Difference between revisions of "Part:BBa J23115"
 
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==Lambert_GA 2019 Characterization==
 
==Lambert_GA 2019 Characterization==
 
Lambert_GA 2019 tested several combinations of constitutive promoters and ribosomal binding sites to characterize each by measuring enzyme activity and therefore protein expression. The gene expressed, LacZ, codes for β-galactosidase (β-gal), which typically breaks down lactose. Instead of using lactose, we added the sugar ONPG (Ortho-Nitrophenyl-β-galactoside). β-gal breaks ONPG down into galactose and ONP (Ortho-Nitrophenol), which has a yellow color. If there is more ONP present, there is more enzymatic activity and therefore more expression of LacZ. We used a plate reader to measure absorbance at 420 nm, measuring yellow color, and 600nm, measuring cell density. We inputted those absorbance values into the Miller unit formula to calculate enzymatic activity per cell per milliliter.
 
Lambert_GA 2019 tested several combinations of constitutive promoters and ribosomal binding sites to characterize each by measuring enzyme activity and therefore protein expression. The gene expressed, LacZ, codes for β-galactosidase (β-gal), which typically breaks down lactose. Instead of using lactose, we added the sugar ONPG (Ortho-Nitrophenyl-β-galactoside). β-gal breaks ONPG down into galactose and ONP (Ortho-Nitrophenol), which has a yellow color. If there is more ONP present, there is more enzymatic activity and therefore more expression of LacZ. We used a plate reader to measure absorbance at 420 nm, measuring yellow color, and 600nm, measuring cell density. We inputted those absorbance values into the Miller unit formula to calculate enzymatic activity per cell per milliliter.
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<table style="width:100%">
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<tr>
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    <th>Strain Identification Number </th>
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    <th>Promoter Part Number</th>
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    <th>RBS Part Number</th>
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    <th>Relative Strength of Promoter/RBS</th>
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  </tr>
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  <tr>
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    <td>R (positive control)</td>
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    <td>BBa_J23115</td>
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    <td>BBa_B0035</td>
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    <td>Reference/Reference</td>
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  </tr>
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  <tr>
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    <td>1</td>
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    <td>BBa_J23113</td>
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    <td>BBa_B0031</td>
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    <td>Weak/Weak</td>
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  </tr>
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  <tr>
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    <td>2</td>
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    <td>BBa_J23113</td>
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    <td>BBa_B0032</td>
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    <td>Weak/Medium</td>
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  </tr>
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  <tr>
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    <td>3</td>
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    <td>BBa_J23113</td>
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    <td>BBa_B0034</td>
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    <td>Weak/Strong</td>
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  </tr>
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  <tr>
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    <td>4</td>
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    <td>BBa_J23106</td>
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    <td>BBa_B0031</td>
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    <td>Medium/Weak</td>
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  </tr>
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  <tr>
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    <td>5</td>
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    <td>BBa_J23106</td>
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    <td>BBa_B0032</td>
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    <td>Medium/Medium</td>
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  </tr>
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    <tr>
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    <td>6</td>
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    <td>BBa_J23106</td>
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    <td>BBa_B0034</td>
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    <td>Medium/Strong</td>
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  </tr>
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    <tr>
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    <td>7</td>
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    <td>BBa_J23119</td>
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    <td>BBa_B0031</td>
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    <td>Strong/Weak</td>
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  </tr>
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      <tr>
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    <td>8</td>
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    <td>BBa_J23119</td>
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    <td>BBa_B0032</td>
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    <td>Strong/Medium</td>
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  </tr>
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  <tr>
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    <td>9</td>
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    <td>BBa_J23119</td>
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    <td>BBa_B0034</td>
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    <td>Strong/Strong</td>
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  </tr>
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</table>
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</body>
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<center> [[File:T--Lambert GA--tuningreference.png|800px]]
 
<center> [[File:T--Lambert GA--tuningreference.png|800px]]
 
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<br>
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  Figure 1: The highlighted points in yellow represent BBa_J10050 (weak promoter/ weak RBS) compared to the remaining nine combinations highlighted in blue. Combinations showing promoters with the same strength, but different RBS, share similar expression. An increase in promoter strength results in an increase in expression; on the other hand, changes in RBS strength has a negligible effect on expression.</center>
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  <i>Figure 1: The highlighted points in yellow represent the combination of BBa_J23115 (reference promoter) with BBa_B0035 (reference RBS) compared to the remaining nine combinations highlighted in blue. Combinations showing promoters with the same strength, but different RBS, share similar expression. An increase in promoter strength results in an increase in expression; on the other hand, changes in RBS strength have a negligible effect on expression.</i></center>
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<center>After we calculated Miller units, the data showed the reference’s level of expression was between the weak and medium promoter’s. As a result, the reference was graphed between the weak and medium promoter.</center>
 
