The Robot Revolution Comes to Synthetic Biology

Automation allows thousands of possibilities when building weird new organisms

Photo: Ginkgo Bioworks Robots at Work: Ginkgo Bioworks’ lab automates genetic engineering.

Last month, synthetic biologists at Ginkgo Bioworks raised their glasses—filled with genetically modified beer—to cele­brate the launch of a new automated lab. By applying engineering principles to biology, and with the help of some nifty robotic equipment, Ginkgo has created a factory for churning out exotic life-forms, the likes of which have never before been seen on this planet.

The home brew they were drinking was an example of the potential applications of synthetic biology, a new field that builds on recent progress in genetic assembly methods. Scientists can now manufacture snippets of synthetic DNA and slip them into organisms, giving those critters strange capabilities. For example, the brewer’s yeast used to make the beer for the launch party had genes from an orange tree added to its own DNA. During the fermentation stage of the brewing process, those genes caused the yeast to produce ­valencene, an organic compound with a citrusy flavor. Speaking scientifically, it was delicious.

Ginkgo Bioworks, a hip young company based in Boston, recently raised US $100 million on the promise of finding many such useful applications for synthetic biology. It used some of that cash to build Bioworks2, the company’s vast new lab that uses robotic systems to form an assembly line for organisms.

Ginkgo needs to make microbes on a grand scale in order to find those that can function as tiny biological factories for its customers. Many of the altered organisms will be duds, but through highly organized trial and error, the bioengineers will eventually devise a microbe that turns out a desired substance—like a chemical ingredient used for perfumes, beverages, pesticides, or laundry detergents.

The company’s business model centers on the microbes themselves, not the end products. “We’re not in the business of manufacturing chemicals, flavors, or fragrances,” explains Ginkgo creative director Christina Agapakis. “We specialize in the organisms, and we partner with our customers, who will make the product.” Ginkgo licenses organisms to its customers, she says, and gets royalties if they’re used.

But building an organism to spec is no easy task. Genetics still isn’t well understood; there’s no universal catalog of genes that details each one’s characteristics. Even if researchers know what a particular gene does in an orange tree, for example, when they add it to a yeast cell, it might interact with the native DNA in unexpected ways. If they’re adding several genes from different species to that yeast cell, things get even more complicated.

That’s why Ginkgo takes an engineering approach to biology, applying a rigorous design-build-test cycle to the creation of living organisms. The new lab’s extreme automation is critical to this approach, says Patrick Boyle, ­Ginkgo’s head of organism design. “In grad school, I might have taken my five best ideas and tried them out,” Boyle says. “Here we take our 1,000 best ideas, try them all out, and see which works best.”

Engineering Life

How Ginkgo Bioworks Makes Customized Critters

1: DESIGN Organism designers choose genes from a wide range of animals and plants and combine them in hundreds of different ways. Each mashup is a unique fragment of DNA. Illustration: Erik Vrielink

Design: Ginkgo designers search the scientific literature looking for genes that would cause the yeast to produce useful enzymes. The aim: When the designers feed sugar to the yeast, these enzymes should cause it to carry out chemical reactions that ultimately result in rose oil. But there is a dizzying array of genes and enzymes to consider. “If you have 100 possible enzymes that can serve as a step in a four-step pathway, that’s a lot of design space to explore,” Boyle says.

2: BUILD Robotic instruments take all these fragments and insert them into separate yeast cells. They’re integrated into the cells’ DNA and can change how the yeast function. Illustration: Erik Vrielink

Build: Ginkgo outsources the actual manufacturing of synthetic DNA. When a batch of manufactured DNA arrives at Ginkgo, liquid-handling robots build the new organisms by adding the various snippets to yeast cells. “During my Ph.D., I spent a lot of time moving tiny amounts of fluid around,” says creative director Agapakis. “When we started Ginkgo, a lot of the robots looked like eight-armed grad students—there were a lot of pipettes.” The process has ramped up as these robots have gotten more capable. Ginkgo now has liquid-handling robots that quickly move nanoliters of fluid using targeted pulses of sound.

3: TEST Ginkgo’s customers want the altered yeast to churn out specific products. Spectrometry machines analyze all the yeast cells to see if any are producing the desired output. Illustration: Erik Vrielink

Test: Once the robots have created a thousand yeast variants containing different mashups of genes, it’s time to see if the cells are making their rose oil. Mass spectrometry machines crack open the cells and examine all the molecules inside, checking for the product and also determining whether the yeast is healthy. But success on both counts doesn’t necessarily mean the organism will meet the customer’s needs. Boyle says that in the case of rose oil, Gingko studies each yeast’s overall “fragrance profile.” While a cell may be making certain useful fragrance molecules, it may be making others that are not. “I like the fresh-baked-bread smell, but it’s not great when you’re trying to sell a perfume,” Boyle says.

