A conventionally sourced sea bass from a fishery.
Ever wonder why you've never heard of wild-caught organic fish? It's because there's no way to certify a food that has a mysterious history. Mike Selden, a 26-year-old biochemist with an animal lover's heart and an entrepreneur's mind, decided there must be better way to consume one of our planet's primary sources of animal protein. A way that would eliminate the need to kill billions of fish per year while also producing toxin-free, cheap, delicious fish meat for your dinner table. Enter Finless Foods, a young startup with a bold vision. Selden took time out of chauffeuring fish carcasses around San Francisco (no joke!) to share his journey with LeapsMag.
What is the biggest problem with the way fish is consumed today?
There are a lot of problems ranging from metals to animal welfare to human health. Technology is solving those problems at the same time. You've got extreme over fishing, which is collapsing ocean ecosystems and removing populations of fish that are traditionally used as food sources in developing nations.
In terms of animal welfare, fish are killed in massive numbers, billions a year. Even if people don't care too much about that, we want to give them another option.
In terms of health, which I think for most people is the most convincing argument, current fish have mercury and plastic in them. And if you're getting that fish from a farm, you will also have high levels of antibiotics and growth hormones if you're getting it from outside the U.S. What we're doing is producing fish that doesn't have any of those contaminants.
What gave you the idea to start a company around lab-grown fish?
I studied biochemistry and molecular biology at UMass Amherst, traditionally an agricultural school out in the woods of Massachusetts. I have always been an environmental activist and cared about animals. I thought, animal agriculture is so incredibly inefficient, what could be done to change it?
"The worst way you can possibly make a hamburger is with a cow."
Agriculture is a system of inputs and outputs, the inputs being feed and the outputs being meat – so why are we wasting all of this input on outputs we don't care about? Why are we creating these animals that waste all this energy through sitting around, moving around, having a heartbeat, blinking? All of this uses energy and that's valuable input.
The worst way you can possibly make a hamburger is with a cow. It's an awful transfer of energy: you have to feed it many times its own weight in food that could have fed other people or other things.
In February, I got funding from Indie Bio, a startup accelerator for synthetic biology, and moved out to San Francisco with my co-founder Brian Wyrwas. We started working in our lab in March. We're the newest company in the space.
Walk me through the process of creating edible fish in the lab. Do you have to catch a real live fish first and get their cells?
We have a deal with the Aquarium of the Bay, and whenever a fish dies, they call me, I get in a zip car, drive over, and bring the fish back to the lab, where Brian cultures it up into a cell culture. We do use real, high-quality fish stock. From there, we get the cells going in a bioreactor in a suspension culture, grow them into large quantities, and then bring them out to differentiate them into the cells people want to eat—the muscle and fat tissue. Then we formulate it and bring it to people's tables.
How long does the whole process take from the phone call about the fish dying to the food on the table?
There are two different processes: One is a research process, getting the initial cells and engineering them to be what we're looking for.
The other is a production process – we have a cell line ready and need to grow it out. That timing depends on how big of a facility we have. Since we're working with cell division: If you have 1 cell, in 24 hours, you'll have two cells. Let's say you have 1 ton of cells, in 24 hours you'll have two tons of cells.
"We want to give people the wholesome food they are used to in a healthier setting."
How are you looking to scale this process?
We're trying to find a middle ground between efficiency and local distribution. Organic farming is hilariously bad for the environment and horrifyingly inefficient, but on the other hand, industrial agriculture requires lots of transport, which is also bad for the environment. We're looking to create regionally distributed facilities which don't require a lot of transit, so people can have fresh fish even extremely far inland.
What kinds of fish are you "cooking"?
Our first product will be Bluefin tuna. It's a high-quality fish with high demand and it's also a conservation issue. We also currently have a culture going with Branzino, European sea bass, that we're really happy with.
