JBEI-ICE, part registry platform and tools

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.

 

Maximum expected accuracy structural neighbors of an RNA secondary structure

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.

 

Source code for RNAborMEA can be downloaded from http://sourceforge.net/projects/rnabormea/ or http://bioinformatics.bc.edu/clotelab/RNAborMEA/

Synthetic Biology in Mammalian cells

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.

  1. 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
  2. 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
  3. Greber, D., & Fussenegger, M. (2010). An engineered mammalian band-pass network. Nucleic acids research, 38(18), e174. doi:10.1093/nar/gkq671
  4. 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
  5. 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
  6. 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.

E.chromi

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 [1] for further details.

 

–end &&reference

[1] 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

 

Apps Collections for Synthetic Biology

 

Synthetic biology which is inspired by “plug-and-play” concept is supported by standardized biobricks and also computational tools for analysis and optimization [1]. Here are bio-apps collections for you. Personally Tinkercell and UNAFold are mostly used.

Circuit design and simulation
 Biojade http://web.mit.edu/jagoler/www/biojade/
 Tinkercell http://www.tinkercell.com/Home
 Asmparts http://soft.synth-bio.org/asmparts.html
 ProMoT http://www.mpimagdeburg.mpg.de/projects/promot
 GenoCAD http://www.genocad.org/genocad/
 GEC http://research.microsoft.com/gec
 TABASCO http://openwetware.org/wiki/TABASCO#TabascoSimulator
 Hy3S http://hysss.sourceforge.net/index.shtml
Circuit optimization
 Genetdes http://soft.synth-bio.org/genetdes.html
 RoVerGeNe http://iasi.bu.edu/∼batt/rovergene/rovergene.htm
DNA and RNA design
 Gene Designer https://www.dna20.com/index.php?pageID=220
 GeneDesign http://www.genedesign.org
 UNAFold http://www.bioinfo.rpi.edu/applications/hybrid/download.php
 mfold http://mfold.bioinfo.rpi.edu/download/
 DINAMelt http://dinamelt.bioinfo.rpi.edu/
 Vienna RNA package http://www.tbi.univie.ac.at/∼ivo/RNA/
 Vienna RNA web servers http://rna.tbi.univie.ac.at/
 Zinc Finger Tools http://www.scripps.edu/mb/barbas/zfdesign/zfdesignhome.php
Protein design
 Rosetta http://www.rosettacommons.org/main.html
 RAPTOR http://www.bioinformaticssolutions.com/products/raptor/index.php
 HHpred http://toolkit.lmb.uni-muenchen.de/hhpred
 Modeler http://salilab.org/modeller/
 PFP http://dragon.bio.purdue.edu/pfp/
 Autodock 4.2 http://autodock.scripps.edu/
 HEX 5.1 http://webloria.loria.fr/∼ritchied/hex/
Integrated workflows
 SynBioSS http://synbioss.sourceforge.net/
 Clotho http://biocad-server.eecs.berkeley.edu/wiki/index.php/Tools
 Biskit http://biskit.sf.net

 

Suggested pages listing useful bio-apps maybe you will like in synthetic biology research:

  1. 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.
  2. OpenWetWare (http://openwetware.org/wiki/Computational_Tools).
  3. JCVI (http://www.jcvi.org/cms/research/software/#c614). This page is from J. Craig Venter Institute.

 

— end &&reference

[1] 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

“RISC” of Bacteria and Archaea

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 to target gene silencing, would you believe me?

You must have ever heard CRISPR/Cas (CRISPR Associated proteins) System if you have ever read this Science paper [1]. Exactly as the title said, CRISPR, Clustered Regularly Inter-spaced Short Palindromic Repeat, serves as the leading role to provide the “memory” as an adaptive immunity, akin to a blacklist of unwanted visitors, like plasmids or viruses genome.

CRISPR/Cas has different types based on Cas family. Three modules of Cas proteins are Cmr, Cst, Csa. It is an old story in bacteria world as it had been firstly identified in E.coli in 1987. Most have been reported to head for invading DNA, while here what I introduce to you now is an unique and intriguing discovery that in achaeon Pyrococcus furiosus which thrives best under extremely high temperatures, CRISPR/Cmr (one subtype of CRISPR/Cas) targets invading RNA, rather than DNA, thus what I called “RNAi” can makes sense.

In general, the context of CRISPR RNA (crRNA) is typically a sandwich, repeat-sequence-repeat. The internal sequence is termed guide sequence which is complementary to invading RNA only for CRISPR/Cmr, and it is identical to invading DNA for most other cases of CRISPR/Cas.

–How CRISPR/Cmr works?

