Designing and using RNA scaffolds to assemble proteins in vivo

RNA scaffolds are synthetic noncoding RNA molecules with engineered 3D folding harnessed to spatially organize proteins in vivo. Here we provide a protocol to design, express and characterize RNA scaffolds and their cognate proteins within 1 month. The RNA scaffold designs described here are based on either monomeric or multimeric units harboring RNA aptamers as protein docking sites. The scaffolds and proteins are cloned into inducible plasmids and expressed to form functional assemblies. RNA scaffolds find applications in many fields in which in vivo organization of biomolecules is of interest. RNA scaffolds provide extended flexibility compared with DNA or protein scaffolding strategies through programmed modulation of multiple protein stoichiometry and numbers, as well as the proteins’ relative distances and spatial orientations. For synthetic biology, RNA scaffolds provide a new platform that can be used to increase yields of sequential metabolic pathways.

 

Tool Developer Website Summary
mfold University of Albany http://mfold.rna.albany.edu/?q=mfold/RNA-Folding-Form RNA folding software; folding temperature and ionic conditions are fixed
NUPACK California Institute of Technology http://www.nupack.org/ RNA software suite for design and folding analysis with the option of designing RNA reaction pathways
RNA Designer University of British Columbia http://www.rnasoft.ca/cgi-bin/RNAsoft/RNAdesigner/rnadesign.pl RNA design tool using the dot-bracket format; temperature and GC content are adjustable
RBS Calculator Penn State University https://salis.psu.edu/software/ Predicts translation initiation rate in bacteria; takes into account RNA secondary structures for predictions
Nucleotide BLAST National Center for Biotechnology Information http://blast.ncbi.nlm.nih.gov/Blast.cgi BLAST compares nucleotide sequences to sequence database and calculates the statistical significance of any match
Primer-BLAST National Center for Biotechnology Information http://www.ncbi.nlm.nih.gov/tools/primer-blast/ Uses the popular primer3 engine to design primers; results are submitted to BLAST to check for unwanted endogenous match
BioNumbers Harvard Medical School http://bionumbers.hms.harvard.edu/ Registry of useful biological numbers, including genomic GC contents
genormPLUS Biogazelle http://www.biogazelle.com/genormplus/ Algorithm to determine the most stable reference genes from a set of tested candidate reference genes in a given qPCR sample panel

A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems provide bacteria and archaea with adaptive immunity against viruses and plasmids by using CRISPR RNAs (crRNAs) to guide the silencing of invading nucleic acids. We show here that in a subset of these systems, the mature crRNA that is base-paired to trans-activating crRNA (tracrRNA) forms a two-RNA structure that directs the CRISPR-associated protein Cas9 to introduce double-stranded (ds) breaks in target DNA. At sites complementary to the crRNA-guide sequence, the Cas9 HNH nuclease domain cleaves the complementary strand, whereas the Cas9 RuvC-like domain cleaves the noncomplementary strand. The dual-tracrRNA:crRNA, when engineered as a single RNA chimera, also directs sequence-specific Cas9 dsDNA cleavage. Our study reveals a family of endonucleases that use dual-RNAs for site-specific DNA cleavage and highlights the potential to exploit the system for RNA-programmable genome editing.

 

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http://www.sciencemag.org/content/337/6096/816.full

— later I’ll explain a little bit.

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.

 

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[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

RNA switch — Witch

After my vacation in Taiwan this winter, I’ve returned and found an interesting paper [1] , out of thousands of RSS feeds in my google reader. This paper comes from Christina Smolke‘s lab, and I’ve confess that sometimes I cannot help hating her, because of the outstanding researches to make the promising RNA device alive.

Smolke C. here came up with a review (probably her slides during her lab seminar? ) to give us a comprehensive introduction to the star RNA switch device.

It is self-explaining that RNA is promising in biology not just because RNA is the central role in Central Dogma. The above figure demonstrates the versatile role of RNA, sensing various stimuli, and leading to various cell behaviors.

The detailed information will be available inside the paper, and here an information I wish to convey is that: Bio-computing Time is near, or at least, promising RNA becomes valid now. Transcriptional modulation, splicing modulation, RNA stability modulation, RNAi modulation, translational modulation and even post-translational modulation, have been engineered with the help of magic witch — RNA switch.

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[1] Chang, A. L., Wolf, J. J., & Smolke, C. D. (2012). Synthetic RNA switches as a tool for temporal and spatial control over gene expression. Current Opinion in Biotechnology, 1-10. Elsevier Ltd. doi:10.1016/j.copbio.2012.01.005

 

Uploaded and Uploading to SynBio world

Synthetic Biology, an emerging interdisciplinary field, is building up a bridge to get biologists and engineers collaborated widely, science and technology merged tightly, dreams and reality synchronized fully. There are countless fascinating projects and ideas in SynBio world which are supposed to have great implication to our real world and of course, one cannot depict them in details. In addition, it is hard and also does not make sense to trace back the exact date when scientists managed to build novel bio-pathways, when living cells were hijacked by human design, and when some synthetic biology began to appear.

Here I’ll simply follow reviews from 2004 to 2011 published in Nature, and it is amazing to find that these reviews mark out the milestones of SynBio, and introduce what have been uploaded to SynBio.

