How one biotech startup is betting on cows and winning over investors

Cow burps are a climate problem, and one startup wants to reprogram them. Hoofprint Biome is using enzymes to rewire the cow’s microbiome from the inside out, cutting methane production and improving feed efficiency along the way. The company just raised a $15 million Series A round from investors including Amazon’s Climate Pledge Fund, and they’re just getting started. Today on TechCrunch’s Equity podcast, Tim De Chant sat down with Kathryn Polkoff, co-founder and CEO of Hoofprint Biome, to talk through it all. Listen to the full episode to hear about: How enzymes and AI are helping fight climate change (seriously). What it takes to raise money for biotech in a sea of SaaS. Why thinking like a farmer, rather than a climate scientist, was Polkoff’s superpower. As she put it, “That’d be like if you were engineering a car but had never changed the engine — that’s where all the energy comes from.” The future of methane reduction and feed efficiency at scale. Equity will be back Friday with our weekly news roundup, so stay tuned. Equity is TechCrunch’s flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday. Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. For the full episode transcript, for those who prefer reading over listening, check out our full archive of episodes here. Credits: Equity is produced by Theresa Loconsolo with editing by Kell. We’d also like to thank TechCrunch’s audience development team. Thank you so much for listening, and we'll talk to you next time. Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Anthony Ha?

  This episode of Equity is brought to you by Schneider Electric. Schneider Electric, your energy technology partner.

• 0:17Speaker 01

  Hello and welcome back to Equity, TechCrunch's flagship podcast about the business of startups. I'm Tim Deschamps, and in this episode, we're bringing on industry experts to help us explore trends shaping the tech world. Today, we're going deep into the world of livestock, specifically cattle. Their burps are a big problem when it comes to climate change. The methane in them is 84 times more potent than carbon dioxide. Now, we have to get into the weeds a bit, pun intended, before we can tackle investor interest. And trust me, there is interest. Startups are lining up with solutions. Some are using seaweed, others are creating drugs to solve the problem. But today's guest is taking a different approach. We're joined by Catherine Polkoff, co-founder and CEO of Fiffprint Biome, a biotech startup

• 0:59Speaker 01

  that's using enzymes to reprogram a cow's microbiome from the inside out. Catherine, welcome to the show.

• 1:04Speaker 02

  Thanks for the invitation. Excited to be here.

• 1:07Speaker 01

  Great. Well, I want to get into this, kind of rewind a bit and go back in time. I want to understand how you became interested in cows and their burps.

• 1:17Speaker 02

  Yeah, not something that if you had told me when I was five years old, this is my job that I would have predicted. But I actually could have said that I would have been working with livestock or large animals. I started in animal science, so I did a bachelor's and a master's in animal science back at the University of Illinois. While I was there, actually, CRISPR had just come online. And so I started by using gene editing in beef and dairy cattle.

• 1:42Speaker 01

  So for those who don't know, can you define CRISPR real quickly?

• 1:45Speaker 02

  Yeah, it's a tool that actually lets us edit the DNA of cattle. And the idea was, hey, there might be a trait that we know increases milk yield or makes cows more tropically adapted, or any number of things. And the idea was, why don't we just copy and paste this trait into cows we know that have great genetics? Thought that was a great way that we could just improve cattle production and feed the world. It does work, but the path to market It is a little bit too slow and it for the amount of impact we need and the time scales we need it on, we need something that can work a little bit faster. But for my time there, I saw just a tremendous amount of biotech being developed for human health and I was really excited about what we could do with biotech, but there was kind

• 2:27Speaker 02

  of a gap of what was making it back to livestock production and making it to agriculture. That's when I decided to get my PhD, build out that toolbox and figure out how to bring these tools back to livestock.

• 2:37Speaker 01

  Yeah, so your road from the initial idea of editing cows' genomes directly took a bit of a turn, would you say?

• 2:44Speaker 02

  Yeah, definitely. I think the real reason it took a turn was because I met my co-founder. He had been working in the microbiome and so he knew everything there is to know about microbes. And so when he asked me to start a company with him, it was this perfect convergence of, okay, he knows microbes and I know livestock and animal anatomy. And of course, he came from a rural town in Washington where his dad was the large animal vet. So it was this perfect convergence of expertise.

• 3:09Speaker 01

  So describe what you guys are getting into with Hoofprint.

• 3:12Speaker 02

  Yeah, so maybe just talk a little bit about cows first.

• 3:15Speaker 01

  Yeah.

