I’m super excited to be moving Oscillator over to ScienceBlogs! Make sure to update your bookmarks and visit me over at http://scienceblogs.com/oscillator!
I like using synthetic to mean “working together”, in “real” synthetic biology as bringing together (synthesizing) a lot of components from different living things in order to create a unique whole, and in “natural” biology in terms of how every living thing must live together with others in communities made up of complex interdependent relationships. I’ve recently been reading a lot of Lynn Margulis’s work on Serial Endosymbiotic Theory (SET): how eukaryotic cells developed through multiple endosymbiotic events between different species of bacteria, with early cooperative relationships leading to intricate co-dependence and entire new domains of life. I love this picture from her article “Serial endosymbiotic theory and composite individuality” for its complexity and for highlighting how deeply connected all life on earth is. We are all synthetic communities.
Rubber can be made chemically from fossil fuels, but natural rubber from tropical trees is still the best source, and in many cases the only usable one (car tires need a lot of natural rubber for the right combination of strength and elasticity). Besides being difficult to grow and relatively inefficient, rubber trees are also facing a fungal plague that could potentially wipe out natural rubber within the next few years. Many labs (including mine) are trying to find or engineer different sources of biological polymers. According to a neat article in The Economist, two groups are working with dandelions as potential a new source of natural rubber. One group is using RNA interference to knock down the expression of a gene that makes the rubber polymers that the plant already makes difficult to process, and the other is using more traditional breeding technologies to improve rubber production, selecting and crossing high producers. Not only do dandelions already produce significant amounts already, but their fast growth and ability to grow just about anywhere (which makes them such good weeds) may make them a valuable agricultural commodity.
It’s an interesting project in many ways. Biological polymers are a fascinating and very broad subject, and understanding and engineering how enzymes make and break down these polymers will undoubtably be important for industrial biological engineering. Moreover, a sustainable biological method for producing rubber locally (instead of the current synthetic methods) will be important for environmental conservation and decreasing oil dependence.
However, this also means that there will be serious competition for rubber tree farmers, with likely many negative effects for the economies of Malaysia, Thailand, and Indonesia, the world’s top rubber producers. This has already happened, when the first round of synthetic—but not as good—rubber entered the market, as well as when indigo dyes began to be chemically synthesized, irreparably damaging the Indian dye economy. These and other issues are discussed in an interesting article by Political Scientists working at MIT, “Aspects of the political economy of development and synthetic biology” from a special issue of Systems and Synthetic Biology. These are important but often neglected aspects of the discussion of the risks and benefits of the potential applications of synthetic biology.
A great article about failure and science by Jonah Lehrer in Wired, Accept Defeat: The Neuroscience of Screwing Up. I will quote the part about the work of Kevin Dunbar studying how scientists work in their “natural environment” at length because it is awesome:
Science is a deeply frustrating pursuit. Although the researchers were mostly using established techniques, more than 50 percent of their data was unexpected. (In some labs, the figure exceeded 75 percent.) “The scientists had these elaborate theories about what was supposed to happen,” Dunbar says. “But the results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.” Perhaps they hoped to see a specific protein but it wasn’t there. Or maybe their DNA sample showed the presence of an aberrant gene. The details always changed, but the story remained the same: The scientists were looking for X, but they found Y…
The experiment would then be carefully repeated. Sometimes, the weird blip would disappear, in which case the problem was solved. But the weirdness usually remained, an anomaly that wouldn’t go away.
This is when things get interesting. According to Dunbar, even after scientists had generated their “error” multiple times — it was a consistent inconsistency — they might fail to follow it up. “Given the amount of unexpected data in science, it’s just not feasible to pursue everything,” Dunbar says. “People have to pick and choose what’s interesting and what’s not, but they often choose badly.” And so the result was tossed aside, filed in a quickly forgotten notebook. The scientists had discovered a new fact, but they called it a failure.
The reason we’re so resistant to anomalous information — the real reason researchers automatically assume that every unexpected result is a stupid mistake — is rooted in the way the human brain works. Over the past few decades, psychologists have dismantled the myth of objectivity. The fact is, we carefully edit our reality, searching for evidence that confirms what we already believe. Although we pretend we’re empiricists — our views dictated by nothing but the facts — we’re actually blinkered, especially when it comes to information that contradicts our theories. The problem with science, then, isn’t that most experiments fail — it’s that most failures are ignored.
