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<p><h3><i>In silico</i> design of Influenza Toehold switches</h3></p> | <p><h3><i>In silico</i> design of Influenza Toehold switches</h3></p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | According to Green <i>et al.</i>, the optimal length of RNA to be detected by a toehold switch is around 30 bp. In other words, a target RNA with 1000 bp in length will give 970 possible switches. However, the performances of each possible switches are different, since the performance is governed by serval parameters in the target region, such as the minimum free energy of the RNA (For more information, please visit <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model"> | + | According to Green <i>et al.</i>(1), the optimal length of RNA to be detected by a toehold switch is around 30 bp. In other words, a target RNA with 1000 bp in length will give 970 possible switches. However, the performances of each possible switches are different, since the performance is governed by serval parameters in the target region, such as the minimum free energy of the RNA (For more information, please visit <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model"> modelling page</a>). To minimize the manpower on screening of the switches, we constructed an <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Software"> online toehold switch design program </a>. Apart from the basic thermodynamic parameters, it also screens for rare codons, stop codons and RFC illegal sites along the sequence. In addition, the built-in BLAST function also automatically screen for nonspecific region to avoid false positive detection. Ultimately, the program can sort a list of “best” Toehold Switch sequence according to their free energy using the embedded function of <a href="https://www.tbi.univie.ac.at/RNA/">“Vienna RNA”</a> (2). The program facilitates the construction of toehold switch by providing a user-friendly interface with novel screening function. |
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− | To detect influenza A, Polymerase Basic Protein 2 (PB2) gene is used as a positive control as it is influenza A-specific. Further subtyping requires a subtype-specific RNA that can also fulfil the criteria for being a good toehold switch. We downloaded the latest influenza gene sequences from the Influenza Research Database and inputted to our program to generate switches to detect H5, H7, N1, N9 and PB2 RNAs. The sequences used are listed below: | + | To detect influenza A, Polymerase Basic Protein 2 (PB2) gene is used as a positive control as it is influenza A-specific. Further subtyping requires a subtype-specific RNA that can also fulfil the criteria for being a good toehold switch. We downloaded the latest influenza gene sequences from the <a href="https://www.fludb.org/brc/home.spg?decorator=influenza "> Influenza Research Database</a>(3) and inputted to our program to generate switches to detect H5, H7, N1, N9 and PB2 RNAs. The sequences used are listed below (Type of flu/ region of origin/ number of lineage/ year of isolation): |
<center><img src="https://static.igem.org/mediawiki/2017/e/e7/Experimap.jpg" style="width:540px;height:360px;"></center> | <center><img src="https://static.igem.org/mediawiki/2017/e/e7/Experimap.jpg" style="width:540px;height:360px;"></center> | ||
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3 toehold switches with “good” predicted performance were chosen to target each RNA (For more information, please visit <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model">RNA thermodynamics modelling page</a>). For example, the three switches are named as H5-1, H5-2 and H5-3 for H5 RNA detection. The figure above shows the detection region of each toehold switch. Before constructing the toehold switches, we ensured all the switches passed our modelling criteria. | 3 toehold switches with “good” predicted performance were chosen to target each RNA (For more information, please visit <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model">RNA thermodynamics modelling page</a>). For example, the three switches are named as H5-1, H5-2 and H5-3 for H5 RNA detection. The figure above shows the detection region of each toehold switch. Before constructing the toehold switches, we ensured all the switches passed our modelling criteria. | ||
