Latest revision as of 01:41, 22 October 2019

constitutive promoter family member

 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

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

Saba: parts BBa_J23118 and BBa_J23110 are the same.

Sequence and Features

Baltimore Biocrew 2019 Characterization

Goal

We, the Baltimore Biocrew, decided to characterize some of the Anderson promoters. These promoters are highly used by iGEM but the relative expression of these promoters have been routinely determined by measuring the fluorescence of a reporter protein. However, the function of a promoter is to start transcription of a gene so it may be more informative to measure the amount of RNA (instead of protein) produced by a reporter gene. Therefore, we decided to further characterize a selection of the Anderson promoters (J23100, J23101, J23103, J23105, J23118) by measuring RNA using reverse-transcription quantitative Polymerase Chain Reaction (qPCR).

Results

We set up samples for qPCR with three or four technical replicates per promoter and no template control samples to measure DNA contamination. We did data analysis using the Livak Method (a standard, comparative method) to determine the relative strength of the promoters from the qPCR data using rrSD as our reference gene, RFP as our target gene, and J23100 as our calibrator sample.

Example:

ΔCT(J23101) = CT(RFP, J23101) – CT(rrSD, J23101)

ΔΔCT(J23101) = ΔCT(J23101) – ΔCT(J23100)

2^(–ΔΔCT) = relative expression ratio

In our first trial of qPCR (8/03/19), we were able to measure the relative strengths for J23100, J23101, J23103, and J23105 which were 1.00, 0.00, 0.81, and 1.93, respectively. Since these strengths did not match the relative expression levels reported by iGEM2006_Berkeley from protein level measurements, we repeated the qPCR (8/10/19) with the same cDNA. The strengths from this second trial were 1.00, 0.00, 0.37, and 0.20. We repeated it again and the relative strengths that we got on 10/12/19 for J23100, J23101, J23103, and J23103 were 1, 0, 2.91, and .32. Next, we made new cDNA by growing new liquid cultures, extracting RNA again, and repeating reverse transcription. From the new cDNA, we repeated the qPCR procedure two more times. The relative strengths for that we got on 9/28/19 for J23100, J23101, J23103, J23105, and J23118 were 1, 24.63, .36, 1.76, and .25. The relative strengths that we got on 10/12/19 for J23100, J23101, J23103, and J23105 were 1, 45.97, 3.20, and 1.26. In addition we measured promoter J23118 twice and got the strengths 1.13 and 1.32.

Here is the relative promoter strengths that we got from the qPCR. Baltimore BioCrew measurements in orange compared to the 2006 Berkeley iGEM, who determined relative strengths from measurements at the protein level, in blue.

To support our RNA measurements we also measured fluorescence of the liquid cultures we used to extract RNA. The cultures were grown overnight so we expected the bacteria to be at the stationary phase, but we measured OD to normalize any differences in growth.

iGEM Team 2019 Stuttgart Characterization

We added quantitative experimental characterization to the following biobricks:
BBa_J23100 BBa_J23112 BBa_J23118
These parts are a family of constitutive promoters. They were present in plasmid BBa_J61002. We analyzed the influence of the mentioned promoters on the expression of red fluorescence protein (RFP), both on protein level (fluorescence spectroscopy) and mRNA level using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).

Biobricks were transformed in E. coli MG1655. Cells were harvested in the early exponential phase and fluorescence was measured. Also, 500 µL of culture was centrifuged and the pellet was used for RNA extraction. In addition to that, E. coli MG1655 was cultured and harvested for RNA isolation without the plasmid BBa_J61002 to ensure, that our primers specifically bind to RFP mRNA.

RT-qPCR was performed and analyzed using the ddCt method. To quantify the expression levels of RFP under different promoters, the cDNA of a house-keeping gene was amplified as well. We chose a GTPase-activation protein (GAP) as a housekeeping gene.


Results of fluorescence spectroscopy

Investigating the grown cell cultures by fluorescence spectroscopy clearly showed emission at 590nm (excitation at 540 nm) indicating a successful expression of RFP. Cells containing the promoter BBa_J23100 showed an emission at 590 nm of 192 +- 13. Compared to that, cells containing the promoter BBa_J23112 showed an emission of 30 +- 1. The highest emission was shown by cells containing the promoter BBa_J23118: 345 +- 4.

Results of qPCR

Figure 1 shows, that RFP expression was about 7-fold higher than the expression of GAP in cells containing promoter BBa_J23100. Compared to that, the expression of RFP in cells containing promoter BBa_J23112 was about 55-fold higher than expression of the house-keeping gene. The highest expression of RFP compared to GAP was observed in cells containing promoter BBa_J23118. Here, RFP expression was 74-fold compared to GAP expression.
Figure 1: Average relative quantification of RFP expression compared to the expression of the house-keeping gene GAP in E. coli MG1655. Cells contained the plasmid BBa_J61002 with different promoters: BBa_J23100, BBa_J23112 and BBa_J23118. As a control E. coli MG1655 were cultivated without the plasmid. RT-qPCR measurements were carried out in technical triplicates. Standard deviation is shown

••••• 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] 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.