The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsisseeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code (http://code.google.com/p/gd-ice/) , a hosting site for community-driven open source projects.
Since RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches; nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure.
Last post I mentioned an interesting research introducing RNA interfere system in bacterium and archaea. It gives a new sight into how similarities the three kingdoms share, and potentially what have been done in mammalian cells can be applied into E.coli to enrich the toolbox of synthetic biologists.
Today let’s take a glimpse at what is on earth the progress in mammalian synthetic biology world. Is the bio-system as feasible to engineer as E.coli, just like iGEM? Is the field quite matured enough? Or still long way to go?
As usual, I chase a line and here share out the reviews that probably gives me the answer.
Weber, W., & Fussenegger, M. (2009). Engineering of synthetic mammalian gene networks. Chemistry & biology, 16(3), 287-97. Elsevier Ltd. doi:10.1016/j.chembiol.2009.02.005
Weber, W., & Fussenegger, M. (2010). Synthetic gene networks in mammalian cells. Current opinion in biotechnology, 21(5), 690-6. Elsevier Ltd. doi:10.1016/j.copbio.2010.07.006
Greber, D., & Fussenegger, M. (2010). An engineered mammalian band-pass network. Nucleic acids research, 38(18), e174. doi:10.1093/nar/gkq671
Weber, W., & Fussenegger, M. (2011). Molecular diversity–the toolbox for synthetic gene switches and networks. Current opinion in chemical biology, 15(3), 414-20. Elsevier Ltd. doi:10.1016/j.cbpa.2011.03.003
Weber, W., & Fussenegger, M. (2011). Emerging biomedical applications of synthetic biology. Nature Reviews Genetics, 13(1), 21-35. Nature Publishing Group. doi:10.1038/nrg3094
Karlsson, M., Weber, W., & Fussenegger, M. (2012). Design and construction of synthetic gene networks in mammalian cells. Methods in molecular biology (Clifton, N.J.), 813, 359-76. Humana Press. doi:10.1007/978-1-61779-412-4_22
Based on the above researches, things in mammalian cells are not splendid engineered as E.coli, probably due to our limited understanding towards eukaryotes.
Nevertheless, there still are some sparkling researches. Here I raise one for example — Rapid Eraser, or precisely, Auxin-controlled protein depletion device.
Though it’s an old story, the bio-eraser inspires a lot. Another real old story is bio-film, the noted first E.coli photograph. An awkward problem is the E.coli bio-films are ONCE-only. If you need another photo, you need buy one more new film . Any modification? Protein Depletion!
Furthermore, let me explain why protein depletion device is wonderful first. Since it’s easy to enable E.coli express different color with natural dye seen under naked eye (seen E.chromi), or with GFP/RFP under UV light, what about rainbow sparkling E.coli Biofilm? The biofilm is more like a neon light. The E.coli itself can change its color from red to yellow, to green, and back to red periodically.
It’s Rainbow E.coli !!!
So how the protein depletion device works? Degron !!! A degron is a specific sequence of amino acids in a protein that directs the starting place of degradation. Once activated by ubiquitylation, for example, the protein will be rapidly degraded, thus seems to be erased.
As for auxin, auxin is employed as the inducing signal. As auxin-triggered degron system is conserved in yeast, avian and mammalian cells, it can be applied to yeast cells, and will not interfere with other proteins as signal noise or lead to fatal error.
What ‘s the speed? 97% depletion in 15~30min ! Very satisfying.
It is recommended that you read the paper  for further details.
 Nishimura, K., Fukagawa, T., Takisawa, H., Kakimoto, T., & Kanemaki, M. (2009). An auxin-based degron system for the rapid depletion of proteins in nonplant cells. Nature methods, 6(12), 917-22. Nature Publishing Group. doi:10.1038/nmeth.1401
Synthetic biology which is inspired by “plug-and-play” concept is supported by standardized biobricks and also computational tools for analysis and optimization . Here are bio-apps collections for you. Personally Tinkercell and UNAFold are mostly used.
Suggested pages listing useful bio-apps maybe you will like in synthetic biology research:
WikiGenes Toolbox ( http://www.wikigenes.org/e/art/e/187.html). As a free on-line tutorial edited by people all around the world, WikiGenes has spirits of Linux: open-source, sharing, interest, so is WikiGenes-Synthetic-Biology page. It enables you fast-learn what is synthetic life.
 Marchisio, M. A., & Stelling, J. (2009). Computational design tools for synthetic biology. Current Opinion in Biotechnology, 20(4), 479-485. Retrieved from http://www.sciencedirect.com/science/article/pii/S0958166909001001
Restriction-modification systems, abortive-phage phenotypes, toxin-antitoxins and other innate defense systems, in the past, have been shown in familiar chapters in typical microbiology textbook, while now what if I say in prokaryotes world “RISC” can serve a role for new kind of antiviral defense, in addition the “RNAi” can even be engineered and designed to lead … Read more