Regenesis (29 page)

Celera (corporate motto: “Speed matters. Discovery can't wait.”) survived, but didn't sell much of its original product (proprietary human genome data).The public probably benefited from an early end—even though the Clinton-Blair victory declaration was something of a sham. But the early end allowed us to move on to totally new methods.

By 2004 the sequencing market was feeding 13,000 of those Applera (née ABI) machines. The company maintained a monopoly on sequencing for about a decade, and had not exactly encouraged innovation, even among its users. Various users had figured out how to get more samples per machine, or better quality of automated reading, or recipes for homemade key enzymes like Taqpolymerase. Rumors spread that researchers had been sent threatening letters for some of these unauthorized applications, and that the instruments had been changed to discourage such “off-label use.”

Once the genome war ended, the real fun began. Various alternative sequencing methods had been percolating for years in the shadows of the “race for the genome.” There was the genomic/multiplex sequencing scheme that Wally and I published in 1984; sequencing by hybridization
(SBH) that Rade Drmanac and colleagues proposed in 1989 and demonstrated in 1993; polonyFiSSEQ (short for polymerase colony fluorescent in situ sequencing) in 1999; and single molecule sequencing methods championed in the early 1990s by Seq Ltd and Los Alamos. The NHGRI (the National Human Genome Research Institute) asked for input for roadmap projects to keep the genomics effort going as the HGP drew to a close, and a few of us suggested a technology goal, specifically a $1,000 human genome. Today we are actually closing in on that goal.

The sequencing field had progressed at about 1.5-fold exponential per year from 1970 to 2004, and from 2004 to 2011 accelerated to tenfold per year. Then we reached a tipping point where there was a veritable explosion, almost an epidemic, of new companies and divisions that collaborated with and/or sued each other. Here, for the record, is a list of them, fairly complete (so far as I know) as of April 2012. Already available technologies include six based on light microscopy of amplified clusters of molecules (Roche-454, CT;
AB-SOLiD
, MA; Dover Polonator, MA; Illumina, CA; Complete Genomics Inc., CA; Intelligent Bio, MA); two based on fluorescent light from single molecule (Helicos, MA; Pacific Bio, CA); and a nonoptic method (Ion Torrent, CT). Not yet available is a mix of some in R&D phase, some in the market but not for full genomes, and some abandoned (GnuBio, MA; Stratos Genomics, WA; Halcyon, CA; ZS Genetics, NH; Bionanomatrix, PA; LightSpeed, CA; GenizonBioSci, QC; LaserGen, TX; GE Global, NY; Genovoxx, Germany; Visigen/Starlight, TX; Genapsys, CA; Nanophotonics Biosci, CA; Base4innovation, UK; Mobious Genomics, UK; Reveo, NY). The six top nanopore sequencing contenders are Nabsys, RI; OxfordNanopore, UK; Electronic Biosciences, CA; IBM-Roche, NY; Genia, CA; NobleGen, MA. Nanopore technology has the questionable distinction of taking the longest time to get from idea to market starting with first patent filed in 1995 and on to the huge boost in February 2012 with the announcement at the AGBT meeting that OxfordNanopore had a handheld, disposable USB stick sequencer, called the MinION, capable of reading a billion base pairs, and a bigger sibling on the way capable of a complete human genome sequencing in fifteen minutes. (Nanopore
sequencing works by measuring the rate that ions flowing through a pore like the one in
Figure 2.1
changes as different portions of a single-stranded DNA sequence flow through it.)

In 1989 I met Craig Venter, who had invited me to the first genome sequencing meeting at the Wolf Trap conference center in Vienna, Virginia, just outside of Washington, DC. By then Craig had a brilliantly simple strategy for sequencing DNA. He was stuck at NIH, where researchers had loads of money but very little space, and great limitations on hiring people. So he brought human cDNA molecules (complementary DNAs useful for a variety of molecular-biological lab tasks) from plasmid libraries from one company (Clontech), and then sent them to another company to grow the plasmids and purify the DNA, then pay ABI (Applied Biosystems) to set up and maintain instruments that would sequence the pure plasmids. Finally he would send the data to Genbank to store in professional databases run by David Lipman and Jim Ostell, leaders in the development of cutting-edge search tools.

