Difference between revisions of "Part:BBa K4583034"

 
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==Usage and Biology==
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Many production processes using microorganisms face the dilemma of conflicting production products and key metabolic pathways. This means that simply introducing product-synthesising genes into engineered bacteria can greatly affect the growth of the microorganism, leading to a situation where production is too low. There are a number of current solutions to this problem. For example, metabolic engineering can regulate metabolic flow using methods such as gene knockdown, promoter replacement, etc. These static strategies are effective for productivity improvement, but are not responsive to changes in the cell or environment. Dynamic control is a favourable solution for the conditional knockdown of essential genes and balances the flow in the metabolic pathway.
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 +
The pathway of PHB synthetsis is conflict with TCA cycle. Both TCA cycle and PHB production pathways use acetyl-coA as raw material, so if only the PHB production gene circuit is simply added to the engineered bacteria, the growth of the bacteria will be greatly affected, and the final result is low PHB production. Quorum sensing system can automatically sense cell density to regulate downstream genetic on/off. It is independent of metabolic pathways and do not need exogenous inducers, which make it a perfect tool to solve this problem. PHB are a form of carbon storage by bacteria. PHB products take up most of the space inside the cell, but will not be released from the cell. The method of mechanical crushing or chemical solvent extraction used in traditional industry is not only expensive, but also brings great pressure to the environment, so we hope to design an auto-lysis system with specific expression time.
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<html>
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<figure>
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  <img src="https://static.igem.wiki/teams/4583/wiki/tca.png"width="600" height="320">
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  <figcaption><b>Fig. 1 </b>. The pathway of PHB synthetsis is conflict with TCA cycle. </figcaption>
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</figure>
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</html>
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This part is about PHB Production Regulation based on the Three-layer Dynamic Regulation Model. It dynamically regulate the PHB production by dividing the process into 3 phases: Growth Phase, Production Phase and Product-release Phase. In this way, the cell can firstly grow up and then put their all effort into PHB production. Finally, in the late stationary phase of cell growth, the enigneered bacteria can express lysis gene.
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===1. Three-layer Dynamic Regulation Model===
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<html>
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<figure>
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  <img src="https://static.igem.wiki/teams/4583/wiki/3layer.png"width="600" height="240">
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  <figcaption><b>Fig. 2 </b>. Three-layer dynamic regulation model </figcaption>
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</figure>
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</html>
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===2. The first and second layer--Growth and production control===
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Quorum Sensing is a way for cells to regulate downstream gene expression based on their own density. The concentration of the signaling molecule - AHL - secreted by the cell increases as the cell density increases. When the concentration of AHL reaches a certain level, it can bind to the corresponding binding protein and alter the expression of downstream genes.
 +
 +
In the first and second layer, this part using a QS-switch to regulate the flow of acetyl-coA. At the early stage of growth, using QS-switch turn on the TCA cycle and turn off the PHB production pathway, so that acetyl-coA flowed into the TCA cycle and the cells grew. When the cell grows to a certain extent, the TCA cycle is turned off, while the PHB production pathway is turned on, and the acetyl-coA flows to the PHB production pathway for PHB production.
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 +
===4. The Third layer--Product-release control===
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In the third layer, this part uses a late stationary phase promoter and an lysis gene. The late stationary phase promoter is used to regulate the expressing time of the downstream gene. When the bacterial reach the stationary phase, the promoter will turn on and then the cell lysis.
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 +
==Characterization==
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===1. Design===
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* Step 1: Plasmid construct.
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* Step 2: Verify the expression time difference between the first and second layers, and between the second and third layers。
 +
* Step 3: Overall characterization
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===2. Protocols===
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Our experimental conditions for characterizing this part were as follows:
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* <em>E. coli</em> MG1655
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* 30<sup>o</sup>C, 48h,  under vigorous shaking
 +
* Plasmid Backbone: PACYC, pUC
 +
* Equipment: Multi-Detection Microplate Reader (Synergy HT, Biotek, U.S.) and Molecular Devices SpectraMax i3x.
 +
We used GFP (excitation at 485 nm and emission at 535 nm), mKate (excitation at 490 nm and emission at 645 nm), and BFP (excitation at 400 nm and emission at 450 nm) to characterize this part. As our focus was mainly on the expression time, we processed the obtained fluorescence data by means of the following equation: x'=(x-min)/(max-min). This treatment makes all data fall between 0 and 1, which is easier to use for comparisons between different fluorescence data (since our focus is on expression time).
 +
* Fermentation analysis: 1% inoculated in 100mL fermentation medium at 37℃ at 250rpm. Three parallel experiments were conducted for each strain. Samples were taken every 3-4 hours in the first 20 hours, OD600 and glucose concentrations were measured every 6-10 hours after 20 hours, and PHB concentrations were measured after 11 hours. During this period, glucose is supplemented to approximately 20g/L in the fermentation broth based on glucose concentration data.
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 +
===3. The Characterization of PesaS and PesaRwt/PesaRc/PesaRp===
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We characterized PesaS-RBS(B0034)-GFP together with PesaRwt-RBS(B0034)-mkate, PesaRc-RBS(B0034)-mkate and PesaRp-RBS(B0034)-mkate. The green curve in the figure shows the results for PesaS. PesaS expression peaks at around 4-6 h and then rapidly declines to 0 at around 8-10 h.
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<html>
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<figure style="text-align:center">
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  <img src="https://static.igem.wiki/teams/4583/wiki/srresults.png"width="540" height="210">
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  <figcaption><b>Fig. 3 </b>. Characterization results of PesaS and PesaRwt-RBS(B0034)-mKate in L19 and L31</figcaption>
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</figure>
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</html>
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<html>
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<figure style="text-align:center">
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  <img src="https://static.igem.wiki/teams/4583/wiki/src.png"width="540" height="210">
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  <figcaption><b>Fig. 4 </b>. Characterization results of PesaS and PesaRc-RBS(B0034)-mKate in L19 and L31</figcaption>
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</figure>
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</html>
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<html>
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<figure style="text-align:center">
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  <img src="https://static.igem.wiki/teams/4583/wiki/srp.png"width="540" height="210">
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  <figcaption><b>Fig. 5 </b>. Characterization results of PesaS and PesaRp-RBS(B0034)-mKate in L19 and L31</figcaption>
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</figure>
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</html>
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===4. The Characterization of PesaRwt/PesaRc/PesaRp and PYU3/PYU7/PYU16/PYU92===
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In the previous section, we first verified that the Growth Phase is temporally decoupled from the Production Phase, and then verified that the Production Phase and the Product-release Phase are temporally decoupled. To be more scientific, we decided to co-characterize the growth phase, the production phase and the product launch phase, and to check that all three were expressed in chronological order and at the required time. Due to the certain red-green crosstalk problem during detection, we constructed PACYC-PYU3-BFP, PACYC-PYU7-BFP, PACYC-PYU16-BFP, PACYC-PYU92-BFP plasmids by ligating the blue fluorescent protein gene BFP with PYU3,7,16,92 promoter in order to make the results clearer and the overall expression time sequence. We constructed 10 strains that each have 3 plasmids.
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<html>
 +
<figure style="text-align:center">
 +
  <img src="https://static.igem.wiki/teams/4583/wiki/3layerresult.png"width="720" height="800">
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  <figcaption><b>Fig. 6 </b>. Ten vaild results</figcaption>
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</figure>
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</html>
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<html>
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<figure style="text-align:center">
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  <img src="https://static.igem.wiki/teams/4583/wiki/example.png"width="450" height="340">
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  <figcaption><b>Fig. 7 </b>. An example of Three-layer dynamic regulation model </figcaption>
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</figure>
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</html>
 