Wall, M. E., Hlavacek, W. S., & Savageau, M. a. (2004). Design of gene circuits: lessons from bacteria. Nature reviews. Genetics, 5(1), 34-42.
Mukherji, S., & van Oudenaarden, A. (2009). Synthetic biology: understanding biological design from synthetic circuits. Nature reviews. Genetics, 10(12), 859-71.
Purnick, P. E. M., & Weiss, R. (2009). The second wave of synthetic biology: from modules to systems. Nature reviews. Molecular cell biology, 10(6), 410-22.
Khalil, A. S., & Collins, J. J. (2010). Synthetic biology: applications come of age. Nature reviews. Genetics, 11(5), 367-79.
Weber, W., & Fussenegger, M. (2011). Emerging biomedical applications of synthetic biology. Nature Reviews Genetics, 13(1), 21-35.
computer_life_parallel
computer parallel to life

The key words highlighted in the title precisely point out what have been accomplished in SynBio world. From the very beginning, SynBio has regarded living cells as machines. In silico, we have physical layer (electric resistance), Boolean Gates, Modules, Computers, and finally Networks. In vivo, we have Genes, Biochemical Reactions, Bio-pathways, Cell, and finally Tissues (furthermore individual bodies), respectively [1]. Systems biology shares such a point of view, however, the distinguishing goal of Synthetic biology, is to re-engineer organisms, which brings to the 2011 review — biomedical applications. More comments and typical examples are available in Synthetic Biology is on its Way to Treating Human Disease from Bio_2.0 by Eric.

Here I really want to highlight a “smart-drug” that kills targeted cancer cells, an application based on microRNA though it is 4-month “old” story. The device can first recognize HeLa cells and furthermore simultaneously induce apoptosis.

miRNA logic device

This project by Xie, etc. aims to construct a classifier marked within the dashed line shown in part D. [2] Five signals, native microRNAs in cells, are used. Two are highly and  exclusively expressed in HeLa cells, while three are in low expression. The mission of the device is to precisely recognize them so that regular cells and HeLa cells can be classified and then produce hBAX protein to induce cell death (shown in  part A).

The device runs like this, and vice-versa.

Hela_high_1 = 1; Hela_high_2 = 1;

Hela_low_1 = 0; Hela_low_2 =  0; Hela_low_3 = 0.

The output = 1. Apoptosis ON. Hela-cell DEATH.

Specifically, part B shows the logic gates for miRNA highly-expressed in HeLa cells, while part C demonstrates those in low expression. The logic gates dealing with miRNA-hela-high and miRNA-hela-low are different. For miRNA-hela-high, Xie, etc. designed a sensor motif for Hela-high markers comprising a “double-inversion” module that allows output expression only if the marker is present at/above its level in Hela cells, otherwise represses the output if the marker’s level is low. Researchers need “double-inversion” module, is because among the 2^5=32 validation experiments, some exceptions come across the undesirable leakiness problem, in other words, when the miRNA-hela-high is set NULL, the output expression is undesirably high. The “double-inversion” module manages to deal with leakiness problem after it’s been incorporated.

logic_device
Logic_device. After "computation", the delivered miRNA-mRNA device will function to induce cell death or leave it alone.

The research itself builds up a example or model. Once you can design miRNA-logic-gates to recognize and exclusively kill HeLa cells, the most widely used immortal cell line in bio-researches, you can apply the same strategy dealing with other cancer cells, which is a potential bio-medical application.

Though it’ s promising,  I guess the next step of the research group is to develop a “capsule” to deliver the miRNA-logic-gates into patients’ cells. As the research still lies in cell-level, not individual-body level, which means it has long way to go.

The rest of the miRNA-device is self-explaining. In addition, more general information about miRNA-mediated mRNA degradation can be available in this animation on Nature.

Synthetic biology is sometimes misunderstood as a duplicate of systems biology, which takes some scientists to clarify the difference and point out the synergy. [3] Now synthetic biology is no more simply a shadow of systems biology, partly because of the accomplished bio-applications.

Auxin by Imperial College London
Auxin by Imperial College London. The green light (expressed GFP) show the position of E.coli inside plant roots.

Applications in real world, win iGEM_2011 as well. In the past, most iGEM teams come up with new designs, new biobricks, new modules, but they leave the applications to “future work”. Awkward. However in 2011, “Auxin” by Imperial College London, “Make it or Break it” by University of Washington, managed to achieve promising application which shows great implications for the future. Of course you can imagine engineered E.coli stimulate plant root growth and probably address the global soil erosion issues, but you can never expect that this idea can really be put into solid ground and into practice NOW! [4] A deep and remarkable thoughts towards iGEM_2011 and applications, by Rob Carlson, is highly recommended.

I keep wondering, what is the next big move, the very next milestone of Synthetic Biology? Could it be de novo direct synthesis of full-genome, Biofuel, or Bio-computers? That leaves to you.

At last, if you want to know more about synthetic biology, this free on-line “textbook” on WikiGenes, is suggested.

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[1]  Andrianantoandro, E., Basu, S., Karig, D. K., & Weiss, R. (2006). Synthetic biology: new engineering rules for an emerging discipline. Molecular systems biology, 2, 2006.0028.doi:10.1038/msb4100073

[2]  Xie, Z., Wroblewska, L., Prochazka, L., Weiss, R., & Benenson, Y. (2011). Multi-Input RNAi-Based Logic Circuit for Identification of Specific Cancer Cells.Science, 333(6047), 1307-1311. doi:10.1126/science.1205527

[3] Smolke, C. D., & Silver, P. a. (2011). Informing biological design by integration of systems and synthetic biology. Cell, 144(6), 855-9. Elsevier Inc. doi:10.1016/j.cell.2011.02.020

[4]  http://2011.igem.org/Team:Imperial_College_London/Project_Chemotaxis_Overview