Team:CSU CHINA/Basic Part
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Basic Parts
| Section | Name | Type | Description |
|---|---|---|---|
| Module1 | BBa_K2908000 | Regulatory | S(GATA3)p |
| BBa_K2908668 | DNA | miR101-BD | |
| BBa_K2908333 | DNA | miR141-BD | |
| BBa_K2908444 | DNA | miR148b-BD | |
| BBa_K2908677 | DNA | GAD | |
| Module2 | BBa_K2908444 | DNA | miR148b-BD |
| BBa_K2908669 | DNA | miR101-sponge | |
| BBa_K2908555 | DNA | miR141-sponge | |
| BBa_K2908666 | DNA | miR148b-sponge | |
| Module3 | BBa_K2908222 | Regulatory | G8p |
| BBa_K2908667 | Protein_Domain | yCD | |
| BBa_K2908444 | DNA | miR148b-BD |
Overview
√ Promoter Design
We identified genes that were differentially expressed in human triple negative breast cancer (TNBC) cells compared to healthy tissues from the publicly available The Cancer Genome Atlas (TCGA) database [1] using R (version 3.0.2). We followed standard procedures to calculate differentially expressed genes between cancer cases compared to controls using t test. The p values were corrected for multiple testing using the Bonferroni correction. We then selected genes that were previously identified as transcription factors (TFs) from the literature. From these genes (ESR1, FOXA1, GATA3, E2F1, PTTG1, UHRF1, FOXM1, MYBL2, PITX1), we selected the ones that verified as the most specific in MDA-MB-231 cells (TNBC cell line) compared to HBL-100 cells (normal breast cell line).(https://2019.igem.org/Team:CSU_CHINA/Collaborations)
We then determined the binding motifs for ovarian cancer-enriched TFs using GREAT, MEME, JASPAR and MOTIFMAP [2-5] and assembled them into our synthetic promoters.
√ miRNA-BD (microRNA binding sites) Design
We designed, constructed, and sequence validated a miRNA sensor library containing all 620 sequences of mature human miRNAs designated as high confidence in miRBase 2124. Our library enables high-information-content screening of miRNA activity in cells and also serves as a source for sequence-validated templates of miRNA targets when building multi-input sensors. We synthesized miRNA target site sets bearing four repeats of the sequence perfectly complementary to the miRNA and inserted them into the 3′ UTR of a reporter construct.[6]
It’s worth mentioning that, the design of this part is instructed by the 2019 team SYSU_CHINA.(https://2019.igem.org/Team:CSU_CHINA/Collaborations)
√ miRNA-sponge Design
Firstly, obtain the basic sequence information of miRNA from miRBASE, analyze which miRNA subtype is specifically described according to the literature table provided, obtain the sequence and identify the seed sequence.[7]
The miRNAsong website[8] was used to design the basic sponge framework, the free energy cutoff was 25Kcal/mol, and the miss was checked by 2-8seed classic matching. Since more than one BS will be connected in the following experiments, spacer connection is directly designed between two BS in the design stage to facilitate the judgment of the overall change after spacer connection. Then manually annotate the mismatch site, spacer sequence. The website does not consider the off-target effect at all, and most of the results are so severe that the 9-12 base combination needs to be manually changed according to the site. Get the combination with lower miss, perform secondary structure verification, and record the passed combination in the table.
Module1
s(GATA3)p (BBa_K2908000)
Construction: We use the JASPER to get the TF binding sites (TF-BSs), and add different spacers between the tandem repeats of TF-BSs to avoid creating new binding sites in order to ensure the specificity.
This figure shows the results we browse using JASPAR by input homo sapiens GATA3.
Then we add a strong and short promoter named lateADEp to ensure the strength of the whole promoter.
miR101-BD (BBa_K2908668)
miR141-BD (BBa_K2908333)
miR148b-BD (BBa_K2908444)
Construction: miRNA-BDs were constructed bearing four repeats of miR-21-5p in the 3’ UTR, or 5’ UTR. Since these miRNA-BDs do not have ATGs, several ATGs were added between the miRNA target sites in some sensors. Extra bases were added to separate the ATGs by a number of bases divisible by three. The distance between the last ATG and the true reporter start codon was either divisible by three or not.
