Difference between revisions of "Part:BBa K2918040"

(Characterization)
(Characterization)
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   <p> We have characterized the behavior of this system under the induction of different concentrations of IPTG. According to our <html><body><a href="http://2019.igem.org/Team:TUDelft/Model">model</a></body></html> this system always yields the same gene of interest (GOI) expression levels when the transcription rate of both genes (TALE and GOI) is changed in the same ratio as can be seen in figure 3. </p><br>
 
   <p> We have characterized the behavior of this system under the induction of different concentrations of IPTG. According to our <html><body><a href="http://2019.igem.org/Team:TUDelft/Model">model</a></body></html> this system always yields the same gene of interest (GOI) expression levels when the transcription rate of both genes (TALE and GOI) is changed in the same ratio as can be seen in figure 3. </p><br>
  
<html><body>     <img src="https://2019.igem.org/wiki/images/f/f8/T--TUDelft--transcriptionvariation.svg" style="width:85%;border:1px solid #00a6d6;" class="centermodel"
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<div><ul>  
      alt="TALE system">
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<center>
    <figcaption class="centermodel"><b>Figure 3</b>: Steady-state GFP production while transcription rates of both TALE and GOI are changed. The lines indicate constant ratio of transcription rates </figcaption></body></html>
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  <li style="display: inline-block;"> [[File:T--TUDelft--transcriptionvariation.svg|thumb|none|550px|<b>Figure 3</b>: Steady-state GFP production while transcription rates of both TALE and GOI are changed. The lines indicate constant ratio of transcription rates]] </li>
 
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</center>
<br>
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    </ul></div>
  
 
<p>In order to measure steady-state GFP levels we measured fluorescence in log-phase using flow cytometry. </p>
 
<p>In order to measure steady-state GFP levels we measured fluorescence in log-phase using flow cytometry. </p>
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In the measurement, <i>E. coli BL21</i> cells without a plasmid were used as a reference for background fluorescence. As a control, <html><body><a href="https://parts.igem.org/Part:BBa_K2918037"> harmonized eGFP </a></body></html> driven by the same promoter and RBS was used. The gating for flow cytometry was determined by eye by selecting the densest region of  <i>E. coli TOP10</i>. Furthermore, the fluorescence histogram was gated to discern between cells that were 'on' and 'off', as in expressing fluorescence or not. Only cells of similar forward and side scatter were compared.  The median fluorescence intensity of the blank is subtracted from the fluorescence intensity of the samples to correct for autofluorescence. In figure 6 we plot the corrected fluorescence of the samples. Figures 7 and 8 show the gating and the fluorescence histogram of each sample for the negative control. Figures 9 and 10 show the same but for our optimized stabilized iFFL systems. </p>
 
In the measurement, <i>E. coli BL21</i> cells without a plasmid were used as a reference for background fluorescence. As a control, <html><body><a href="https://parts.igem.org/Part:BBa_K2918037"> harmonized eGFP </a></body></html> driven by the same promoter and RBS was used. The gating for flow cytometry was determined by eye by selecting the densest region of  <i>E. coli TOP10</i>. Furthermore, the fluorescence histogram was gated to discern between cells that were 'on' and 'off', as in expressing fluorescence or not. Only cells of similar forward and side scatter were compared.  The median fluorescence intensity of the blank is subtracted from the fluorescence intensity of the samples to correct for autofluorescence. In figure 6 we plot the corrected fluorescence of the samples. Figures 7 and 8 show the gating and the fluorescence histogram of each sample for the negative control. Figures 9 and 10 show the same but for our optimized stabilized iFFL systems. </p>
  