2009 was a big year for synthetic biology in the academic press. Several journals had special issues devoted entirely to the topic, most recently Nature Biotechnology, but also Molecular BioSystems, The Journal of the Royal Society Interface, Systems and Synthetic Biology, and EMBO Reports with excellent research articles, reviews, and fascinating commentaries on economic, ethical, and social issues in synthetic biology. Beyond that Google Scholar returns over 1,000 results for “synthetic biology” in 2009, most of which I unfortunately have not had the chance to read. Of the few hundred where I at least read the abstract I have collected my favorites, the TOP 12 PAPERS IN (broadly defined) SYNTHETIC BIOLOGY OF 2009 (according to one grad student)!!! They’re numbered for convenience more than anything, I couldn’t possibly rank them more specifically, deciding on this few was hard enough. If you have favorites that I missed, please add them in the comments!
1.) A tunable synthetic mammalian oscillator, Tigges et. al. Nature, 457, 309-312.
You maybe could tell that I am partial to oscillators, the darling of synthetic biology circuits. Oscillators are cool because they are hard to make, have a clear analog in electrical engineering, are important in many natural biological systems (for a really cool article about circadian rhythms and you, check out Olivia Judson’s New York Times blog post), and could be used as a component for future synthetic systems where timing is important. This paper from Martin Fussenegger’s group is the first robust, tunable synthetic oscillator in mammalian cells; that is, individual cells will glow on and off for many cycles with a time period that can be changed by the experimenter. It’s a big step in terms of oscillator design, and future work will further improve the oscillations and allow for synchronized behavior between populations of cells.
2.) A synthetic mammalian electro-genetic transcription circuit, Weber et. al. Nucleic Acids Research, 37(4) e33.
Another paper from the Fussenegger group, this one is interesting because it brings a new input system to mammalian cell engineering: electricity. It’s not a direct electrical input, as with voltage gated channels (which I think would be cooler, but also requires using specific cell types), but uses the indirect electrochemical breakdown of ethanol to acetaldehyde to activate a synthetic gene network through a promoter that responds to acetaldehyde.
3.) Programming cells by multiplex genome engineering and accelerated evolution, Wang et. al. Nature, 460, 894-898.
Optimization of synthetic (or natural) metabolic pathways for the highest possible production of a desired product can be tedious and extremely time-comsuming work. Researchers from the Church lab at Harvard created a robot that would automatically perform cycles of mutating E. coli genomes and then selecting for cells that produce more lycopene (an important industrial chemical). In a matter of hours they were able to test billions of variations and come up with an optimized pathway that makes more lycopene than the natural system and synthetic pathways that have been more laboriously engineered. This Multiplex Automated Genome Engineering (MAGE) method has the potential to make the dream of fast, easy biological engineering a reality by automating directed evolution on a genome scale.
4.) Synthesis of methyl halides from biomass using engineered microbes, Bayer et. al. JACS, 131(18), 6508-6515.
Synthetic biology blurs the lines between species, treating natural ecosystems as bags of genes to be mined and annotated, searched and modeled, synthesized and networked. It’s hard to tell from the sequence alone though how good an enzyme from a certain species will work in your chassis, how it will cooperate with the other components in your pathway, whether it will even function at all. This paper from the Voigt lab deals with just that problem with brute force testing of ninety variants of a single enzyme, collated from genomic datasets and synthesized chemically for expression in E. coli. It’s incredible for the scope and scale, for the output—very high levels of methyl halides, precursors of many important chemicals including fuels—and for the work towards improving our understanding of enzyme function vs. sequence (and the idea that it’s going to take a lot more than bioinformatics alone to get the job done).
5.) Synthetic protein scaffolds provide modular control over metabolic flux, Dueber et. al., Nature Biotechnology, 27, 753-759.
Chemical engineers think of industrial production of chemicals in terms of pipes and vats, and genetic engineers use the language of chemical engineering in analogy: cells as “vats”, pathways as “pipelines,” with chemical intermediates passed between different enzymes that perform different chemical processes in the transition from input metabolites to useful chemicals. This paper from the Keasling lab uses a synthetic scaffold protein to capture and link together the enzymes of a particular pathway to make a more literal pipeline, drastically improving the function of the pathway be preventing “leaks” of the intermediate chemicals that are harmful to the cell. The scaffold protein itself is interesting because it is made up of proteins that control signal transduction in human cells, creating an entirely parallel system in bacteria that will not interfere with signaling or metabolism of the chassis cell. Not only that, it’s been useful for my research (maybe one of the big papers of 2010!)
