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Author: Patrick Boyle
Biology is the most powerful known manufacturing “technology.” Proof of this is all around: at the continental scale, the Earth’s land surface is defined by plant life, much of which has been harnessed with agriculture. At the nanoscale, biological systems routinely self-organize with a precision that can’t be matched by the most advanced silicon chip fabrication methods. Even nonbiological technology like petrochemistry uses building blocks that were once biological: petrochemicals, the defining building block of 20th century manufacturing, are derived from the decomposition of pre-historic biomass.
For over 4 billion years, biology has been evolving solutions that scientists and engineers are only now beginning to understand and adapt. For example,
All of these applications are advantaged by the fact that biological systems self-assemble, self-repair, and self-replicate. In effect, a microbrewery can serve as a common manufacturing platform for any number of products, simply by engineering the microbe grown in the fermenter.
These advances are possible because the tools are finally available to read (sequence) and write (synthesize) DNA. Both of these technologies have been improving at a rate faster than Moore’s law for nearly 20 years. This exponential improvement in the ability to program DNA is driving a technological revolution that rivals the computer revolution of the 20th -century—and is impacting manufacturing at a scale not seen since the industrial revolution of the 19th century.
History of Synthetic Biology
Manufacturing with biology far predates the ability to genetically engineer biology. The domestication and breeding of plants and animals for food, clothing, and other materials is synonymous with the emergence of civilization, as these biotechnologies allowed humans to settle in towns and cities with access to cultivated bio-based products.
The earliest domestication efforts were considerable engineering feats in their own right: modern corn bears little resemblance to the teosinte grass that served as the starting point for domestication (Doebley et al. 2006). Similarly, many distinct vegetables such as mustard, broccoli, cauliflower, and even kohlrabi are human-crafted variants of common ancestor species (Dixon 2017). Dogs, cattle, and other animals were similarly differentiated from their wild ancestors via selective breeding over thousands of years.
In the 20th century, the advent of genetic tools and the ability to read and write DNA allowed biologists to consider directly engineering biological organisms for the first time. Many of the early examples of genetic engineering have been extraordinarily successful: human insulin produced in microbes, developed by Genentech in the 1980s, allowed a transition away from the use of animal insulins isolated from pig and cow pancreases (Fraser 2016). In agriculture, genetically modified crops entered use in the United States in the 1990s, and today more than 90 percent of US-grown soybean, cotton, and corn is genetically modified (USDA 2019).
Simply put, biology appeared to be the only technology capable of coordinating atoms with nanometer precision into complex three-dimensional structures. For example, bacterial flagella (tail-like features that propel many bacteria) are self-assembling rotary motors, with a diameter of approximately 25 nm, that rotate at greater than 100 Hz. A typical Escherichia coli cell is about 1 µm in length and has several flagella (van den Heuvel and Dekker 2007).
It is hard to imagine how to design machines at the nanometer scale of comparable complexity without biology. Inspired by this, in the mid-1990s a group of electrical engineers, computer scientists, and biologists began to meet regularly to discuss the application of engineering principles to biology. DARPA worked with this group to convene an Information Science and Technology (ISAT) study in 1996 on “cellular computing” that laid the groundwork for the field: seeking to develop methods to understand and program DNA for the purposes of engineering biological organisms to produce new products (Knight and Matsudaira 2016).
Synthetic biology combines efforts from many fields: computer science and electrical engineering abstractions to describe cellular circuitry, metabolic engineering to engineer the metabolic pathways of cells, genetics to understand the control elements of gene expression, and systems biology to measure and simulate cellular systems, among others. Many of the principles developed in the 1996 ISAT study remain relevant to understanding the approaches and applications of synthetic biology today. In particular, a technology development roadmap from that study -predicted the development of progressively -better tools and modeling capabilities that underlie much of today’s rapidly developing synthetic biology “stack” (figures 1 and 2; Canine 2018).
