Mostrando entradas con la etiqueta Genomics. Mostrar todas las entradas
Mostrando entradas con la etiqueta Genomics. Mostrar todas las entradas

jueves, 23 de febrero de 2017

10 Breakthrough Technologies 2017


These technologies all have staying power. They will affect the economy and our politics, improve medicine, or influence our culture. Some are unfolding now; others will take a decade or more to develop. But you should know about all of them right now.
  1. Reversing Paralysis 
    Scientists are making remarkable progress at using brain implants to restore the freedom of movement that spinal cord injuries take away.
  2. Self-Driving Trucks Tractor-trailers without a human at the wheel will soon barrel onto highways near you. What will this mean for the nation’s 1.7 million truck drivers?
  3. Paying with Your Face
    Face-detecting systems in China now authorize payments, provide access to facilities, and track down criminals. Will other countries follow?
  4. Practical Quantum Computing
    Advances at Google, Intel, and several research groups indicate that computers with previously unimaginable power are finally within reach.
     
  5. The 360-Degree Selfie
    Inexpensive cameras that make spherical images are opening a new era in photography and changing the way people share stories.
     
  6. Hot Solar Cells
    By converting heat to focused beams of light, a new solar device could create cheap and continuous power.
     
  7. Gene Therapy 2.0
    Scientists have solved fundamental problems that were holding back cures for rare hereditary disorders. Next we’ll see if the same approach can take on cancer, heart disease, and other common illnesses.
  8. The Cell Atlas
    Biology’s next mega-project will find out what we’re really made of.
  9. Botnets of Things
    The relentless push to add connectivity to home gadgets is creating dangerous side effects that figure to get even worse.
  10. Reinforcement Learning
    By experimenting, computers are figuring out how to do things that no programmer could teach them.

miércoles, 11 de mayo de 2016

A DNA Sequencer in Every Pocket

A biotech company is building devices that will allow people to decipher genes in remote jungles, at sea, or even in space—and they say they’re just getting started.

Zachary Bickel
Aboard the International Space Station, six people are currently orbiting the planet at 17,000 miles per hour, taking in fifteen sunrises and sunsets every day. The view is unbeatable; the floating sensation, sublime.

But good luck to them if they get sick.

There’s nothing on board the ISS that can definitively diagnose a disease, or identify the microbes behind it. Instead, sick astronauts have to settle for describing their symptoms to medical staff on the ground. They have no way of knowing for sure if their disease is bacterial, viral, or something else, or if raiding the station’s finite supply of antibiotics would do them any good.

If an astronaut could decipher the full genetic code of whatever’s plaguing her, she could identify the offending bug and work out if it’s vulnerable to any drugs. But until recently, this scenario would have been laughably impractical. Sequencers were all the size and weight of microwaves and fridges. They’d be impossible to cart aboard a space station, and probably wouldn’t have survived the trip.

Thanks to a British company called Oxford Nanopore Technologies, that’s no longer true.

In the spring of 2014, the company released a USB-powered sequencer called the MinION (pronounced “min-eye-on” not “min-ee-un,” and neither yellow nor cute). Four inches long, one inch wide, and 87 grams in weight, it’s smaller than most chocolate bars and smartphones. Earlier this year, I clutched one in my hand, with room for several more. One scientist describes it asthe DNA sequencer you can forget in your jacket pocket, which I’ve done once.

Finally, we have a sequencer that’s small enough that we can send it up into space,” says NASA engineer Kristen John. Having tested the MinION on an Earthbound flight simulator, she and her colleagues will be sending one to the ISS in June, along with some DNA samples to test. If it performs as well in microgravity as it does on the ground, astronauts could finally monitor their health in real-time, which could be crucial for future, ambitious missions. On a voyage to Mars, “we’ll lose the ability to resupply antibiotics,” says microbiologist Sarah Castro. “What we take with us is what we’ll be limited to. We’ll need to know what’s causing an infection to know how to treat it appropriately.”

With the MinION, astronauts could also do experiments to see how bacteria respond to microgravity, without first having to dunk their samples into fixatives and bring them back to Earth. And they could study microbes in the space station’s air, water, and food. “Currently, we’re telling the crew what they were eating, breathing, and drinking six months after the fact,” says Sarah Castro.

While one MinION is heading off-world, others have already traveled around the world. These tiny machines and their companion devices are set to revolutionize and democratize the world of genomics, unmooring it from well-equipped institutions and laboratories and releasing it into society at large. If Oxford Nanopore gets its way, people will be able to sequence DNA in hospitals and jungles, yachts and security checkpoints, classrooms and living rooms. But as history has shown, getting its way has never been easy.

* * *

A nanopore is exactly what it sounds like: a small hole. Typically, it’s a tiny peg-shaped protein with a hollow tube at its core, just a few billionths of a meter wide. In Oxford Nanopore’s devices, the protein sits in a synthetic membrane, submerged in liquid. When a voltage is applied across the membrane, ions flow through the pore, creating an electric current. But if something blocks the pore—say, a strand of DNA—the ions are impeded and the current drops.

The four building blocks (or bases) of DNA—A, C, G, and T—each change the current through the nanopore in different ways. By measuring that current, you can decipher the sequence of a DNA strand as it threads through the pore like a piece of ticker-tape.

This is dramatically different from traditional sequencing, where scientists have to amplify DNA molecules to create many identical copies, break those copies into small pieces, sequence the pieces individually, and finally assemble the fragmented sequences into a cohesive whole. It’s like reading a book by transcribing it, shredding it, and taping it back together. By contrast, nanopore sequencing is like reading the undamaged text from cover to cover. DNA can be sent through the hole without amplification or fragmentation, and sequenced in a long, continuous run.

