 We are live everybody. Thank you for joining us. I apologize for a few minutes after 8 o'clock. That happens sometimes. I had a flooded basement, but it's not flooded anymore. Now I have a new carpet and everything is fine. Welcome to the live broadcast of Twist where we will record all of the podcast, but it's going to be edited a bit for the podcast version. Thank you for joining us for all of the fun right now. You get all the things, all the things right now. And we're going to go live. You ready? Everyone ready? I'm ready. Everyone's ready. So we are going live in. I'm a little out of focus aren't I? I'll have to fix that in a minute. My IT department is slacking in three, two, this is Twist. This week in science, episode number 812, recorded on Wednesday, February 17, 2021. Fungus February Fun. It's going to be great. I'm Dr. Kiki. And tonight on the show, we will fill your heads with spider legs, death and fun guys. But first, disclaimer, disclaimer, disclaimer. As a cold snap grips much of Texas and millions are without power and temperatures drop below zero, some strange news is coming out of the fossil fuel industry maybe via the Texas governor and Fox News that wind turbines are to blame for power outages. Yes, the Green New Deal, so alive and well in Texas is the reason for the power outages according to Fox News and Governor Abbott. Few fun facts. Denmark gets 41% of its electricity from wind, Germany 21%, Canada and Sweden have hundreds of dedicated wind farms generating power and they all work in the cold weather, which is very common in those countries. State of Iowa, a little closer home, 40% of its energy comes from wind, the most in the United States. Now, Western Iowa is seeing rolling blackouts from this winter cold snap as well, but that's because 50% of its gas powered generators went offline. Texas on the other hand only gets 10% of its energy from wind and has had similar issues with generators freezing, not the wind turbines mind you, but the gas generators are failing. The point is that government officials pointing fingers out of political convenience while ignoring the real issues is so 2020. It does nothing to solve the actual problems because it ignores the actual cause. And that's just the sort of dangerous thinking that led us to bring you, This Week in Science, coming up next. I've got the kind of mind that can't get enough. I wish it happened every day of the week. There's only one place to go to find the knowledge I seek. I want to know. Good science to you Kiki and Blair. Gotta unmute myself and a good science to you too, Justin Blair and everyone out there. What an energizing dance intro this week. This is fun. I love it. Welcome everyone to another episode of This Week in Science. We are back again. We've got all sorts of science to fill our show tonight. Also an interview talking about fun guys and genetics, genomics, all the good stuff. And I have stories about fish because fish are cool. I also have a story about, oh, Planet Nine. We got to keep up with Planet Nine and how less is actually more in your brain. Justin, what is in your segment of the show? I've got killer caterpillars, Neanderthal resistance, and why snip calling is trickier than you thought. All right, snip calling. Okay, I want to find out all about that. Blair, what is in the animal corner? Oh, I have cats, dogs, cockroaches, and spiders. All the animals. Yay, cats and dogs. Hopefully there will be no fighting like or reigning like. All right, so Sadie heard me. We are joined by Sadie as well. It's wonderful. Jumping into the show, I would like to remind you that if you have not yet subscribed to This Week in Science, you can find us on Facebook, on YouTube, on Instagram, although we're not live videoing on Instagram, but we're there. We're on Twitter. We're on Twitch, live streaming, and we are just about all places podcasts are found. Search for This Week in Science. You can also go to twist.org, our website, to find us. All right, jumping hot off the presses. I want to talk about how we all need a little perseverance. You get it? Because perseverance, the NASA Mars rover is landing on Mars tomorrow. Less than 24 hours until it begins its descent of terror. And we can say that because the Curiosity rover had to go through its seven minutes of terror or whatever it was. And they're basically using the same landing descent technique that the Curiosity rover had used previously. However, this time, as we've talked about before, on this show and interviews and stories, the Perseverance rover is not alone. It is carrying with it a little Martian helicopter called Ingenuity. And ingenuity is supposed to test how well we can create aircraft for the Martian atmosphere. So that's actually a very interesting question, because lower atmospheric density, but also a little less gravity. So does it all balance out? Or this is interesting physics at work here. Yeah, had a great conversation with my 10-year-old Kai about the physics involved in aircraft. Beyond that, though, the Perseverance rover is going to be once it lands. It's got a little tool for digging. It's going to be taking cores several inches down below the surface, below the regolith. And those cores, remember the interview with Mapperwocky? And he talked about how the Perseverance rover is going to dig up little cores and then leave them like little packages, little poops on the ground behind it. And then someday, another helicopter based off of ingenuity, another craft will come around and scoop all those little collected bits up. Scoop all the poop. Scoop the poop. But it's not poop. It's just Martian soil. And take it and eventually have a return mission to earth to bring soil samples back to our planet, which is really exciting. This is the long game they're working on right now. See, this is important because this will give us our baseline before we all go to Mars and ruin whatever's happening. I hope that there's no ruining. Yeah. I mean, we all, there's red bars, red Mars, green Mars, blue Mars by Kim Stanley Robinson kind of got people thinking in the direction of terraforming. And who could we take Mars and turn it into something else that we want it to be, you know, something more earth like. And another instrument on perseverance called moxie is going to be testing conversion of carbon dioxide in the Martian atmosphere into oxygen. It's going to it's like a battery. It's a little it's going to use stored up energy. It's going to electrically chemically convert CO2 to O2 to see if one day we can create oxygen that's breathable or oxygen liquid fuel that could be used to power aircraft. Then beyond that, there's a whole other study that came out this week that was really pretty neat, where researchers published a proof of concept using cyanobacteria from earth in a simulated Martian environments with simulated Martian soil using all the everything in the in the proportions that they would be found on Mars atmospheric pressure, temperature, molecular components of the atmosphere and the soil. And they found that nitrogen fixing oxygen producing cyanobacteria can grow. Yeah, so maybe one day. I mean, this is also, huh, all right, maybe there is life on Mars that we haven't discovered yet, or maybe one day we could take life there if we haven't already. Yeah, Mars is a fest destiny. That's the plan eventually. If there's nothing there at first, and then if there is something there at first, it's gonna be so dynamically interesting to study that I'll have to pause the Mars a fest destiny for a little while and then we'll go there and it won't matter because we're gonna need a second planet. We need a backup. I don't want a backup planning. Yes, you do. If you've ever had a hard drive crash that wasn't backed up, you immediately go, oh, I should have had a backup. I know. Yeah. I'm not saying I'd go to have a backup. It's good practice. We just had Damon and have him get the show started and, you know, and some cyanobacteria. That's right. And potatoes. But yeah, still we got this also like temp, like you said, temperature. I think you listed it all. Temperature, pressure, the water, the chemical make up, and radiation is still going to be a thing for you. That's also one. So a little bit of work. That's a long time thinking though. That's what this the long game, everyone. We have to keep thinking long term. All right. Long term. I'm just talking about right now, right now. What story do you have, Justin? Oh, me? Oh, God. Yeah. Okay, here we go. If you want to get away with murder, one of the first rules is what? You tell me. I don't know. Hide the evidence. Have you never gotten away with the murder? Yeah. Don't get caught. Don't get caught. Yeah. Don't let anyone know that you've committed a murder. Okay. So the tomato fruit worm caterpillars are doing just that. They silence their victims' cries for help as they devour their appendages. Of course they do. Good, good. These appendages are leaves. Are they noodley appendages? No. The caterpillars are eating plants. So how do you silence a plant from telling other plants that there's a predator there? Normally, a plant does what? It releases a chemical compound? Yeah. Right. Volatile compounds, right? Or compounds into the ground. But yeah. Yeah. The volatile compounds, exactly what we're looking for here. So those go out and they either attract a predator or they tell all the other plants to start some sort of other defense mechanism within them that might be a bitter taste or something of this nature. What they found was that these, this is a team of researchers who have discovered that the caterpillars are releasing an enzyme that basically keeps the plant from expressing any of those volatile compounds into the air. This is Gary Fulton, Professor and Head of the Department of Entomology at Penn State. Discovering a new strategy whereby an insect uses saliva to inhibit the release of airborne plant defenses through direct manipulation of plant stomata. Stomata are the tiny pores. That's the way the plant gets those, what are actually herbivore induced plant volatiles, hippies, into the air to either attract the predator of their predator or to alert the other plants to get their defenses up. It's also involved in CO2 exchange. So they've discovered it's making this very specific enzyme that it's in its spit that keeps the stomata closed, prevents it from interacting with the environment. That is such a... That's amazing. It's like it's gagged. A shrinkage. And then, yeah, and then it goes about eating it. Yikes. So yeah, so the, it's a pretty interesting story just as a one-off of the sort of arms race in nature kind of a thing. But they also think that they may be able to to utilize this enzyme in the future when, if they need to do, keep plants from reacting to the stresses of, say, global warming or this sort of thing. It may be another tool or mechanism to be used in agriculture at some point. Yeah, I wouldn't... It was on Mars. Maybe it would help on Mars, right? You're not feeling pain from being in this habitat. That's fine. You're okay. You can't, little potatoes can't scream to tell the other potatoes. In space, when a potato screams. Oh my goodness. Yikes. Yeah, yikes. Oh my goodness. I feel