Design Principles for Synthetic Biology
Two founding design principles of synthetic biology remain especially relevant: the concept of reusable parts and the engineering design cycle.
Synthetic biologists seek to identify and take advantage of modular subunits of biology as reusable parts, to allow the design of more complex systems. For example, genetic control switches such as promoters (the DNA elements that control transcription of a gene into messenger RNA), ribosome binding sites (RNA elements that control the translation of messenger RNA into protein), and other genetic parts have been repurposed to construct oscillators, logic gates, and memory circuits in cells (Boyle and Silver 2009).
The engineering design cycle breaks down the process of engineering into three stages: design, build, and test (DBT).
In contrast to other engineering disciplines, synthetic biologists engineer organisms shaped by evolution, not design. As such, the DBT process in biology requires many more iteration loops than is typical for more mature fields such as mechanical engineering (Petzold et al. 2015). Many successes in synthetic biology follow hundreds or even thousands of failed designs, and often function in only a narrow range of conditions, such as a tightly controlled fermentation tank. These challenges have led to a worldwide effort to develop better “foundries,” facilities that leverage automation to enable rapid prototyping of biological designs, often by conducting many experiments in parallel (Hillson et al. 2019). But trends in DBT technologies have accelerated progress in synthetic biology.
Systems biology, modeling of cellular systems, and data science have enabled synthetic biologists to develop better design algorithms. As in many other fields, machine and deep learning methods are being applied to large biological datasets to refine biological designs (Camacho et al. 2018).
Build technologies in biology have centered around the ability to read and write DNA, the core programming substrate for biology. Here improvement has been defined by two technologies advancing faster than Moore’s law: DNA sequencing and synthesis.
Over the past 20 years, the cost to sequence a human genome has fallen more than a millionfold, to less than $1,000 per genome (NIH 2019). This revolution in sequencing technology has led to exponential growth in the number of sequenced genomes across the tree of life, yielding novel functional parts for synthetic biologists.
Similarly, the cost of DNA synthesis has steadily decreased to today’s price of pennies per base pair (Carlson 2017). DNA synthesis is impressively cheap considering the chemistry involved, but still represents a key bottleneck to progress: imagine paying $0.07 per bit when writing a software program.
Finally, test approaches in biology often make use of cheap DNA sequencing as readouts, and new high-throughput methods for mass spectrometry are allowing researchers to measure the majority of metabolites and proteins in engineered cells (Petzold et al. 2015).
Security for Biology
Synthetic biology is the only engineering discipline where the engineers are made of the same substrate that they are engineering. Since the advent of DNA engineering technologies in the 1970s, researchers and the broader community have raised concerns about the potential misuse of engineered biology to cause harm. As early as 1975, researchers convened to consider the hazards of engineering DNA (Berg et al. 1975). In -Cambridge, Massachusetts, public hearings were held in 1976 to develop guidelines for using DNA editing technology as a research tool (Lindsay 1976). These hearings and resulting regulations (such as standard biosafety ratings) have been credited for the emergence of Cambridge and Boston as leading biotech hubs, as the regulations allowed universities and companies to perform this research in a sanctioned environment.
The rapid progress of biological research has led to continual reassessments of biosecurity (NASEM 2017, 2018; NRC 2004). Given the lessons learned in other fields of engineering—particularly in computing and constantly evolving challenges to cybersecurity—safety and security standards, methods of forensics and attribution, and design of biological safety mechanisms must be continually anticipated and addressed. Some examples of these approaches include the biosafety level (BSL) standard, screening protocols to prevent the synthesis of known harmful sequences (DHHS 2015), and deep learning research to identify engineered DNA in sequencing experiments.
