Team:SJTU-BioX-Shanghai/Results-cn

结果

抑制泄漏

在我们的表征实验中，STAR可以有效抑制下游基因的表达。我们采用sfGFP（BBa_K515005）作为下游的报告基因，对应STAR1/3系统设计了Target有无的对照（见图1），监测其生长过程中荧光值和OD值的变化。

As the fig.1 and fig.2 show, during the 400mins of culture, the expression of sfGFP with target is far lower than those without.

图1 抑制泄漏表征质粒的示意图 其中含Target1的表征质粒构建在pCDF duet-1质粒上，含Target3的表征质粒构建在pET duet-1质粒上。这两种表征系统都配以常启动子J23119，和同样的终止子。

如图1A、1B所显示，在培养的400min里，有Target1或Target3存在时sfGFP的表达明显地降低。而在两个STAR系统的比较中，可以看出由我队设计并改进的STAR3系统的target抑制效果更好，其荧光值只略高于空白对照，与无target情况下sfGFP的表达形成鲜明对照。在实验中我们有平行进行三次生物学重复，其结果一致显示Target3的抑制下过更强。图3C表现出在培养的第600min，不同实验组的标准荧光值差距。这里我们取荧光值/OD600来消除细菌生长对荧光值带来的影响。

Figure.2 Characterization of Target in DH5α E. coli cells. (A) Normalized fluorescence monitored over time for cell lines incorporating the Target1 sequence of STAR system in the absence or presence of transcribed target molecules. (B) Normalized fluorescence monitored over time for cell lines incorporating the Target3 sequence of STAR system in the absence or presence of transcribed target molecules. (C) Normalized endpoint fluorescence (600 minutes) for cell lines in the absence or presence of Target 1 or 3 molecules. We used two separately plasmid system described in the Design for characterization experiments involving STAR. For the absence of target condition, the plasmid did not include target sequence but just the J23119 promoter. Normalized fluorescence was calculated by dividing fluorescent signal by the O.D.600 value of the culture. Background was determined using DH5α cells with no plasmid transformed. Error bars represent standard deviation from 3 technical repeats.

STAR can work as a molecular switch，T for off A for on

When only T (target) exists in the system, the expression of the downstream gene is closed; when A (antisense) and T (target) are present at the same time, the inhibition of T is reduced and the downstream gene is re-actived. We used sfGFP as reporter gene to validate this function of the STAR system.

Figure 3 STAR as a molecular switch to characterize the plasmid diagram, which contains STAR1 expression system constructed on the pCDFDuet-1 plasmid, containing STAR3 expression system built on the pETDuet-1 plasmid. And every STAR system is built on a single plasmid respectively.

The results displayed in Figure 4A/4B show that the expression of SFGFP is greatly increased in the presence of both Target and Antisense which is a complete STAR system over the course of 500 minutes of culturing. The graphs from Figure 3C/3D represent the normalized fluorescence once the growth data (optical density) has been considered. The data from these graphs shows that sfGFP expression is increased more than 2-fold (for STAR1) and 4-fold (for STAR3) at 600 minutes of culturing, when STAR is present. This indicates that STAR is successful in the regulation of the growth repressing gene in our circuit.

Figure 4 Characterization of STAR system in DH5α E. coli cells. Characterization of STAR system in DH5α E. coli cells. (A) Normalized fluorescence monitored over time for cell lines incorporating the STAR1 system in the absence or presence of transcribed STAR molecules (B) Normalized fluorescence monitored over time for cell lines incorporating the STAR3 system in the absence or presence of transcribed STAR molecules. (C) Normalized endpoint fluorescence (600 minutes) for cell lines in the absence or presence of STAR1 molecules. (D) Normalized endpoint fluorescence (600 minutes) for cell lines in the absence or presence of STAR3 molecules. We used the single-plasmid system described in the Experimental Design for characterization experiments involving STAR. For the absence of STAR condition, the plasmid did not include STAR sequence. Normalized fluorescence was calculated by dividing fluorescent signal by the O.D.600 value of the culture. Background was determined using DH5α cells with no plasmid transformed. Error bars represent standard deviation from 3 technical repeats.

STAR × chromoprotein

In order to achieve visualization and multi-factor detection simultaneously, we selected chromoproteins as downstream expression gene. In a large number of pigment proteins, we chose those with obvious color distinction, that is the three primary colors RGB (red, green, blue) for the experiment. We used eforRed (BBa_K2285012), amilGFP (BBa_K592010), cjBlue (BBa_K592011), amilCP (BBa_K1357009) to represent the corresponding three primary colors.

In the experiment, we linked Targets with four chromoproteins. On the dual-expression vector (STAR1 system on pCDFDuet-1 vector, STAR2 system on pETDuet-1 vector) and the relevant Antisense 1 and Antisense 3. Therefore, for future users, this kind of gene circuit can be inserted downstream of other corresponding response elements, such as operon, repressor and so on to obtain different expression of chromoproteins induced by different external stimuli, and then the visible depth of different colors can reflect the quantity of the stimuli.

Figure 5 four kinds of chromoproteins we used in the construction of expression vector.

Figure 6 T + chromoprotein + A gene circuit diagram. In the project we ligated two genes in the same expression vector, so transform one plasmid can achieve to report a factor. In this way, not only the burden of the host can be reduced, but the multi-factor detection will be convenient as well.

	eforRed	amilGFP	amilCP	cjBlue
STAR1	In stock	In stock	In stock	In stock
STAR3	Not in stock	In stock	In stock	Not in stock

The table above shows the STAR system with chromoproteins that we have now verified. We have submitted standardized parts of the corresponding all eight Target + chromoprotein on the plasmid pSB1C3, and the corresponding Antisense on pSB1C3. We also welcome the future iGEM teams to contact us and we are happy to provide a complete plasmid for the STAR 1 / STAR 3 × chromoproteins on the dual-expression vector (pETDuet-1, pCDFDuet-1) for further construct other circuit using for detection.