<html><body><img src="https://2019.igem.org/wiki/images/a/a9/T--TUDelft--IPTGtitration.svg" style="width:60%;border:1px solid #00a6d6;" class="centermodel"
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        alt="TALE system">
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<div><ul>  
          <figcaption class="centermodel"><b>Figure 6</b>: Steady-state GFP fluorescence measurement of promoter variation using FACS. The graph depicts T7 and 0.5 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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<center>
</body></html>
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  <li style="display: inline-block;"> [[File:T--TUDelft--IPTGtitration.svg|thumb|none|550px|<b>Figure 6</b>: Steady-state GFP fluorescence measurement of promoter variation using FACS. The graph depicts T7 and 0.5 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.]] </li>
<br>
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</center>
<br>
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    </ul></div>
 +
 
  
 
<p>Figure 6 shows that our optimized TALE system results in the same expression level independent of IPTG concentration, while in the unrepressed T7 system the expression increases with increased IPTG induction.  
 
<p>Figure 6 shows that our optimized TALE system results in the same expression level independent of IPTG concentration, while in the unrepressed T7 system the expression increases with increased IPTG induction.  
 
<br> <br>
 
<br> <br>
  
<html><body><img src = "https://static.igem.org/mediawiki/parts/8/8a/T--TUDelft--L1etascatter.png" alt="Modeling" style="width:60%";></body></html>
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<div><ul>  
<html><body><figcaption><br><b>Figure 7: Scatter plot of forward and side scatter of <i>E. coli BL21</i> cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6. </b></figcaption></body></html>
+
<center>
<br>
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  <li style="display: inline-block;"> [[File:T--TUDelft--L1etascatter.png|thumb|none|550px|<b>Figure 7:</b> Scatter plot of forward and side scatter of <i>E. coli BL21</i> cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6.]] </li>
 +
</center>
 +
    </ul></div>
  
<html><body><img src = "https://static.igem.org/mediawiki/parts/b/b2/T--TUDelft--L1etafluorescence.png" alt="Modeling" style="width:60%";></body></html>
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<div><ul>  
<html><body><figcaption><br><b>Figure 8: Raw fluorescence values of our negative control. Black is<i>E. coli BL21</i>cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction. </b></figcaption></body></html>
+
<center>
 +
  <li style="display: inline-block;"> [[File:T--TUDelft--L1etafluorescence.png|thumb|none|550px|<b>Figure 8:</b> Raw fluorescence values of our negative control. Black is<i>E. coli BL21</i>cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction. ]] </li>
 +
</center>
 +
    </ul></div>
  
<br>
+
<div><ul>
 +
<center>
 +
  <li style="display: inline-block;"> [[File:T--TUDelft--LM23scatter.png|thumb|none|550px|<b>Figure 9:</b> Scatter plot of forward and side scatter of <i>E. coli BL21</i> cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6. </b>]] </li>
 +
</center>
 +
    </ul></div>
  
<html><body><img src = "https://static.igem.org/mediawiki/parts/8/8f/T--TUDelft--LM23scatter.png" alt="Modeling" style="width:60%";></body></html>
+
<div><ul>  
<html><body><figcaption><br><b>Figure 9: Scatter plot of forward and side scatter of <i>E. coli BL21</i> cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6. </b></figcaption></body></html>
+
<center>
<br>
+
  <li style="display: inline-block;"> [[File:T--TUDelft--LM23fluorescence.png|thumb|none|550px|<b>Figure 10:</b> Raw fluorescence values of our stabilized system. Black is<i>E. coli BL21</i>cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction.]] </li>
 
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</center>
<html><body><img src = "https://static.igem.org/mediawiki/parts/b/bc/T--TUDelft--LM23fluorescence.png" alt="Modeling" style="width:60%";></body></html>
+
    </ul></div>
<html><body><figcaption><br><b>Figure 10: Raw fluorescence values of our stabilized system. Black is<i>E. coli BL21</i>cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction. </b></figcaption></body></html>
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<br>
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===References===
 
===References===

Revision as of 23:22, 19 October 2019

T7 promoter based optimized iFFL

Genetic implementation of an incoherent feed-forward loop (iFFL) in which a stabilized 0.1 T7 promoter is controlling GFP expression.

