SYNTHETIC BIOLOGY DEPENDS ON AUTOMATION
Genomics has been the focal point of life sciences research over the past decade, enabling a better understanding of disease beyond its physical manifestation and into its underlying drivers. This has opened significant opportunities across the therapeutic spectrum in both disease diagnosis and treatment. These advances would not have been possible without the immense progression in underlying DNA sequencing technology.
The first human genome sequence was completed in 2003, a project that lasted almost 15 years at a $3 billion dollar expense. Within the decade, the cost of sequencing an entire genome dropped from millions to merely thousands, a dramatic 500-fold reduction in cost. Beyond total expense, advances in speed are equally indicative of progress in the field with work that can now be completed on the scale of days as opposed to years. Advents in NGS technology continue to push the boundaries of cost and time forward as companies innovate to achieve devices with greater efficiency, storage and computing power.
Despite this capacity to inexpensively and rapidly determine entire sequences of existing genomes, our ability to synthesize DNA still lags behind. Today, it’s estimated that roughly 3,000 times more DNA is sequenced vs. synthesized, a phenomenon known as the DNA read-write gap. This differential can be attributed to several factors spanning technology to market dynamics. First and foremost, producing or “writing” DNA with single nucleotide precision is a technically complex feat and limits the length of dependable sequences that can be manufactured. Individual oligonucleotides are first produced and are then assembled to create longer constructs, increasing both time requirements and opportunity for error. Like sequencing, this technology has a much higher cost profile in its nascent stage: synthesizing just a thousand nucleotides today runs over $100 while millions of nucleotides can be sequenced, or read, for just cents.
An offset in the underlying market drivers for sequencing and synthesizing technologies has also contributed to the current (and likely temporary) gap in DNA read-write. While widespread demands for screening and diagnostics propelled sequencing forward, newer fields such as synthetic biology are stimulating the catch up in our capacity to write DNA. The rationale for innovation in DNA synthesis is clear: leveraging synthetic biology techniques, living systems can be transformed to produce desired outputs in vivo. Biological parts and complete devices can be constructed from scratch to improve the throughput and energy efficiency of manufacturing products that are in demand today. This has the capacity to dramatically evolve food, agriculture, chemicals and health industries, just for some initial examples.
DNA synthesis remains a key rate-limiting step in this paradigm. To achieve sufficient scale and widespread adoption, the growth in the magnitude of DNA synthesized must outpace the cost additions made to do so. As an alternative to increasing labor (with unfavorable cost: output implications), robotics and automation have a key role to play in this evolution. Automation addresses both the cost efficiency and performance of DNA writing. With integrated systems and devices such as liquid handlers, multiplex approaches can be efficiently implemented to enable the synthesis of thousands of DNA constructs in parallel, yielding commercial-scale production volumes. As another perk, this creates an environment with reduced capacity for human error to improve the accuracy thresholds of this manufacturing. In sum, automation can dramatically increase the output of quality DNA product without raising the incremental cost of doing so.
Leading synthetic biology companies are already evidence of these trends having adopted automation into their production laboratories, positioning them at the forefront of the commercially-scaled biological factory. While Twist Biosciences uses automation for the direct production of DNA, Gingko Bioworks applies this technology to design the organisms that serve as the mini factories of the future: the biological devices themselves. The transformative potential of DNA writing is clear and its evolution is likely analogous to the rapid development of DNA sequencing. As market dynamics further grow demand for scaled DNA production, enabling automation technologies will be the focal point to close the DNA read-write gap.
