.coli</i> and <i>P.putida</i> are different they cannot be compared directly, gating was based on the most dense regions in the scatter plot for each organism. In order to compare the GFP expression levels between each organism, the background fluorescence for each organism was subtracted by its respective blank .
 
                                 The circuit was transformed in <i>E.coli</i> and <i> P.putida</i> and, output fluorescence was measured by flow cytometry during logarithmic growth phase. To correct for background fluorescence, <i>E.coli</i> and <i> P.putida</i>  without plasmids were used as blanks. GFP under the control of P<sub>BHRsp1</sub> was used as a positive (unrepressed) control. As the cell morphologies of <i>E.coli</i> and <i>P.putida</i> are different they cannot be compared directly, gating was based on the most dense regions in the scatter plot for each organism. In order to compare the GFP expression levels between each organism, the background fluorescence for each organism was subtracted by its respective blank .
                                </p>
+
                            </p>
 
                             <h3>Results</h3>
 
                             <h3>Results</h3>
 
                             <p>
 
                             <p>
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                             <figcaption class="centermodel"><b>Figure ...</b>: Steady-state GOI production while translation rates of both TALE and GOI are changed. The lines indicate the constant rate of the translation rates. </figcaption>
 
                             <figcaption class="centermodel"><b>Figure ...</b>: Steady-state GOI production while translation rates of both TALE and GOI are changed. The lines indicate the constant rate of the translation rates. </figcaption>
 
                             <br>
 
                             <br>
                                <p>
+
                            <p>
 
                                 In figure …., the median fluorescence of the gated populations is plotted. Significantly large difference in expression levels is observed between the unrepressed controls and the broad host range promoter based iFFL systems in <i>E.coli</i> and <i>P.putida</i>. However, similar levels of expression were observed from iFFL systems in <i> E.coli</i> and <i>P.putida </i>. The difference in expression levels between the unrepressed circuit is significantly higher than the difference in expression levels between the iFFL system (578530 and 2351.2 respectively).
 
                                 In figure …., the median fluorescence of the gated populations is plotted. Significantly large difference in expression levels is observed between the unrepressed controls and the broad host range promoter based iFFL systems in <i>E.coli</i> and <i>P.putida</i>. However, similar levels of expression were observed from iFFL systems in <i> E.coli</i> and <i>P.putida </i>. The difference in expression levels between the unrepressed circuit is significantly higher than the difference in expression levels between the iFFL system (578530 and 2351.2 respectively).
  

Revision as of 06:24, 21 October 2019

Sci-Phi 29

Parts Construction

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Part Characterization

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Orthogonalibity

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Orthogonal Replication

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Toxicity Assay

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Controllability

Overview

The behavior of genetic parts and circuits in different bacterial species is unpredictable as it is influenced by host-dependent variations (Liu et al., 2018) . Interspecies variations (Adams, 2016), such as copy number of plasmids (De Gelder, Ponciano, Joyce, & Top, 2007), transcription rates of promoters (Meysman, et al., 2014), translation initiation rates of ribosome binding sites (RBS) (Omotajo, Tate, Cho, & Choudhary, 2015) and the codon usage of coding sequences (Sharp, Bailes, Grocock, Peden, & Sockett, 2005) influence the functioning of genetic parts. We implemented a unique control system motif (incoherent feed forward loop) into a genetic circuit to achieve gene expression independent of these variables. Furthermore, the iFFL loop was demonstrated to show similar expression across E.coli and P.putida .

Construction

We modeled the genetic implementation of the iFFL loop and varied the identified variables. Based on the results from the modeling, we made design choices.

  • Results
      We learned through the implementation of the model that constant transcriptional and translational rates of TALE and GFP needs to be maintained to achieve gene expression independent of transcriptional and translational variations respectively. TALE system
      Figure 5: Steady-state GFP production while transcription rates of both TALE and GOI are changed (aT/aG = constant). The lines indicate constant ratio of transcription rates

      To achieve constant ratios of transcriptional rates of TALE and GFP, we used the orthogonal T7 promoter and its variants to express TALE and GFP genes. The following constructs were successfully cloned by Golden Gate Assembly. To achieve constant ratios of translational rates for TALE and GFP, we used the same ribosome binding sites for the expression of TALE and GFP. Furthermore, to demonstrate expression independent of translational rates, we switched constructed circuits with different RBSs. When transcriptional units are placed in series, leaky expression of the gene in the second transcriptional unit can occur. This is due to the efficiency of the terminator of the first transcriptional unit. The model shows that leaky expression significantly affects the ability of the iFFL system to adapt to changes in copy number.