Legend has it, David Deamer from the University of California, Santa Cruz, came up with the idea in 1989, while driving down California’s Interstate 5; he was reputedly so struck by it that he had to pull over to jot it down. It took a decade for him and his colleagues to show that they could capture DNA, funnel it through a nanopore, and differentiate between the various bases. And it took Oxford Nanopore almost the same amount to time to create a rugged, workable sequencer based on this technology. (Deamer and other nanopore pioneers sit on its technology advisory board.)

Founded in 2005, the company’s original plan was to produce a device very much like other sequencers—a large bulky box called the GridION that, in the words of one blogger, was “rocking the VCR-machine-circa-1992 look.” The idea of shrinking it down came from chief technology officer Clive Brown, a fidgety and outspoken man who was once described as “the most honest guy in all of next-gen sequencing.” When I ask him about the MinION’s origins, he says, “You can thank Illumina,” referring to the San Diego-based company that leads the sequencing market. “I’m desperately thinking of ways of bringing them down.

In an earlier job, Brown helped to develop a DNA sequencer for a company called Solexa that, against his wishes, was sold off to Illumina in 2007. The sale helped transform Illumina into a sequencing juggernaut, whose machines drive almost every large sequencing center in the world, giving the company an almost unshakeable monopoly on the industry. In 2009, this colossus invested $18 million in Oxford Nanopore for the right to commercialize the upstart company’s technology, and their CEO got a chance to observe ONT’s board meetings. “He poo-pooed everything I said,” says Brown. “So I’d go away and think: what is the simplest thing I can make that works, and that doesn’t look like an Illumina box.” (Illumina declined to comment for this story.) Parker predicts that sequencers will become like telescopes: a formerly boutique scientific instrument that you can now buy from a toy store.

Brown revealed the MinION to the world in February 2012, at a conference in Florida. He spent most of his time talking about the traditional GridION, only mentioning the smaller device in his last two slides. “Almost as a punchline,” he says. It was a “megaton announcement,” said one scientist. Another tweeted: “I felt a great disturbance in the force, as if a million Illumina investors cried out in pain.” One enthusiastic fellow tried to break into Brown’s hotel room.

Crucially, the MinION was an Oxford Nanopore product, through and through. It used a variation on nanopore sequencing that wasn’t covered by the company’s deal with Illumina, and the two severed their financial ties in 2013. But, meanwhile, Oxford Nanopore was also inadvertently cutting itself off from the scientific community. At Florida, Brown had claimed that the MinION would be out by the end of 2012. It wasn’t. The company was beset by manufacturing problems that led to long delays. Worse still, they went silent, costing them both credibility and support. Many alienated scientists wrote off the MinION as vaporware.

Brown was unapologetic, and reportedly took note of the critics. “Clive has a list. A list of people that says he’ll see to it won’t get a MinION when it comes out,” wrote microbiologist Nick Loman in 2013. “I can’t tell if he’s joking.” Another geneticist, who did not want to be named, told me, “There are a lot of us who are concerned about criticizing the company because our access to the technology could be arbitrarily revoked.

* * *

In 2015, the largest Ebola outbreak in history was entering its second year. More than 10,000 people had died and many more had been infected. Scientists and health workers were making solid progress at containing the epidemic, but one crucial element was missing: Ebola genomes.

By sequencing viruses in an outbreak, scientists can more effectively develop diagnostic tests and vaccines. By comparing viruses from different places and times, they can work out how many strains are at play and whether they’re mutating, and plan control measures accordingly. By comparing sequences from different patients, they can work out who is infecting whom, and curtail those routes of transmission.

But over the course of the Ebola outbreak, only a small number of viral genomes had been sequenced. The virus had struck remote regions, so samples had to be shipped to distant labs to be analyzed. Understandable, thought Nick Loman, but intolerable. Rather than waiting for outbreak samples to arrive at sequencing facilities, why not take the facility to the outbreak?

When Oxford Nanopore finally released the MinION via an early access program in February 2014, Loman was one of hundreds of scientists who signed up. In exchange for a $1,000 deposit, they got a MinION and a regular supply of flow cells—the disposable wafers that drive the sequencer, each containing 512 nanopores. These early versions were plagued by shipping problems, unreliable reagents, and technical difficulties, forcing several scientists to abandon them in frustration. But Loman persisted.

In June 2014, he used the MinION, now debugged and refined, to successfully study a Salmonella outbreak at a Birmingham hospital. And in April 2015, his student Joshua Quick travelled to Guinea with three MinIONs, inexplicably called Ribz, Chicken, and Brisket. He also brought three laptops, some chemical reagents, a centrifuge, and a thermocycler stolen from a lab mate—a mobile diagnostic laboratory that fit into just two suitcases and unfolded onto two small desks. Within two days of arriving, Quick started sequencing Ebola.

During the outbreak, the MinION proved its worth. Traditionally, scientists have to collect hundreds of samples, send them off, and wait for results to return after days or weeks—a slow process, ill-suited to the immediacy of an epidemic. But the MinION churns out results quickly; in one instance, Quick went from sample to sequence in under 24 hours. And those sequences emerge in real-time, almost as soon as the DNA strands cross the nanopores. “As that data is generated, it’s analyzable,” says Loman. “It’s a more interactive approach to sequencing.

Over six months, the team sequenced 142 Ebola genomes, which their colleagues used to monitor the last vestiges of the outbreak. As Lauren Cowley, who took over the pop-up lab from Quick, told me last year: “I saw, first-hand, epidemiologists being able to accurately track transmission routes in real time and then intercept the chain to prevent further transmission of the virus.