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<p><h3>Construction of toehold switch and trigger-expressing plasmid</h3></p> | <p><h3>Construction of toehold switch and trigger-expressing plasmid</h3></p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | The upper picture showed the general structure of our toehold switch. mRFP was chosen as the reporter of our toehold switches because it is very distinguishable by naked eyes while at the same time it can be quantified by measuring the fluorescence signal using a plate reader. | + | <center><img src="https://static.igem.org/mediawiki/2017/d/dc/CUHK_toeholdstructure.jpg" width="50%" height="auto"></center> |
+ | <p style="font-family: roboto;font-size:115%;"> | ||
+ | The upper picture showed the general structure of our toehold switch (For detailed structure, please visit our <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model"> modelling page</a>). mRFP(E1010) was chosen as the reporter of our toehold switches because it is very distinguishable by naked eyes while at the same time it can be quantified by measuring the fluorescence signal using a plate reader. The switch sequence generated by our program was linked with promoter(J23100) and reporter sequence. The trigger sequences was linked with promoter(J23100). Switches and triggers DNA were synthesized by IDT’s sponsored gBlock synthesis service. The gBlocks were used as template and amplified by PCR. The bands with correct size were gel-purified. We inserted the purified PCR products into pSB4C5 (for switch) or pSB1K3 (for trigger) using restriction cut and ligation. Sequencing results confirmed all 30 constructs were cloned. | ||
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+ | Due to safety and budget concern, partial sequence of the viral gene was used. Below listed the partial sequence we used: | ||
+ | <div class="some-padding"></div> | ||
+ | <div class="some-padding"></div> | ||
+ | <div class="some-padding"></div> | ||
+ | <div class="some-padding"></div> | ||
+ | <div class="panel-group" id="accordion" role="tablist" aria-multiselectable="true"> | ||
+ | <div class="panel panel-default"> | ||
+ | <div class="panel-heading" role="tab" id="P0"> | ||
+ | <h4 class="panel-title"> | ||
+ | <a role="button" data-toggle="collapse" data-parent="#accordion" href="#P0-collapse" aria-expanded="false" aria-controls="P0-collapse"> | ||
+ | <div> | ||
+ | <div class="col-md-11">Click here to view trigger sequences </div><div class="col-md-1"><i class="fa fa-arrow-down fa-10" aria-hidden="true"></i></div> | ||
+ | </div> | ||
+ | </a> | ||
+ | </h4> | ||
+ | |||
+ | </div> | ||
+ | <div id="P0-collapse" class="panel-collapse collapse" role="tabpanel" aria-labelledby="P0"> | ||
+ | <div class="panel-body"> | ||
+ | <ol> | ||
+ | |||
+ | <table width="80%"> | ||
+ | |||
+ | <tr> | ||
+ | <th>Respective switch</th> | ||
+ | <th>Trigger sequence</th> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td>PB2-1</td> | ||
+ | <td>AAACAUUGAAAAUAAGAGUACAUGAAGGAUAUGAGGAAUUCACAAUGGUUGGGCG | ||
+ | <br>AAGAGCAACAGCCAUUCUAAGGAAAGCAACCAGAAGACUGAUCCAACUGAUAGUGAGUG | ||
+ | <br>GGAAAGUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>PB2-2</td> | ||
+ | <td>CAAGGCAACCAAGAGGCUUACGGUGCUUGGGAAGGAUGCAGGUACAUUGAUGGAAG | ||
+ | <br>ACCCGGACGAGGGAACAGCAGGAGUGGAAUCUGCAGUAUUGAGGGGAUUUCUGAUUCUG | ||
+ | <br>GGCAAUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>PB2-3</td> | ||
+ | <td>AGAGUUAGUAAAAUGGGAGUAGAUGAAUAUUCCAGCACUGAGAGAGUGGUCGUGAG | ||
+ | <br>UAUUGAUCGUUUCUUGAGGGUCCGAGACCAGAGGGGAAACGUACUCCUGUCUCCCGAAG | ||
+ | <br>AGGUUUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | |||
+ | <tr> | ||
+ | <td>H5-1</td> | ||
+ | <td>UAGGGAUAAUGCAAAGGAGCUUGGUAACGGUUGUUUCGAGUUCUAUCACAGAUGUG | ||
+ | <br>AUAAUGAAUGUAUGGAAAGUGUAAGAAACGGAACGUAUGACUACCCUCAAUAUUCAGAAG | ||
+ | <br>AAGCUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>H5-2</td> | ||
+ | <td>AGUGGAGAAAAUCAAUCCAGCCAAUGACCUCUGUUAUCCAGGGAAUUUCAACGACU | ||
+ | <br>AUGAAGAACUGAAACACCUAUUGAGCAGAAUAAACCAUUUUGAGAAAAUUCAGAUCAUUC | ||
+ | <br>CCAAUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>H5-3</td> | ||
+ | <td>CAUCAUAGCAACGAGCAGGGGAGUGGGUACGCUGCAGACAAAGAAUCCACUCAAAGG | ||
+ | <br>GCUAUAGAUGGAGUCACCAAUAAGGUCAAUUCGAUCAUUGACAAAAUGAACACUCAGUUU | ||
+ | <br>GAGUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N1-1</td> | ||
+ | <td>CAUCAUAGCAACGAGCAGGGGAGUGGGUACGCUGCAGACAAAGAAUCCACUCAAAGG | ||