bad for the plants, but at the same time it's amazing that caterpillars, these caterpillars are able to do that. I want to know more about more caterpillars. How many caterpillars have this ability? How many other insects have this ability? Yeah, it's the first time they've seen one at all. So it's a pretty cool discovery by itself. It's also, they feel like it was, I feel like it wasn't that long ago, not even, wasn't even 10 years ago that we were first talking about these defense mechanisms of plants. I don't feel like we've even had that on the radar that long. And now finding, of course, those countermeasures and a whole natural world arms race that continues to go on and on. Of course, there is. Who else has arms races, Blair? Well, besides caterpillars, how about just cats? They have an arms race amongst wildlife, the cats that are allowed to go outside of homes have huge problems on wildlife, birds, lizards, small mammals. They're all just in big trouble from these savage predators. And a new study from the U.S. Exeter tells us that actually domestic cats hunt less wildlife if they are fed a meat rich diet and played with more often. They were introduced to premium commercial food where protein came from meat as opposed to other sources, and that reduced the number of prey animals brought home by 36%. Five to 10 minutes of daily play, which you have a cat and you're not playing with it for five to 10 minutes. At least five to 10 minutes. How could you have a pet and not play with it? Come on. Five to 10 minutes of play with a cat also results in a 25% reduction of wild hunting. So just two very simple things you can do there. Feed your cat a protein-based diet that's actually meat-based, which is good for them anyway since they're carnivores, but also then interacting with them and playing with them. The play in this study involved simulating hunting specifically by moving a feather toy on a string on a wand, which is my favorite game to play with a cat, so that they could stalk, chase, and pounce, and then they would give the cats a toy mouse when they succeeded on pouncing so that they succeeded in their hunt. And so that would make a real kill. And so all of that to say by other measures like this bird-safe collars, that reduces 42% of hunting of birds, but has no effect on mammals. And cat bells actually have no proven statistical effect on hunting, which I was surprised to hear because a bunch of cats actually learn how to hunt. More quietly. So all that to say, forget it all, just have an indoor cat. All of it to say, just have an indoor cat. But also, hey, if for some reason you have an older cat who can't adjust to their new way, if you get a new cat, please make it an indoor cat. But if you have an older cat that won't adjust to being inside all the time, play with it. Make sure it has a protein-rich meat-based diet. Maybe that will help reduce this a little bit. Now I'm thinking that the neighborhood cats that stalk around my house, I just need to leave plates of meat out for them so they won't kill the birds in my yard. In some sort of 10 minutes. It sounds like a protection racket. The cats are like, you like birds in your backyard? You don't want them to get hurt? Here's what you do. You leave out a little piece of meat for me. Every other day, you'll be fine. Sure would be a shame if something happened to these birds. And if you do that, then the cats win. Yeah. Yeah, no. Don't go against the cat mafia. Don't go against them. I don't know. They've got the weather racket. That thing is like cats on Nostra. Cats on Nostra. Okay. Now we're just going downhill. How about we take it? Let's take a trip. Let's take a trip away from the cats, away from the cats. Remember last year or a couple of years ago, we spoke with a couple of astrophysicists about their ideas, Mike Brown and Batigan. I'm forgetting his first name, Dr. Batigan, about their assessment of trans-Neptunian objects, objects that are way out past Neptune and have these big elliptical weirdo orbits. Yeah. One of the guys killed Pluto. Yes. That was Mike Brown. Yes. And now, because I think his daughter told him that he like owes the galaxy or the solar system a planet that he's been now trying to track down. Planet nine. Planet nine. So Planet nine is this hypothesized really big planet that's dark, that's way out there past Neptune, past Pluto, past way out there. It's out in the dark, but it has a gravitational effect. And so the reason they think that there is a planet nine is because a bunch of these objects, according to their analyses that are out there, are clumping. And they say the clumpiness as a result of this big gravitational object that's way out there that's kind of herding these trans-Neptunian objects into clumps. Kind of where they're associated. Well, a new study that is out this week that has been published by another group of astrophysicists, they have taken a look at a different group of trans-Neptunian objects. And they conclude that you can't conclude anything about clumpiness of trans-Neptunian objects because it's all about bias of where you're pointing your telescope in the sky and when. So there happens to be a bias to when we point telescopes to certain places in the sky because objects could be highlighted against the light of the Milky Way, or there could be other aspects to why they're looking in certain places at certain times. And so what they say is that they could not, they could not, I guess, get rid of the null hypothesis that there was no clumpiness. And so this clustering is something that is just a bias and there's no plan at nine. But Battigan and Brown are saying that, look, look, you just gotta look some more. The clustering, it's there and we're gonna keep looking at objects and you gotta look at it in the right way and there's gonna be more telescopes and we're gonna keep looking. So different teams of researchers with different results who are scientifically battling it out for a planet's existence in the distant solar system. This is like reality television material except not because it's just science, it's reality and we are working through hypotheses right now and this is, it's fabulous. And this is also why like everyone in college who got really frustrated at having to take stats, this is exactly why you have to take stats, is to figure out exactly how you can know if you think there's a thing and if there is questionable doubt of whether there is a thing. Yep. There's a lot of amorphous words we're saying like. I love the null hypothesis. The null hypothesis says there is not a thing. Yeah, there's nothing. There's not that thing. You're tripping. Basically it's the statistical version of you're tripping. You're tripping, boo. Cold tripping. All right. Anyway, moving forwards. Oh, Blair, you had cats. Now do you want to talk about dogs? Yeah, real quick, just a very silly study about dogs and everything you assume about dogs is wrong. So your pet dogs, they're putting on a show for you. They are far more likely to play with one another when their owner is present and being attentive than when they are not. So they took 10 pairs of pet dogs that had lived together for at least six months. These are dogs that live together and play together all the time. They get along well. They ordinarily engage in play at least once a day. And then they videotaped these dogs under three conditions. One, the owner was absent. Two, the owner was present but ignoring them. And three, the owner was present and showering them with attention in the form of verbal praise and petting. And that overall the availability of owner attention facilitated play. So if you are there and you are paying attention to your dogs, they are more likely to play with each other. They saw more bowing, hip nudges, wrestling, chasing, gentle bites, all the good dog playing stuff. So they have a few theories why this could be. One, the owner's attention is a reward. And they're like young children asking their owner to watch them do something cool. Come see what I could do. Two, they might have learned. Look at me. Look at me. Exactly. I could do a handstand. Look at me. They think it's cute when we do this. We should do it. Two, they've learned that playing amongst themselves leads to bigger prizes like the owner joining in or taking them outside. You guys are getting too rowdy. Go outside. That's praise, right? That's reward. Three, they might actually provide a sense of safety because even though they know each other when dogs are playing, there's always a chance it could escalate and get a little nippy. And having the human there to intercede is like insurance. But four, and this is the one I really like, is that the human's presence might be a trigger that creates oxytocin, which leads to an emotional state that manifests as play. Interesting. So it's the hormone neurochemical influence that leads to these behaviors, which are social in nature, the play and the sociality and the bonding that come from it. Hmm. Pro social behavior at the result of neurotransmitter hormones. Yes. So more studies needed, obviously, and this is only 10 pairs of dogs. It's not a huge disabled size, but it is very interesting that you would think that I would think two dogs that live with each other, you left them alone. They would play all day, but it sounds like they're more encouraged to play when the humans are just very interesting. Nice. Yeah. No, they're not just keeping each other company. They're keeping you entertained. So my last study, Justin, you don't have another story in the rundown. So just for your segment, did you have one more for the start this round? No, I didn't see a spot for it. So I didn't. Oh, there it is. I got a couple of stories later. I want to jump in the interview. Okay. Awesome. All right. So my last story for this early part of the show, our stories to start things out, has to do with genetic diversity of salmon and trout and how we find out about that diversity where the fish are. You can catch the fish or now there is environmental DNA. So you don't actually have to catch the fish. You just sample the water and get leftovers of the fish. You can find their DNA in little, then little water samples or in soil samples from the bottom of a river or a stream, a waterway. Researchers at Oregon State University have just published their research looking at a bunch of different trout and salmon species in Oregon, Northern and Southern Oregon. And they found a lot of interesting connections between watersheds in Northern and Southern Oregon that are not connected. So like the Deschutes waterway and the Klamath waterway, they're not connected. However, people hypothesized that they were connected at one point in time. And they actually found genetic evidence from this environmental DNA that connects these completely distant subspecies, these different not subspecies, but these different populations of salmon, Deschutes salmon and Klamath salmon, they got some history in there, according to environmental DNA. They also were looking at another area, let me see if I can find, Umpqua, the Umpqua watershed area. They found a lot of really interesting stuff going on in Umpqua where they found unique genetic variants of cutthroat