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Team:SYSU-China/Project/Result/element test
From 2013.igem.org
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Suicide Gene: The Cruel Guard and Its Ancillary Facility
Comparison between Suicide Genes: who is the most tough killer?
We have selected several Suicide Gene candidates which functions in different pathways and patterns. In order to choose one that is most capable of mediating death in cancer cell, we first carried out a parallel experiment to compare their performance. The candidates were cloned into plasmid pcDNA3.0 in the MCS after CMV promoter just as shown in picture A, and then transfected into HEK293(PEI) and HepG2(Lipo2000). A GFP processed in the same way was used as a negative control to both indicate the transfection efficiency and normalize the death effect bring about by transfection process.Pictures were taken 48 hr after the transfection process.
To achieve a better resolution of the lethal effect, we tried two techniques with the 48hr cells. The first one is DAPI staining done in RIP1 and RIP3 groups. DAPI can specificly binds to DNA but is rejected by living cells to some extent. With DAPI staining, more cells were darkly dyed in the group of RIP1 and RIP3 compared to GFP control. Broken nuclei membrane can be noticed in cells transfected with RIP1 because DAPI blue spreaded all over cytopkasm The second one is flow cytometrycounting(FCM counting). Cells were stained by PI and then analysed by FCM counting. Dead cells binded more PI per cell in a similar reason to DAPI staining. These two techniques were complementary to each other in a certain degree, for DAPI is superior in morphological observation while FCM counting is good at counting.
Figure 1. Performance of different Suicide Genes candidates in causing apoptosis.(A).plasmids construction.(B)Apoptosis phenotype of Apoptin(VP3). The protein was expressed in fusion with a GFP. Compared with 0 hr , apoptosis rose 48 hr after transfection, and GFP vision indicated the transfection efficiency.(C,D) Wells transfected with RIP1\RIP3 both showed significant phenotype of apoptosis compared with GFP control, 48 hr after transfection. After DAPI staining, dead cell showed deep blue color and the phenotype was better visualized.(E)DAPI staining of RIP1, zoomed in vision.We can clearly observe boundary of cells which indicate a broken nucleus membrane and DNA spread all over the cells(F,G).PI staining and FCM data of our Suicide Gene.
The figure shows that Both RIP1 and RIP3 had a outstanding performance in mediating apoptosis. Although Apoptin also killed cell in the results, its performance wasn’t stable since we cannot reproduce the results with another construction( data not shown.) However, according to many paper, this is a powerful protein with a specificity in killing cancer cell, which persuade us to keep working with it in the latter experiments. Moreover, we also test Bax/Bax S184A with the same method. However, no significant phenotype could be observed(data not shown) and thus we abandoned them in our Suicide Gene list.
The PI staining and FCM data showed that the apoptosis rate of RIP1 and RIP3 were about 51.7% and 47.6%, which were significantly higher than the GFP control but rather lower than resent studies. However, this difference may be caused by the relatively low transfection efficiency in Heg G2. More details link to Modeling.
MicroRNA-Target Devices: Security Gate for Liver Cell
Performance comparison between target-sites: CULT and Complete
Two kinds of target-sites were taken into consideration just as mentioned in module Design. To make a comparison between their knockdown efficiency under different concentration of miR122, another orthogonal experiment was performed and two plasmids(fig2.A) were co-transfected by PEI into HEK293 cell line. Pictures were taken 24 hours after transfection.
Figure 2. Comparison of performance of different target-sites in knocking down GFP expression. (A) Plasmids A/B/C/D produced mRNA of GFP with different target-site in its 3’ UTR. Plasmids E produced miR122. Plasmids used in this experiment had the problem of producing a background noise of GFP, which was solved later(see below).(B) Knockdown effect of different target site under different miR122 level. The fields of vision were chosen so that they could well represent the average level of the wells.