+ | <br>GCUAUAGAUGGAGUCACCAAUAAGGUCAAUUCGAUCAUUGACAAAAUGAACACUCAGUUU | ||
+ | <br>GAGUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N1-2</td> | ||
+ | <td>GUUUUCAUUUAAAUACGGCAAUGGUGUUUGGAUCGGGAGAACCAAAAGCACUAAUU | ||
+ | <br>CCAGGAGCGGCUUUGAAAUGAUUUGGGACCCAAAUGGGUGGACUGGAACGGACAGUAGC | ||
+ | <br>UUUUCUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N1-3</td> | ||
+ | <td>AGAAGAUAAUAACCAUCGGAUCAAUCUGUAUGGUAAUUGGGAUAGCUAGCUUAAUG | ||
+ | <br>UUACAAAUUGGAAACAUAAUCUCAAUAUGGAUCAGUCAUUCAAUUCAGACAGGGAACCAA | ||
+ | <br>UGCCUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>H7-1</td> | ||
+ | <td>ACACCAGAAUGCACAGGGAGAGGGAACUGCUGCAGAUUACAAAAGCACUCAAUCGGC | ||
+ | <br>AAUUGAUCAAAUAACAGGGAAAUUAAACCGGCUUAUAGCAAAAACCAACCAACAAUUUGAG | ||
+ | <br>UUUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>H7-2</td> | ||
+ | <td>ACACAUUAACUGAAAGAGGAGUGGAAGUCGUCAAUGCAACUGAAACGGUGGAACGAAC | ||
+ | <br>AAACAUCCCCCGGAUCUGCUCAAAAGGGAAAAGGACAGUUGAUCUCGGUCAAUGUGGACUC | ||
+ | <br>CUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>H7-3</td> | ||
+ | <td>AGUGGCUACAAAGAUGUGAUACUUUGGUUUAGCUUCGGGGCAUCAUGUUUCAUACUUC | ||
+ | <br>UAGCCAUUGUAAUGGGCCUUGUCUUCAUAUGUGUAAAGAAUGGAAACAUGCGGUGCACUAU | ||
+ | <br>UUAGCGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N9-1</td> | ||
+ | <td>UUAGUCACAAGAGAACCCUAUGUUUCAUGCAACCCAGAUGAAUGCAGGUUCUAUGCUCU | ||
+ | <br>CAGCCAAGGAACAACAAUCAGAGGGAAACACUCAAACGGUACAAUACACGAUAGGUCCCAGUAG | ||
+ | <br>CGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N9-2</td> | ||
+ | <td>AAUAACUUAACUAAAGGGCUCUGUACUAUAAAUUCGUGGCACAUAUAUGGGAAAGACAAU | ||
+ | <br>GCAGUAAGAAUUGGAGAAAGCUCGGAUGUUUUAGUCACAAGAGAACCCUAUGUUUCAUGCUAG | ||
+ | <br>CGGCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | <tr> | ||
+ | <td>N9-3</td> | ||
+ | <td>ACUACUUUAAAGAGGGGAAAAUAUUGAAAUGGGAGUCUCUGACUGGAACUGCUAAGCACAU | ||
+ | <br>UGAAGAAUGCUCAUGUUACGGGGAACGAACAGGGAUUACCUGCACAUGCAAGGACAAUUUAGCG | ||
+ | <br>GCCGCUGCAGCUCGAG</td> | ||
+ | |||
+ | |||
+ | </tr> | ||
+ | |||
+ | |||
+ | |||
+ | </table> | ||
+ | |||
+ | </ol> | ||
+ | </div> | ||
+ | </div> | ||
+ | </div> | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
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+ | <p style="font-family: roboto;font-size:115%;"> | ||
Below is a table with the information of the backbone: | Below is a table with the information of the backbone: | ||
<table width="79%"> | <table width="79%"> | ||
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<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | These two backbones with different Ori and antibiotic resistance genes were used because they will be used in the following experiments. Two co-transformed plasmids should not have the same type of origin of replication (Ori), or otherwise, they will compete for the replication machinery and affect the copy number. In addition, having two different antibiotic resistance genes avoid dropping out of either one of the plasmids during selection. | + | These two backbones with different Ori and antibiotic resistance genes were used because they will be used in the following experiments. Two co-transformed plasmids should not have the same type of origin of replication (Ori), or otherwise, they will compete for the replication machinery and affect the copy number(4). A higher copy number is chosen for the trigger plasmid to ensure trigger expression is in excess in cells. In addition, having two different antibiotic resistance genes avoid dropping out of either one of the plasmids during selection. |
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− | To use the biobricks to clone switches and triggers, user can just order 2 oligos (similar to primer) and insert the short DNA into the biobricks by restriction cut and ligation. For the 2 oligos (about 60 nt), one oligo should contain forward toehold switch sequence with AGGG at the 5’ end, and another one should contain reverse complement toehold switch sequence with AGTA at the 5’ end. To allow convenient screening of clones, there is a constitutive promoter (J23100) and RBS (B0034) situated between the two Eco31I sites. Digestion by Eco31I will remove them, and the subsequent insertion of switch will block the translation of mRFP, resulting in white colonies, whereas ligation of single digested plasmid will give red colonies. | + | To use the biobricks to clone switches and triggers, user