document.documentElement.scrollTop = 0; // For IE and Firefox
document.documentElement.scrollTop = 0; // For IE and Firefox
}
}
+
</script>
−
+
<style>
−
function myFunction() {
+
.collapse.navbar-collapse {
−
var x = document.getElementById("myDIV");
+
float:right;
−
if (x.style.display === "block") {
+
padding: 0;
−
x.style.display = "none";
+
padding-right: 5%;
−
} else {
+
−
x.style.display = "block";
+
−
}
+
}
}
#headlink{color: black;
#headlink{color: black;
text-decoration:none;
text-decoration:none;
}
}
−
+
</style>
−
</script>
+
Revision as of 21:06, 14 October 2018
Part Collection
Choosing the optimal promoter and RBS combination for a gene of interest can be crucial, since small changes in the protein expression level can lead to large changes in the resulting effect inside synthetic gene circuits.
To address the challenge of choosing the right promoter, we created a Promoter-RBS library as this year’s parts collection. With our measurement vector, the library could be easily expanded by future iGEM teams and the results are comparable due to normalization of the reporter signal with the help of a second reporter.
Our collection contains a variety of iGEM standard promoters like the Anderson promoter library, as well as inducible promoters.
Furthermore we added a vector (BBa_K2638560) to asses the promoter-RBS combination expression strength accurately, based on two reporter genes.
This collection is closely involved in our whole project. We tested all of our Promoter-RBS combinations which are important for all of our parts. It is also possible to determine only the strength of the Promoter or the RBS.
With the part collection we improved our siRNA toolbox, offers the probability to choose the strength of a knock-down, when a specific promoter is used.
Furthermore, we used the Promoter-RBS combination to determine the optimal expression of our membrane proteins and our anti-toxicity project.
To sum up, we analyzed X promoter-RBS combinations, modeled Y more and therefore provided the iGEM community with detailed information regarding their future projects.
In addition, we designed a database that allows us to easily find a promoter or promoter-RBS combination. If you want to express a slightly toxic protein, you can find a weak combination and if you want to express a reporter geneyou can choose the optimal strength.
Figure 1: Ferritin is suitable for metal recycling, since it can form e.g. iron, silver and gold nanoparticles in its cavity.
Figure 2: Alignment of the protein sequences of the wild-type and the mutated human ferritin heavy chain. The Alignment was produced with Clustal Omega (Goujon et al., 2010, Sievers et al., 2011).
Figure 3: Protein structures of the wild-type human ferritin (A, RCSB ID 4oYN) and the mutated human ferritin (B, RCSB ID 3ES3). Despite the mutations of ten amino acids the ferritin retains its shape. The protein structeres were generated with Chimera (Pettersen et al., 2004).
Figure 4: Possible applications of nanoparticles produced with ferritin.
Molecular graphics and analyses performed with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH P41-GM103311. Butts, C.A., Swift, J., Kang, S., Di Costanzo, L., Christianson, D.W., Saven, J.G., and Dmochowski, I.J. (2008).. Directing Noble Metal Ion Chemistry within a Designed Ferritin Protein † , ‡. Biochemistry 47: 12729–12739.
Castro, L., Blázquez, M.L., Muñoz, J., González, F., and Ballester, A. (2014).. Mechanism and Applications of Metal Nanoparticles Prepared by Bio-Mediated Process. Rev. Adv. Sci. Eng. 3.
Ensign, D., Young, M., and Douglas, T. (2004).. Photocatalytic synthesis of copper colloids from CuII by the ferrihydrite core of ferritin. Inorg. Chem. 43: 3441–3446.
Goujon, M., McWilliam, H., Li, W., Valentin, F., Squizzato, S., Paern, J., and Lopez, R. (2010).. A new bioinformatics analysis tools framework at EMBL-EBI. Nucleic Acids Res. 38: W695-699.
Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., and Ferrin, T.E. (2004).UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem 25: 1605–1612.
Sievers, F., Wilm, A., Dineen, D., Gibson, T.J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., Thompson, J.D., and Higgins, D.G. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7: 539.
Ummartyotin, S., Bunnak, N., Juntaro, J., Sain, M., and Manuspiya, H. (2012). . DSynthesis of colloidal silver nanoparticles for printed electronics. /data/revues/16310748/v15i6/S1631074812000549/.
Wang, L., Hu, C., and Shao, L. (2017a).. The antimicrobial activity of nanoparticles: present situation and prospects for the future. Int. J. Nanomedicine 12: 1227–1249.
Wang, Z., Gao, H., Zhang, Y., Liu, G., Niu, G., and Chen, X. (2017b).. Functional ferritin nanoparticles for biomedical applications. Front. Chem. Sci. Eng. 11: 633–646.