The World Health Organization declared the epidemic over in February 2016. But just as Ebola waned, another adversary ascended. This year’s big threat is the mosquito-borne Zika virus, which has been linked to a birth defect called microcephaly and other conditions. Zika has spread throughout the Americas and the Pacific, and once again, geneticists are playing catch-up. “There’s probably about 10 or 15 publicly available sequences,” says Loman, none of which are from northeast Brazil where the outbreak began. “It’s logistically quite difficult to access samples, and very difficult to ship them out of Brazil for sequencing,” he adds.

So once again, Loman is taking sequencers to the samples. In a month or so, his team will load a caravan with MinIONs and other laboratory equipment, and drive it around coastal Brazil, from Belem in the north to Salvador in the east. He hopes that this road trip will reveal more about Zika’s origins, how often it has entered the Americas, how it interacts with the immune system, how many strains there are, and whether it interacts with other viruses. “We have no real feel for that at the moment,” he says. “With Zika, there’s so little known.

The MinION isn’t the only option for a project like this. In 2013, one group of scientists sailed a more traditional microwave-sized sequencer around the Southern Line Islands, some of the most remote landmasses on the planet. But the MinION is so lightweight, robust, and responsive that “it just makes things easier,” says Loman. One team took it into the Tanzanian rainforest to identify frogs. Another is planning to take it aboard a marine research vessel in the Indian Ocean this summer. John and Castro are sending it into space.“We had someone who wanted to sequence poo to identify the defouling dog in their Californian neighborhood.

Despite its strengths, the MinION still doesn’t come close to competing with Illumina’s top-of-the-line sequencers in either cost or power. It can easily sequence the tiny genomes of viruses and bacteria but it’s too slow to handle the much larger genomes of animals or plants. (For comparison, the human genome is a thousand times bigger than that of the bacterium E. coli, and the wheat genome is five times bigger still.)

That may change as Oxford Nanopore rolls out Fast Mode—a hardware and software upgrade that will rev up the MinION’s speed by 4 to 7 times. The company is also launching the PromethION—the MinION’s bigger, badder cousin. Built for large-scale sequencing, its 144,000 nanopores could conceivably churn out 120 gigabytes of data every day, equivalent to 40 human genomes. The first of these beasts has already shipped, and more are set to follow.

Quality matters as much as quantity though, and concerns over low accuracy have plagued the MinION since its release. An Illumina sequencer has an error rate of just 0.1 percent. By contrast, Loman got error rates of around 10 percent in his Ebola work (although those plummeted when he read each genome several times and combined the results). “The error rate is now in single figure percentages in our hands, and we’re not at the limit,” adds Brown.

The technology also needs to be more robust. For now, the flow cells last for a couple of months—good enough for many applications but not, say, NASA’s extraterrestrial ambitions. They are costly, too: $500 each if you buy them in bulk. “If they were a fiver, that would be awesome,” says Loman. A drop of that magnitude isn’t unfeasible, but Oxford Nanopore has other financial concerns to worry about. In February, Illumina filed a lawsuit against them, claiming that they are using a particular nanopore that infringes upon Illumina’s patents—a claim that CEO Sanghera has snarkily denied. (“It is gratifying to have the commercial relevance of Oxford Nanopore products so publicly acknowledged by the market monopolist,” he said.)

Whether this means a rival nanopore sequencer is in the works is anyone’s guess. Even if Oxford Nanopore remains the only company producing such tech, and even if they can surmount their technical and legal challenges, they’ll face one final obstacle: Their little-sequencer-that-could is still reliant on the trappings of laboratory science. You can’t just drip a spot of blood or water into the flow cells; you need to prepare the sample first. That process requires chemicals and equipment like centrifuges, thermocyclers, and pipettes, not to mention training in molecular biology. And once the sequences are ready, you need specialized software and expertise to interpret the strings of As, Cs, Gs, and Ts.

Which means that the MinION can go anywhere, but it can’t be used by anyone. Or, at least, not yet.

* * *

What does VolTRAX mean?” I ask Clive Brown. “It doesn’t mean anything; I just made it up,” he answers. “The way it works here is I say we need a name, and there’s silence throughout the company. I say, ‘What about this?,’ and they all poo-poo it. I say, ‘So what are your suggestions?,’ and there’s nothing. So we go with my name, which is how we ended up with MinION.

The etymology of VolTRAX may be farcical, but its purpose is not. This domino-sized add-on for the MinION is designed to prepare a biological sample—say bodily fluids, or swabs of soil—for sequencing. It moves liquid through a network of fine channels, bombards it with chemical reagents to extract DNA, and loads that DNA into the MinION. “We spend a lot more time in the lab preparing samples than we do sequencing,” says Loman. “If, and it’s a big if, you could drop the clinical sample onto the chip that does it all for you, it would be hugely advantageous.

VolTRAX is set to go out to early users this summer. Jon Wetton, a geneticist and forensic scientist at the University of Leicester, wants to use it to fight illegal wildlife trafficking, by sequencing telltale genes that act as identity badges for different species. Conservationists have already used this technique, known as DNA barcoding, to track sources of elephant ivory or identify whale meat posing as sushi. But samples must be shipped for analysis, and “you’re looking at weeks or months to get the results back,” says Wetton. “That can’t be done on anything perishable, or if you’ve got a suspect in custody. But with an on-the-spot test, you could confiscate, arrest, or do something about it.

With a nanopore sequencer, inspectors could tell the difference between a cut of beef or bush meat from threatened apes and monkeys. They could analyze the blood on a suspected poacher’s tools to reveal the identity of the last animals it cut. They could work out if seized caviar belong to legitimate fish species or endangered sturgeon. “You could answer a whole slew of serious wildlife crime issues with the same test,” says Wetton.