<!-- Add more about the biology of this part here
 
<!-- Add more about the biology of this part here
 
===Usage and Biology===
 
===Usage and Biology===

Revision as of 17:40, 11 October 2023


PesaS-B0034-GFP-PesaRp-B0034-mKate-PYU7-BFP

PesaS-B0034-GFP-PesaRp-B0034-mKate-PYU7-BFP


Usage and Biology

Many production processes using microorganisms face the dilemma of conflicting production products and key metabolic pathways. This means that simply introducing product-synthesising genes into engineered bacteria can greatly affect the growth of the microorganism, leading to a situation where production is too low. There are a number of current solutions to this problem. For example, metabolic engineering can regulate metabolic flow using methods such as gene knockdown, promoter replacement, etc. These static strategies are effective for productivity improvement, but are not responsive to changes in the cell or environment. Dynamic control is a favourable solution for the conditional knockdown of essential genes and balances the flow in the metabolic pathway.

The pathway of PHB synthetsis is conflict with TCA cycle. Both TCA cycle and PHB production pathways use acetyl-coA as raw material, so if only the PHB production gene circuit is simply added to the engineered bacteria, the growth of the bacteria will be greatly affected, and the final result is low PHB production. Quorum sensing system can automatically sense cell density to regulate downstream genetic on/off. It is independent of metabolic pathways and do not need exogenous inducers, which make it a perfect tool to solve this problem. PHB are a form of carbon storage by bacteria. PHB products take up most of the space inside the cell, but will not be released from the cell. The method of mechanical crushing or chemical solvent extraction used in traditional industry is not only expensive, but also brings great pressure to the environment, so we hope to design an auto-lysis system with specific expression time.