trout, the lesser extent, the rainbow trout. There was just a lot of genetic diversity that was not really expected. And so it is pointing a direction for researchers to look at the Umpqua watershed region for future investigation of these various species. Very fun stuff. But yeah, they went out. They sampled the environment and they found these amazing connections between different fish species that they wouldn't have necessarily known about. Very cool. All right, everybody, this is This Week in Science. We are here as we are every Wednesday talking about science with you and we hope that you are enjoying the show. If you would like some cool piece of twist merchandise, we have a store. Head over to twist.org, click on our Zazzle link and you'll be able to find a veritable cornucopia of things that are twists in nature. We've got hats, we've got mouse pads, we've got mugs, we've got lots of items with Blair's Animal Corner art on them. So head over to twist.org, click on that Zazzle link, support the show and enjoy some twist, twisty merchandise. Now I'll come back in and let me introduce our guest for the evening. Tonight we are joined by Dr. Ivan Leachko. He is the founder and CEO CSO, Chief Science Officer of Phase Genomics and one of the inventors of their core technology, which is called Hi-C technology. It's applying proximity ligation data to different facets of genomics. He received his bachelor's degree at Brandeis University in 2001, PhD in 2007 at Cornell and then worked as a postdoctoral professional at the Department of Genome Sciences at the University of Washington in Seattle. He has authored more than 40 academic papers and a number of patents in the field of genomics and synthetic biology. He founded Phase Genomics in 2015 and leads the organization in an executive as well as technical role. Ivan, thank you so much for joining us tonight on the show. Thank you so much for having me. This is super fun. I hope that you're enjoying yourself. We try to enjoy ourselves and the science and all of it. We think it's fun, it's interesting and if we can spark a little curiosity, that's what we try to do. I'm curious about your pathway into starting a business and entering into the field of genomics. How did you get interested in this field and end up where you are? Sure, thanks. I'll give you a little bit of the origin story. As long as there are superhero powers involved like origin stories. I could be villain, you don't know. I'm an immigrant, but I immigrated to the U.S. when I was 11 years old. I've always wanted to do biology. I always wanted to do genetics. I started early on in life. I got my first job in a lab at the age of 16. I'm just kind of pipetting stuff and doing DNA, jockeying. This was back in Philadelphia, and then more of that in undergrad, more of that in grad school, postdoc, basically just 20 years of genetics. Then you get there. You're like, I don't have any other skills. I only know how to research. How are you doing it? We did lots of cool stuff, lots of technology development during my years. Towards the end of my postdoc, we came up with some cool technology. I should say that there is a technology that you mentioned called Hi-C, which we use. We did not invent it. We just invented a couple of cool things to do with it, which is a distinction that's totally not important to you guys, but I'm going to go back and hear some stuff. Very important. In the other lab at UMass by Iris Lieberman-Aden. We've come up with some creative ways of using it that were new at the time, and we started doing all these crazy projects. I'll kind of talk a little bit about them, what we do, but they were just very novel. They went in different directions that were not originally intended, and they were working extremely well. At some point, we were like, this technology is very powerful. It's very useful to people all over the scientific community, but it's also esoteric and complicated and hard to use. If we don't turn it into a product, it's going to fizzle out. It's basically like, no one's ever going to hear about it. That's true for so much of research. When you work in academic labs, people are brilliant. They come up with amazing stuff all the time, but as soon as you kind of invent the thing, usually you just go on and you try to invent some other thing. They focus on making it work super well once or twice a couple of times. You publish it, you get it out there. You hope somebody else picks it up and turns it into something that can be used a lot, but it often doesn't happen. We were like, we don't want this technology to go away as soon as we stop working on it. We have to turn it into a product. We have to make it so that other scientists have access to it, that it's easy, that it's something people can just use. It's applicable. That's basically how phase development got started. My co-founder, we knew each other for a long time. He was my DM in Dungeons and Dragons with my house. He left Microsoft, which is where he was working for a long time. We paired up and we started this startup. We've been growing it since then. We got all this cool science going on. What are you doing with this technology? You're making these things easier. We talk about this stuff on the show all the time, but for maybe somebody who might be tuning in for the first time, what is the difference between genetics and genomics? The omic aspect. In one word, the difference between genetics and genomics is scale. Genetics, you're studying a gene or some genes. Genomics is when you're studying all the genes at the same time. Genomics is basically a combination of genetics and computer science. DNA sequencing used to exist. It existed before the genomics era where you would sequence like one gene. You would sequence like a thing. Now the new technology that is out, it's called next generation sequencing, it's when you're sequencing the whole human genome. You're sequencing a whole something. You scoop a bunch of water from a pond with fish in it and you sequence all the DNA and you use computers to figure out where do these sequences come from, which what are the different fish, etc. It's like genetics plus data. Genetics plus digitizing genetics. That's what genomics is. You're a bioinformagician. Bioinformagician, yes. That is part of what I do. I've done some of that. I've done 20 years of like petting stuff. You've wet lab, too. And now you're doing the bioinformatic stuff as well. That's probably what's underlining a lot of the what the company is doing. It's both. In our case, both. What's cool about this technology is that and why we started the company is because it's not just like you have like a new protocol for some wet lab magic. It's not just like a new algorithm for analyzing data. It's both. And you have to basically make both of them work together. And no one's going to do just one and not the other. And that was sort of why that was kind of one of the reasons why we kind of really felt like it would go away if we didn't commercialize it. So I feel like this is the shark tank and I don't know what the product is yet. Because the first the first thing is like in any anything in researching when you got a whole genome out there, where do you start asking a question or trying to narrow down so you can actually learn something from your data is one issue. And is that is that what what phase genomics is sort of zeroed in on it. Oh, so yeah, so so so basically the high level summary of what we do is what our platform does is it makes it so that scientists can discover more stuff from a lot of different genomic. To answer your specific question like how does it start usually the best way of going about something is having the question first. Yeah, generating the data later. You know the opposite happens most of the time. Usually you're like, now what do I do with it? Yeah. But but having and then you pretend like you had a question the whole time. That's post hoc analysis. Yeah. Like like if they sequence that fish pond and they discovered that it was full of like, I don't know, like virus causes some disease, they'd be like, Oh, you know what, we were studying as disease virus the whole time. You don't know it's out there. And that's kind of that kind of as a segue to what I'm gonna to where I'm gonna go with this. But what so what our tech does is it allows you to discover stuff in a lot of the sequencing efforts that you can't any other way. And so it applies to it applies to almost everything. It applies to doing things in your genome. It applies to doing things in the environment. It applies to agriculture. It applies to microbial stuff like microbiome and infectious disease. These kinds of applications. And so it's a sort of a hammer that hits many nails and we have a lot of different applications for it. And so that's a again, I still haven't told you what the product is. Right. I've got over here. I've got like right there's the next gen sequencing methods that are out there. There's the alumina. There's the Oxford nanopores stuff that can get these long reads or these very good small reads. And then you have the bio and for magicians creating the algorithms to decipher all of that information that comes out of it. So what is yours doing that's step different from running it through the machine and running it through some algorithms that are already short. So here's how all DNA sequencing works. You take a DNA molecule like it's like a long string of letters, right? And you stretch it out and you break it into a bunch of pieces. And you like read the pieces. And then you have multiple copies of the same thing. And so that the pieces, when you break them, they're going to overlap. You're going to have staggered ones. And when you read them all, you can then try to overlap them back together to try to reconstruct what the original super long sequence was. Right. It's a little bit better than if you cut up a book into small pieces. That's kind of tough to put all the pieces together. If you cut up 40 copies of the same book or the same page of the book, it's actually a little easier. Right. Right. But here's the thing. So let's, let's keep going with the book. You're right. Like you took 100 copies of the same book, you shredded them to tiny pieces. Now you try to reconstruct the book. You can do it. But here's the thing. What happens when you have a break between chapters? Like you have that blank page. Right. Right. What happens when you have the same phrase repeated a bunch of different times? Like what happens if, I don't know, like repeat some, some combination of words. I was thinking of something funny, but I can't think of one. Like, it was the best of time. I don't know. Like, right. If it said it over and over again for a page, how do you know? Like the other side of that. Right. So that's the problem. The problem is that you're trying to take a sequence that's maybe a hundred million letters long or, you know, whatever, like a hundred thousand letters long, a million letters long, super long. And there's repeats all over. And there's other sequences that are just hard. Like, what happens if you have a hundred like A's in a row? Right. Stuff like that. And so, so when you do these overlapping things, it