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===Functional Parameters===
 
===Functional Parameters===
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====UT Austin iGEM 2019: Characterization of metabolic burden of the Anderson Series====
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<h3>UT Austin iGEM 2019: Characterization of metabolic burden of the Anderson Series</h3>
  
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===Description===
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<h4>Description</h4>
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The 2019 UT Austin iGEM team transformed the Anderson Series promoters into our 'burden monitor' DH10B strain of E. coli which contains a constitutive GFP cassette in the genome of the cell. This GFP expression rate fluctuates depending on the number of ribosomes available for the host cell to sustain itself. Using this strain, the relative burden (percent reduction in growth rate) of each Anderson Series part was determined. Our results showed a range of growth rate reductions for each of these parts due to ribosomal reallocation from the genome of the host cell, towards the expression of RFP. Anderson Series parts with strong promoters are depicted with darker red colors and Anderson Series parts with weak promoters are depicted with lighter pink colors to show relative RFP expression.
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The 2019 UT Austin iGEM team transformed the Anderson Series promoters into our 'burden monitor' DH10B strain of E. coli, which contains a constitutive GFP cassette in the genome of the cell. GFP expression fluctuates depending on the number of ribosomes available. Using this strain, we characterized the relative burden (percent reduction in growth rate) of each Anderson Series part. Our results showed a range of growth rate reductions for each of these parts due to ribosomal reallocation from the genome of the host cell, towards the expression of RFP. Anderson Series parts with strong promoters are depicted with darker red colors and Anderson Series parts with weak promoters are depicted with lighter pink colors to show relative RFP expression.
 
We saw a positive correlation between relative promoter strength and metabolic burden; parts with stronger promoters expressed less GFP and had a lower growth rate than parts with weaker promoters. The regression line for the graph below was constructed by measuring the burden of 5 parts that were created by the 2019 UT Austin iGEM team that each contained an Anderson Series promoter (<partinfo>J23104</partinfo> or <partinfo>J23110</partinfo>), an RBS of varying strength, and a BFP reporter. For more information on characterization of these parts through the burden monitor, visit our team’s wiki page: [https://https://2019.igem.org/Team:Austin_UTexas]
 
We saw a positive correlation between relative promoter strength and metabolic burden; parts with stronger promoters expressed less GFP and had a lower growth rate than parts with weaker promoters. The regression line for the graph below was constructed by measuring the burden of 5 parts that were created by the 2019 UT Austin iGEM team that each contained an Anderson Series promoter (<partinfo>J23104</partinfo> or <partinfo>J23110</partinfo>), an RBS of varying strength, and a BFP reporter. For more information on characterization of these parts through the burden monitor, visit our team’s wiki page: [https://https://2019.igem.org/Team:Austin_UTexas]
  
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<h4>Importance of Characterizing Burden</h4>
 
<p> Although often we cannot avoid using a specific burdensome part, knowing in advance that it is burdensome, and that it has a high chance of mutating into a non-functional genetic device, can help with troubleshooting and coming up with alternatives. In the specific case of fluorescent protein-expressing devices, Fluorescence-activated cell sorting (FACS) can be used to filter out individual cells that meet a certain fluorescence threshold. This way, the cells expressing lower levels of the fluorescent protein are weeded out of the population.</p>
 
<p> Although often we cannot avoid using a specific burdensome part, knowing in advance that it is burdensome, and that it has a high chance of mutating into a non-functional genetic device, can help with troubleshooting and coming up with alternatives. In the specific case of fluorescent protein-expressing devices, Fluorescence-activated cell sorting (FACS) can be used to filter out individual cells that meet a certain fluorescence threshold. This way, the cells expressing lower levels of the fluorescent protein are weeded out of the population.</p>

Latest revision as of 20:18, 21 October 2019

constitutive promoter family member

BerkiGEM2006-PromotersEppendorfs.jpg
BerkiGEM2006-Promoters.jpg

 
 Variant RFP (au)
 J23112           1
 J23103           17
 J23113           21
 J23109           106
 J23117           162
 J23114           256
 J23115           387
 J23116           396
 J23105           623
 J23110           844
 J23107           908
 J23106           1185
 J23108           1303
 J23118           1429
 J23111           1487
 J23101           1791
 J23104           1831
 J23102           2179
 J23100           2547
PBca1020-r0040.jpg

Constitutive promoter family
Parts J23100 through J23119 are a family of constitutive promoter parts isolated from a small combinatorial library. J23119 is the "consensus" promoter sequence and the strongest member of the family. All parts except J23119 are present in plasmid J61002. Part J23119 is present in pSB1A2. This places the RFP downstream of the promoter. Reported activities of the promoters are given as the relative fluorescence of these plasmids in strain TG1 grown in LB media to saturation. See part BBa_J61002 for details on their use.