      TALE system
      Figure 9: Comparison of a perfect terminator and a leaky terminator on the expression level at different plasmid copy number.
      We therefore designed our genetic circuit such that the transcriptional units of TALE and GFP are oriented in opposite directions.

Copy number

Copy number of plasmids vary when used in different bacterial hosts and this significantly alters behaviour of parts. We used a modeling approach to study the behavior of a genetic implementation of an iFFL. This model shows complete independence to copy number of the steady-state gene expression.
  • Results -- Copy number independence

      We have modeled the genetic implementation of the iFFL for a wide range of copy numbers. For all of these simulations the steady-state GFP expression was taken.

      Results

      As can be seen in figure ..., the system is completely independent to copy number.

Portable T7 expression system

To facilitate the development of portable gene expression systems and reduce host dependency, the iFFL system was successfully expressed along with the Universal Bacterial Expression Resource (UBER) system (Kushwaha & Salis, 2015).
  • Experimental design

      To test the independence to copy number we cloned our T7 promoter based optimized iFFL and a control into low and medium copy number backbones ( pICH82113 , and pICH82094 respectively) from the MoClo toolkit.



      To reduce dependency on host transcriptional machinery, we co-transformed these constructs with the UBER portable T7 expression system. The UBER system expresses T7 RNAP at a stable level as described on our design page . Constructs used:

      Results

      We ....

Transcriptional variation

Behavior of promoters (transcriptional rates) significantly changes across different bacterial hosts (Yang S et al., 2017) . Hence, promoters either need to be re-characterized for each bacterial hosts or promoters specific to the host need to be identified. Using iFFL, we demonstrated gene expression independent of transcriptional rates when the transcription rate of both genes (TALE and GOI) maintain the same ratio, as predicted by modeling .

  • Results -- Independence to promoter strengths

      To validate our model prediction, we designed T7 promoters based iFFL systems with varying promoter strengths. We compared our wild-type T7 promoter based iFFL system (figure 1) to a iFFL system based on a T7 promoter variant with 50% strength compared to the wild-type (figure 2) (Ryo Komura et al., 2018) (medium T7 based iFFL system). As a control we express GFP without any TALE (figure 3).

      TALE system
      Figure 1: T7 based iFFL. Both genes are controlled by a T7 promoter.

      TALE system
      Figure 2: Medium T7 based iFFL. Both genes are controlled by a medium strength version of a T7 promoter.

      TALE system
      Figure 3: Negative control, T7 promoter controlling GFP.


      The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the median of the samples and the resulting values are plotted (figure ...).

      Results

      TALE system

      Figure 6: Steady-state GFP fluorescence measurement of promoter variation using flow cytometry. The graph depicts T7 and medium T7 iFFL systems, expected to give the same fluorescence according to the model. As a control, GFP under control of an unrepressed T7 promoter was used.

      In figure ..., similar GFP fluorescence can be observed for the iFFL systems while the unrepressed control system shows high fluorescence. This suggests successful insulation of gene expression from change in promoter strengths.

  • Results -- Independence to IPTG concentration

      Aside from testing gene expression independent of transcriptional variation by using promoters of different strengths, the effect of different concentrations of IPTG on the iFFL loop was tested. Change in IPTG concentrations, changes in-vivo concentrations of T7 RNAP and this contributes to variations in transcriptional rates. In unrepressed systems, the expression of the GOI is a function of IPTG concentrations. However, in iFFL systems, since the transcriptional rates of TALE and GFP are under control of T7 promoters, similar GOI expression is expected (figure 1). As a control we expressed GFP under the control of T7sp1 promoter was used (figure 2). TALE system

      Figure 1: Optimized T7 based iFFL. TALE is under cotntrol of weak T7 promtoer. GFP is controlled by a T7 promoter.

      TALE system
      Figure 2: Negative control, T7 promoter controlling GFP.

      The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the samples and are compared.

      Results

      Figure ... the GFP fluorescence of the unrepressed control changes with changing concentrations of IPTG while the iFFL system shows the same GFP expression across different IPTG concentrations. Thus, the iFFL system has been shown to insulate gene expression against changes in transcription rates (achieved by varying IPTG concentrations). .

      TALE system
      Figure ...: Steady-state GFP fluorescence measurement of IPTG titration using FACS. The graph depicts a T7 iFFL system induced using different levels of IPTG, which according to the model should give the same result. As a control GFP under control of an unrepressed T7 promoter was used.

