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/

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

DNA Nanotechnology Kills Cancer

Here I recommend you a wonderful bio-app, named: caDNAno. The open-source software, caDNAno,  will enables you  design  three-dimensional
DNA origami nanostructures. You can fold your DNA in any shapes. One of the features is no programming required, thus even our kids can give it a try, and perhaps can get a Science paper published [1].

What will DNA origami do?

Drug loaded and kill cancer cells. DNA is known to carry the genetic information, but here DNA changes its faces. No more genetic codes. Since the four basic bricks of DNA, A, T, G and C, will bind in pairs (A-T, G-C) according to Watson-Crick base paring principles, scientists could use the principle and engineer the DNA self-assembly to get designed 3-D structures, for example, a medicine capsule.

How does DNA robot work?

First we need drug loaded. When DNA is designed to a box with the help of caDNAno for example, it can be loaded with drugs, which is easy.

Second part, killing target without fault, is tough and tricky, just as quoted from the author.

Whether or not these structures will work in a living organism remains to be seen. For one thing, they are designed to communicate with molecules on a cell’s surface. “If your therapeutic target is inside the cell, it’s going to be tricky,” says Bachelet, a postdoctoral fellow at Harvard Medical School in Boston, Massachusetts, and one of the authors of the study [1].

One method to achieve target-killing, in my mind, is still to use the base paring principles. DNA nano-box per se is made up of four bases, thus a sequence can be designed as a switch to open or keep locking the nano-box.

Is it safe? 

This is question is inevitable though I don’t want to expand. DNA nano-robot, is intrinsic DNA sequence, thus it is sensitive to DNase, enzyme to degrade DNA. Once DNA nano-robots are destroyed, which is quite easy, the payload will be leaked out to be harmful to nearby cells and tissues.

What can DNA nanotechnology do? 

DNA nanotechnology can be applied to bio-computing and shows great promise. Qian, researches at California Institute of Technology, built up a bio-computing network based on DNA chain displacement. It is straightforward to watch the introduction video provided in the original paper [2].

 

 

DNA nanotechnology has a long way to go, nevertheless it shows promise in bio-computing and future therapeutics.

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[1] Douglas, S. M., Bachelet, I., & Church, G. M. (2012). A Logic-Gated Nanorobot for Targeted Transport of Molecular Payloads. Science, 335(6070), 831-834. doi:10.1126/science.1214081

[2] Qian, L., & Winfree, E. (2011). Scaling Up Digital Circuit Computation with DNA Strand Displacement Cascades. Science, 332(6034), 1196-1201. doi:10.1126/science.1200520