That still leaves the significant problem of parsing the data, but Oxford Nanopore has a solution for that, too: an online hub called Metrichor, where people can connect to ready-made apps for analyzing DNA sequences. One such app, developed by Oxford Nanopore itself, is called “What’s In My Pot?” or WIMP. It takes sequences and identifies the organisms they belong to. The team have already field-tested it on microbes from a sewage-contaminated river behind their own building, and on unpasteurized milk from the back of a New York lorry.

Third-parties can develop Metrichor apps, too. “It’s the classic iPhone approach; you give a developer kit to anyone,” says Dan Turner, the director of applications at Oxford Nanopore. “Veterinary companies are developing an app that can check your dog’s pedigree. And we had someone who wanted to sequence poo to identify the defouling dog in their Californian neighborhood.

Since the service is cloud-based, anyone with an internet connection and a MinION, as Oxford Nanopore hopes, could, “sequence anything, anywhere.” Without either laboratories or laboratory skills, a dairy farmer could monitor the quality of their milk. An astronaut could scrutinize their air and water. A supermarket chain could check for dangerous bacteria in its food chain.“We’re entering a second age of genomics.”

Students could try their hands at sequencing, too. At Columbia University, Sophie Zaaijer recently developed a genomics course where undergraduate and masters students sequenced samples of food taken from New York restaurants, supermarkets, and Zaaijer’s lunchbox. They then identified any microbes within using WIMP. Normally, such students would only learn theory and manipulate data. This time, “they could really connect to the technology,” says Zaaijer. “They held this device, and they could see DNA being read through the pores in real-time.

Similar plans are afoot all over the world. In a survey of educators, carried out by geneticists Karen James, respondents dreamt about using nanopore sequencers to get undergraduates, school students, and members of the public to study everything from feathers in Maori cloaks, to poop from animals in safari parks, to their own snot. “If every school had a MinION and was streaming data to the internet … the implications are absolutely mind-boggling,” says Joe Parker from the Royal Botanic Gardens at Kew. “But to be attractive to a citizen scientist, the price needs to come down.

He is optimistic, though. “Ten years ago, there was some sci-fi stuff floating around about this nanopore thing. Five years ago, no one had heard from Oxford Nanopore, and many people thought they had gone away. Now, we know it definitely works. The ball’s in their court to show that they can lower their prices and scale up.

* * *

Kris Griffin was 32 when he went to his doctor with a bad back, and came away with a diagnosis of chronic myeloid leukaemia. Thankfully, two drugs—first imatinib, and now dasatinib—have kept his cancer under control with minimal side effects. Eight years on, Griffin is doing well. He’s an education consultant based in Kidderminster, England; husband to a partner he married just after his diagnosis; and father to a four-year-old boy. “I live a normal life,” he says.

He isn’t cured, though. His disease is caused by the abnormal merger of two chromosomes, creating a chimeric gene called BCR-ABL that makes his blood cells divide uncontrollably. That’s what dasatinib inhibits. To check that the drug still works, Griffin has to visit a hospital several times a year, so his doctors can measure the number of cells that carry the fused gene. The trips eat into his days, and the results can take weeks to arrive. “And there’s no bigger reminder to someone that they’re doing poorly than walking through those doors,” Griffin says.

He has always dreamed of carrying out the tests himself in the comfort of his own home, in the same way that people with diabetes can monitor their own blood sugar levels. A year ago at a London conference, he “saw this chap on stage with this little device,” he recalls. That was Clive Brown.

Brown spoke about using nanopore sequencing on people, to analyze the bits of DNA that are released into our bloodstreams by our dying cells. To cancer researchers, this circulating DNA acts as a liquid biopsy, which can reveal whether tumors are progressing, responding to treatments, or evolving resistance to drugs. Many companies, Illumina included, are getting in on the action, and developing blood-based tools for cancer screening.

But Brown thinks that if MinION and VolTRAX become cheap and accurate enough, people could monitor their circulating DNA themselves. “We need to get the price down by an order of magnitude, but there’s no reason why you couldn’t take a daily snapshot of the contents of your blood,” he tells me. He wants to bridge the worlds of DNA sequencing and the quantified self. “My intention is to give people a tool where they can understand their own biology and make their own inferences about it.” 

Griffin lit up when he heard Brown’s vision. Maybe he could eventually monitor his own BCR-ABL levels and just upload the data to his doctors. “The power it could give to patients ... Psychologically, it feels so important,” he says. He has been liaising with Oxford Nanopore ever since, and even though they’ve assured him that the technology still needs work, he is undeterred. “I want to be the guinea pig—the first person with CML to monitor my blood at home. I think this will mean everything to so many people.

Daily monitoring might also reveal signs of an infection before symptoms occur. And it might reveal answers to questions that haven’t been asked yet. “No one has systematically inventoried circulating DNA over a long period, even in just one person,” says Brown. “What’s the baseline? It’s unknown at the minute. But we can get the data.

There’s still the challenge of getting DNA out of your bloodstream and into a VolTRAX. “You want a simple, idiot-proof sampling device—some kind of pen with a consumable tip that contains all the gubbins for the nanopores,” says Brown. “You touch it to something that’s already wet—a drop of spit or a bit of food—and it does the rest for you.” It could gently prick the skin, or simply sample the fluids that leak out of capillaries and circulate between skin cells; blood sugar monitors, which Sanghera helped to pioneer, already use both methods.

A sampling device could also be used to check for viruses in air or bacteria in a food-production line. It might not even need a human operator; just program it to collect regularly, and upload the data to the cloud. That would make what Brown calls the Internet of Living Things: a network of sensors, sequencing the world.

What if you can track every beef burger? What is it, where did it come from, and what’s growing on it?” he asks. “What if every package that goes through an airport had a swab taken off it? Or the air supply in a hospital? We have interest from plant breeders who want to track what’s happening to their crops. I spoke to someone in the defense industry who wanted to detect pathogens in real-time on the London Underground.