Sequence and Features


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal XhoI site found at 250
    Illegal XhoI site found at 3335
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
    Illegal AgeI site found at 1277
  • 1000
    COMPATIBLE WITH RFC[1000]

The two transcriptional units in this composite part are oriented outwards.

Usage and Biology

An Incoherent feed-forward loop (iFFL) is a unique control systems motif where the output signal is robust to changes in the input signal. This is achieved by the introduction of a repressor.

  • Figure 1: Overview of incoherent feed-forward loop

iFFL can be applied to genetic circuits to achieve expression independent from copy number, transcriptional and translational rates. To implement the iFFL in a genetic circuit, TALE proteins can be used. These proteins consist of repeats where 12th and 13th amino acids can vary, these are called the repeat variable diresidue (RVD). RVDs have been shown to bind to DNA in a simple one-to-one binding code (Doyle, Stoddard et al., 2013). The direct correspondence between amino acids allows scientists to engineer these repeat regions to target any sequence they want. In our system, we used the TALE protein as a repressor by engineering promoters to contain the binding site of this specific TALE protein (0.1 T7sp1 promoter, 0.5 T7sp1 promoter and PBHRsp1 promoter).
In our genetic circuit, a unrepressed promoter controls the expression of TALE protein while the promoters with the TALE binding sites drive expression of GFP.

  • Figure 2: Overview of how the TALE proteins represses GFP

When transcriptional units are placed in series due to low effieciency of terminators, leaky expression of the gene in the neighbouring transcriptonal unit can occur. This significantly influences the behavior of the iFFL genetic circuit (Segall-Shapiro et al., 2018). Hence, the transcriptional units in the circuit are oriented outward to achieve insulation from influence of the neighboring transcriptional unit.

An interesting application of the iFFL is to achieve controllable gene expression across different bacterial species. Gene expression in different bacterial contexts is influenced by changes in copy number, transcriptional and translational rates. To achieve expression robust to changes in transcriptional and tranlational rates, the ratio of transcriptional and translational rates of GFP and repressor need to be constant. This can be achieved by using orthogonal T7 promoter and its variants (T7 promoter, 0.5 T7 promoter, 0.1 T7 promoter, 0.5 T7sp1 promoter and T7sp1 promoter ).

Apart from being able to achieve stable gene expression across different bacterial species, it is necessary to attain different levels of gene expression. The T7 promoter based optimized iFFL can be used to obtain higher levels of gene of interest (GFP) expression as the expression of TALE is driven by a lower strength promoter (0.1 T7 promoter) compared to the promoter (0.5 T7sp1 promoter) driving GFP expression.

Strain Construction

The construct was assembled by golden gate assembly based modular cloning system. First, the individual transcriptional units were cloned into level 1 destination vectors pICH47761 and pICH47822 by BpiI based golden gate assembly. The multi-transcriptional unit construct was assembled by a BsaI based golden gate. The assembly was a one-pot restriction-ligation reaction where the individual level 1 constructs were added along with the destination vector pICH48055. The correct clone was distinguished by blue-white screening and the construct was confirmed by sequencing. The cloning protocol can be found in the MoClo section below.

Modular Cloning

Modular Cloning (MoClo) is a system which allows for efficient one pot assembly of multiple DNA fragments. The MoClo system consists of Type IIS restriction enzymes that cleave DNA 4 to 8 base pairs away from the recognition sites. Cleavage outside of the recognition site allows for customization of the overhangs generated. The MoClo system is hierarchical. First, basic parts (promoters, UTRs, CDS and terminators) are assembled in level 0 plasmids in the kit. In a single reaction, the individual parts can be assembled into vectors containing transcriptional units (level 1). Furthermore, MoClo allows for directional assembly of multiple transcriptional units. Successful assembly of constructs using MoClo can be confirmed by visual readouts (blue/white or red/white screening). For the protocol, you can find it here.


Note: The basic parts sequences of the Sci-Phi 29 collection in the registry contain only the part sequence and therefore contain no overhangs or restriction sites. For synthesizing MoClo compatible parts, refer to table 2. The complete sequence of our parts including backbone can be found here.