• 3:16Speaker 02

  There's 1.5 billion cows on the planet, so when we think about the scale of this, it's huge. But the magic thing about cows is that they are able to eat grass and forage and refuse and they're the ultimate upcyclers, right? But it's not actually the cow that's doing the work, it's the microbes in the cow's stomach. So you've probably heard cows have four stomachs, or like the main one is the rumen, which is a 40 gallon trash bin size container of just microbes that are fermenting grass. I really think, yeah, this is, it's amazing, the microbes are doing the work.

• 3:47Speaker 01

  Because grass by itself, I mean, most of what cows are eating in the wild is grass, right? And it's really hard to digest.

• 3:53Speaker 02

  No, it's like, people don't eat grass for a reason, right? Like, it just doesn't work unless you have the microbes. And the microbes, as part of this process in the rumen, they make these short chain fatty acids. And that's where the cow gets a ton of energy. These same fatty acids have benefits in human microbiomes too, if you want to dive down the rabbit hole.

• 4:11Speaker 01

  Really?

• 4:12Speaker 02

  But to stick to cows, the fermentation process is where the cows are getting their energy, but it's also where the methane is coming from. Cows aren't the ones making methane, it's the microbes that are making methane. So at Hoofprint, there's kind of two main objectives here. One, we took a look at the fermentation processes that are happening in the rumen microbiome and we're like, look, these are great for the cows, but these can be more efficient. Two, we need to get rid of the methane, like that's a non-negotiable.

• 4:38Speaker 01

  The thing that really struck me about your story is unlike a lot of other startups who are coming at this from first trying to tackle the methane emissions, you came about it the other way.

• 4:49Speaker 02

  I mean, here's a couple of things. One, if you want to have a product to use in livestock production, it has to be good for the farmer and it has to be good for the cow. Methane, yeah, it actually costs cows up to 12% of feed energy. So it's already not good for the cow.

• 5:02Speaker 01

  12%, that's a lot. Like, give us an idea of what kind of margins we're talking about in agriculture.

• 5:07Speaker 02

  Oh, my gosh, at 12%, that's more than profitability, right? It's a huge return. So if you can get all the energy that you're losing from methane back into the cow, that's already an unheard of product. I mean, that's major.

• 5:18Speaker 01

  So that's where you began. So you said, is there a way that we can improve the efficiency of the rumin, the microbiome that's driving this fermentation process? But the microbiome is kind of a messy place, right? At least from our perspective, it's not one thing, it's not three things. It's a lot of different microbes there. And are they all kind of working toward the same thing?

• 5:39Speaker 02

  No, it's kind of the wild, wild west, I think, in the microbiome. And it's easy to think like, okay, well, cows have evolved and therefore the microbes evolved with a purpose. Well, like, yeah, the purpose was for them to survive and them to grow. And it just so happens that like, they also need to feed cows if they're going to survive long term. But it doesn't mean that they're the most efficient possible. And so this is why I've said before that if we're thinking about breeding cows, long term has been designing a car, well, microbiome is the engine. And we need to optimize the engine here. And we just haven't touched it yet for many products.

• 6:11Speaker 01

  So what in the rumin is the thing that's driving these methane emissions?

• 6:16Speaker 02

  There's one specific type of microbe called methanogens. And they steal the nutrients from other microbes and just pump it into methane gas.

• 6:24Speaker 01

  So they're kind of like freeloaders, I guess.

• 6:25Speaker 02

  You could say they're freeloaders, yeah. And they're worse than freeloaders, right? Because they're now costing the cow, but they're also making a huge problem for the climate that doesn't give anybody a benefit.

• 6:35Speaker 01

  Right. If I'm not mistaken, that's about 6% of global greenhouse gases. Is that right?

• 6:40Speaker 02

  Yeah, the methane tends to be just so much more potent than carbon dioxide that it just tends to compound on how much of an impact it has on warming. But it is an opportunity, right? Because methane has such a shorter half-life that if we reduce methane today, we can see a meaningful impact on the climate in the next 10 years.

• 6:57Speaker 01

  So describe how you're going about tweaking the rumen to eliminate methane and give the cows more nutrients.

• 7:05Speaker 02

  Yeah, well, you know, when we started, the hypothesis was like, I bet nature has already solved this problem. Nature has made so many solutions to so many things. And so we copied nature and leveraged some AI and machine learning tools to mine the dark matter of microbial DNA and started looking for what nature had done to essentially reshape the microbiome in a way that doesn't make methane. That involved discovery of a lot of enzymes. And the next challenge for us was to like, what of these enzymes works in every cow in the world every time?