For now, these ideas seem far-off, and perhaps far-fetched. Then again, so was the concept of a portable sequencer five years ago, or before that, the very idea of reading DNA by forcing it through a tiny hole. “Nobody believed it would work at all to start with,” says Brown. Whether Oxford Nanopore succeeds or not, Joe Parker says that their efforts will force their competitors to up their game, injecting fresh blood into a market that risks stagnation

Whatever the outcome, he foresees that we will enter a “second age of genomics,” one where sequencers will become like telescopes: a formerly boutique scientific instrument that you can now buy from a toy store. That would not only make sequencing ubiquitous, but it would vastly increase the amount of publicly available genomic information. “It’s the difference between doing astronomy with only a handful of telescopes versus everyone having one,” he says. “It changes the amount of sky you can look at.

ORIGINAL: The Atlantic 
By ED YONG
APR 28, 2016 

domingo, 13 de marzo de 2016

Craig Venter: Future Pathways for Synthetic Genomics

Is a Genomic Version of Moore’s Law in the Offing?

J. Craig Venter, Ph.D.
J. Craig Venter, Ph.D., is regarded as one of the leading scientists of the 21st century for his numerous contributions to genomic research. In addition to his past key positions, he is founder, current chairman, and CEO of the J. Craig Venter Institute (JCVI), a not-for-profit, research organization dedicated to human, microbial, plant, synthetic, and environmental genomic research, and the exploration of social and ethical issues in genomics.

Dr. Venter, who is also co-founder, executive chairman, and co-chief scientist of Synthetic Genomics (SGI) and co-founder, executive chairman, and CEO of Human Longevity, spoke to GEN.

GEN: Dr. Venter, you have been on the frontlines of genomics, synthetic genomics, and synthetic biology. Please talk about your research in synthetic biology and synthetic genomics?

Dr. Venter: JCVI’s synthetic biology program started in 1995, when my team sequenced the first genome. That same year we sequenced a second genome, the smallest one known (Mycloplasma genitalium) in collaboration with Clyde Hutchinson, who was then at the University of North Carolina. That led Clyde and I, along with our colleague Hamilton Smith, M.D., to start discussing the concept of comparative genomics and wondering what the most primitive and simplest genome that could exist would be.

That is basically how the field of synthetic genomics got started. We felt that the only way to answer this question would be to make a synthetic chromosome that contained all the necessary genes, and to use that to create a new life form.

That idea took close to 20 years to achieve. In 2010 we recorded the first synthetic cell. It involved making a synthetic version of, mostly, Mycoplasma mycoides. Although it contained a number of significant changes, it was primarily based on a pre-existing species, and with it we were able to show that the creation of a new life form was possible.

Ongoing work at JCVI with funding mainly by Synthetic Genomics (SGI), a company that was spun out of the Institute, and done together with Dan Gibson’s team at SGI, has been focusing on designing a species from scratch on the computer on first principles.

In our final design of this synthetic cell, more than 10% of the genes that are essential for life are of unknown function. That reality somewhat limits what can be done in terms of synthetic genomics. We define synthetic genomics as truly 

  • designing biological processes and genomes and then 
  • building them from scratch chemically

with the process improving as you gain more experience.

However, if we can’t design even the smallest organism based on first principles, because we don’t know what all the components do, the challenge is greater than we initially thought. This, though, should also alleviate a lot of people’s fears about the ease of being able to design super-bugs, super-organisms, and super-species. It’s proving hard to do with less than 500 genes, let alone at a much more complex level. 

GEN: Given this new reality, how are you now moving forward with your synthetic genomics program?

Dr. Venter: We are using a lot of computer metaphors and are in the process of defragging the genome. Two billion years of evolution have not been highly orderly; in fact, they’ve been quite messy. In any genome we have looked at there is not a lot of order to it except, for example, some symmetry around origins of replication that have been maintained. Despite what people used to think, that gene functions would be more organized, they tend to be scattered all over the genome based on changes that genomes have been subject to throughout evolution.

It’s analogous to what happens to a computer hard drive when it gets highly fragmented over time, with information stored haphazardly and not in any organized fashion. You can run a program to defrag your hard drive and organize the information back into files. We have been defragging the genome by rebuilding the chromosome and linking together related genes: for example, grouping all of the genes associated with glycolysis in a single cassette, and the genes associated with cell division in another cassette. In this way, future design can at least start with these cassettes. I suppose we will also have to create a cassette of genes of unknown function, at least until they get sorted out.

We think that this new fundamental cell, largely created by direct design, will be a great experimental tool. We are even thinking of creating a public contest around it and awarding a prize to whoever adds on the best evolutionary functions to the cell. This self-replicating cell represents an early, relatively primitive form of cellular life. If we add genes and complex functions to it we should be able to convert the cell into a much more complex organism.

During research I did while writing my book, Life at the Speed of Light, I came across some of the early history from researchers in the 1800s and early 1900s, where one French researcher said, essentially, give me a basic protoplasm and I will be able to recreate all of life. At that time it wasn’t known what was in the protoplasm—they didn’t know what DNA was or that proteins were discrete molecules—but the assumption was that it contained the building blocks of life.

Now we can attempt to recapitulate evolution on a much faster stage, and certainly use this ability as a very informative learning tool.

GEN: Focusing now on synthetic biology, how would you describe the progress being made and the direction in which this field is heading?

Dr. Venter: I think synthetic biology is more or less a redefinition of the field of molecular biology. And systems biology is, perhaps, a more modern term for physiology. People are largely doing the same things they were doing before, but maybe with a different goal in mind. People who were mainly doing fundamental molecular biology now claim that they are doing synthetic biology.

