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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">RNA thermodynamics 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> ( | + | 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">RNA thermodynamics 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 (Type of flu/ region of origin/ number of lineage/ year of isolation): | + | 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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− | 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. 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. | + | 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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<p> <h3>Characterization of chromoproteins</h3> </p> | <p> <h3>Characterization of chromoproteins</h3> </p> | ||
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− | Different types of body fluid have different pH (below figure). Since we are going to use body fluid as sample in our influenza diagnostic test, we would like to investigate if the pH in body fluid can interfere with the reporter protein we used in our 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 ( | + | Different types of body fluid have different pH (5)(below figure). Since we are going to use body fluid as sample in our influenza diagnostic test, we would like to investigate if the pH in body fluid can interfere with the reporter protein we used in our 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: mRFP and amajLime 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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− | References: | + | <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. | |
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− | + | 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, | |
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− | + | 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. | |
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− | + | 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. | |
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− | + | 5. Schwalfenberg GK. The alkaline diet: is there evidence that an alkaline pH diet benefits health? J Environ Public Health. 2012;2012:727630. | |
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− | + | 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. | |
Revision as of 10:33, 28 October 2017