can just order 2 oligos (similar to primer) and insert the short DNA into the biobricks by restriction cut and ligation. For the 2 oligos (about 60 nt), one oligo should contain forward toehold switch sequence with AGGG at the 5’ end, and another one should contain reverse complement toehold switch sequence with AGTA at the 5’ end. To allow convenient screening of clones, there is a constitutive promoter (J23100) and RBS (B0034) situated between the two Eco31I sites. Digestion by Eco31I will remove them, and the subsequent insertion of switch will block the translation of mRFP, resulting in white colonies, whereas undigested plasmid or ligation of single digested plasmid will give red colonies. |
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<p> <h3>Improving existing biobricks and project: Cancer switches</h3> </p> | <p> <h3>Improving existing biobricks and project: Cancer switches</h3> </p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | Previously, the Chang Gung University (CGU) Taiwan 2015 team also worked on toehold switch. They designed toehold switches to detect biomarker of oral cancer. We investigated their project and found that their toehold switches have room for improvement. | + | Previously, the <a href="https://2015.igem.org/Team:CGU_Taiwan/Results"> Chang Gung University (CGU) Taiwan 2015 team</a> also worked on toehold switch. They designed toehold switches to detect biomarker of oral cancer. We investigated their project and found that their toehold switches have room for improvement. |
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− | Firstly, they use luciferase as reporter gene. We think that luciferase is not feasible to be used for on-site diagnosis since the luciferase activity need to be measured by a reader. Secondly, we inputted the sequences of those oral cancer biomarkers into our program and found that a better switch can be designed by choosing another region for detection (see modelling page). Therefore, we improved their biobricks by using <i>in silico</i> design of switch and RFP as a reporter. | + | Firstly, they use luciferase as reporter gene. We think that luciferase is not feasible to be used for on-site diagnosis since the luciferase activity need to be measured by a reader. Secondly, their toehold switches did not worked as expected because the reporter expression was suppressed when trigger was added.Thirdly, we inputted the sequences of those oral cancer biomarkers into our program and found that a better switch can be designed by choosing another region for detection (see <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/Model"> modelling page</a>). Therefore, we improved their biobricks by using <i>in silico</i> design of switch and RFP as a reporter. |
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<p> <h3>Characterization of chromoproteins</h3> </p> | <p> <h3>Characterization of chromoproteins</h3> </p> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | Different types of body fluid have different pH (figure). | + | Different types of body fluid have different pH (5)(below figure). Inspired by a <a href="https://2017.igem.org/Team:Hong_Kong-CUHK/HP/Gold_Integrated"> medical expert</a> we interviewed, we would like to investigate if the pH in body fluid can interfere with the reporter protein we used in our test, since we are going to use body fluid as sample in our influenza diagnostic test. Fluorescent signal is known to be pH-dependent because pH can change the folding and conformation of the fluorophore, and ionization states can also cause shift in the Excitation/Emission spectra (6). Therefore, we characterized the fluorescence of 2 fluorescent proteins: <a href="http://parts.igem.org/Part:BBa_E1010"> mRFP(BBa_E1010) </a> and <a href="http://parts.igem.org/Part:BBa_K1033916"> amajLime(BBa_K1033916)</a> at different pH. We want to find out their optimum pH and see if they are suitable to be the reporter protein in our diagnostic test. |
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<th width="20%">Body Fluids</th> | <th width="20%">Body Fluids</th> | ||
<th width="20%">pH</th> | <th width="20%">pH</th> | ||
− | |||
</tr> | </tr> | ||
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<td>Blood</td> | <td>Blood</td> | ||
<td>7.4</td> | <td>7.4</td> | ||
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</tr> | </tr> | ||