never works perfectly. There's, so there's three technologies, three main technologies that are used for sequencing DNA. One is from a company called Illumina. There when they sequence, when they read the little DNA pieces, they give you very accurate reads, but they're short. They're like a couple of hundred base pairs long, but they're very accurate, but you can only read a hundred letter, like, like 300 letters at a time. There is another company called Pacific Biosciences, PacBio. They read, like, 10,000 letters long, but it's super accurate, just like the Illumina ones. The difference is the Illumina ones gives you a ton of reads, like hundreds of millions of these things. The Pacific biosciences ones are longer, but fewer, fewer. Yeah. Less, less coverage. Less coverage, right. Coverage is like when you throw these little reads on top of a sequence, how deeply do they pile up, right? So, right. So super long, super accurate. Then you have Oxford Nanopore, which sequences even longer molecules, but they tend to be a little bit more error prone. And so they're these trade-offs and they're also, you know, tend to be more expensive and stuff like that. But, you know, also in order to sequence a super long molecule, you need to actually purify a super long DNA molecule. DNA likes to break because it's a little so, but no matter which technology you use, when you try to put that giant book jigsaw puzzle of sequence back together, it's not, it's going to be in chunks, in pieces, right? So you're going to get, like, half a page here, a page there, and you're going to be like, well, how do they all fit together? Like, what's chapter one? What's chapter two, right? Like, and so, and you don't know. And so actually putting the genome together into actual chromosomes is extremely difficult. You can sequence, like, sequencing is easy, everybody does it, but actually putting it into an actual chromosome is really hard. And now... That's where your technology comes in. That's where our technology comes in. Yeah. But let's add another layer to it. Let's say you're not sequencing just one person. Let's say you're sequencing a scoop of soil that has 10,000 different bacterial genomes in it, or some water with fish DNA in it that comes from God knows how many fish. What else is in there? Algae, viruses, right? All this stuff. Like, now it's like taking 100 books, 1,000 books, different ones, ripping them up. Now you don't even know which pieces belong to which book. Right? So there is this, like, sequencing DNA is fine. It's cool. It's totally common. Putting it all together is super hard. And so what our technology does... Oh, thank you. Our technology puts the jigsaw puzzles together. Long story short. Here's a little video of how it works. So high C technology was really neat. It was designed originally to look at how a genome folds together. That's what the original inventors invented it for. Because when your genome is inside of a cell, it's like a hairball and there's a lot of biology in there. It's like there's pieces of DNA that are touching other pieces and they're folding around and they're doing stuff and it's like genes get turned on and turned off based on where they are. And this method, what it does is it captures sequences that are next to each other. There's a bunch of molecular trickery that allows you to extract these little junctions where they're touching and sequence the junctions. And you can tell what's touching what. Now you would say, okay, I can tell what's touching what. Oh, this cartoon is great. I haven't watched this cartoon in forever, so it's fun to watch it. So you basically chop the stuff up. You glue the little pieces together. And then you're sequencing these junctions. It gives you a readout of sequence A and sequence B were connected. They must have been touching each other. And you're doing that for millions of sequences at the same time, like bazillions of them, all at once. And that essentially lets you count how often every sequence was touching every other sequence. And if you know which sequences are touching each other more, that means they were closer and which sequences are touching each other less means they're further. That's how you figure out the three-dimensional shape of your genome. That's how awesome it is. It's like art. It's like using sequence to infer three-dimensional stuff. And that was actually one of the reasons I really kind of fell in love with the technology even before this company stuff we did. But here's the thing. DNA is basically like a long noodle. And so if you're close together, if you're touching a lot, that means you're close. If you're touching less means you're far. Like there's three-dimensional distance and two-dimensional distance are related. So if two things are close to each other in three dimensions, they're also close to each other in two dimensions. So now imagine you have this jigsaw puzzle or book that's been ripped into pieces. But you know the three-dimensional distance between every two pieces. Now you can put that together. And this is where the bio-in-fap informagician stuff really comes into play. Because it's not just two-dimensional. You're starting to really put things into perspective. When you started, that just the wet lab part of the protocol. Just doing the laboratory stuff without even sequencing took like a week. And it cost like a thousand dollars just to do one, just to do the pipetting stuff. And you have to sequence it. It's another couple grand. And then nobody knows what to do with the software. Like software is really hard. And so we had to make it easy and make it cheap, make it scalable. But so that's one thing. Now here's the other one. Let's say we have a microbial sample. Let's say you have a bunch of bacteria living together. Or like a plant that's been infected with a fungus. Or some of that mixture of stuff. Last week on the show, I brought up a story about a rust, a fungus rust on a plant. So something like that. I got pictures of that in my slide deck. But so yeah, that kind of stuff happens all the time. Things generally don't hang out on their own. Like everything is always touching everything else. But now, so you have a bunch of genomes, they're all mixed together. But if you know which ones are touching, because they were touching in the very beginning of the experiment, you know which ones came out of the same cell. The little touches were trapped before the cells were all broken and the DNA was all mixed together. Right. So they were part of either the pathogen genome or say the plant genome. Which lets us separate genomes from these complex mixed communities. What that means is like if you go into a soil sample and you scooped it, there's thousands of bacterial species living in there. 999 of them would have never been sequenced before. Right. That's the cool thing. So the company is focused on discovery. The technology is all about it's all about discovering new stuff and discovering more stuff. And you know, whether it's like what's going on with your genome, like a piece of your chromosome flipped around, our technology will tell you that whereas normal sequencing can't sometimes because it's the same sequence, it just flipped. Right. But that might cause cancer. If you're going into a bacterial, a microbial environment where there's a bunch of bacteria and nobody's sequenced before. Right. Remember, like you have more bacterial cells in you than human cells. Right. By a lot. And you know, and the environment is like a wild, wild west. Nobody knows what's out there. The ocean, like water, like people like there are these crazy things where like the viruses in the water in the ocean are one of the, they play a role in the carbon cycle of the earth because those cyanobacteria that suck up the carbon out of the atmosphere, bacteriophages kill them and they sink to the bottom and they become like coral and stuff. Right. And so viruses in the water of which there are uncountable amount untold numbers in actual, like the global warming, like climate change type carbon cycle. So there's so much out there. We don't know. And so the whole point of this technology and why we were so excited about spinning it out is like, we just discover stuff by the hundreds, like every time we process a sample, maybe it's like somebody's poop, maybe it's some soil, maybe it's water, maybe it's coral. Coral is like a little sponge full of bacteria. Right. Like whatever it is, there's always new things in there. There's always tons of new bacteria and you couldn't have found them unless you had some way to separate it all apart. So we would just be a bunch of DNA otherwise. Right. So you can tell where they were touching even after the fact. That's the so because because normally if you took like these samples that we're talking about the fish sample, right, we have a bunch of skeletons of different types of fish and things that we already know about that could be in there that we're comparing our sequences to. So we took all these, we have a bunch of books with the sort of in gray all of the lettering. Right. We do the sequence and we can do, oh, we can fit this here, this can go here, this can go and we paste them in until we have enough of a recognition. If we don't know what's in there, we can't identify anything novel, anything new because we haven't tagged it. Even when you, if you know everything going into a sequence or you tag everything, so when it comes out, you still have an identified where Yeah, you can get some information because things are similar to each other. So you can like, you can be like, I don't know exactly what strain this is, but this is probably a carp or whatever. Right. Cause you feel like it's got a bunch of carp genes in it. Like they're not the same as ever. Like, so yeah, so when you get smaller, then when the genome gets smaller and smaller and smaller, then it becomes impossible. It's all looks like noise. So this technology can actually separate and distinguish that noise from how small of, how small of a piece are the reads? How long, I mean, how long of a read do you need? I guess. So the reads we use are actually the short Illumina reads. And so we can use long reads too. We work with, we work with like all the sequencing technologies, but you know, it works differently in different things, but but that's kind of the idea. The idea is like, if you know how, like if you know the three dimensional distance between things and what's touching, you can do all this stuff with it. And that's really our contribution. Again, like we didn't invent high C, but all this stuff about separating populations and like putting genomes together, like that's our stick. Right. So from, from that, considering how bacteria also have horizontal gene transfer, when you're looking at the fungal species, bacterial species, microbes, viruses that are trading things back and forth, I guess it, I guess you're still just looking at individuals, right? Because you're looking at the genes, the chromosomes that are in the genes of the individual cells, but can you tell you anything? Yeah, kind of. It's not completely a single cell because like if you have two of the same one, it's hard. The sequencing doesn't know