These promoter parts can be used to tune the expression level of constitutively expressed parts. The NheI and AvrII restriction sites present within these promoter parts make them a scaffold for further modification. JCAraw

Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal NheI site found at 7
    Illegal NheI site found at 30
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]

Usage and Biology

Lambert_GA 2019 Characterization

Lambert_GA 2019 tested several combinations of constitutive promoters and ribosomal binding sites to characterize each by measuring enzyme activity and therefore protein expression. The gene expressed, LacZ, codes for β-galactosidase (β-gal), which typically breaks down lactose. Instead of using lactose, we added the sugar ONPG (Ortho-Nitrophenyl-β-galactoside). β-gal breaks ONPG down into galactose and ONP (Ortho-Nitrophenol), which has a yellow color. If there is more ONP present, there is more enzymatic activity and therefore more expression of LacZ. We used a plate reader to measure absorbance at 420 nm, measuring yellow color, and 600nm, measuring cell density. We inputted those absorbance values into the Miller unit formula to calculate enzymatic activity per cell per milliliter.

Strain Identification Number Promoter Part Number RBS Part Number Relative Strength of Promoter/RBS
R (positive control) BBa_J23115 BBa_B0035 Reference/Reference
1 BBa_J23113 BBa_B0031 Weak/Weak
2 BBa_J23113 BBa_B0032 Weak/Medium
3 BBa_J23113 BBa_B0034 Weak/Strong
4 BBa_J23106 BBa_B0031 Medium/Weak
5 BBa_J23106 BBa_B0032 Medium/Medium
6 BBa_J23106 BBa_B0034 Medium/Strong
7 BBa_J23119 BBa_B0031 Strong/Weak
8 BBa_J23119 BBa_B0032 Strong/Medium
9 BBa_J23119 BBa_B0034 Strong/Strong

T--Lambert GA--tuningreference.png


Figure 1: The highlighted points in yellow represent the combination of BBa_J23115 (reference promoter) with BBa_B0035 (reference RBS) compared to the remaining nine combinations highlighted in blue. Combinations showing promoters with the same strength, but different RBS, share similar expression. An increase in promoter strength results in an increase in expression; on the other hand, changes in RBS strength have a negligible effect on expression.


After we calculated Miller units, the data showed the reference’s level of expression was between the weak and medium promoter’s. As a result, the reference was graphed between the weak and medium promoter.

USTC_2009's MEASUREMENT

K176014


•••••

University of Texas at Austin iGEM 2019

UT Austin iGEM 2019: Characterization of metabolic burden of the Anderson Series

Description

The 2019 UT Austin iGEM team transformed the Anderson Series promoters into our 'burden monitor' DH10B strain of E. coli, which contains a constitutive GFP cassette in the genome of the cell. GFP expression fluctuates depending on the number of ribosomes available. Using this strain, we characterized the relative burden (percent reduction in growth rate) of each Anderson Series part. Our results showed a range of growth rate reductions for each of these parts due to ribosomal reallocation from the genome of the host cell, towards the expression of RFP. Anderson Series parts with strong promoters are depicted with darker red colors and Anderson Series parts with weak promoters are depicted with lighter pink colors to show relative RFP expression. We saw a positive correlation between relative promoter strength and metabolic burden; parts with stronger promoters expressed less GFP and had a lower growth rate than parts with weaker promoters. The regression line for the graph below was constructed by measuring the burden of 5 parts that were created by the 2019 UT Austin iGEM team that each contained an Anderson Series promoter (BBa_J23104 or BBa_J23110), an RBS of varying strength, and a BFP reporter. For more information on characterization of these parts through the burden monitor, visit our team’s wiki page: [1]

Fig.1:Growth vs GFP Expression graph showing the relative burden positions of the Anderson Series promoters. The parts with strong promoters are depicted in dark red and are clustered near the bottom of the graph because they have lower growth rates and express lower levels of GFP as a result of high cellular burden. The parts with weaker promoter are depicted in light pink ad are clustered near the top of the graph because they have higher growth rates and express higher levels of GFP as a result of low cellular burden.


Table.1: Burden measurements for the Anderson Series promoters measured as percent reduction in growth rate ± 95% confidence interval.

Importance of Characterizing Burden

Although often we cannot avoid using a specific burdensome part, knowing in advance that it is burdensome, and that it has a high chance of mutating into a non-functional genetic device, can help with troubleshooting and coming up with alternatives. In the specific case of fluorescent protein-expressing devices, Fluorescence-activated cell sorting (FACS) can be used to filter out individual cells that meet a certain fluorescence threshold. This way, the cells expressing lower levels of the fluorescent protein are weeded out of the population.