Difference between revisions of "Part:BBa J23101"

Latest revision as of 14:37, 26 October 2020

constitutive promoter family member
For video explanation on this promoter family and its use, visit [http://www.synbiotrails.org/#!/trail?id=org.clothocad.trails.youtube.TranscriptionModels here].

 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

Contribution

Group: Valencia_UPV iGEM 2018
Author: Adrián Requena Gutiérrez, Carolina Ropero
Summary: We adapted the part to be able to assemble transcriptional units with the Golden Gate assembly method
Documentation: In order to create our complete [http://2018.igem.org/Team:Valencia_UPV/Part_Collection part collection] of parts compatible with the Golden Gate assembly method, we made the part BBa_K2656007 which is this part adapted to the Golden Gate technology.

Sequence and Features

USTC_2009's MEASUREMENT

BBa_K176012

Characterization by GreatBay_China 2018

Team GreatBay_China 2018 characterized J23119Part:BBa_J23119, Part:BBa_J23105, and Part:BBa_J23101 by assembling them with Part:BBa_B0034 and a sfGFP Part:BBa_I746916 on three vectors: pUC20 (copy number about 500/cell), pR6K (copy number about 15/cell), pSC101 (copy number about 2/cell). Then we measured the fluorescence by Flow Cytometry as a reference for the TALE stabilized promoter library.

The result indicate that the strength of J23119, J23105, and J23101 are about the same as described by team iGEM2006_Berkeley, and the fluorescence increases as the copy number of the vector increases

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.

Added by KEYSTONE_A 2020 Team

J23101 can be used as a strong constitutive promoter in bacterial cellulose producing strain K. rhaeticus iGEM.

Visual Results as Normally Open Switches

Figure above: Constitutive promoter average strengths in K. rhaeticus iGEM and E. coli, normalized against J23104. Although all promoters are functional, their relative strengths differ between K. rhaeticus and E. coli. For K. rhaeticus, data is shown as grey bars, with standard deviation of N=3 biological replicates, characterized in liquid HS-medium containing cellulase, measured 3 h post-inoculation. Relative promoter strengths in E. coli are superimposed as black stripes.

References: Florea, M., Hagemann, H., Santosa, G., Abbott, J., Micklem, C. N., Spencer-Milnes, X., ... & Chughtai, H. (2016). Engineering control of bacterial cellulose production using a genetic toolkit and a new cellulose-producing strain. Proceedings of the National Academy of Sciences, 113(24), E3431-E3440.

••••• 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. </table>

Characterization in a cell free system - BOKU-Vienna 2020

The main goal of this series of experiments was to compare the expression strength of 3 constitutive promoters when used in a cell free expression system.¹ This expression system includes the core RNA polymerase and sigma 70 transcription factor. Three closely related promoters of well documented expression strength controlled by sigma 70, as well as a single terminator (T_B1001) were chosen, as described in the parts section. The promotores are: BBa_J23101 for better readability called “101”, BBa_J23105 “105” and BBa_J23109 “109”. To accurately measure expression strength the fluorescent protein mCherry was utilized as the expressed protein, as one can deduct expression strength based on fluorescence measurements. The complex of promotor, gene and terminator was then assembled via Golden Gate cloning into the Golden Gate backbone 02, which additionally contains an Ampicillin resistance gene as a selection marker:

With this assembled plasmid, a transformation was carried out. The transformation was then distributed on Agar plates lazed with Ampicillin as a selection marker. From these plates colonies were picked to prepare liquid overnight cultures, from which the DNA was purified using Miniprep kits.³ The success of the Golden Gate Cloning was then confirmed utilizing restriction digests as well as outsourced sequencing.

The data clearly shows that the respective expression strength in E. coli (101>105>109) remains the same in this cell free expression system.⁴ However, the difference between 101 compared to 105 and 109 is far more pronounced than the difference between 105 and 109. To see the differences better, especially between 105 and 109, a second experiment was carried out. For this, plasmid DNA with higher concentration was produced. Through this, a higher concentration of cell free reaction mix was possible. The different parameters can be seen in table 2 compared to table 1.

Table 4. Fluorescence of mCherry at assay 2:

Interestingly, a drop-off in fluorescence past 7.5 hours can be seen for 101. This might be the result of experimental errors and different operators. This seems as a more coherent explanation than a decay of protein. Even though the incubation time was longer and the concentration of the cell free expression system higher, the difference between 105 and 109 is hardly visible. In fact, 109 showed no activity at all as can be seen in table 4.

To produce a notable amount of a protein of interest, the promoter 101 seems to be the best choice. 105 shows some activity compared to 109 which produced no measurable amount of protein. This result seems valid. However, this result is meaningful for this very expression system.