Applications of Engineered Biology
Many of the current applications of engineered biology are products of engineered microbes. Microbes have a number of properties that make them useful to engineers: they exhibit fast growth rates, have many genetic tools, and can produce products at commercial scale via fermentation. Many of the early applications for synthetic biology sought to engineer microbes to produce sustainable drop-in replacements for products typically derived from petrochemicals, such as 1,3-propanediol (used in specialty polymers like DuPont’s Sorona -product), 1,4-butanediol (used in compostable plastics), -lactic acid (used to produce polylactic acid polymers), and farnesene (both a fuel and bio-rubber monomer) (Gustavsson and Lee 2016). But the commercial viability of commodity petrochemical replacements was challenged by the falling price of oil in the 2000s, leading to a pivot to higher-value products.
Today, most companies in the synthetic biology space are focusing on products such as fragrances, higher-value materials, and drugs (Schmidt 2017). Because fragrances typically command a high price but are produced in low volume, they were a natural starting point for companies seeking to develop and commercialize new biomanufactured products.
This focus has parallels with the development of synthetic chemistry as a field, which initially focused on the production of high-price low-volume synthetic dyes before expanding to other products (Yeh and Lim 2007). The approach to transfer the production of volume-limited high-value products to more scalable microbial platforms may be best exemplified by the current competition to produce cannabinoids via fermentation, with hundreds of millions of dollars invested in just the past two years (Costa et al. 2019).
Beyond drop-in chemical replacements, many new applications are emerging that are unique to biology. More energy-efficient laundry detergents are effective in cold water in part because they contain enzymes that improve stain removal (Reed 2018). And several companies, such as Indigo Ag, Pivot Bio, and (Ginkgo-affiliated) Joyn Bio, are developing microbial treatments that enhance plant growth or lower the need for conventional fertilizer (Molteni 2018).
Next-generation materials like fermented spider silk may revolutionize textiles, with both Bolt Threads in California and Spiber in Japan developing clothing made of the product (Feldman 2018). Prized for its high strength-to-weight ratio, spider silk is also being explored as a product for aerospace use via a partner-ship between the German company AMSilk and Airbus (Hyde 2018). Moving the production of silk to microbes means that the proteins that make up silk fibers can be rapidly customized to fit new applications.
Similarly, there has been a growing interest in the production of animal proteins in microbes, allowing vegan production of meat and other animal products without harm to animals. Products such as the Impossible Burger by Impossible Foods in California use microbially produced leghemoglobin protein as a replacement for the hemoglobin proteins that contribute to meat flavor (Wolf 2019). Other companies (including Ginkgo spinout Motif Foodworks) are pursuing the production of a variety of animal proteins to produce vegan dairy foods and other animal-derived products like leather. This approach is also seen as a means to provide high-protein diets more sustainably, given the high-energy requirements for animal-based meat production (Sheikh 2019).
It is impossible to predict which of the many applications of synthetic biology will come to define the field as it matures. Unlike all other fields of physical engineering, biology is unique in that it depends on a programmable substrate in the form of DNA. As such, rapid progress has been made on the basis of exponentially improving tools for reading, writing, and debugging biological systems.
It is too soon to know just where and how synthetic biology will evolve, but the stunning diversity of the natural world provides a compelling example of what can be achieved with biology.
Berg P, Baltimore D, Brenner S, Roblin RO, Singer MF. 1975. Summary statement of the Asilomar conference on recombinant DNA molecules. Proceedings, National Academy of Sciences 72(6):1981–84.
Boyle P, Silver P. 2009. Harnessing nature’s toolbox: Regulatory elements for synthetic biology. Journal of the Royal Society: Interface 6(Suppl 4):S535–46.
Camacho D, Collins K, Powers R, Costello J, Collins J. 2018. Next-generation machine learning for biological networks. Cell 173(7):1581–92.
Canine W. 2018. The synbio stack, part 1. Pleasant Hill CA: SynBioBeta. Available at https://synbiobeta.com/the-synbio-stack-part-1/.
Carlson R. 2017. Guesstimating the size of the global array synthesis market. Synthesis, Aug 30.
Costa KA, Vavitsas K, Limas M, Joseph-Nelson B, Cumbers J. 2019. Cannabinoid Fermentation: Scalability, Purity, and Sustainability. Pleasant Hill CA: SynBioBeta.
