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)
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”
