Last week, Forbes had an article about the advances in genomics, which focused on the Ion Torrent sequencing platform. It’s a good overview of genomics and the Ion Torrent technology, albeit a bit much on the cheerleading side. For instance, this:
Audaciously named the Personal Genome Machine (PGM), the silicon-based device is the smallest and cheapest DNA decoder ever to hit the market. It can read 10 million letters of genetic code, with a high degree of accuracy, in just two hours. Unlike existing DNA scanners the size of mainframes and servers, it fits on a tabletop and sells for only $50,000, one-tenth the price of machines already out there. For the first time every scientist, local hospital and college will be able to afford one. If the PGM takes off and regulators let him, your family doctor could buy one–and so could you, if, say, you wanted to see how fast that thing growing in your fridge is mutating.
Invented by engineer and entrepreneur Jonathan Rothberg, such desktop gene machines could transform medicine, agriculture, nanotechnology and the search for alternative fuels. Using DNA sequencing, Rothberg says, doctors in the not-too-distant future will finger genetic weak spots in tumors and treat cancer patients with customized drugs. (This is already happening at some cancer centers.) Kids born with rare diseases will get large portions of their genome decoded to pinpoint the cause, eliminating guesswork and misdiagnoses.
Outside the lab, rescue workers in the Third World might use portable gene machines to trace bacteria or viruses causing waterborne epidemics. Airport officials could take genetic samples from travelers to track infectious bacteria and viruses before they become outbreaks. Engineers can use DNA readers to concoct designer microbes to grow future fuels. DNA sequencing will help farmers breed supercrops that grow faster, resist pests and drought and need less fertilizer. Synthetic biologists might harness bacteria to make laundry detergent, clothes, furniture, even concrete that self-heals cracks.
Sounds pretty groovy! I should get me one of these things (by the way, the statement “10 million letters of genetic code, with a high degree of accuracy, in just two hours” is why we need science and technology reporters–because they would know the PGM is conservatively about fifty times slower than current Illumina sequencing…).
And I’m copasetic with this application:
Tracking the movement of infections in hospitals, airports and public places like shopping malls to identify microbes and prevent them from becoming epidemics–that has to be a $10 billion industry. Running tab: $70 billion.
Wonder if anybody is doing this…
But I digress. The problem is that sequencing prepared DNA is the easy part. First, you have to prepare the DNA, which involves molecular biology. You have to ‘isolate’ the DNA: that is, get rid of all of the non-DNA stuff. Typically, this involves buying some kits from biotech companies (not so expensive), heating and cooling stuff (temperature controlled heating blocks), pipetting (cheap), and centrifugation. Admittedly, this is much better than the bad old days of using phenol and chloroform–wouldn’t want to play with that in your kitchen. But if you’re interested in sequencing “that thing growing in your fridge”, you’ll probably have to pay someone to do this. Although DIY centrifugation does fill me with images of people spinning around really fast in their backyards:
So now, you’ve isolated the DNA. Next, you have to prepare it for sequencing (‘library construction’). Again, more molecular biology.
So now we do the sequencing. Then we actually have to make sense of the raw and semi-processed data: a full-blown genome doesn’t just pop out of the machine. You have to assemble small sequences into a genome. Not a trivial computation problem, especially with large genomes. There’s an app for that, but you’ll need a computer and the right software. Then, once you’ve assembled your genome (or your fridge’s mold’s genome), you have to identify the genes–this is called annotation. Again, not trivial in terms of computation.
None of these things are impossible obviously (we do them routinely), and potentially, companies could do the various steps in a fee-for-service model (although whether this would be cheaper than a company performing the whole process is debatable). But there is a difference between a sequencing revolution and a genomics revolution. High-throughput sequencing is an essential component, but, to make genomics broadly accessible, it’s all of the other steps that have to be ‘personalized’ and made affordable.
Tomorrow, I’ll discuss how the Revolution Will Be Standardized (or it won’t be much of a revolution).