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<td>Saliva</td> | <td>Saliva</td> | ||
<td>6.4</td> | <td>6.4</td> | ||
− | |||
</tr> | </tr> | ||
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<td>Ileum fluid</td> | <td>Ileum fluid</td> | ||
<td>8.0</td> | <td>8.0</td> | ||
− | |||
</tr> | </tr> | ||
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<td>Serum</td> | <td>Serum</td> | ||
<td>7.2</td> | <td>7.2</td> | ||
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</tr> | </tr> | ||
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<td>Stomach juice</td> | <td>Stomach juice</td> | ||
<td>1.5</td> | <td>1.5</td> | ||
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</tr> | </tr> | ||
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<td>Urine</td> | <td>Urine</td> | ||
<td>5.8</td> | <td>5.8</td> | ||
− | |||
</tr> | </tr> | ||
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<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | To examine the performance of mRFP and amajLime under different pH, we inserted the biobricks into pSB1A2 and expressed them in <i>E. coli</i>. mRFP and amajLime were then purified form lysed cells by anion exchange chromatography (AEC) and hydrophobic interaction chromatography (HIC). | + | To examine the performance of mRFP and amajLime under different pH, we inserted the biobricks into pSB1A2 and expressed them in <i>E. coli</i> C41(DE3) . mRFP and amajLime were then purified form lysed cells by anion exchange chromatography (AEC) and hydrophobic interaction chromatography (HIC). |
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− | Below picture shows the SDS–PAGE analysis of purification | + | Below picture shows the SDS–PAGE analysis of purification of amajLime (left) and mRFP (right). |
<center><img src="https://static.igem.org/mediawiki/2017/4/42/CUHK_SDSPAGE1.jpg" style="width:70%;height:auto;"></center> | <center><img src="https://static.igem.org/mediawiki/2017/4/42/CUHK_SDSPAGE1.jpg" style="width:70%;height:auto;"></center> | ||
<p style="font-family: roboto;font-size:115%;"> | <p style="font-family: roboto;font-size:115%;"> | ||
− | F.1 to F.3 represents chronological order of elutions in HIC. Samples ( | + | F.1 to F.3 represents chronological order of elutions in HIC. Samples (10µl) were mixed with 10 µl 2X SDS gel-loading buffer and 10 µl of the mixture were loaded on the SDS-gel. The purest fraction, F.2 in both cases, were selected to proceed to pH stability test, where purified proteins were diluted in buffers in the range of pH 2-12 to a final concentration of 100 µg/mL, and the fluorescence intensity was recorded by BMG ClarioStar plate reader. |
</p> | </p> | ||
+ | |||
+ | <h3>Shipping</h3> | ||
+ | Since iGEM requires standard backbone pSB1C3 for shipping, we later sub-cloned our biobricks into pSB1C3. Agarose electrophoresis and sequencing revealed that all biobricks were successfully inserted. Below showed our 1% agarose gel photo (our biobricks ~ 1000bp, pSB1C3 ~ 2000bp): | ||
+ | <center><img src="https://static.igem.org/mediawiki/2017/1/1b/CUHK_Shipclone.jpg" style="width:70%;height:auto;"></center> | ||
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+ | <h3>References:</h3> | ||
+ | 1. Green AA, Silver PA, Collins JJ, Yin P. Toehold switches: de-novo-designed regulators of gene expression. Cell. 2014 Nov 6;159(4):925-39. | ||
+ | <br> | ||
+ | 2. Lorenz, Ronny and Bernhart, Stephan H. and Höner zu Siederdissen, Christian and Tafer, Hakim and Flamm, Christoph and Stadler, Peter F. and Hofacker, Ivo L. ViennaRNA Package 2.0. Algorithms for Molecular Biology, 6:1 26, 2011, | ||
+ | <br> | ||
+ | 3. Zhang Y et. al. Influenza Research Database: An integrated bioinformatics resource for influenza virus research. Nucleic Acids Res. 2017 Jan 4;45(D1):D466-D474. | ||
+ | <br> | ||
+ | 4. Nordström K, Dasgupta S. Copy-number control of the Escherichia coli chromosome: a plasmidologist's view. EMBO Rep. 2006 May;7(5):484-9. | ||
+ | <br> | ||
+ | 5. Schwalfenberg GK. The alkaline diet: is there evidence that an alkaline pH diet benefits health? J Environ Public Health. 2012;2012:727630. | ||
+ | <br> | ||
+ | 6. Battad JM et al. A structural basis for the pH-dependent increase in fluorescence efficiency of chromoproteins. J Mol Biol. 2007 May 11;368(4):998-1010. | ||
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Latest revision as of 20:57, 1 November 2017