History of the term
In 1974, the Polish geneticist Waclaw Szybalski introduced the term "synthetic biology", writing: Let me now comment on the question "what next". Up to now we are working on the descriptive phase of molecular biology. ... But the real challenge will start when we enter the synthetic biology phase of research in our field. We will then devise new control elements and add these new modules to the existing genomes or build up wholly new genomes. This would be a field with the unlimited expansion potential and hardly any limitations to building "new better control circuits" and ..... finally other "synthetic" organisms, like a "new better mouse". ... I am not concerned that we will run out exciting and novel ideas, ... in the synthetic biology, in general. When in 1978 the Nobel Prize in Physiology or Medicine was awarded to Arber, Nathans and Smith for the discovery of restriction enzymes, Waclaw Szybalski wrote in an editorial comment in the journal Gene: The work on restriction nucleases not only permits us easily to construct recombinant DNA molecules and to analyze individual genes, but also has led us into the new era of synthetic biology where not only existing genes are described and analyzed but also new gene arrangements can be constructed and evaluated. Nevertheless, the term was largely unused or abandoned until the early 21st century (e.g., SB1.0, the First International Meeting on Synthetic Biology, was held in 2004).
Biology
Biologists are interested in learning more about how natural living systems work. One simple, direct way to test our current understanding of a natural living system is to build an instance (or version) of the system in accordance with our current understanding of the system. Michael Elowitz's early work on the Repressilator is one good example of such work. Elowitz had a model for how gene expression should work inside living cells. To test his model, he built a piece of DNA in accordance with his model, placed the DNA inside living cells, and watched what happened. Slight differences between observation and expectation highlight new science that may be well worth doing. Work of this sort often makes good use of mathematics to predict and study the dynamics of the biological system before experimentally constructing it. A wide variety of mathematical descriptions have been used with varying accuracy, including graph theory, Boolean networks, ordinary differential equations, stochastic differential equations, and Master equations (in order of increasing accuracy). Good examples include the work of Adam Arkin, Jim Collins and Alexander van Oudenaarden. See also the PBS Nova special on artificial life.
Chemistry
Biological systems are physical systems that are made up of chemicals. Around 100 years ago, the science of chemistry went through a transition from studying natural chemicals to trying to design and build new chemicals. This transition led to the field of synthetic chemistry. In the same tradition, some aspects of synthetic biology can be viewed as an extension and application of synthetic chemistry to biology, and include work ranging from the creation of useful new biochemicals to studying the origins of life. Eric Kool's group at Stanford, Steven Benner's group at Florida, Carlos Bustamante's group at Berkeley, and Jack Szostak's group at Harvard are good examples of this tradition.
Engineering
Engineers view biology as a technology. Synthetic Biology includes the broad redefinition and expansion of biotechnology, with the ultimate goals of being able to design and build engineered biological systems that process information, manipulate chemicals, fabricate materials and structures, produce energy, provide food, and maintain and enhance human health and our environment . A good example of these technologies include the work of Chris Voigt, who redesigned the Type III secretion system used by Salmonella typhimurium to secrete spider silk proteins, a strong elastic biomaterial, instead of its own natural infectious proteins. One aspect of Synthetic Biology which distinguishes it from conventional genetic engineering is a heavy emphasis on developing foundational technologies that make the engineering of biology easier and more reliable. Good examples of engineering in Synthetic Biology include the pioneering work of Tim Gardner and Jim Collins on an engineered genetic toggle switch, the Registry of Standard Biological Parts, and the International Genetically Engineered Machine competition (iGEM).
Re-writing
Re-writers are Synthetic Biologists who are interested in testing the idea that since natural biological systems are so complicated, we would be better off re-building the natural systems that we care about, from the ground up, in order to provide engineered surrogates that are easier to understand and interact with. Re-writers draw inspiration from refactoring, a process sometimes used to improve computer software. Drew Endy and his group have done some preliminary work on re-writing (e.g., Refactoring Bacteriophage T7). Oligonucleotides harvested from a photolithographic or inkjet manufactured DNA chip combined with DNA mismatch error-correction allows inexpensive large-scale changes of codons in genetic systems to improve gene expression or incorporate novel amino-acids (see George Church's and Anthony Forster's lab synthetic cell projects. As in the T7 example above, this favors a synthesis-from-scratch approach.
Human practices: Emerging social, ethical, legal challenges
In addition to numerous bioscientific challenges, the vast potential of synthetic biology to play a formative role in contemporary human life raises new questions for bioethics, biosecurity, biosafety, health, energy and intellectual property. To date considerable focus has been given to the so-called dual-use challenge. For example, while the study of synthetic biology can lead to more efficient ways to produce cures (e.g. against malaria), it may also lead to synthesis or redesign of harmful pathogens (e.g., smallpox). In addition, scientists, funders, policymakers, ethicists and others have recognized challenges presented by a post 9/11 political milieu. A new range of potentially malicious actors and actions (i.e., terrorists/terrorism) must now be taken into account by those seeking to govern scientific domains; and the internet and other new media provide global access to technological know-how and scientific knowledge. Such global access cannot be addressed using existing models of nation-specific regulation.(New Scientist, November 12, 2005). Some detailed suggestions for licensing and monitoring the various phases of gene and genome synthesis are beginning to appear. Other initiatives, such as OpenWetWare, diybio, biopunk, biohack, and possibly others, take a more proactive approach towards the proliferation of open source synbio projects.