Fig. 1 . The pathway of PHB synthetsis is conflict with TCA cycle.
This part is about PHB Production Regulation based on the Three-layer Dynamic Regulation Model. It dynamically regulate the PHB production by dividing the process into 3 phases: Growth Phase, Production Phase and Product-release Phase. In this way, the cell can firstly grow up and then put their all effort into PHB production. Finally, in the late stationary phase of cell growth, the enigneered bacteria can express lysis gene.

1. Three-layer Dynamic Regulation Model

Fig. 2 . Three-layer dynamic regulation model

2. The first and second layer--Growth and production control

Quorum Sensing is a way for cells to regulate downstream gene expression based on their own density. The concentration of the signaling molecule - AHL - secreted by the cell increases as the cell density increases. When the concentration of AHL reaches a certain level, it can bind to the corresponding binding protein and alter the expression of downstream genes.

In the first and second layer, this part using a QS-switch to regulate the flow of acetyl-coA. At the early stage of growth, using QS-switch turn on the TCA cycle and turn off the PHB production pathway, so that acetyl-coA flowed into the TCA cycle and the cells grew. When the cell grows to a certain extent, the TCA cycle is turned off, while the PHB production pathway is turned on, and the acetyl-coA flows to the PHB production pathway for PHB production.

4. The Third layer--Product-release control

In the third layer, this part uses a late stationary phase promoter and an lysis gene. The late stationary phase promoter is used to regulate the expressing time of the downstream gene. When the bacterial reach the stationary phase, the promoter will turn on and then the cell lysis.

Characterization

1. Design

  • Step 1: Plasmid construct.
  • Step 2: Verify the expression time difference between the first and second layers, and between the second and third layers。
  • Step 3: Overall characterization

2. Protocols

Our experimental conditions for characterizing this part were as follows:

  • E. coli MG1655
  • 30oC, 48h, under vigorous shaking
  • Plasmid Backbone: PACYC, pUC
  • Equipment: Multi-Detection Microplate Reader (Synergy HT, Biotek, U.S.) and Molecular Devices SpectraMax i3x.

We used GFP (excitation at 485 nm and emission at 535 nm), mKate (excitation at 490 nm and emission at 645 nm), and BFP (excitation at 400 nm and emission at 450 nm) to characterize this part. As our focus was mainly on the expression time, we processed the obtained fluorescence data by means of the following equation: x'=(x-min)/(max-min). This treatment makes all data fall between 0 and 1, which is easier to use for comparisons between different fluorescence data (since our focus is on expression time).

  • Fermentation analysis: 1% inoculated in 100mL fermentation medium at 37℃ at 250rpm. Three parallel experiments were conducted for each strain. Samples were taken every 3-4 hours in the first 20 hours, OD600 and glucose concentrations were measured every 6-10 hours after 20 hours, and PHB concentrations were measured after 11 hours. During this period, glucose is supplemented to approximately 20g/L in the fermentation broth based on glucose concentration data.

3. The Characterization of PesaS and PesaRwt/PesaRc/PesaRp

We characterized PesaS-RBS(B0034)-GFP together with PesaRwt-RBS(B0034)-mkate, PesaRc-RBS(B0034)-mkate and PesaRp-RBS(B0034)-mkate. The green curve in the figure shows the results for PesaS. PesaS expression peaks at around 4-6 h and then rapidly declines to 0 at around 8-10 h.

Fig. 3 . Characterization results of PesaS and PesaRwt-RBS(B0034)-mKate in L19 and L31

Fig. 4 . Characterization results of PesaS and PesaRc-RBS(B0034)-mKate in L19 and L31


Fig. 5 . Characterization results of PesaS and PesaRp-RBS(B0034)-mKate in L19 and L31

4. The Characterization of PesaRwt/PesaRc/PesaRp and PYU3/PYU7/PYU16/PYU92

In the previous section, we first verified that the Growth Phase is temporally decoupled from the Production Phase, and then verified that the Production Phase and the Product-release Phase are temporally decoupled. To be more scientific, we decided to co-characterize the growth phase, the production phase and the product launch phase, and to check that all three were expressed in chronological order and at the required time. Due to the certain red-green crosstalk problem during detection, we constructed PACYC-PYU3-BFP, PACYC-PYU7-BFP, PACYC-PYU16-BFP, PACYC-PYU92-BFP plasmids by ligating the blue fluorescent protein gene BFP with PYU3,7,16,92 promoter in order to make the results clearer and the overall expression time sequence. We constructed 10 strains that each have 3 plasmids.

Fig. 6 . Ten vaild results

Fig. 7 . An example of Three-layer dynamic regulation model
Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal BamHI site found at 1261
    Illegal XhoI site found at 981
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal AgeI site found at 2375
  • 1000
    INCOMPATIBLE WITH RFC[1000]
    Illegal BsaI.rc site found at 860
    Illegal BsaI.rc site found at 1926
    Illegal SapI.rc site found at 1308