Table 1: Overview of different level in MoClo

Level Basic/Composite Type Enzyme
Level 0 Basic Promoters, 5’ UTR, CDS and terminators BpiI
Level 1 Composite Transcriptional units BsaI
Level 2/M/P Composite Multiple transcriptional units BpiI

For synthesizing basic parts, the part of interest should be flanked by a BpiI site and its specific type overhang. These parts can then be cloned into the respective level 0 MoClo parts. For level 1, where individual transcriptional units are cloned, the overhangs come from the backbone you choose. The restriction sites for level 1 are BsaI. However, any type IIS restriction enzyme could be used.


Table 2: Type specific overhangs and backbones for MoClo. Green indicates the restriction enzyme recognition site. Blue indicates the specific overhangs for the basic parts

Basic Part Sequence 5' End Sequence 3' End Level 0 backbone
Promoter NNNN GAAGAC NN GGAG TACT NN GTCTTC NNNN pICH41233
5’ UTR NNNN GAAGAC NN TACT AATG NN GTCTTC NNNN pICH41246
CDS NNNN GAAGAC NN AATG GCTT NN GTCTTC NNNN pICH41308
Terminator NNNN GAAGAC NN GCTT CGCT NN GTCTTC NNNN pICH41276

Characterization

We have characterized the behavior of this system under the induction of different concentrations of IPTG. According to our model this system always yields the same gene of interest (GOI) expression levels when the transcription rate of both genes (TALE and GOI) is changed in the same ratio as can be seen in figure 3.


In order to measure steady-state GFP levels we measured fluorescence in log-phase using flow cytometry.

The protocol for preparation of samples for the flow cytometry assay is as follows:

  1. Samples were grown overnight
  2. Overnight cultures were diluted to OD = 0.01 into 1 mL, and grow for 2 hours on 37 degrees 250 rpm shaking in 2 mL Eppendorf tubes.
  3. Overnight cultures were diluted 1:100 into 5 mL, and grow for 4 hours on 37 degrees 250 rpm shaking in 50 mL eppendorf tubes. Induce with IPTG.
  4. Samples were kept at 4 degrees for 1 hour

In the measurement, E. coli BL21 cells without a plasmid were used as a reference for background fluorescence. As a control, harmonized eGFP driven by the same promoter and RBS was used. The gating for flow cytometry was determined by eye by selecting the densest region of E. coli TOP10. Furthermore, the fluorescence histogram was gated to discern between cells that were 'on' and 'off', as in expressing fluorescence or not. Only cells of similar forward and side scatter were compared. The median fluorescence intensity of the blank is subtracted from the fluorescence intensity of the samples to correct for autofluorescence. In figure 6 we plot the corrected fluorescence of the samples. Figures 7 and 8 show the gating and the fluorescence histogram of each sample for the negative control. Figures 9 and 10 show the same but for our optimized stabilized iFFL systems. </p>


  • File:T--TUDelft--IPTGtitration.svg
    Figure 6: Steady-state GFP fluorescence measurement of promoter variation using FACS. The graph depicts T7 and 0.5 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.


Figure 6 shows that our optimized TALE system results in the same expression level independent of IPTG concentration, while in the unrepressed T7 system the expression increases with increased IPTG induction.

  • Figure 7: Scatter plot of forward and side scatter of E. coli BL21 cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6.
  • Figure 8: Raw fluorescence values of our negative control. Black isE. coli BL21cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction.
  • Figure 9: Scatter plot of forward and side scatter of E. coli BL21 cells without a plasmid. The region selected is the gating we considered to obtain the values depicted in figure 6. </b>
  • </center>

  • Figure 10: Raw fluorescence values of our stabilized system. Black isE. coli BL21cells without a plasmid. Green is 0 mM IPTG, blue is 0.1 mM, pink is 0.5 and purple is 1 mM IPTG induction.

References