Thus Craig's little NIH team accomplished what other labs could not because they were struggling to develop ways to do all of these steps on their own and to minimize costs. Perhaps they felt that their peers would not fund or renew their grants if they outsourced nearly every aspect of their research, but Craig didn't buy into that penny-wise, pound-foolish dichotomy. The success of his approach surprised its numerous critics. When the project transitioned to TIGR-HGS, and NIH became concerned, I claimed that NIH shouldn't worry, since completing 95 percent of the cDNA molecules was probably harder than 95 percent of the genome since the two molecules varied wildly in abundance and, unlike the genome, cDNAs had far less evident measures of completeness. Craig responded “Thanks—I think.” Around this time I was working for CRI as a consultant. I hatched a youthful prank to slip synthetic codes into the TIGR plasmid prep pipeline that might be decoded much later. Something similar
seemed to plague a later effort to sequence DNA from pristine Atlantic Ocean samples, which instead found what looked more like Atlantic City, with genome messages in bottles resembling human sewage.

A fanatic is a person who, upon losing sight of his goal, redoubles his efforts. This is the story of EngeneOS, Codon Devices, and Gen9.The dream was to do for biology what Intel had done for electronics. In 2001, Joseph Jacobson, Eric Lander, Daniel Wang, Stephen Benkovic, and I formed the founding scientific advisory board of EngeneOS (Engineered Genetic Operating System).

The company was one of the first to be financed by the Newcogen Group (later Flagship Ventures), a venture capital firm that had been the brainchild of Noubar Afeyan. Noubar had made some big money on an invention in the field of separation science, and in his time has founded or cofounded more than twenty life sciences and technology start-ups. One of them was Celera Genomics, where Craig Venter did some of his first work on sequencing the human genome.

The EngeneOS website claimed that its “technology platform starts with the ‘source code' of Nature's operating system, embodied in the genomic sequences of various organisms. The company is combining this information with modern molecular biology techniques, engineering and design principles to develop Engineered Genomic Operating Systems. These systems will consist of component device modules supported by modeling and design tools.”

In other words, EngeneOS expected to build a library of proprietary modular components, including engineered cells and proteins, as well as hybrid devices composed of biological and nonbiological materials. These modular elements would contribute to the design and fabrication of programmable biomolecular machines with novel form and function. It was an ambitious program: start with nature's operating system, reprogram it, and collect your output in the form of fabulous new engineered organisms.

So what happened?

Nothing. EngeneOS spun off various parts of itself before it ever really got started. The final spin-off was in 2004, when I, together with Drew Endy, Keasling, and others, cofounded Codon Devices, of Cambridge, Massachusetts, to develop tools for large-scale gene synthesis, CAD, and synthetic biology applications. Codon was very much a redo of EngeneOS. Our vision was not to compete with existing custom synthetic DNA firms, but to focus on the new opportunities in complex biological systems and miniaturization of processes, analogous to VLSI (very large-scale integration) in computer chips. We started with Samir Kaul as acting CEO. He was an inspiring leader in part because he had experience in the science of genomics and had worked with Craig Venter and his team on the first genome sequence of a plant (the mustard relative,
Arabidopsis).We
cornered the market on intellectual property related to DNA error correction as well as the thought leaders in the new field, the BioFab 9 mentioned earlier: David Baker (the undisputed king of protein prediction and design), myself, Jim Collins (genetic switches), Drew Endy (T7 refactoring, iGEM, the biobrick parts registry), Joe Jacobson, Jay Keasling (metabolic engineer), Paul Modrich (mismatch repair), Cristina Smolke (riboregulators), and Ron Weiss (genetic circuits for spatiotemporal patterning).

Unfortunately, despite all this intellectual horsepower, Codon Devices too fizzled and restructured. The CEO replacing Samir really liked the idea of a short-term payoff, as did several board members, and so they emphasized the idea of competing with existing companies that were doing DNA sequencing and synthesis rather than creating a market for something that didn't exist.

Later, Codon undercut the prices of other companies, plus they had a great sales force. But the sales force was so good at bringing in orders and so good at undercutting everybody else's prices that it started operating at a loss per customer. But even though the losses were very small per customer, they started adding up.