• 7:40Speaker 01

  Is that something where AI helped? I mean, how do you go about winnowing that list down to a reasonable number?

• 7:45Speaker 02

  Yeah, I think both my co-founder and I would say this company would not exist without AI or ML. Just on just so many different levels. One was is just being able to like actually distill that signal from noise of like, what do these enzymes even look like? You know, what was nature thinking really? And then two, being able to like, test so many things. Okay, all of these variables, like, we don't know, to your point earlier, like, the rumen is a very complicated place. Being able to distill that down into something actionable of like, okay, we're going in the right direction. Or like, we can run so many more experiments. So we have some proprietary models where we can learn really quickly about what's working, what types of enzymes we should be using. And then we can run 20 years of experiments in one

• 8:29Speaker 02

  year and just accelerate.

• 8:31Speaker 01

  And these are experiments that you're doing in the lab then? Or are you running stuff kind of in silico, doing early modeling work and then taking a subset of that to the lab?

• 8:42Speaker 02

  Exactly that, yeah. So we can just do so much more when we can do in silico modeling and then just test a smaller bit in the lab.

• 8:49Speaker 01

  Yeah, this is an interesting angle here because I feel like AI often gets a lot of, how should I say, discredit when it comes to the climate. There's kind of that impact of ChatGPT queries and being so much more than general search queries and also this rush to secure power. This seems like something, I don't want to say unexpected, but maybe something people haven't been hearing about.

• 9:12Speaker 02

  We think about that too, right? As a climate company, we want to be working in a way that's most efficient for the climate. But the reality is a lot of the problems in the world are just like too complicated for humans to solve. There's just too many variables to like keep in your mind at the same time. And so by having essentially a black box of like, okay, here's the input, here's the output, help us solve this, you know, nature can do that, like especially in biology. Nature has run millions of experiments and has an output. Humans can't do that, but AI can do that.

• 9:43Speaker 01

  Yeah, so maybe if you could describe some of the inputs that you're talking about here, are you looking at just kind of like a world of enzymes and then plugging them into a world of bacteria and seeing what happens? And what does this data look like? Are you gathering it from existing studies? Are these experiments that you've run yourself to begin with to get that data?

• 10:00Speaker 02

  Yeah, it's all, for us, it's all in-house. We're kind of in a field where nobody's, nobody's really touched. But what it looks like is, okay, we're starting with this list of enzymes. There's, there's a lot of them. And then we get some sort of experimental results. Some of them are great, some of them are not great. Then we can say, okay, what about these things are great? And then feed that into the model, do more enzymes, get more results and just kind of build this mechanism where we're not having to like manually be like, ah, yes, well, this parameter of this protein, you know, it's like, okay, more complicated than we can even understand. Like, I'm not going to ever be able to tell you how the bond angle affects the efficacy of this thing, but AI keeps that in mind.

• 10:49Anthony Ha?

  Every company today is looking for an edge. Better insights, faster decisions, greater resilience. But as AI drives new growth, it also creates new demands on energy and infrastructure. Schneider Electric is connecting energy, automation, and digital technologies to help organizations make smarter decisions and operate more efficiently. Because the future won't be shaped by AI alone, it will be shaped by energy and industrial intelligence. Schneider Electric, advancing energy tech.

• 11:17Speaker 01

  So what kind of models are you using here? Are these kind of what you think of as large language models? Or is there something a little bit more specific from there?

• 11:24Speaker 02

  Yeah, it's a mix of everything, really. I think the main huge game changer in protein engineering was AlphaFold and being able to have sequence turned into actually something tangible that you can hold in your hand. And that unlocked just a tremendous amount for us. And then the next kind of level is proprietary, right? Because it's like very unique to like how your enzyme works. And yeah, you just got to do a lot of math, I guess.

• 11:49Speaker 01

  Yeah, can you describe AlphaFold very briefly?

• 11:51Speaker 02

  Yeah, so AlphaFold comes out of Google. Going all the way back, everyone knows you have DNA, and then the DNA gets turned into RNA, and RNA gets turned into protein. But the protein comes from letters that are amino acids. And so these amino acids all have different charges and different properties that make them fold into a shape. I mean, for a long time, people just like tried to do like X-ray crystallography where you just try to take a picture of the protein and just figure out like what it looks like. That was until just a couple of years ago.