The result shows that with the same copy number, complete target-site works better than CULT target-site, which fits the results of the 2010 Heiderburg iGEM team. What’s more, two copies target-site works better than single site, which encourage us to further build target-sites of more copy number and employed more quantitating experiments.
Plasmid E used in the experiment produced background GFP, which was a problem neglected by us. After finding out the problem, we did quick-change to introduce a stop-codon into the CDS of GFP, which proves very efficient. The new miR122 expression plasmids were applied to other experiments just as mentioned. However, we found that although this did interfere our results to some degree, we could still gain insight into the problem so the data was kept.
Quantitative characterization and target-site modelling
In order to build a precisely controlled device, we decided to further characterized the complete-target-sites of different copy number and chose the most suitable one for pathway construction. To begin with we designed another orthogonal experiment crossing the two variables, target-site-number N and MiR122 concentration M, with a more precise gradients for MiR122. But soon we found that it would be too labour-costing and decided that a better way was to replace it with 2 dosage-gradient experiments and a mathematic model. （fig.3）
Figure 3.Two strategies of characterizing MiR122-Target system.We adapt the latter strategy,making use of modeling principle,to simplify the work.
A.Dosage experiment testing performance of 2 copies complete target-site
Firstly we fixed the target-site number at 2 and set up a concentration gradient for miR122 expression plasmid (fig.7,A, plasmid CEP) to gain insight into its dosage effect. Plasmids A and B were co-transfected using PEI into HEK293 cell line. The gradient were set up from 0 to 0.5ug of plasmid per well. The experiment was done with 2 parallel groups of wells( that is, 6 wells as a group and there were 2 repeats) to leave samples for both Western-Blot and RT-qPCR(since both techniques require destruction of sample). To ensure the parallelity so that the two data can be employed to illustrate the problem together, we had repeated the experiment 2 times till we gained same fluorescence intensity with corresponding wells(data not shown).
Figure 4. Dosage effect of miR122 on 2 copy number target-site.(A)Plasmid CG2T produced GFP mRNA with a 2 copies Complete target-site in its 3’ UTR,while plasmid CEP produced miR122 without making fluorescence noise. (B)A gradient of total plasmid amount per well was set up as shown. A significant positive correlation between fluorescence knockdown efficiency and plasmid CEP concentration can be observed.(C) RT-qPCR showed that plasmid CEP successfully express miR122 in cells, the level of which was in a good linear correlation with the transfection concentration through linear-regression analysis(see Heptocyte). (D).Western-Blot showing the GFP level in each well.(E).GFP expression level derived by scanning densitometry,which is in good correlation with fluorescence observation.
The results showed a simple and elegant linear correlation between knockdown efficiency and miR122 concentration.What's more, we have planned to repeat the experiment and make a statistic data.
B.Performance of complete target-site of different copy number
Secondly we fixed the miR122 concentration at 0.75ug to ensure an optimal performance of each targets and let target-site number be the variable this time. Since we had already made sure of the relationship of miR122 level and plasmid concentration, RT-qPCR was no longer needed and so was the parallel groups.
Apart from the 2 and 4 copy target-site, we have also constructed a mixed-up plasmid with 2 complete target-site followed by 2 CULT target-site(2+2).
Figure 5. Comparison of knockdown efficiency of different target-site.
The results show that 4 copy target-site has the most brilliant knock-down efficiency, which is about under such a miR122 level, which conforms to the data given by 2010 Heiderburg using dual-fluorescent system. What’s more, in Part1 we have already proved that 2 copy target-site works better than 1 copy target-site. Finally we decided to first continue further construction of the pathway with the 2 copy target-site, considering that its moderate knockdown efficiency may well coordinate with the other two systems. And if the efficiency turns out improper, we can replace it with other candidates easily with our molecular designing.
C.Modelling
In order to better understand the quality of our miR122-Target system, we have employed interpolation technique with Matlab to model its performance. The modeling can be seen at Modelling module in Results. Also, we have planned a more well-designed experiment to test and characterize all target-sites(in fact, there are 8 of them, produced by permutation and combination of different numbers of complete and CULT). The data derived from that would better support the modeling work.