Codon Devices was disassembled in 2009. Nevertheless, we rescued parts of it in the form of yet a third start-up try at the original concept, this time called Gen9bio Inc. The idea was to start with DNA microarray chips on which gene-size (500 to 1,000 base pair) strands of DNA could
be assembled. This sort of synthetic gene-building capacity would be used to produce both a large set of enzymes that are useful in making pharmaceuticals, and a set of constructs for optimizing overproduction of proteins in industrial-scale mammalian culture.

The company is so new that it just recently established its own web page. But it does have a few million dollars in initial financing and, of course, high hopes.

In 2001 Genomatica began as a metabolic engineering software company. Bernhard Palsson, Christophe Schilling, and others at UCSD had pursued a particularly useful brand of systems biology that combined tools from economic optimization with the detailed pathways of metabolism. The cell is like an industry, having a few choices of input materials, various ways to convert them into intermediate chemicals and, finally, end products. Given constraints on various transport and manufacturing speeds, one can adjust the entire network to maximize production of one particular product. In 2006 Genomatica morphed into a full-fledged synthetic biology company including wet lab experiments and a scale-up strategy.

The company aims to use its proprietary engineered
E. coli
bacteria to produce sustainable, green chemicals, at lower cost and with a smaller footprint than the products of conventional chemical companies. The initial chemical, Bio-BDO (1,4-butanediol), is used to make spandex, automotive plastics, running shoes, and insulation, among other things, and has a $4 billion market worldwide. The company has produced Bio-BDO at the pilot scale, and in 2011 was ramping up to demonstration-scale production. Genomatica has at least $84 million in financing and by all appearances looks to be one of the emerging leaders in the sustainable chemicals industry.

And now for a genuine and detailed synthetic genomics success story. In 2004 Jay Keasling, from the University of California–Berkeley, and one of the BioFab 9, received a grant from the Bill and Melinda Gates Foundation to make
E. coli
bacteria (and later baker's yeast) produce a precursor
drug for the antimalaria drug artemisinin. Starting at zero, a few foreign genes not found in yeast had to be found and introduced, resulting in nonzero but still minuscule amounts of a useful intermediate product. The gene was resynthesized to achieve better codon usage, and indeed this improved yield 142-fold. Next, the yeast mevalonate pathway was optimized, resulting in a 90-fold greater output. Debugging yielded another 50-fold increase. Then optimization of the methods of fermentation (not the genome) gave another 25-fold boost. Finally a very clever idea of tethering some key enzymes via a scaffold normally used for very different purposes gave a shockingly high additional 75-fold improvement. Multiplying these factors to get to a billion-fold improvement in yield says more about how low we started than about how far we have come. For the latter, the better measure is how close to the theoretical maximum we are.

A general rule of thumb for maximum yields (as seen for Dupont's PDO process; see Prologue) is 100 grams per liter and 3 grams per liter per hour. Artemisinin precursors are typically made at 1 gram per liter, so theoretically there is some room for improvement here. In 2008 Jay's company, Amyris Inc., granted a royalty-free license to this technology to pharmaceutical giant Sanofi-Aventis for the manufacture and commercialization of artemisinin-based drugs, with a goal of having them on the market by 2012.

In part due to Jay's success in bringing this previously uneconomic drug to a cost point suitable for developing nations, in 2007 British Petroleum committed $500 million for synthetic biology research on biofuels at Berkeley. (
Chapter 4
is devoted to the biofuel applications of genome engineering.)

The million-fold plummeting costs of sequencing (
Figure 7.1
) could have meant the end of profit if customers hadn't thought of something to do with the sequences. One might call it a “shovel-rush.” ABI had carefully groomed its monopoly for years and then a bunch of yahoos came in
without a plan. Remarkably, the field responded by increasing demand by more than a million-fold, as if the auto industry started selling cars for $0.03 instead of $30,000 and people responded by ordering 2 million cars per household. And begging for more! For reading DNA, some of us had confidence (since 1977) that there would be a market of between 1 and 6 billion people with 6 billion base pairs each (over 10
¹⁹
bp). The response to an analogous drop in costs of writing DNA is less well articulated—until now.