6.) A synthetic genetic edge detection program, Tabor et. al. Cell, 137(7), 1272-1281.
The “bacterial camera” made with a synthetic light-sensing pathway has been around since 2005, with bacteria that turn black in response to red light, essentially
“printing” an image onto a petri dish covered in the cells. This paper improves on the old design with the addition of many new abstractable transcriptional logic components. Instead of every cell that experiences the light turning color, the bacteria only activate color production when they experience something different from their neighbors, so that only the edges of the lit-up area turn dark. It’s a neat little system, and represents a very sophisticated and compex synthetic network made up of many components.
7.) Spatiotemporal control of cell signalling using a light-switchable protein interaction, Levskaya et. al. Nature, 461, 997-1001.
Light can also be used to activate synthetic pathways in mammalian cells (!!!). This paper is great, it introduces a totally new way of interacting with mammalian cells and it introduces a new functional “part” for synthetic biology, controlling the cytoskeleton to directly alter the shape of the cell. Awesome!
8.) Systems-level engineering of nonfermentative metabolism in yeast, Kennedy et. al. Genetics, 183(1), 385-97
This one is a little biased (it’s from my lab), but it’s a neat paper that uses metabolic modeling in order to find non-intuitive gene deletions that would increase metabolic flux through the formate production pathways in yeast (formate is an industrial commodity and is can be efficiently converted to hydrogen gas by E. coli). The modeling is called flux balance analysis, which uses only steady state information about metabolism in order to find optimum “solutions” to how the cell allocates resources. It’s an interesting way to solve the problem of first of all collecting all the data and second of all having enough computational power to actually model metabolism as the dynamic system that it is, and it can be used for rapidly generating interesting hypotheses and designs for metabolic engineering.
9.) Snowdrift game dynamics and facultative cheating in yeast, Gore et. al. Nature, 459, 253-256.
This is one of my new favorite things—evolutionary dynamics of symbiosis using synthetic “ecosystems” of several species of microorganisms that “cooperate” or “cheat” by using the environment’s resources without giving other cells anything in return. It’s a fascinating look at how cooperation may be more “natural” than we think, and that evolution and natural selection don’t have to be just about bloody and selfish competition for survival. Expect a lot more about this from me in 2010!
10.) Measuring the activity of BioBrick promoters using an in vivo reference standard, Kelly et. al. Journal of Biological Engineering, 3(1).
It’s hard to believe that this paper only came out in 2009, because this kind of foundational work on characterizing BioBrick parts is so critically important for the engineering of biological systems. Almost every project in synthetic biology involves an extended period of optimization, and kinetic components such as promoter strengths are a main focus of such efforts. With a standardized, reproducible method for comparing different promoters, it will be much easier to choose parts “off the shelf” for future synthetic biology project. There is a lot more work to be done, and it will need a lot more papers (or specification sheets?) like this.
11.) Solving a Hamiltonian Path Problem with a bacterial computer, Baumgardner et. al., Journal of Biological Engineering, 3(11).
This paper comes from the 2007 Davidson-Missouri Western iGEM project, where the students used engineered genetic systems in bacteria to solve an NP complete problem. Cool!
12.) How to choose a good scientific problem, Uri Alon, Molecular Cell, 35(6), 726-728.
To round out the list, the least synthetic biology paper, but a thought-provoking, important, and wonderfully touchy-feely look at nurturing good scientists as a mentor and good advice for students for choosing interesting and important problems to study and how to go with the flow when things inevitably don’t work as planned.
That was 2009, here’s to a happy, healthy, intellectually stimulating 2010!
Synthetic biology has been used to describe many scientific activities for the past hundred years, and is still far from a concrete definition. Nature biotechnology asked 20 experts in the field how they define synthetic biology, leading to a great article that highlights many of the different pursuits of synthetic biology researchers as well as the common emphasis on engineering principles. Kristala Prather sums it up nicely in her response: “If you ask five people to define synthetic biology, you will get six answers.”