There are so many directions in which this could go. With the discovery of CRISPRs we have a new tool set to enable things perhaps to go faster and in a different direction than just taking straight synthetic approaches. I think the combination of CRISPRs and synthetic biology is pretty stunning.

One of the most important programs at Synthetic Genomics is the company’s collaboration with United Therapeutics, in which it is literally rewriting the pig genome to create pig organs that will survive in humans as replacement organs for transplantation, e.g., hearts, lungs, kidneys, and livers. Similar to what was done with monoclonal antibodies early on, in which they were humanized and replaced with human gene constructs, making it possible to grow human monoclonal antibodies in mice. Obviously, changing everything associated with rejection of allogeneic transplants is much more complex, but we have already had some limited success. We are literally starting at the design phase.

We have created a new, highly accurate version of the pig genome that we’ll be working with, which carries all of the genes that we have identified as being important, and we are going through and systematically changing those in the pig genome. For some of those we rewrite the gene and put a wholly new synthetic construct and a landing pad into the pig genome; whereas for others, when there are only minor edits needed between the pig and human genes, we use CRISPRs just to edit the genes and convert the pig sequence to a human sequence.

Dan Gibson at SGI made a big breakthrough early on in this process when he found that he could combine all of the different enzymes for all of the different processes in a single tube at a single temperature. This is called the “Gibson assembly,” and it allowed the process to be carried out by a robot. SGI has an instrument called the BioXp™, which is an automated DNA assembly robot that takes oligonucleotides or subsets and builds them into larger constructs. It is a commercial instrument currently being used in several labs. If we are not able to write large pieces of DNA, then there won’t be a lot of development in the field. 

"Future Pathways for Synthetic Genomics" is part 1 of a 2 part interview with Craig Venter. Part 2 will appear in the April 1 issue of GEN, and will focus on tools and technologies needed to advance synthetic genomics research.

ORIGINAL: GEN
Mar 1, 2016 (Vol. 36, No. 5)

sábado, 26 de septiembre de 2015

The War Over Genome Editing Just Got A Lot More Interesting


The cutting circle GETTY IMAGES
IF YOU WANT to drop some real DNA editing knowledge—like, I don’t know, at a party!—here’s a tip. Instead of calling the much hyped precise genome-editing tool CRISPR, call it CRISPR/Cas9. CRISPR, you see, just refers to stretches of repeating DNA that sit near the gene for Cas9, the actual protein that does the DNA editing.

Well, at least for now. Today, gene-editing scientists dropped some curious news: They’ve found a CRISPR system involving a different protein that also edits human DNA, and, in some cases, it may work even better than Cas9.

The discovery comes at a time when CRISPR/Cas9 is sweeping through biology labs. So revolutionary is this new genome editing technique that rival groups, who each claim to have been first to the tech, are bitterly fighting over the CRISPR/Cas9 patent. This new gene-editing protein called Cpf1—and maybe even others yet to be discovered—means that one patent may not be so powerful after all.

And there’s good reason to think more useful CRISPR proteins are out there. CRISPR sequences are a part of primordial immune systems, found in some 40 percent of bacteria and 90 percent of archaea. In a study published today in Cell, Feng Zhang (no relation to this writer) and colleagues trawled through bacterial genomes looking for different versions of Cpf1. They found two, from Acidominococcus and Lachnospiraceae, that can snip DNA when scientists insert them into human cells.

There are definitely many more defense systems out there, and maybe some of them might even have spectacular applications like with the Cas9 system,” says John van der Oost, a microbiologist at Wageningen University who is a co-author on the paper. “We have the feeling it’s just the tip of the iceberg.

Zhang and van der Oost’s search was deliberate, but the initial discovery of CRISPR/Cas9 as a gene-editing tool was not. Back in the 1980s, microbiologists saw strange repeating sequences in the DNA of bacteria. Those clustered regularly interspaced short palindromic repeats became CRISPR, and scientists realized they were evidence of an immune system bacteria used to defend against viruses. The spacers between the repeats are in fact snippets of viral genomes, which CRISPR-associated proteins called Cas use as “mug shots” to recognize viruses and shred their DNA.

Many different proteins are associated with CRISPR. But in the early 2010s, Emmanuelle Charpentier, who was studying the flesh-eating bacteria Streptococcus pyogenes, stumbled onto one with special powers. Her bacteria happen to carry Cas9 proteins, which have the remarkable ability to precisely cut DNA based on a RNA guide sequence. In 2012, Charpentier and UC Berkeley biologist Jennifer Doudna published a paper describing the CRISPR/Cas9 system and speculated about its genome editing capabilities. And they filed a patent application. Much more on that patent later.

The Obscure Protein
While Cas9 has driven thousands of lab experiments and millions of dollars in funding for startups trying to capitalize on the technology, Cpf1 has remained relatively obscure. This study drags Cpf1 into the limelight. “It’s a very comparable to Cas9 and it has a few different features which could be quite useful,” says Dana Carroll, a biochemist at the University of Utah.

That’s because Cas9 isn’t perfect, despite its hype as a laser-precise genome editing tool. Cpf1 offers some slight advantages. For example, when it cuts double-stranded DNA, it snips the two strands in slightly different locations, resulting in overhang that molecular biologists call “sticky ends.” Sticky ends can make it easier to insert a snippet of new DNA—say, a different version of a gene—though the Cell paper does not actually show data directly comparing Cas9 and Cpf1 when inserting DNA.

Cpf1 is also physically a smaller protein, so it may be easier to put into human cells. It requires only one RNA molecule instead of two, with Cas9. But it’s not a rival so much as a complementary tool: The two proteins favor binding to different locations in the genome, so together, they might allow more flexibility in where scientist want to cut.

But Cpf1 has implications reaching far outside the lab.