GAD (GAL4-VP16)( BBa_K2908677)
This part is the same as the BBa_K2580666 removing the CMV promoter. We will use the name GAD in our project in replace of GAL4-VP16.
Module2
s(ESR1)p (BBa_K2908444)
This figure shows the results we browse using JASPAR by input homo sapiens ESR1.
Construction: We use the JASPER to get the TF binding sites (TF-BSs), and add different spacers between the tandem repeats of TF-BSs to avoid creating new binding sites in order to ensure the specificity.
Then we add a strong and short promoter named lateADEp to ensure the strength of the whole promoter.
miR101-sponge (BBa_K2908669)
We test the efficiency of miR101-sponge inhibiting the miR-101, picture A shows the sequence of this part; The heat map shows as (B).
miR141-sponge (BBa_K2908555)
We test the efficiency of miR141-sponge inhibiting the miR-141, picture A shows the sequence of this part; The heat map shows as (B).
miR148b-sponge (BBa_K2908666)
We test the efficiency of miR148b-sponge inhibiting the miR-101, and the heat map shows as below (A); Picture B shows the sequence of this part.
Module3
G8p (BBa_K2908222)
Yeast cytosine deaminase (yCD) (BBa_K2908667)
The cytosine deaminase (CD)/5-fluorocytosine (5-FC) approach is the next most widely studied suicide gene therapy approach. CD is uniquely expressed in certain fungi and bacteria and it converts the prodrug 5-FC (used to treat infections by fungi such as Candida albicans and Cryptococcus neoformans) into the active agent 5-fluorouracil (5-FU). While 5-FC is nontoxic to human cells because of the lack of CD, 5-FU is used to treat cancers like colon, pancreatic, and breast cancer. The cytotoxic effects of 5-FU occur following its conversion to 5-fluoro-2'-deoxyuridine-5'-monophosphate (5-FdUMP). 5-FdUMP is an irreversible inhibitor of thymidylate synthase and thus inhibits DNA synthesis by deoxythymidine triphosphate (dTTP) deprivation and causes DNA strand breakage, leading to cell death.
References
[1] Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A.A., Kim, S., Wilson, C.J., Leha´ r, J., Kryukov, G.V., Sonkin, D., et al. (2012). The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607.
[2] Bailey, T.L., Boden, M., Buske, F.A., Frith, M., Grant, C.E., Clementi, L., Ren, J., Li, W.W., and Noble, W.S. (2009). MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208.
[3] Bell, D., Berchuck, A., Birrer, M., Chien, J., Cramer, D.W., Dao, F., Dhir, R., DiSaia, P., Gabra, H., Glenn, P., et al.; Cancer Genome Atlas Research Network (2011). Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615.
[4] McLean, C.Y., Bristor, D., Hiller, M., Clarke, S.L., Schaar, B.T., Lowe, C.B., Wenger, A.M., and Bejerano, G. (2010). GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501.
[5] Sandelin, A., Alkema, W., Engstro¨ m, P., Wasserman, W.W., and Lenhard, B. (2004). JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 32, D91–D94.
[6] Jeremy J. Gam, Jonathan Babb & Ron Weiss, NATURE COMMUNICATIONS (2018), A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity.
[7] Ebert, M.S., and Sharp, P.A. (2010). MicroRNA sponges: progress and possibilities. RNA 16, 2043–2050.
[8] Tomas Barta, Lucie Peskova & Ales Hampl, (2018), miRNAsong: a web-based tool for generation and testing of miRNA sponge constructs in silico, Scientific Reports.
[9] Ko, T.-P., Lin, J.-J., Hu, C.-Y., Hsu, Y.-H., Wang, A.H.-J., Liaw, S.-H, Crystal structure of yeast cytosine deaminase. Insights into enzyme mechanism and evolution, (2003) J.Biol.Chem. 278: 19111-19117.