• 12:20Speaker 01

  That sounds really expensive, too.

• 12:22Speaker 02

  It's incredibly expensive. And like even then, like just, yeah, it's too difficult and too slow. And so AlphaFold, using a variety of models, they were able to actually say, hey, this sequence yields this structure. And it's dynamic. Proteins are always dynamic, they're wiggling around, so it's difficult, but generally, it's incredibly correct. It was a game changer for the field.

• 12:43Speaker 01

  So you've got all of these ways now to do experiments that would have taken you years and cost a ton of money in the lab, and now you can do them pretty quickly, or at least get a good idea of what the results are going to be, basically, in a computer model, or several computer models. How do you think that changed the appeal of what you were doing when it came to investors?

• 13:04Speaker 02

  Oh, yeah. Investors have the strength of pattern recognition, right? And so for them, they look at a company and they plot data points of, okay, this is the direction that we're moving in. And for us, it was like, wow, these data points mean that they're moving really quickly just because the amount of work they've been able to do in such a short amount of time. And that was one of the major unlocks for us. The other thing at our company is like, we're obsessed with efficiency of like, how quickly can you get an answer? Or how do you design an experiment where you get the most information out of the least work? And sometimes that means like having everybody use ChatGPT as their like thought partner or experiment design partner or like help them plot data. It's just an amazing tool for efficiency.

• 13:46Speaker 02

  But I think as far as investors look at that, it's like, oh, I've seen other biotech companies spend, you know, 10 years to get to this point or more. And that was transformative.

• 13:55Speaker 01

  And recently, that trajectory caught the attention, I guess, of SOSV, Amazon's Climate Pledge Fund, Breakthrough Energy Fellows. And you got a $15 million Series A.

• 14:07Speaker 02

  Yeah, we are so excited. And it's, I gotta say, it's a tough environment out there, but like, we just have the best investors. I'm excited with how the syndicate turned out.

• 14:16Speaker 01

  So how was pitching in a market like this for a product like you have?

• 14:20Speaker 02

  It was certainly challenging. The thing is, people are very optimistic about the technology and you can show them a lot of data. But right now, people want to see, you know, market traction and revenue or something a little bit later stage. And so we're kind of at that spot where we're so close, but like, we need the money to kind of get over the hump. And so it's tough right now.

• 14:41Speaker 01

  And is it specifically tough for biotech, ag tech?

• 14:45Speaker 02

  I think the feeling, post-fundraise feeling, and maybe this is, maybe this is just you asked me at a weird time. The feeling is that there were some maybe overfrothy investments. And now is the time where those companies are trying to go back out and raise and not having as much of a good time raising. And then a lot of investors look at their portfolio and say, either we invest in new things or we protect what we've already invested in. And it just becomes like a fear to invest in new things, but also difficulty protecting existing investments. And it makes it a very difficult environment for everyone.

• 15:20Speaker 01

  Yeah, but you guys were able to break through and capture some of that new investment money. What do you think helped you stand out?

• 15:27Speaker 02

  A few things. And one, you mentioned this in the beginning, is just a lot of people want to solve the methane problem. But like for us, there's two rules. One, it has to be a natural solution. So these enzymes are already used widely in livestock production. They're nature's tools. There's enzymes everywhere. And then two, it has to increase feed efficiency. So that was like the main, for people who are looking to solve the problem, we were very differentiated from the companies in this space.

• 15:50Speaker 01

  Yeah. What are those companies? Can you describe just kind of, you don't have to name names here, but like, describe generally what the other approaches are.

• 15:57Speaker 02

  So there's a few small molecules that'll inhibit methane production.

• 16:03Speaker 01

  So small molecules are kind of like a traditional drug, right?

• 16:05Speaker 02

  Yeah, or like it's a chemical.

• 16:07Speaker 01

  Tylenol or something like that.

• 16:08Speaker 02

  Yeah, exactly, exactly. One other key differentiator for us, I think, was the cost of goods and the capex rescaling. So our enzymes are made with fermentation and it's like really, really scalable for a low cost. And I think compared to like the other kind of interest was like in seaweed. And seaweed, it's just, I won't say impossible to get the economics right, but it makes it really, really difficult. Because in agriculture, this is where the margins are so low. And especially in biotech, everybody thinks of it in terms of pharma. And pharma can just have these astronomical margins. So nobody has really optimized biotech for something that is meant to be used in agriculture. So like, that's something that we pay constant attention to. And one of the things that helped us.