 

As recalled, the internal sequence of crRNA is complementary to invading RNA as the “seed” region, and more importantly only Cmr complex can contribute to RNA cleavage.

The 8 nt 5′-end tag, among the short repeat sequence in crRNA, will lead crRNA to bind to invading RNA. It is suggested that the 8 nt 5′-end tag plays a discrimination function to classify self-RNA and non-self RNA.

Once crRNA and invading RNA get paired, hydrolysis of the target RNA takes place at a fixed distance, 14nt, from the 3′-end of the small guide RNA. Thus the invading RNA will be degraded and its expression will be turned OFF. In this way Pyrococcus furiosus help themselves against foreign viruses invading with RNA gnome.

Thus I cannot help raising an analogy between CRISPR/Cas system and noted RISC (RNA-induced siliencing complex) in eukaryotes [2]. They all have the progess: processing to be matured, base-pair induced target cleavage.

–Can CRISPR/Cmr engineered?

Yes, we can. The magic is the 8nt 5′-end tag, whose sequence is AUUGAAAG. Scientists had hacked the “immune” system to suppress target gene expression [3], here with the example beta-lactamase (bla) mRNA. The internal sequence, or guide sequence had been designed complementary to 5′-end bla mRNA sequence with the required 5′-end tag. Good result is the gene get silenced which shows promise to another novel silencing systems in bacterium and archaea.

–Questions

CRISPR/Cmr with RNA as its target is just one subtype of CRISPR/Cas system. Other types target DNA. 

If we took a deep look at the general features of all the systems, and compare them with eukaryotic RNAi side-by-side,[4] there are still lots of questions remained unsolved, and mechanisms left mysterious.

How the invading sequence get integrated into CRISPR loci?


CRISPR/Cas system is adaptive immune system, not innate. Bacteria and archaea are not born with it, and they need immune stimulation at first to gain a short of sequence from invading virus or plasmids. And it is the short foreign sequence that gets integrated into CRISPR loci between two short repeat sequences and enables crRNA to bind with RNA/DNA.

But what is mechanisms of the acquisition? Unknown[4].

How to discriminate self or invading?

For CRISPR/Cas system that target DNA, the 5′-end tag (in short repeat region) is critical for distinguishing self from non-self. If the 5′-end tag mismatches the invading DNA, the invaders must die. If the tag precisely matches foreign DNA, it is considered as the host CRISPR locus itself and does not “attack”. What about  CRISPR/Cmr? 

To discern the function of 5′-end tag in CRISPR/Cmr targeting RNA. Three disturbance experiments are conducted. When the 5′-end tag is totally deleted, substituted by other types of sequences (one is precisely complementary to itself, two are with just first one or two bases complementary to itself), these three new tags are no more original 5′-end tag leading to the silencing effect disappear, just as expected. Thus it can be concluded that 5′-end tag is sufficient and critical for RNA silencing. 

But an interesting experiment leaves the tag’s function more confusing[3]. If the target transcript sequence is complementary to the tag, even though the target is known to be CRISPR hosts sequence, the RNA cleavage is not prevented. Just like shown in the right half figure, the target sequence cannot escape from being killed even it is complementary to the 5′-end tag. Thus 5′-end seems not to be the key commander in discrimination, or there are other molecules hold the key? At least, another unknown issue. 

What can Synbio do?

A DNA silencing systems in bacteria, and novel RNA silencing system in archaea!!! It leaves up to you.

 

–end &&reference

  1. Barrangou, R., Fremaux, C., Deveau, H., Richards, M., Boyaval, P., Moineau, S., Romero, D. A., et al. (2007). CRISPR provides acquired resistance against viruses in prokaryotes. Science (New York, N.Y.), 315(5819), 1709-12. doi:10.1126/science.1138140
  2. van der Oost, J., & Brouns, S. J. J. (2009). RNAi: prokaryotes get in on the act. Cell, 139(5), 863-5. doi:10.1016/j.cell.2009.11.018
  3. Hale, C. R., Majumdar, S., Elmore, J., Pfister, N., Compton, M., Olson, S., Resch, A. M., et al. (2012). Essential Features and Rational Design of CRISPR RNAs that Function with the Cas RAMP Module Complex to Cleave RNAs. Molecular Cell, 1-11. Elsevier Inc. doi:10.1016/j.molcel.2011.10.023
  4. Wiedenheft, B., Sternberg, S. H., & Doudna, J. a. (2012). RNA-guided genetic silencing systems in bacteria and archaea. Nature, 482(7385), 331-338. doi:10.1038/nature10886

Copyright: The attached figures belong to publications with reference number, respectively.