like which one it is, but, but kind of, yeah, it's sort of the right thing. So yeah, so antibiotic resistance in, in, in bacteria is, is a huge problem, right? They're saying it's going to kill more people by 2050 than cancer. And part of the reason why it's so explosive and like almost all the drugs don't work anymore is because antibiotic resistance travels on little pieces of DNA that are called mobile elements. They could be plasmids, which are these little circles of DNA. They could viruses, which like grab, like they pinch off pieces of DNA and jump around, right? But they're, they're mobile elements. It's horizontal gene transfer and stuff like that. And, and yeah, let's say you have two bacteria. And so what ends up happening is one bacterium will like, let's say, have a bunch of these antibiotic resistance genes floating around. And there's a bunch of other ones that don't. And then you hit the population with an antibiotic and everybody dies, except for like the guy who all the plasmids and it starts sharing them. It like they jump around. So through horizontal gene transfer, they can move to different micro, to different bacteria. And now all of they, all of them become resistant as well. And so you have these sweeps. And so understanding mobile elements, this DNA jumping from species to species is super important. There's no way to do it by sequencing. Like you, let's say you sequence a bunch of bacterial soup. How do you know that this virus was in bacteria A or bacteria B? You can't tell. That's one of the things that our technology can do. And it can tell us how these mobile elements are distributed across the populations. You know, things like that. So there's, there's like all these kind of funky tricks we can do in fungi. Like there's a lot of examples of like, like, so maybe I should, should I break like steer the ship back to like, yeah, yeah, we can talk about, talk about the fun, the fungi's fungi February and the fungal work that you're doing. Yeah. So one of the things that, that has been really fun is, is fungus for the fun and fungus. That's right. So, so within this microbial soup, right? There's also like, the fungi are a super important and super neglected community because they're just hard to study. There's tons of them out there. Like if you take up a scoop of soil and remove the plant material, like, like 80% or something, I don't know, 50%, 80% of what's left is fungi. Like they're just like every, like they're everywhere. They, they are the largest like non plant source of biomass. Almost all like 90% of the plants out there have symbiotic relationships with them. They're called mycorrhizal relationships, the little roots, like require each other. You know, the largest creature on earth is a fungus. This is just like a fun trivia fact. Like the largest single creature on earth is a, it's a, it's a honey mushroom that is like, that's like, it's like two, like it's 2000 acres big. Oh, wow. The fungus lives underground. Like the thing you see, the mushroom, that's just like the apple from the tree. That's not just a little reproductive thing. The actual creature is underground and it like spreads across multiple forests and stuff and they can like sequence them from different forests. They can tell it's the same dude. Right. And so they're everywhere. They're super important, but they're hard to study. We know so little about them. And, and so some of what we do is with fungi. And so they, they have these crazy biological things. Another fun thing about fungi is that they were one of the like, they're an organism that humans domesticated very early. That was one of my, when I think about like, that's a fact that just kind of makes me kind of happy, like to think we domesticated fungi. They're like, they're like cats and dogs. Like my, my, my, the button, the white mushroom. Yeah. Oh, okay. The bread, we make beer, we do all this stuff and we're doing it for tens of thousands of years. And, you know, that's a domestication of fungi. And, and there's all these crazy tricks they do, like the rust, you mentioned rust, right? So there are many rust organisms out there. And what they do is they infect fungi are super good at killing plants, like fungi are like great at digesting like plant cell walls and killing plants. So there's a lot of plant pathogens out there. And these rusts, you know, they, they do like enormous amounts of damage. There's like, there's one, we wrote a grant about this where one strain of oat crown rust, one, like a 2012 or something killed like half of the oats in Minnesota. Wow. You can go crazy. They do, they can do crazy damage. Yeah, but it's also, also though, fungi and expressed end enzymes are also responsible for your pre-weathered genes, your pre-stressed genes also are thanks to the fungi enzymes. Yeah. And about 15% of all vaccines are grown in yeast, which is a fun yeast. Yeast is like the most amazing worker. I did 10 years of yeast research. Never complains. My sourdough starter is very excited about this conversation. Everybody's sourdough starters are very excited about this conversation. They're like, my ears are burning. What's that, bread? You can get yeast to express just about any molecular compound that you want to use for anything. Anything. They're just amazingly compliant. Yeah. Yeah. That's, that's about right. If you guys want, I can show you. So what we did was we, we were doing all these fungal projects and they were super interesting in different ways. And we started like a little contest on Twitter. It's not a contest. It's just an event, a little raffle giveaway. We give away like branded socks. We give away like free products and stuff like that. We call the fungus February and the idea was people, scientists post pictures of their favorite science fungus and then somebody like wins a thing. And let's see, do you want me to share slides? How do I do this? If you have slides, you may certainly share them. You can hit the share button at the bottom of the screen. There it is. Oh, fun with fungus. Yay. Yeah, I would share exactly how much you wanted me to talk or not about stuff. But so I live in the Pacific Northwest. Oh, great. A vet, like an amazing place to, and we also do a lot of mushrooming. That's a hide thing unrelated to research. But, but so we did fungus February at some point. And so we did this little Twitter contest where we're like, do you guys like fungus? You like to do fungus science, post up pictures of your favorite science fungus, and somebody's going to win something. And people started posting like the most amazing stuff. Like, so this is a rust right here. I'm assuming you guys can see this. I didn't. Yeah, yeah, yeah. This is the like good old saccharomyces cerevisiae, the brewing yeast that is the workhorse of a lot of research. And some of them are like, you know, some of them have these like multi-nucleate cells and all sorts of other stuff. Here's some other funky ones. They like, some of them will glow in the dark, you know, some of them have these crazy multi-nucleate cells, lots of different genomes in the same cell. Like they'll just like, they'll mix tons of genetic material from different strains or like they'll end up replicate themselves a lot. So they make this gorgeous stuff. Some of them will like wear crazy pixelated shades. You can see this one. So, so yeah, we did all this stuff. And like so much interesting biology is coming out of it. We, we work not like I said mentioned, we work not just in fungi. Like I have a little video. We work on all sorts of organisms. We've done genomes of like, I think possibly thousands of things, hundreds of things at least, plants, animals, mosquitoes, cannabis, like fruity things. This is what the technology is like I was telling you about, like you kind of write the stuff curls up and then you trap the little, the little junctions between the sequences that are touching and then you can tell what's far, what's close and you can separate mixed DNA. And so this is a rust story. So one of the cool things about rust and its biology is that they do this thing where different strains, different strains will actually mate with each other and the nuclei, which is like a nucleus is where the DNA is, right? And so the nuclei of the two will just hang out in the same cell. And so you basically get a strain that's like two strains in the same cell. Okay. And depending on which combinations of things are in them, it determines like how virulent they're going to be. So this was a publication from a group from a, well, it's a lot of people. Most of my collaborators are in Australia, but there's this UG99 strain that's like the deadliest wheat stem rust pathogen. And what we, you know, let's imagine you're sequencing a strain of fungus and you need to figure out what sequences are in nucleus A and which ones are in nucleus B, right? Because you got to figure out like, what's in the red one? What's in the blue one? Well, how do you do it if you sequence it all together, right? And it's just very hard because you have, they kind of look the same, they're in the same cell, like you can't tell apart. And that's what our technology does is it separates stuff out. So they were able to separate out the two, they're called haplotypes or sub genomes or there's a couple different names for it, but actually separate the two different ones. And what they found was that half of it, like one of the lineages, let's call it red, was a known one that was like sequenced a long time ago, it's from Africa. And the other one, the blue one was a new one that they didn't, didn't really know like where it came from. So you can try to understand what genes they have and sort of how they contribute to virulence. This one we just did, this is just a fun one. I don't have like a whole cool science finding. There's a fungus out there called mummy berry, which it affects blueberries. That just makes me sad right away. I love blueberries. But it does it through the craziest mechanism. What it does is it has like a bee or like some other pollinator will carry like little fungal spores and they will land on the flower, like the flowers have this tube in the middle, right? This styler canal and it'll land on top of it and it'll basically act like a piece of pollen. Because normally what happens is the pollen will land over here and it makes a little root that goes down into the ovary and then it fertilizes the ovary and that's how you get a berry. Well, this thing lands up there. This is a fungus now. It's not a pollen, but it makes like a little tentacle that goes down. It acts like a pollen. It makes a little tentacle that goes down, infect the ovary, and then when the flower turns into a berry, it becomes one of these mummy berries. It becomes like one of these like little possessed, like a little demon possessed. So it's no longer a blueberry. It is a mummy berry and when it pops, it's going to throw more fungal spores everywhere. There's a bunch of spores and it's like seeds. So we assemble that one. It's got all this cool biology. Here's another. I'm kind of going back to the separating things. So yeast, which is everybody's favorite lab organism, or my favorite. This is what they look like on their