Patent Wars
Not long after Doudna and UC Berkeley filed a patent, the Broad Institute and MIT filed their own patent on behalf of Zhang for the CRISPR/Cas9 system. Zhang had been working on actually showing that CRISPR/Cas9 can edit mammalian genomes in mammalian cells, an application he published in 2013 and says he came up with independently. The Broad’s and MIT’s attorney paid a fee to accelerate their application. Ultimately, the US Patent and Trademark Office awarded the patent to Zhang, MIT, and the Broad Institute. The University of California, obviously unhappy with the decision, filed an application for an interference proceeding to get the USPTO to reconsider. That process is ongoing.

But biotech companies have raced ahead to develop therapeutics and techniques with the system. Feng and Doudna have since licensed their technology to rival companies, Editas and Caribou. Charpentier also cofounded Crispr Therapeutics in Switzerland. Whoever wins the patent dispute will have a monopoly on CRISPR/Cas9 technology, the hottest new thing in biotech.

But with Cfp1, the stakes of that specific patent dispute go down. A lab or company could use Cfp1 without infringing on the CRISPR/Cas9 patent. “It takes power away from whoever the winner is going to be,” says Jacob Sherkow, a professor at New York Law School1 (Zhang has indicated the rights to Cpf1 may not necessarily go to the company he cofounded, Editas.) Whether a CRISPR/Cfp1 system is patentable as a separate invention—Sherkow says it probably is—perhaps isn’t even relevant because its very existence means Cas9 is no longer the only game in town.

And if biologists keep trawling through bacterial genomes, they might find even more proteins to join Cfp1 and Cas9. Who knows what else is hiding in the genomes of microbes?

ORIGINAL: Wired
09.25.15

jueves, 20 de agosto de 2015

Google Won The Internet. Now It Wants to Cure Diseases

Click to Open Overlay Gallery RAFE SWAN/GETTY IMAGES

WHEN GOOGLE CO-FOUNDER Larry Page dropped his now-famous blog post revealing that Google was reorganizing itself as Alphabet, one of the most striking things was what he chose to highlight as the kind of work these newly independent non-Google companies would be pursuing.

The companies that are pretty far afield of our main Internet products [are] contained in Alphabet instead,” Page wrote in the blog post announcing Alphabet’s existence. “Good examples are our health efforts: Life Sciences (that works on the glucose-sensing contact lens), and Calico (focused on longevity).

Google has long dabbled in medicine, but Page’s announcement signaled that he wants biomedical research to be more than just a side project for his newly christened company. Behind the scenes, efforts were already well under way to transform Google into a place that was serious about life sciences.

Under Alphabet, life sciences will become its own independent division, though it doesn’t have an official name just yet. (The company says to expect more news soon.) But a few hints suggest the life sciences group had been operating fairly independently already. Last month, CFO Ruth Porat singled out life sciences during a quarterly earnings call as one of the areas Google sees as “longer-term sources of revenue.” To get there, the company has been quietly recruiting top scientific talent, from immunologists to neurologists to nanoparticle engineers.

Google Life Sciences is focused on shifting health care from a reactive, undifferentiated approach to a proactive, targeted approach,” reads one of the company’s recent job listings. Biomedical researchers at Google will work to transform the “detection, prevention, management and even our basic understanding of disease,” the company says. In other words, just like everything else it does, the company once known as Google intends to train its outsized ambition on fixing the most basic problems afflicting human health.

Building An Infrastructure
For the past two years, Google’s life science efforts have been headed up by Andrew Conrad, previously the chief scientific officer at LabCorp and the co-founder of the National Genetics Institute. He leads more than 150 scientists who come from fields as wide-ranging as astrophysics, theoretical math, and oncology. “Our central thesis was that there’s clearly something amiss in Western medicine,” Conrad told Steven Levy of Backchannel back in October.

Sam Gambhir, a professor of radiology, bioengineering, and materials science at Stanford University who has collaborated with Conrad since before Google Life Sciences was a formal division within Google X, says the division isn’t just playing around. Gambhir says projects on which he’s partnered with Google’s life sciences team include the use of nanotechnology to improve diagnostics as well as devices to continuously monitor biomarkers.

They’re systematically building an infrastructure to tackle things in-house as well as collaborate with multiple universities,” Gambhir tells WIRED. “It’s a very serious effort, and it seems to have always been supported from the very top of the company.

Tackling Chronic Disease
One of the longest-standing efforts has been a project to develop new ways of diagnosing and treating diabetes. Last year Google unveiled a smart contact lens diabetics can use to read blood sugar levels through the tears in their eyes. Pharmaceutical giant Novartis announced that it would license the smart lens tech from Google, and the two companies are exploring other uses for the tech. Just this month, Google announced it was partnering with Dexcom, a glucose-monitoring company, to focus on making a continuous glucose monitor that’s cheaper, more convenient than current solutions, and disposable, the company said.

Google is also diving deep into genomics. Gambhir says a committee of scientists from Google, Duke University, and Stanford University have been meeting multiple times a week for about a year now to work on the design of what Google has called its Baseline Study, a project that will ultimately collect anonymous genetic information from 10,000 people to create a “baseline” picture of what a healthy human being looks like on a molecular level. Gambhir, a collaborator on the project, says Baseline is intended to be a “longitudinal study on human health to understand the transition from health to disease.

Other work on the molecular level include a cancer-detecting pill that pairs with a wristband, all part of what Google called its “nanoparticle platform.” Part of getting the wearable to work correctly included understanding how light passed through skin, which led Conrad and his team to make artificial human skin. Life Sciences is looking at other chronic diseases, too. In January, Conrad told Bloomberg that the team planned to partner with multiple sclerosis drugmaker Biogen to study environmental and biological contributors to the disease’s progression.