There's a concept in science called a model organism – one that is extremely well studied and understood. Like the fruit fly, for example. For fish, it's the zebra fish, which is used for genetic research, but no one eats it. It's tiny, so we started by thinking: what fish do people eat that is also close evolutionarily to the zebra fish? We came up with carp, even though it's not too widely eaten.
But our process is very species agnostic. We've done work in trout, salmon, goldfish. Any fish with a dorsal fin works with our process. We tried a wolf eel but it didn't work. Eels are pretty far evolutionarily from fish, so we dropped that one.
From left to right, Ron Shigeta (IndieBio), Brian Wyrwas (Finless Foods), Amy Fleming (The Guardian), and Jihyun Kim (Finless Foods) tasting the first ever clean carp croquettes.
(Courtesy Mike Selden)
Why fish as opposed to, say, a cow?
Scientifically, there are a lot of advantages. Fish have a simpler structure than land animals. A fillet from a cow has complex marbling going on between the fat and muscle. When it's fish, like sashimi, it's in layers of muscle and fat. So it's simpler to build, plus fish are cold-blooded, so because they breathe underwater, our equipment needs less complexity. We don't need a CO2 line and we don't need to culture our cells at 37 degrees Celsius. We culture them at room temperature.
It's also easier to get to market since there's much higher value. Chicken in the last year was $3.84 per pound in America, whereas Bluefin tuna is between $100 and $1200 a pound. Because this is about dropping cost, we can get to market faster and give investors a better value proposition.
What's also cool is that something like Bluefin tuna is something many people haven't had the opportunity to eat. We can get these down in cost until there is price parity with any cheap conventional fish. We want to give people a choice between buying something like albacore tuna in a can –with mercury and plastic– or high-quality tuna without any contaminants for the same price.
Do you shape them like fish fillets to help the consumer overcome whatever discomfort they might feel about eating a bunch of lab-grown cells?
Yeah, people want to continue eating food they are eating, and that's fine. We want to give people a better option. We don't want to give them something weird and out there. We want to give them the wholesome food they are used to in a healthier setting that also solves some environmental issues.
How about the taste? Have you done any blind side-by-side tests with the real thing and your version?
Not blind taste tests. But we have been tasting it, and it is firmly fish. I even tried leaving it outside of the fridge – and man, that tasted like spoiled fish.
We want it to have the exact same properties as real fish. We don't want people to have to learn how to cook with it. We want them to just bring it into their homes and eat it exactly like they were doing before, but better.
What you're growing isn't the whole fish, right? It is not an actual organism?
Right, we're only growing muscle cells. It doesn't know where it is. There is no brain, nervous system, or pain receptors.
Are you the only people in this lab-grown food space working on fish?
We're the only ones doing fish so far. Other companies are doing chicken, duck, egg white, milk, gelatin, leather, and beef.
Are people generally weirded out by sci-fi lab food, or intrigued?
It's been very positive. When people sit down and talk to us, they realize it's not some crazed money grab or some weird Ted talk, it's real activists using real science trying to solve real problems. Sure, there will be some pushback from people who don't understand it, and that's fine.
When can I expect to see Finless Food at my local Whole Foods?
We plan on being in restaurants in two years, and grocery stores in four years.
What about people who aren't big fans of fish in the first place? Like those who don't eat sushi, because consuming something raw with an unknown history isn't very appetizing.
There are too many examples of food poisoning because fish are in a less clean environment than they should be, swimming around in their own fecal matter, and being doused in antibiotics so their diseases don't transmit. It's a bit of a mess. That's why as an industry, we're calling this clean meat. Fish is a healthy thing, or at least it should be, with Omega 3 and 6, and DHA. This is a way for people to continue getting those nutrients without any of the questions of where it came from. For people who are skeptical of fish, we invite you to dive in.
Brian Wyrwas, Co-Founder & CSO, and Mike Selden, Co-Founder & CEO
(Courtesy Mike Selden)
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