There is also an ongoing, comprehensive, and open online discussion of so-called “societal issues” online at OpenWetWare, at the SYNBIOSAFE forum on issues regarding ethics, safety, security, IPR, governance, and public perception (background document).
Recently, efforts have been made to think beyond the “societal issues” model of ethics, politics, and science in relation to synthetic biology. This effort refuses the established convention of imagining society outside of and downstream of scientific practices, such that bioethics is assigned the task of limiting the negative impact of science on society. By contrast recent approaches focus on the integral and mutually formative relations among scientific and other human practices. These human practices approaches attempt to invent ongoing and regular forms of collaboration among synthetic biologists, ethicists, political analysts, funders, human scientists and civil society activists. To date collaborative work on “governance” or “society” or “ethics” in relation to synthetic biology has largely consisted either of intensive, short term meetings, aimed at producing guidelines or regulations, or standing committees whose purpose is limited to protocol review or rule enforcement. Such work has proven valuable in identifying the ways in which synthetic biology intensifies already-known challenges in rDNA technologies. However, these forms are not suited to identifying new challenges as they emerge. An example of efforts to develop ongoing collaboration is the Human Practices component of the Synthetic Biology Engineering Research Center (SynBERC), an NSF funded collaboration among a number of leading research universities. In Europe, the multi-partner project SYNBIOSAFE, coordinated by IDC, is investigating the biosafety, biosecurity and ethical aspects of synthetic biology. The International Consortium for Polynucleotide Synthesis was formed in 2006 to encourage sharing of ideas and resources for pro-actively monitoring synthetic gene orders and enforcing safe practices, (ICPS). The recently formed Industry Association Synthetic Biology (IASB) has also started to tackle open biosecurity problems for biotech companies doing gene synthesis.
Key enabling technologies
There are several key enabling technologies that are critical to the growth of synthetic biology. The key concepts include standardization of biological parts and hierarchical abstraction to permit using those parts in increasingly complex synthetic systems. Achieving this is greatly aided by basic technologies of reading and writing of DNA (sequencing and fabrication), which are improving in price/performance exponentially (Kurzweil 2001). Measurements under a variety of conditions are needed for accurate modeling and computer-aided-design (CAD).
Sequencing
Synthetic biologists make use of DNA sequencing in their work in several ways. First, large-scale genome sequencing efforts continue to provide a wealth of information on naturally occurring organisms. This information provides a rich substrate from which synthetic biologists can construct parts and devices. Second, synthetic biologists use sequencing to verify that they fabricated their engineered system as intended. Third, fast, cheap and reliable sequencing can also facilitate rapid detection and identification of synthetic systems and organisms.
Fabrication
A critical limitation in synthetic biology today is the time and effort expended during fabrication of engineered genetic sequences. To speed up the cycle of design, fabrication, testing and redesign, synthetic biology requires more rapid and reliable de novo DNA synthesis and assembly of fragments of DNA.
In 2002 researchers at SUNY Stony Brook succeeded in synthesizing the 7741 base poliovirus genome from its published sequence, producing the first synthetic organism. This took about two years of painstaking work. In 2003 the 5386 bp genome of the bacteriophage Phi X 174 was assembled in about two weeks. In 2006, the same team, at the J. Craig Venter Institute, has constructed and patented a synthetic genome of a novel minimal bacterium, Mycoplasma laboratorium and is working on getting it functioning in a living cell.
In 2007 it was reported that several companies were offering the synthesis of genetic sequences up to 2000 bp long, for a price of about $1 per base pair and a turnaround time of less than two weeks.
Modeling
Models inform the design of engineered biological systems by allowing synthetic biologists to better predict system behavior prior to fabrication. Synthetic biology will benefit from better models of how biological molecules bind substrates and catalyze reactions, how DNA encodes the information needed to specify the cell and how multi-component integrated systems behave. Recently, multiscale models of gene regulatory networks have been developed that focus on synthetic biology applications. Simulations have been used that model all biomolecular interactions in transcription, translation, regulation, and induction of gene regulatory networks, guiding the design of synthetic systems.
Measurement
Precise and accurate quantitative measurements of biological systems are crucial to improving understanding of biology. Such measurements often help to elucidate how biological systems work and provide the basis for model construction and validation. Differences between predicted and measured system behavior can identify gaps in understanding and explain why synthetic systems don't always behave as intended. Technologies which allow many parallel and time-dependent measurements will be especially useful in synthetic biology. Microscopy and flow cytometry are examples of useful measurement technologies.
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