DHHS [US Department of Health and Human Services]. 2015. Screening Framework Guidance for Providers of Synthetic Double-Stranded DNA. Washington.
Dixon G. 2017. The origins of edible brassicas. Plantsman 16(3):180–85.
Doebley J, Gaut B, Smith B. 2006. The molecular genetics of crop domestication. Cell 127(7):1309–21.
Feldman A. 2018. Clothes from a Petri dish: $700 million bolt threads may have cracked the code on spider silk. Forbes, Aug 15.
Fraser L. 2016. Cloning insulin. Genentech. Available at https://www.gene.com/stories/cloning-insulin.
Gustavsson M, Lee SY. 2016. Prospects of microbial cell factories developed through systems metabolic engineering. Microbial Biotechnology 9(5):610–17.
Hillson N, Caddick M, Cai Y, Carrasco JA, Chang MW, Curach NC, Bell DJ, Le Feuvre R, Friedman DC, Fu X, and 4 others. 2019. Building a global alliance of biofoundries. Nature Communications 10(1).
Hyde E. 2018. Why is global aeronautics leader Airbus partnering with synthetic biology startup AMSilk? Pleasant Hill CA: SynBioBeta. Available at https://synbiobeta.com/why-is-airbus-partnering-with- synthet ic-biology-startup-amsilk/.
Knight T, Matsudaira P. 2016. Cellular computing, ISAT summer study, August 1996. Available at https://dspace.mit.edu/handle/1721.1/101009.
Lindsay LL. 1976. Recombinant DNA and the Cambridge City Council. Boston: State House Science Resource Office. Available at https://www.biodiversitylibrary.org/item/129417#page/6/ mode/1up.
Molteni M. 2018. Farmers can now buy designer microbes to replace fertilizer. Wired, Oct 2.
NASEM [National Academies of Sciences, Engineering, and Medicine]. 2017. Dual Use Research of Concern in the Life Sciences: Current Issues and Controversies. Washington: National Academies Press.
NASEM. 2018. Biodefense in the Age of Synthetic Biology. Washington: National Academies Press.
NIH [National Institutes of Health]. 2019. The cost of sequencing a human genome. Bethesda MD: NIH National Human Genome Research Institute. Available at https://www.genome.gov/about-genomics/fact-sheets/ Sequencing -Human-Genome-cost.
NRC [National Research Council]. 2004. Biotechnology Research in an Age of Terrorism. Washington: National Academies Press.
Petzold CJ, Chan LJG, Nhan M, Adams PD. 2015. Analytics for metabolic engineering. Frontiers in Bioengineering and Biotechnology 3(135).
Reed S. 2018. Fighting climate change, one laundry load at a time. New York Times, Jan 1.
Schmidt C. 2017. Takeaways from SynBioBeta SF 2017. Pleasant Hill CA: SynBioBeta. Available at https://-synbiobeta.com/takeaways-from-synbiobeta-sf-2017/ .
Sheikh K. 2019. Got impossible milk? The quest for lab-made dairy. New York Times, Aug 2.
USDA [US Department of Agriculture]. 2019. Recent trends in GE adoption. Washington: USDA Economic Research Service. Available at https://www.ers.usda.gov/data-products/adoption-of- genetical ly-engineered-crops-in-the-us/recent-trends-in- ge-adoption.aspx.
van den Heuvel M, Dekker C. 2007. Motor proteins at work for nanotechnology. Science 317(5836):333–36.
Wolf J. 2019. The microbial reasons why the Impossible Burger tastes so good. ASM Articles, May 16.
Yeh B, Lim W. 2007. Synthetic biology: Lessons from the history of synthetic organic chemistry. Nature Chemical Biology 3(9):521–25.
 The Finding Engineering-Linked Indicators (FELIX) program (https://www.iarpa.gov/index.php/research-programs/felix) is an initiative of the Intelligence Advanced Research Projects -Activity (IARPA).