4: SCALE UP Ginkgo puts its best producers into bioreactors to see how they fare at industrial scale. Lessons learned help the organism designers make choices for the next round of experiments. Illustration: Erik Vrielink

Scale Up: Ginkgo adds one extra step to the typical engineering cycle, since a modified yeast cell that looks like a winner in the lab might not perform as well in the customer’s fermentation vats. In one corner of the lab, robotic systems fill and monitor rows of benchtop bioreactors, using a variety of sensors to watch the processes inside.

To understand how this works in practice, take Ginkgo’s first efforts in the perfume business. The company is working with the French fragrance maker Robertet on a yeast that spits out rose oil, because extracting the substance from rose petals is expensive.

If even their best oil-producing yeast isn’t up to spec, the company’s organism designers go back to the drawing board, using the results of the experiment to inform their next 1,000 best guesses. One of these days, Ginkgo’s bioengineers say, they’ll make the perfect batch—one that comes out smelling like a rose.

ORIGINAL: IEEE Spectrum

By ELIZA STRICKLAND

Posted 29 Nov 2016

"AI & The Future Of Civilization" A Conversation With Stephen Wolfram

"AI & The Future Of Civilization" A Conversation With Stephen Wolfram [3.1.16]

Stephen Wolfram

What makes us different from all these things? What makes us different is the particulars of our history, which gives us our notions of purpose and goals. That's a long way of saying when we have the box on the desk that thinks as well as any brain does, the thing it doesn't have, intrinsically, is the goals and purposes that we have. Those are defined by our particulars—our particular biology, our particular psychology, our particular cultural history.

The thing we have to think about as we think about the future of these things is the goals. That's what humans contribute, that's what our civilization contributes—execution of those goals; that's what we can increasingly automate. We've been automating it for thousands of years. We will succeed in having very good automation of those goals. I've spent some significant part of my life building technology to essentially go from a human concept of a goal to something that gets done in the world.

There are many questions that come from this. For example, we've got these great AIs and they're able to execute goals, how do we tell them what to do?...

STEPHEN WOLFRAM, distinguished scientist, inventor, author, and business leader, is Founder & CEO, Wolfram Research; Creator, Mathematica, Wolfram|Alpha & the Wolfram Language; Author, A New Kind of Science. Stephen Wolfram's EdgeBio Page

THE REALITY CLUB: Nicholas Carr

AI & THE FUTURE OF CIVILIZATION

Some tough questions. One of them is about the future of the human condition. That's a big question. I've spent some part of my life figuring out how to make machines automate stuff. It's pretty obvious that we can automate many of the things that we humans have been proud of for a long time. What's the future of the human condition in that situation?

"AI & The Future Of Civilization" A Conversation With Stephen Wolfram (Play Video at this link)

More particularly, I see technology as taking human goals and making them able to be automatically executed by machines. The human goals that we've had in the past have been things like moving objects from here to there and using a forklift rather than our own hands. Now, the things that we can do automatically are more intellectual kinds of things that have traditionally been the professions' work, so to speak. These are things that we are going to be able to do by machine. The machine is able to execute things, but something or someone has to define what its goals should be and what it's trying to execute.

People talk about the future of the intelligent machines, and whether intelligent machines are going to take over and decide what to do for themselves. What one has to figure out, while given a goal, how to execute it into something that can meaningfully be automated, the actual inventing of the goal is not something that in some sense has a path to automation.

How do we figure out goals for ourselves? How are goals defined? They tend to be defined for a given human by their own personal history, their cultural environment, the history of our civilization. Goals are something that are uniquely human. It's something that almost doesn't make any sense. We ask, what's the goal of our machine? We might have given it a goal when we built the machine.

The thing that makes this more poignant for me is that I've spent a lot of time studying basic science about computation, and I've realized something from that. It's a little bit of a longer story, but basically, if we think about intelligence and things that might have goals, things that might have purposes, what kinds of things can have intelligence or purpose? Right now, we know one great example of things with intelligence and purpose and that's us, and our brains, and our own human intelligence. What else is like that? The answer, I had at first assumed, is that there are the systems of nature. They do what they do, but human intelligence is far beyond anything that exists naturally in the world. It's something that's the result of all of this elaborate process of evolution. It's a thing that stands apart from the rest of what exists in the universe. What I realized, as a result of a whole bunch of science that I did, was that is not the case.