robots are working side by side to crank up the speed of nature.

They’re taking synthetic DNA, remixing it and programming microorganisms, turning these

living samples into mini-factories that could one day pump out new foods, fuels, and medicines.

Every piece of DNA here is barcoded and cataloged in what’s considered the world’s largest

genetically engineered strain bank.

This biological assembly line is at the heart of an emerging field that's raising billions

of dollars and attracting a ton of attention: synthetic biology.

We are surrounded by biology.

It's personal care products, it's the clothes we wear in the form of cotton and hemp.. it's

the houses we live in, it's gasoline, it's medicine.

And because biology is in everything, if we have the power to engineer biology, we have

the power to affect every single aspect of our life.

Nature’s had billions of years of trial and error to engineer biology and select its

best designs.

But we only just figured out how to read the source code 50 years ago.

Because every living thing - you, me, this exotic bird, that oozing amoeba - are built

from a unique set of instructions that come down to just four letters.

It's the DNA that designs what the microorganism does, it's the DNA that decides what the organism

looks like, how it acts, if it will grow or if it will not grow, it all comes down to

DNA.

But thanks to a few technology curves, we can now read, write, cut, and paste DNA faster

and cheaper than ever, creating a whole new set of instructions beyond what nature intended.

Synthetic biology is defined not by tools, but by intent.

The vast majority of biologists in the world are looking to understand something more about

nature.

And discover some secrets of nature as an end in of itself.

And that's a profoundly empowering pursuit.

What we're trying to do in synthetic biology instead is, engineer nature to do something

that we want it to.

So synthesize a vitamin.

Or detect something in the environment.

Or make a food product that you don't normally make.

If you’ve ordered an Impossible Whopper at Burger King, you’ve taken a bite of an

engineered food product.

"The "meat flavor" comes from heme, an iron containing molecule from a special soybean

protein, that was isolated from fermented yeast.

Tasty.

The goal, and the intention, is purely different.

It's to elicit a function, and create a product, create an item, create a cellular machine.

Thinking of cells as programmable machines is a convergence of biology, engineering,

and computing.

It sees the building blocks of life that form cells and then tissues and so on - as parts

that can be re-assembled, programmed, and standardized.

Just like transistors and logic gates inside a computer chip.

A computer understands zeros and ones.

That's the code.

You can see biology in very much the same way, where DNA is a code.

And if you can work with that, you can encode your organism.

This all sounds like they’re making GMOs, and you’d be right to make that association.

Synthetic biology does leverage genetic engineering as a tool in its toolkit.

But instead of engineering wheat by adding or tweaking a specific gene to make it more

drought resistant for instance, synthetic biology has the potential to turn that it

into something totally different.

You can create code that does not exist anywhere in nature.

You can make up your complete own code.

Josh and Jaide both work at Ginkgo Bioworks, a synthetic biology start-up that’s kicking

this concept into high gear.

They have unconventional titles, like organism engineer and head of design, and give much

of the lab benchwork to the robots, freeing up their time for designing and tweaking.

It's like taking a tour through the visitor's center at Jurassic Park, just swap the dino

blood for e.coli.

We did a rough count the other day, and realized that we have worked in over 50 organisms,

or so, in the last year.

Some organisms are really good at making proteins.

Some are really good at making fatty hydro-phobic molecules.

Some are good at making drugs and vitamins.

Some are really easy, genetically, to manipulate.

And so, rather than reinvent that in some organism, we want to make use of that.

Once you pick an organism you want to run with, how exactly do you engineer it to do

what you want?

At Ginkgo, it’s a classic engineering cycle: design - build - test.

I lead a group of computational biologists, and data scientists that is designing the

experiments, designing the DNA's, designing the organisms and the genotypes to support

the various organism engineering programs.

I work with the foundry to make sure that the overall vision of the organism engineering

gets fulfilled.

So step one is identify the DNA that you need, and have the DNA synthesized.

High throughput DNA synthesis means that we can actually design DNA in a computer.

And then actually have a machine make it, without us having physically stitched together

all of these different pieces of DNA in the lab.

So that's changed our ability to write DNA, and create DNA, really, really profoundly.

As a graduate student, when I was doing an experiment, I was always thinking about the

ten or the 20 samples, that I could physically handle on my own.

And fit into an apparatus to answer a question I cared about.

Here we can do things at scale.

We will design a library of a thousand or 5,000 genes, and then we can take those and

screen those all in one go, find the best candidates, and then use those to build the

best possible pathway.

After we've put a nice pathway together, we will start improving the strains.

We have protein engineers, so if we need to modify our proteins to become more efficient

or be more specific.

We can use them for that task, we have data scientists, we have experts in machine learning

and artificial intelligence.

Our foundry is basically an automated laboratory.

We have different platforms of technologies put together to be able to do everything from

generating the DNA, to putting it into strains, to growing them in fermenters and testing

how they would potentially look at in industrial scales.

Every piece of DNA ever made every container, every reagent, everything has a barcode.

For every strain we make, we generate a lot of data.

All that data will be put into our database that has been designed by our software engineers.

Right now, rough order of magnitude, I think we're doing millions of operations per month.

But even with this operational efficiency and rapid prototyping, biology is still a

messy science and they’re constantly going back to the drawing board.

For me, this makes it really fun.

A good experiment is something that tells you you were wrong.

And that's a moment when you learn something new, and when you change the plan.

So, we do it all the time.

Because there is so much knowledge we don't have, it's very much a numbers game.

The more we can test, the higher probability we have of success, and the more things we

test, the more knowledge we accumulate.

And all that knowledge can be reused for future projects.

It's a grand vision: seeing biology as a symbiotic manufacturing technology and rewiring organisms

to do what we want them to do.

This could be applied to so many problems that the potential seems limitless.

We started out many, many years ago, actually working in flavors and fragrances.

Which it seems like a little frivolous, but there's a lot of interesting biology there.

A lot of flavors and fragrances are extracted from really rare plants, that only grow in

specific climates.

Or plants that are growing extinct.

And if we can actually bring those out of luxury markets.

And make those sustainably.

Then those environments, those biomes, can actually thrive and survive.

We're trying to engineer bacteria to sense and to respond to treat complex diseases.

Some of the things I'm most excited about now, actually, are agriculture.

A lot of people don't realize it.

But about 3% of the world's carbon budget is spent making chemical fertilizer every

year.

So we started a joint venture to develop organisms that can both fix nitrogen, so basically fertilize

soil.

And form symbioses with grain crops.

We try to make biology easier to engineer, to create solutions that will help ensure

a sustainable future, not to destroy it.

Yet with this new venture comes the opposite side of the coin: the risks.

There’s still a lot we don’t understand about fundamental biology, and while nothing’s

left the lab yet for Ginkgo, scientists are tinkering with life’s building blocks and

rewriting its code right now.

What would our world look like with more synthetic organisms and products in circulation?

And with the pace and cost of these technologies becoming more accessible than ever, what’s

the risk of someone turning a synthetic organism into a dangerous pathogen?

These are open questions and challenges ahead, and will take a mix of policy experts, scientists,

and government leaders to figure out as the field speeds forward, one gene tweak at a

time.