• 16:50Speaker 01

  Yeah, I was gonna say, it isn't just margins in agriculture. It's also scale too, right?

• 16:54Speaker 02

  Absolutely. And this is where yeast fermentation, you can get into like hundreds of thousands of liters and many, many sites in the world.

• 17:02Speaker 01

  So as you're progressing down this series A path, what are some of the challenges you're facing?

• 17:07Speaker 02

  Inherently, I think biology is hard. And so one of the things that maybe I didn't expect is I thought, okay, you start the company, you want to do B, so you make A, and you get to B. But it turns out there's just like all these problems that you have to solve before you can solve the problem you want to solve.

• 17:26Speaker 01

  What are some of those?

• 17:27Speaker 02

  I mean, it's everything just from like scale up of the protein to figuring out like in human therapeutics, like every experiment has ever been done in humans, there's a protocol for it. You go in livestock and you're like, well, surely somebody's isolated that microbe or certainly somebody's done this experiment and like they're just like they haven't like they're just and so you have to invent the protocol to do the experiment. And that took a little bit more of a grease than we we anticipated. But again, this is kind of why we go back to like obsessed with being efficient because otherwise you're just never going to get through it.

• 18:00Speaker 01

  Yeah. So you've made it to the point where you're pretty confident you've got a product that works. How do you make sure that works everywhere?

• 18:07Speaker 02

  Yeah. This is where we actually started trying to ship in rumen samples, rumen fluid samples, like microbial samples from cows from all over the world and just testing everything just at a small scale. Right. We're a big believer in do as much as you can in like a small scale and then kind of scale it up and try it in these larger trials. That's one thing. Two, like I think we just have more data now. So you can just have collaborations over overseas and just like, can you try this in this condition or these cows or whatever?

• 18:36Speaker 01

  So you're starting to roll out on farm trials now that the funding is in, is that right?

• 18:40Speaker 02

  Yeah, they're just around the corner. I think that's like the next thing that we're most excited about. Yeah.

• 18:45Speaker 01

  How many different sites and like, what kind of places are you going to?

• 18:48Speaker 02

  Yeah. So there are two things where we have to measure for, right? One is the efficiency and then one is the methane. And so for the efficiency and as far as like regulatory enzymes have been used in livestock enough that like, it's like, okay, check these boxes. But on the methane side, the standards are still being established. And so it's a lot of, hey, like, what would help you feel comfortable counting this in your carbon accounting budget? And what does this protocol say? Or, you know, what does this country say? And so it's, it's still being established because it is new territory. And there are some organizations doing great work on this out there. So we're partnering with them.

• 19:20Speaker 01

  And then on the farmer's side, obviously, the sales pitch is the improved feed efficiency. Do you have a specific number that you're targeting? And I guess, how do you prove that to farmers?

• 19:29Speaker 02

  Yeah, in the dairy, it becomes a little bit easier because you can actually see the milk every single day and how much yield is impacted or improved. And for the very sophisticated dairies, you can like measure intake. And so you can see how much goes in and how much comes out. And this is true in feedlots to some extent, right? Because cows are getting weighed often. It gets a little bit more difficult in pastures because a lot of times it's that one looks ready for market and that one could use a couple, you know, like depending on the market. So that's something to continue to iterate on. As far as efficiency, I think the first product specs are only the beginning. And I think the opportunity for improving the yield is going to be just continuous for us. And so we're just going to have to kind of draw the line of like, okay, this is as fast as we can get to market

• 20:14Speaker 02

  with a product and then continue to deliver benefits to the farmers.

• 20:17Speaker 01

  Do you think you can ever hit that 12%?

• 20:19Speaker 02

  Yes.

• 20:20Speaker 01

  Excellent.

• 20:20Speaker 02

  Absolutely.

• 20:21Speaker 01

  Well, we are just about out of time. But Catherine, where can listeners find you online?

• 20:26Speaker 02

  You can find me on LinkedIn. That's probably where I'm most active. And then you can look at printbio.com is where the company is located.

• 20:35Speaker 01

  Excellent. Well, thanks so much again for joining us on the show. And to our listeners, you can find me on X at T Deschamps and Blue Sky at Deschamps. And of course, you can find Equity at EquityPod. Talk to you next time.

• 20:49Rebecca Bellan?

  Equity is produced by Teresa Locum Solo with editing by Kel. We'd also like to thank TechCrunch's audience development team. Thank you so much for listening and we'll talk to you next time.