microscope. They're super cute. These little things they have, they're called bud scars. So they bud, they like pinch off the cell. Little babies, little tiny baby yeast. And yeah, they kind of look like babies. I don't know why. Babies, like they look like eyes or something. But every time a baby cell falls off, they leave one of these little bud scars behind. You can actually age, you can actually tell how old they are by how many bud scars they have. Fascinating. Yeah. But what they like to do is, they like to mate with each other. So they have two, like they're called mating types. You can kind of like genders. They're called A and alpha. And when they come next to each other, they secrete like little pheromones. And then they make this thing called a schmoo. And this is a scientific, official, super scientific technical term. I swear. The schmoo. Because they can't, they can't move. Like they can't, like not like bacteria. They have like little hairs and stuff to move around. These guys, they just reach towards each other. And then they do like, they have little kids. Aww. And then they go boosh. And then they, and then they become one. Oh my little schmoo. The ultimate yes. It's the most romantic thing you've ever seen. We will become one. Yeah. And then they can make, and then they make a diploid, which has two genomes in one. But what's cool is, this doesn't have to be the same species. So there are, there are different species that will mate with each other. And they will make these, these hybrids. In fact, this is super common in your life. Because every logger yeast, every logger is made by, by hybrid yeast. In fact, it's, it's like our normal saccharomyces cerevisiae, the Brewerty, mated with this one called you by honest. This is what they discovered a few years ago. This is what it's like in the wild. Can you imagine this is, it's, it's growing on the side of a tree in Patagonia. It looks, yeah. It looks like little fruits or like oranges or lemons or something that somebody glued to the, to the bark of a tree. Yep. Exactly. Those are, those are, that's fungus. How did it get to Europe? Like nobody knows how it got to Europe. But this is like the mating of these two things is how you get loggers. I love a good logger. So yeah. So fungi, like they'll mate with each other, two different species. And so we did a little experiment when we were first starting out, you asked me kind of how we got into this startup thing. And this was one of our earliest projects. When it, when we started working on it, we said, we're going to go to an open fermentation brewery. Right. You go to a brewery that makes beer. And you know, some of them, some of the micro breweries, they, they, they use like natural inoculation. Basically they leave their stuff hanging out and it gets infected by something. And then they like, if it tastes like decent beer, they'll bottle it. And so we went to such a brewery called, called Epic Ales down in South Seattle. And we got some of their open fermentation beer. It was awesome. And then we, but we did science to it. We like, give us some sample out of that beer. Beer is science. And then you did science to the beer. Yep. And we science. That's cool. Good. And so, so this is like a data version of what I was telling you about separating a mixed community. This is a very simple mixed community. Beer normally doesn't have like hundreds of things in it. It's usually has like one or two, but open fermentation beer is a little bit more complex because they have like a bunch of bacteria and stuff too. So, and so. When you say open fermentation beers for the people who don't know what that is, does that mean they're just leaving the lid off when it's fermenting? So anything. Yeah. Yeah. Okay. Yeah. And so this is like, it's like a craft brewing thing. It gets infected by something out of nature, out of the air. And then you kind of brew it up with that. Well, this one, so what you're seeing these clusters is like, it looks kind of like a soccer ball. So the big spots, these groups of colors on the soccer ball, these are DNA sequences that in that sample, we're all mixed together. But our data are special, this proximity ligation, this high C data, it is connecting the pieces that we're touching each other and separating them into these groups, right? So like all of these pink ones, like they were all touching each other a lot, which means they all came out of one organism. And this same thing with this orange one. And so you separate the genomes out of this mixed soup. And now you can be like, ah, I got this green genome and I got this brown genome and I got this. So you can tell which organisms live there, even if they've never been sequenced. And here's one of the cool things. So actually like four of them, four of these bugs, like we gave them names, but they actually were not sequenced before. But especially this green one was an interesting surprise. It was a yeast, but its genome was double the size of a normal yeast. And half of it was mapping to a known organism and the other half was not mapping to anything. So it was like half, like the genome was double the size of a normal genome and half of it is known and half of it is unknown. And so we said, well, maybe this is a hybrid. Maybe this is a new hybrid that nobody's discovered before. And it totally was. So like, because it's beer, it's easy to grow these things like it's cultivable. And so I grew, I grew in these like super cute velvet, velvety kind of colonies. So for those of you in the audience who don't know what this is, this is a Petri dish full of like jello that like yeast will live on. And you put a few of them on there and one cell will like land here or there. And because they can't move, that one cell is going to start growing and multiplying over and over and over until it builds this little mountain called a colony. But they're all like, just like lots of cells that came out of the same clone. So it makes this like cute little colony. And we can look at them under a microscope. They're like really cool. They line up in these little palisades it's called. Like they're like side by side growers. I don't know why, but that's not like normal. Like it's interesting. And it turned out indeed that this thing had two genomes in it. One genome was from a known organism. One genome was from an unknown organism. And when I talk about this in scientific conferences, I present this data to show like, how else would you be able to tell from sequencing a mixed community that there was a hybrid in there? Like how would you know that it's not just two different species? Like how do you know they were inside the same cell? And that's like, you wouldn't know. Technology does. Yeah. So away from the, I guess, more, it's still going to be fungoli and microbialy. There was a, you made a comment about, you made a comment about poop earlier, just on the fly. You have worked with cats. I have worked on many poops. Yes. In fact, in fact, one of them. Yeah, please tell. Poops. And if there are any bioinformagicians in the audience, we actually sequenced the poop of a famous celebrity cat named Little Bubb. So a few years ago, we had another kind of Twitter thing called hashtag meowcrabiome. And we wanted to sequence, yeah, so we got, we got Little Bubb's poop. And we sequenced it and we discovered a bunch of new bacteria. And it's on our website. You can download it. It's for educational purposes. We didn't publish it. It's like, it's just for anybody to play with if they want to. So Little Bubb, unfortunately, has passed away recently. But, yes. But her poop DNA sequence lives on. Did you find anything interesting? I mean, was there any kind of interesting insight about an internet celebrity cat? In particular. Well, let me say that. What we found, they think is what a lot of pet owners, like, there were, I mean, like, there were a lot of new bacteria in there, but there were also a lot of, like, known human bacteria in there. And I think somebody was like, why don't you, can we make the case that, like, pets and their owners share stuff? Which is probably true. Yeah. Not necessarily just on the outside, either. Correct. Okay. I have a couple of questions. Back to the Shark Tank version of the show, where we find out. What do you use to sequence? Are you doing the sequencing or are you getting the sequence? Well, so, yeah. So we own sequencing equipment of our own and, but we also, like, outsource sequencing to providers who have the, like, mega machines. Okay. So, but do you use, or are you using Illumina? Here's Illumina primarily. Okay. So here's the question. Like, is this, is this cost-wise? And I have more efficient than going through and tagging everything on a robot before putting it in a sequencer? Like, because it sounds like you don't really need to have anything identified. If you're doing a bunch of short, you know, you're taking a hundred micro, 400 microbial samples and putting it in. Normally you have to, actually you can do more than that. You have to label each one with this sort of tag that's associated with it that gets read out of the machine later and it goes through a whole process of algorithm interpretation and looking for that tag and making sure it's associated with the thing that went in in the first place. Can you just bypass that whole part of the system? To some extent, yes. Right. So normally what you would do is you would separate the little bacteria in it physically and, like, grow them up separately and then sequence them separately and say, like, yeah. So, like, you know, that sample I showed you had eight bugs but, you know, like, if we take a soil sample, it might have 800. So you now have to sequence eight, you have to grow 800 things. And sequence- Separately, though. Separately. Because you kind of have to have them separately tag them so when they go into the thing, they come out as knowing what it came from in the beginning. You don't need to do any of that. Right. And keep in mind that I'm glad that I'm blowing your mind. I love this. Yeah. And keep in mind that when you're trying, the problem with the microbiome stuff is that most of the stuff out there won't grow. Either we haven't figured out how to culture it properly or it's unculturable, that people call it. Or it requires other members of the community to survive. And so it will never grow by itself, right? And then there are practical things, like there are these filamentous fungi, like, you can't separate them. Like, they grow as clumps, these snowflakes and stuff like that. You can't get a cell off. So there's lots of other issues. It's not perfect. Sometimes if a community is simple, if you're just trying to figure out, which strain of E. coli is in your chicken or whatever, like, you don't need this stuff. It's heavy weight. It's designed for discovery things. Because we'll go into a soil sample. We'll discover hundreds of new bacteria, hundreds of new viruses, a bunch of new antibiotic resistance genes, whether or not. Like, it's like more information. Like, if you want that information, cool. If you're doing a diagnostic, you may not need that. You're just trying to be like, is this like a pathogenic thing or not a pathogenic thing? And that may be