Ageless Problems
Last September, Google bought Lift Labs, maker of Liftware—a high-tech spoon designed to help people with neurodegenerative tremors eat. But Google wouldn’t be Google (er, Alphabet wouldn’t be Alphabet) if it was just concerned with addressing the symptoms of disease. Aging itself is another problem it hopes to disrupt. Calico, which is organizationally separate from the life sciences group, aims to maximize the human lifespan by preventing aging. The life sciences division, meanwhile, is focused on staving off diseases that could interfere with Calico’s goal. Neither of those efforts seems very closely tied to Google’s original business model of targeting ads to users based on Internet searches. Now that life sciences have become independent under Alphabet, it looks like they don’t have to be.


ORIGINAL: Wired
08.19.15 

miércoles, 20 de mayo de 2015

Can We Identify Every Kind of Cell in the Body?

A microscopic quest to find out what we’re really made of.

WHY IT MATTERS
There is still no accurate atlas of human cell types.
A microfluidic device (at center) can carry out experiments on individual cells.
How many types of cells are there in the human body? Textbooks say a couple of hundred. But the true number is undoubtedly far larger.

Aviv Regev. Regev received her M.Sc. from Tel Aviv University, studying biology, computer science, and mathematics in the Interdisciplinary Program for the Fostering of Excellence. She received her Ph.D. in computational biology from Tel Aviv University. Photo: Broad Institute
Piece by piece, a new, more detailed catalogue of cell types is emerging from labs like that of Aviv Regev at the Broad Institute, in Cambridge, Massachusetts, which are applying recent advances in single-cell genomics to study individual cells at a speed and scale previously unthinkable.

The technology applied at the Broad uses fluidic systems to separate cells on microscopic conveyor belts and then submits them to detailed genetic analysis, at the rate of thousands per day. Scientists expect such technologies to find use in medical applications where small differences between cells have big consequences, including cell-based drug screens, stem-cell research, cancer treatment, and basic studies of how tissues develop.

Regev says she has been working with the new methods to classify cells in mouse retinas and human brain tumors, and she is finding cell types never seen before. “We don’t really know what we’re made of,” she says.

Other labs are racing to produce their own surveys and improve the underlying technology. Today a team led by Stephen Quake of Stanford University published its own survey of 466 individual brain cells, calling it “a first step” toward a comprehensive cellular atlas of the human brain.

Such surveys have only recently become possible, scientists say. “A couple of years ago, the challenge was to get any useful data from single cells,” says Sten Linnarsson, a single-cell biologist at the Karolinska Institute in Stockholm, Sweden. In March, Linnarsson’s group used the new techniques to map several thousand cells from a mouse’s brain, identifying 47 kinds, including some subtypes never seen before.

Historically, the best way to study a single cell was to look at it through a microscope. In cancer hospitals, that’s how pathologists decide if cells are cancerous or not: they stain them with dyes, some first introduced in the early 1900s, and consider their location and appearance. Current methods distinguish about 300 different types, says Richard Conroy, a research official at the National Institutes of Health.

Individual cells are captured and separated in bubbles of liquid, readying them for analysis.
The new technology works instead by cataloguing messenger RNA molecules inside a cell. These messages are the genetic material the nucleus sends out to make proteins. Linnarsson’s method attaches a unique molecular bar code to every RNA molecule in each cell. The result is a gene expression profile, amounting to a fingerprint of a cell that reflects its molecular activity rather than what it looks like.

Previously, cells were defined by one or two markers,” says Linnarsson. “Now we can say what is the full complement of genes expressed in those cells.

Although researchers determined how to accurately sequence RNA from a single cell a few years ago, it’s only more recently that clever innovations in chemistry and microfluidics have led to an explosion of data. A California company, Cellular Research, showed this year that it could sort cells into micro-wells and then measure the RNA of 3,000 separate cells at once, at the cost of few pennies a cell.

Scientists think the new single-cell methods could overturn previous research findings. That is because previous gene expression studies were based on tissue samples or blood specimens containing thousands, even millions, of cells. Studying such blended mixtures meant researchers were seeing averages, says Eric Lander, head of the Broad Institute.

Single-cell genomics has come of age in an unbelievable way in just the last 18 months,” Lander told an audience at the National Institutes of Health this year. “And once you realize we are at the point of doing individual cells, how could you ever put up with a fruit smoothie? It is just nuts to be doing genomics on smoothies.

Lander, one of the leaders of the Human Genome Project, says it may be time to turn pilot projects like those Regev is leading into a wider effort to create a definitive atlas—one cataloguing all human cell types by gene activity and tracking them from the embryo all the way to adulthood.

It’s a little premature to declare a national or international project until there’s been more piloting, but I think it’s an idea that’s very much in the air,” Lander said in a phone interview. “I think [in two years] we’re going to be in the position where it would be crazy not to have this information. If we had a periodic table of the cells, we would be able to figure out, so to speak, the atomic composition of any given sample.

Gene profiles might eventually be combined with other efforts to study single cells. Paul Allen, Microsoft’s cofounder, said last December he would be spending $100 million to create a new scientific institute, the Allen Institute for Cell Science It will study stem cells and video their behavior under microscopes as they develop into various cell types, with the ultimate goal of creating a massive animated model. Rick Horwitz, who leads that effort, says that it will serve as a kind of Google Earth for exploring a cell’s life cycle.


The eventual payoff of collecting all this data, says Garry Nolan, an immunologist at Stanford University, won’t be just a catalogue of cell types, but a deeper understanding of how cells work together. “The single-cell approach is a way station that needs to be understood on the way to understanding the greater system,” he says. “In 50 years, we’ll probably be measuring every molecule in the cell dynamically.

ORIGINAL: MIT Tech Review
May 18, 2015