Figure 6. Modeling of MiR122-Target system.
Tet-Off system: Controlling panel for iPSC
We also used eGFP to test the switching and driving performance of Tet-Off System, which would be a convenient controlling panel to switch pathway state between On and Off and thus provided protection for iPSC. We have collected and constructed three TRE elements of different generations.and thus made a comparison between them.
Figure 7. Performance of Tet-off system in switching between different state.Two plasmids(fig.) were co-transfected into Bosc cell line using PEI. The wells with only plasmids B/C or D characterized the basal leaky expression of different pTRE elements, which can be viewed as the first Off-state. The well with both plasmids represents the On-state of the system, and the well further added with dox represents the second Off-state. Dox concentration was chosen according to protocols in order to give a best performance of the system and avoid hazard on cell growth.
The results showed that pTRE-Tight has the least leaky expression and a good switch response between On and Off state. However, in our experiments leaky expression was too high of pTRE2 and pTRE3G elements, and they cannot response to tTA and DOX properly(data not shown),which confused us a lot since according to protocol from Invitrogen, pTRE3G should have the best performance. We have repeated the experiments several times in troubleshooting, but gained no satisfactory results. So we decided to progress with pTRE-Tight in the first place and leave the other ones as alternative schemes.
In addition, we have received another version of Tet-off system in which the regulatory protein is fused by TetR and KRAB. According to our test result, the KRAB Tet-off system has the best fold increase but its leakage effect is higher the pTight. Maybe the leakage effect can be further eliminated by carefully select the optimal clone in stable cell lines. However, we abandon this system because KRAB theoretically does not work well in ES cells for our usage in iPSCs .
Figure 8. KRAB the new tet off system
Further test for parts combination
Since we have successfully proved that each device of our pathway worked well, we even wanted to further prove our device making use of the convenience of transient transfection, given that Lenti-Virus infection is too time-consuming. So we designed combinational experiments, centered on our protagonist, the Suicide Gene, to further confirmed the devices’ performance in working coordinately, including the test for combination of Suicide gene and tet-off system, the test for combination of Suicide Gene and MicroRNA-Target system and the test for the whole device. However, because of the time limited, we have to spend more energy on learning and researching the technology of stable cell lines establishment and assay, we finally did not choose to finish every experiments before Regional Jamboree.
Figure 9. Combinational test: Tet-Off system and Suicide Gene
Figure 10. Rescue experiment:MiR122-Target system and Suicide Gene
Figure 11. Orthogonal experiment of all three devices.
Lentivirus
Packaging:
We packaged two batches of lentivirus, one containing the upstream tTA plasmid, the other containing the downstream suicide gene and target plasmid.
Figure 12. The map of plasmids for lentivirus packaging.
The package of lentivirus vectors was done in HEK 293T cell lines in 10cm cell culture plates, along with two packaging plasmid: psPAX2 and pMD2G. Both of them were 3rd generation packaging plasmid. We then collected the CM supernatant after 48h and 72h, and transfered all of them into tubes.
Centrifugation:
Because these lentivirus vectors were supposed to infect not only Hep G2 cell lines but also mouse iPSCs, which was very difficult to infect, the requirement of the MOI (Multiplicity of Infection) was much higher than normal experiments, so before infecting cells, we ultracentrifugated these viral vectors.
Figure 13. The steps for lentivirus packaging and centrifugation.
Here is the photo of the 48hr culture medium with lentivirus.
Figure 14. The colors of culture medium with different lentivirus.
After successfully testing for each parts, it's the right time to think about the assays in different period of cells.
Click the cells to see the results.
Sun Yat-Sen University, Guangzhou, China
Address: 135# Xingang Rd.(W.), Haizhu Guangzhou, P.R.China