enough, right? So, but you know, but for discovery efforts, like that's kind of what this is geared to be. Yeah, that's fascinating. I'm very impressed with the applications or the potential applications of what you've got there. Well, this would be a great thing to do with the Martian cores. This is immediately what I'm thinking about here because, so you know, we're always talking about how, no matter how clean the stuff is that we're sending up there, there's always stuff that we're sending up there. So this would be the perfect way to do that, right? Is you could, you could sequence this Martian dirt and you'd be able to pretty quickly parse out if there's anything that you haven't seen before versus things that you have. Yeah, I mean, assuming something like is growing here. Somebody's actually there. Because we always accidentally throw. Well, we do find something. So we discover there's just like I know bacteria. Let it sit for a while and then sequence it again after a couple of years and see what it did. Yeah, I think you'll find Carl who works in the clean room back at NASA. Exactly. You'll also find oddly, Carl's cat was also represented. Yeah, is that like everything is contaminated? At some point, yeah, everything will get there. Just be like this bacteria came from Matt Damon's poop. Is this an abandoned potato farm? Yeah. So you've also worked in synthetic biology and there is this idea of like one day we're going to be able to put DNA printers on Mars and print our own special bacteria that will live there. But if you're thinking into the future of where your technology, the stuff that your company is doing and like the future of this chromosomal genomics, like what do you where do you hope that it's going to go? The kinds of discoveries or things that it might lead to? Yeah. Well, I mean, there are many. I mean, the general trend is that we are moving further and further into like the information space. Like like not to get too kind of like trippy, but like life is basically information, right? It's just math. Life, the whole universe is just math. Math is applied information. We emerged from math. And so the more we understand how everything works, everything becomes better, right? So new like the most applied things are like new diagnostics, new medicines, trying to understand what the mutations are in your body and how are you sensitive or resistant to particular drugs? You know, customized therapies, customized medicines, that kind of stuff in the agriculture space. You know, like what we're saying, like like plants need fungi, plants need bacteria. Nobody knows what's going on in the soil, but they know that like there's like good soil and bad soil. Like like sometimes farms will fail and try to understand sort of being able to, let's say predict what crop is going to grow best over here. What crop is going to grow best over there. Trying to understand, trying to be like, we found like a really good combination of microbes that we can spray on the crops instead of pesticides. And you know, and use, use, and they do. That would be cool. There's a whole thing that people are, it's a big area of development in the agriculture space using naturally, natural bacteria as fertilizers and pesticides instead of like chemicals, right? Nitrogen fixation, bacteria, we have, there's tons of nitrogen in the air, right? Air is like 70% nitrogen, but like, but like plants can't consume it. They need bacteria to turn it into like ammonia, basically to fix it and then plants can use it. That's why we spray ammonia like fertilizers and plant salt. But what if we didn't have to do that? What if we just got a bunch of bacteria that did that more efficiently and now you have, you know, better, everything, you know, plants grow better without having to even necessarily do like GMO stuff, right? It's probiotics for plants. I love it. Yeah. I mean, like, I'm not like, when I think synthetic biology too, like synthetic biology usually refers to using like bacteria or microbes to make stuff. So like using them to make things, you know, you guys know like impossible foods, right? It's the company that like they make, they make meatless burgers, right? Well, what they've learned is that the trick to making a meatless burger taste like meat is making it taste like blood. And so the trick is to make it, and so they synthesize their hemoglobin, they make heme, they make like a version of heme. Out of fun, guys. They grow it in yeast. And so yeast makes the heme that then goes into these plant-based burgers, right? I mean, there's like so much stuff. Like some of it is like super crazy. Some of it is super practical. But I think the whole thing is pushing us from like a lower information state to a higher information state. We like know more about everything. We can do all sorts of cool things. I think that's fantastic. I want to know more about more things. Take us there. Take us there, Ivan. What is one thing if you want people to have a takeaway message about genomics and about the technology you use? What's like the one takeaway message you hope people will take with them? I think that people shouldn't be scared of it. I think it's very easy to make science scary and confuse people with it. Everything from like vaccines to GMOs to like all this other stuff. And I think people should remember that like making harmful genetic things is harder than they think. Like you're not just going to magically release like super stuff. And the information that you can get and the benefits of getting the genomic information out of systems is super valuable. And so the message is there's an enormous amount of stuff out there. We've barely scratched the surface of what we know. And we should like keep trying to learn more all the time. That's definitely that's something I'm seeing here that I feel like was brought to light for me from this interview was every time I see an article pop up that, oh, we sequenced another genome. It's like, okay, cool, I guess, nice. But now it's much more clear to me how important that is and how knowing things, it's like the conversation you're having about the null hypothesis. Knowing what you know allows you to know what you don't know. That makes any sense at all. No, it doesn't. It does. So I didn't get it. It does. It gives you more ideas of things that, what else? Oh, it gives you more questions. And it's true. This is the thing that we know. This is the thing that we don't know. And being like, okay, we're sequencing this genome. Why? And it kind of goes back to what you guys asked before. Like how do you do it? So sometimes we just, sometimes people do these genome projects just to do them and then figure out, because there's a little bit of a chicken and egg until you do it, you like don't know what the question really is, you know? And so sometimes, but that doesn't that end up with too much information? Like if you didn't, like I'm going to zero out everything, but this narrow field, there's so much data that how can you distinguish noise from not noise? It's just too much, right? It is too much. Yeah. And you have to figure out some way to take important insights out of an overwhelming amount of data. I mean, I think like, I think probably like, I don't know what it is, like every month we generate like 10 times the, like all the books that I've ever been written, you know? Yeah. It's a ridiculously large amount of information to be able to sort through. And then what do you learn from it? Right? Like, because the problem is, and this is a problem for our field, for the genomics field, we can generate sequence data way faster than we can figure out what it means. Because to actually figure out, like what does this gene do? You got to do like experiments in the lab with cells and maybe mice, and maybe people, and maybe you have to let that stuff, and that takes forever. Sequencing and doing computer stuff is fast. Right? That's sort of the race. So you've got, so then you can, yes, you can generate all these things, but until like, these genes have been annotated until somebody can put a name on it, and not just a name like, we'll call this gene Fred. Okay, Fred's a gene now. What does Fred do? Nobody knows. We know Fred's a gene, but now you have to go through experimentation and knock out for one specific gene to know what its effect even was on the larger body. Mind that gene Fred may not do anything. It may only do things in conjunction with five other genes. Right? That's like, how much of gene is being expressed? Does it need to be a lot or a little? Like cancer is all about good genes going bad. Like, there's no gene that was designed to make cancer. Right? They all supposed to be good things, and then you like change little function, and now it's got a completely different action. Right? And it's only bad for the larger organism. It's not necessarily bad in the terms of the minor ecosystem of the tumor and all that kind of stuff. So it's all perspective. Yeah, now it's all about substantial stuff and we're like, doesn't it even mean anything? Does it? What does it mean? Yeah. Can it position it on a chromosome? Sorry? Can it locate the position on a chromosome or what? Could what locate? Yeah, what you're doing as well. Like tell you where it is on a chromosome, next to what, next to what, and we're all in. So this is okay. Yeah, yeah. So suddenly you start getting genes that work in conjunction that are local to each other or you can start figure, if you started doing association. It's all another level. It's not even DNA anymore. Now you're talking RNA, you're talking proteins. Yes, that's different. You have like all this other stuff. So yeah, I mean, I'm just talking about like the blueprint. Like I'm just talking about like where stuff is. Like the running greens is like a whole separate dimension. Yeah. Ivan, thank you so much for joining us tonight. Yes. Yeah, thank you for having me guys. It was great. Where can people find you if they are curious about phase genomics? You can find me at phasegenomics.com. You can find me at my name, hashtag at Ivan Leachko on Twitter. If you are interested in genomics and startups, we also run a little event sometimes called Genome Startup Day. So that's just genomestartupday.com. We bring a bunch of genomics startup founders. We talk to them about their experiences, things like that. And so yeah, that's our website. If you're interested, we have a whole section on publications and how it works. And we have like a news articles and blog. There's a lot of stuff on there. You can follow us on Twitter, LinkedIn, the usual social media type thing, except we're not Facebook. I don't think we do anything on Facebook. It's probably better that way. Don't let the Facebook overlords mad. You never know. Just saying anything. Quiet, Kiki. Quiet, Kiki. Thank you so much. This has been absolutely wonderful. Yeah, really great getting to speak with you. And thanks to my good friends at S2S PR who connected us. Yes. Many thanks to Eric for connecting us for this conversation. It was, yeah, it's been really, really fun getting to find out about your technology, getting to find out about how we can delve into business. Yeah, genomes a little bit more. Let's get to