In order to prevent the limitations and errors produced by human eyes and achieve greater accuracy and convenience to measure on the basis of the visualization effect, and at the same time to meet the easy operation and cost-effective characteristics, we designed a simple pumping device, an app for analysis of results and a box providing a stable environment for the camera. More detailed information please look to the Detector and Analysis page of our wiki.

Figure 7 the result of filtration and box and app front page (A) pET duet-1 plasmid with eforRed gene was transformed into BL21(DH3) E. coli, and cells with different concentration were filtered on the glass fiber filter. (B) the schematic map of the box which can give a proper distance between mobile phone and filter to be photographed. We already have a finished product of this box, to see more information please click the Detector page.

Response ability

During experiments to validate the responsiveness of the STAR system, we constructed two systems mediated by lac operon and As promoter. The lac operon is the one on MCS1 of plasmid pCDFDuet-1, and As promoter is provided by iGEM2006_Edinburgh BBa_J33201.

Figure 8 lac operon and As promoter control STAR gene loop diagram. As promoter and lac operon should be added on the upstream of Antisense, and the two circuits is constructed on the same plasmid.

The characterization of lac responsiveness is mainly carried out using the STAR1 system, and sfGFP, which is more easily quantitatively monitored, is used as a downstream reporter gene to determine its accuracy. Afterwards, by using eforRed as the reporter gene, visualization of pigments was performed.

Figure 9 Characterization of lac operon and As promoter for STAR. A) The presence of IPTG-induced STAR 1 system with lac operon in the case of fluorescence versus time. The plasmid we use is pCDF duet-1. Characterization cells are BL21 (DH3) E. coli. And each control group and experimental group were formed from the same colony. And a total of three repeated tests were conducted to verify the effectiveness. B) with eforRed as the downstream reporter gene STAR 1 system under lac operon’s manipulation of the color characterization C) As + STAR 3 system enzyme electrophoresis diagram. The marker used in the figure was DL2000, and the third lane was an expression product constructed using the restriction endonucleases NdeI and KpnI digested at both ends of As + antisense 3, and the second lane was a restriction on the use of T3 + sfGFP Endonuclease PstI and EcoRI digested to construct the expressed product. The electrophoresis tank buffer was 0.5 x TBE and the gel contained 1% agarose, using Dye DuRed, running 120 v / 100 mA for 20 min.

From the above, fluorescence emitted by gene under the control of STAR1 system containing lac operon changes over time. The difference between the group treated with ITPG and the control becomes greater and greater. The fluorescence of ITPG group generally not higher than the control and 10 hours after treating ITPG, fold activation reach a value of 6, which indicates that our STAR system is very effective as a RNA switch. Due to the limitation of time, we haven’t finished the characterization of STAR3 and chromoproteins so we plan to continue the rest of our work in the future. What’ more, according to the results from our characterization experiment, STAR3 system has greater fold activation than STAR1. There is every reason to believe that STAR3 system can response to change of environment more accurately. STAR systems are actually competent candidates for molecular switch.

On the part of regulation of As promoter, we have built the complete STAR3 system that can sense As3+. From the electrophoretogram, the first band is about 600-700bp, indicating the existence of As+A3, and the second band, about 900bp long, indicates the existence of T3+sfGFP. All of these result prove the success of our construction. In fact, we have proved that our construct is correct via Sanger Sequencing.

Multi-factor detection

Due to the strong orthogonality of STAR system and the differences between colors of selected chromoproteins, we can build a multi-factor detection reporting system. In a multi-factor detection, the double-factor detection is the most direct and easiest to distinguish. The future iGEM team can use our reporting system to build their own multifactorial detection system by adding different downstream reporter genes.

To simulate the actual situation in multifactorial responds to the color changes incurred by factors of interest, we started with co-transformation of two plasmids containing different chromoproteins.

Figure 10 Characterization of chromoprotein co-transformation.

We tried to use heavy metal ions as concrete examples of multiple factors. In the experiment, we selected As promoter and Co promoter as Antisense starting elements. Specifically, in the presence of As3 + and Co2 +, the corresponding repressor is released, activating the expression of antisense, subsequently reducing the inhibitory effect of Target. Next, downstream chromoproteins are expressed, resulting in obvious changes of colors. At the same time in a certain range of metal ion concentration, when the metal ion concentration increases, more Target are disrupted by Antisense, and the color gets brighter and brighter. And two STAR systems were established on different compatible plasmid backbone: pCDF duet-1, pET duet-1, which provided convenience for the transfer of the two expression vectors into the same host E. coli.

Figure 11 gene circuit of multi-factor detection with STAR

Figure 12 electrophoretogram of Co+STAR1、As+STAR3

We have successfully construct STAR 1 system with Co promoter and STAR 3 system with As promoter separately. And the electrophoretogram and sequencing both accord with the design. But because of the time limit, we haven’t done characterization experiments about multi-factor detection.

Reference

Chappell J, Takahashi MK, Lucks JB. 2015. Creating small transcription activating RNAs. Nat Chem Biol 11:214–220.
Meyer, S., Chappell, J., Sankar, S., Chew, R., and Lucks, J. B. (2016) Improving fold activation of small transcription activating RNAs (STARs) with rational RNA engineering strategies Biotechnol. Bioeng. 113, 216.