  • Results -- Tunability

      The predictions made by modeling not only tell us that we can maintain the same level of gene expression but also that we can easily tune the expression levels by changing one of the promoters. By changing one of the promoters to another variant of T7 we can expect a different level of expression, while at the same time expect it to behave similarly when transferred between organisms. Through the use of T7 variants we could achieve wide ranges of expression levels, which can be used to establish complex genetic circuits, while also expecting it to work similarly in different biological contexts.

      We tested the prediction by changing the promoter controlling the TALE protein to a variant of T7 which has been shown to be about 10% in strength compared to the wild-type (Ryo Komura et al., 2018). According to the model the expression should increase.

      We measure GFP fluorescence using flow cytometry. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the samples and are compared.

      Results

      Figure ... clearly shows higher fluorescence when a lower T7 promoter version is used to express the TALE protein in comparison to our systems with the same ratio in promoter strengths for both genes.

      TALE system
      Figure ...: Steady-state GFP fluorescence measurement of E. coli BL21DE(3) cells expressing our iFFL systems. The graph depicts a different T7 iFFL systems, one with both promoters T7, one with both medium strength and one where the promoter controlling of the TALE is weak. As a control GFP under control of an unrepressed T7 promoter was used.

Conclusion

Results above indicate successful implementation of the iFFL system to insulate from transcriptional variations. Transcriptional variations were achieved by using T7 promoters of different strengths and by induction at different IPTG concentrations. Furthermore, we demonstrated the tunability of the iFFL system to achieve different levels of gene expression. As predicted by our model, we achieved gene expression independent of changes in transcriptional rates by maintaining constant ratios of transcriptional rates of TALE and GFP genes.

Translational variation

In order to see the effect of translational variation on the expression levels of the gene of interest (GOI) we modeled our system for a range of translational rates for both genes (TALE and GOI).
  • Results

      As can be seen in figure … the steady-state expression levels of GFP remain the same when the translation rates are kept constant.

Conclusion

According to our model solution we can maintain the same level of GOI expression when both translation rates remain constant. We therefore designed our system to contain the same RBS in front of both TALE and the GOI.

Expression across different organisms

To achieve similar gene expression across different organisms the iFFL system needs to be robust to changes in copy number, transcriptional and translational rates. We experimentally demonstrated gene expression independent of transcriptional variations and through modelling showed adaptation variations in copy number and translational variation of our iFFL system. Through the implementation of the iFFL loop using engineered broad host range promoters, we successfully demonstrated similar GFP expression across E.coli and P.putida. Thereby demonstrating gene expression insulated from variations associated to microbial hosts.

  • Results -- Expression across organisms

      Broad host range promoter (PBHR) was designed by combining the conserved -10 and -35 regions from E.coli and B.subtilis (Yang S et al., 2018) and the promoter was engineered to contain a binding site for TALE repressor (PBHRsp1). Using the PBHR and PBHRsp1, we constructed an iFFL genetic circuit driving GFP expression. The circuit was transformed in E.coli and P.putida and, output fluorescence was measured by flow cytometry during logarithmic growth phase. To correct for background fluorescence, E.coli and P.putida without plasmids were used as blanks. GFP under the control of PBHRsp1 was used as a positive (unrepressed) control. As the cell morphologies of E.coli and P.putida are different they cannot be compared directly, gating was based on the most dense regions in the scatter plot for each organism. In order to compare the GFP expression levels between each organism, the background fluorescence for each organism was subtracted by its respective blank .

      Results

      Figure ... clearly shows higher fluorescence when a lower T7 promoter version is used to express the TALE protein in comparison to our systems with the same ratio in promoter strengths for both genes.

      TALE system
      Figure ...: Steady-state GOI production while translation rates of both TALE and GOI are changed. The lines indicate the constant rate of the translation rates.

      In figure …., the median fluorescence of the gated populations is plotted. Significantly large difference in expression levels is observed between the unrepressed controls and the broad host range promoter based iFFL systems in E.coli and P.putida. However, similar levels of expression were observed from iFFL systems in E.coli and P.putida . The difference in expression levels between the unrepressed circuit is significantly higher than the difference in expression levels between the iFFL system (578530 and 2351.2 respectively).

Conclusion

The implementation of the iFFL significantly decreased the differences in expression levels between organisms. Our system sets the basis for controllability across organisms.

Cross species codon harmonization


Future Plan

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References