business. All right. We must move on with the show. Thank you. All right. See you guys. Thanks again. Thanks. Have a great night. Bye. This is This Week in Science. We are talking about science. We have a bit more of the show coming up. We have stories ahead. For those of you that are enjoying the show, hey, make sure you click that like button, subscribe, get notifications for when we go live. And if you would like to help Twist grow, please get a friend to subscribe today. If you're subscribed, maybe get a friend to subscribe too. And then you can share the show together. It's amazing. You talk about it together. It'll be fantastic. More the merrier. Thank you. I think there's a thing happening right now. Oh, wait. I'm getting a broadcast. It's coming in loud and clear because I do believe it's time for Blair's Animal Corner with Blair. Who's there? Thanks. So disarming. Anyway, hey, it was Valentine's Day last weekend. Roses are red. Violets are blue. You know the saying, if you chew off my wings, I'll chew off yours too. It's as old as time. This is a study about wood-eating cockroach couples. They are monogamous, these cockroaches. They live in Japan. This is a piece of research from Kyushu University in Japan. And a couple of researchers, Haruka Osaki and Aitikasuya, they happened across some wood cockroaches. That had chewed off wings out in the wild. They were very confused by that. And so they decided to bring some into the lab to study. Now, wood-eating cockroaches normally feast on fallen trees in the wild. And in more recent days have of course taken to eating wood that makes up people's homes. And while they were studying some of these bugs in the wild, they noticed that most of the adult roaches had wings that were almost entirely chewed off. So they took 24 young adult pairs with wings still intact and brought them into the lab to study. It appears as though these cockroaches use wing chewing as part of an after-copulation grooming practice. I love you. I will chew your wings off. That was really great. I had fun. Did you have fun? Great. Let's chew each other's wings off. Usually, one of the pair was groomed in such a way after a mating session, but it varied how much the chewing would happen between one and the other. In some instances, one would eat the wings and then the other would kind of start, stop, and then just leave. In other instances, the one being chewed on would shake their body to let the other one know, okay, enough. That's enough. You took enough of my wings off. Thank you very much. Out of the 24 pairs, 12 chewed each other's wings down to the extent that they had seen in the wild. So this seemed consistent. As I mentioned, they are monogamous. So the prevailing theory now is that this is actually a form of grooming, that cockroach wings are susceptible to mites or mold. And so eating wing tips could be a way to remove mites or mold to ensure survival to a later date. But now you can't fly and you don't have wings. But hey, no more mites. You're clean now. It's grooming gone too far. It would be as if it were monkeys grooming each other, but instead of just grooming off the ticks and mites and stuff, they're actually pulling all the hair off. I'm not going to yuck their yum here today. Say, you know what, cockroaches, you do you. You do you, cockroaches. You're such a good person, Blair. I'm not going to king shame cockroaches today, is all I have to say about that. But you know, happy Valentine's Day to those cockroaches, especially. Now moving on, I have a much more complicated story about spider legs. So a lot of people are afraid of spiders. There's a lot of theories where that comes from. There was a really cool story we did years ago now, I think where it seems like there's actually genetic inherent fear of spiders in humans from a very young age. But a lot of people will cite the way spiders legs move, as the problem that creeps them out. They they move around almost as if they have a mind of their own. So a recent study looking at Araneus diadematis, which is the common garden spider, otherwise known as Charlotte from Charlotte's Web, looked at how they make their webs, and what part of their body is really in charge of that web building, which is a really complicated process, actually. So in order to figure that out, researchers actually over many, many years and many, many experiments with spiders, they were able to make a virtual spider. So this is a spider in a computer simulation. It's a simulated spider. Yes, Theseus is the spider's name. They ran Theseus through countless numbers of webs that they scanned, they took pictures of from the real world. So they were picking real spider webs, and then kind of teaching Theseus the shape of these webs. So then they were able to set Theseus on the kind of the web scaffolds that a spider would make. So spider webs are made out of a bunch of different types of of webbing. And so you have kind of the main scaffolding pieces of the web, and then they make that final last pass of the sticky sensory webs on top, which is the real trap, the real way that they catch their food. And so they were able to send Theseus on this final route of building the web, all based on learning from the real spider construction. And what it looks like is actually an iterative process where they don't just go around in a spiral pattern. If you watch a spider build a web, there's a lot of turning back and forth and zigzagging, and it almost looks nonsensical, but it's actually really specific. It's in order for them to fill out each of these individual holes, because the spider web, if you think about it, is not a perfect circle. So that means that their scaffolding pieces are not always symmetrical. So if you have this kind of elongated web, then some spaces in the elongated portions are going to be bigger than spaces on the sides that are smaller. And so doing some zigzagging in those larger bits will make sure that they have covered the entire surface area of the web with evenly spaced out sticky sensory webbing. So that means they have to make these decisions in the moment, these iterative decisions. Okay, I went here, now I have to go here. Okay, here this needs more. So now I need to turn back and forth here. All right, so now I'm going to go back over there, and I need to fill this part in. So it builds upon itself. Too big of a gap here. I need to fill this up. This isn't the way I want it. Well, this is looking pretty good. Maybe I'll keep going. Nope, got to turn around. Yes. And so what they found was that this is actually something that the brain has outsourced into the spider's legs. The spider legs build the webs, semi-autonomously. They are closed feedback loops inside of each leg. So the legs are basically feeling... Tension detectives. Yeah, they're feeling the distance. They're feeling the tension. They want it to... They're plucking their violin strings. Stability, something's not right here. It needs another pass. But it's not the spider deciding. It's the spider's legs deciding. Sensing and reacting. Wow. Yes. And so they also confirmed this by figuring out what happens when spiders lose legs. So when a spider leg becomes trapped, they'll ditch it. And then they regenerate when they molt and they get their next exoskeleton. Wait, I didn't know that's a spider's leg. Yeah! How did I not know spiders do that? They grow new legs? Crabs do it too. Stock with exoskeletons do this because they don't have any internal anatomy that stops them from doing it. So basically they're just rebuilding an exoskeleton. So you can do that. That's easy. And especially if you're growing and what you do is you're rebuilding an exoskeleton by molting all the time. It's what they do. Imagine if every few months you built a whole new set of bones. It would be easy to regrow an arm. Yeah. No problem. What? So anyway, so when they discard their trapped leg or it breaks off or whatever happens, they do get another leg, but it's usually a little shorter. It doesn't match the rest of the body perfectly. But it has brand new hairs and sensors. And it still is able to build these perfect webs and these individual legs act in the same way. So if you go around collecting spiders' legs, you too can build webs. Wait, no. That's not the way it works. Probably not. Okay, so wait. What does a spider's web look like if they lose a leg and then try to make a web? It probably looks the same. I mean, they have eight. I got plenty. Yeah. But I wonder. I think this was a really interesting story. After last week, we were talking about dragonfly brains and how I was talking about how they're kind of rudimentary. So this is part of that, right? Is that a spider brain, this is part of where this study came from. A spider brain, as far as you can tell, is not capable of making something as complex as a spider web. So this helps answer that question. Because it's not the brain, it's just the legs. It's the, they've outsourced it. Yeah. But there are other ganglia around. But that gets at, it's like very almost octopus-like where octopus legs have their own brains. I was thinking exactly that. Yes, it's very octopus-like. And of course, the researchers looking at this, what's their next choice after this? Better bring it to robots. So a decentralized system would be perfect for robots. They call this morphological computing roboticists. And they've only recently discovered its power through looking at the animal kingdom. And now they want to kind of push that towards robots because it could totally change the game if you can take external stimuli and not have to feed it back to a centralized computer. Yeah, well, I mean, I think for so long we have had this goal of figuring out the human brain. Or, you know, the brain. Humans have this big brain. And so it's all about the brain. But one of the earliest things you learn about in physiology is the reflex arc and how spinal reflexes allow us to walk. We have this same kind of... We're not building webs, but we're able to walk. We're able to run. We're able to have these patterned movements that it's basically once you start moving, you have offloaded that cognitive effort to your spine and to the rest of your body. I must not have... No wonder I was so bad at track the whole time. I'm like, left, right, left, right, left, left. Oh, no, I'm falling! You're thinking too much. Thinking too much. Just it, oh no. Oh yeah, so they can... They also say another example of a decentralized task in the human system is your heartbeat. And your heart... Yeah, so your heartbeat, you have the pacemaker cells that keep it all on rhythm. And you have your vagal currents that come in and kind of go, oh, slow down now or speed up. You have your other stimulating nerves that come in and make it go faster. But just to keep your heartbeat going, it's got its own rhythm. It doesn't need anybody telling what it to do. And it speeds up and slows down. It's got it all figured out. But yeah, so this is a very cool example of... We thought for a long time, we thought the human eye was the best that eyes could get. It's like, oh wait, actually, birds have really good eyesight. Oh wait, there's mantis shrimp. Oh wait, nautilus have pinhole eyes that are actually pretty good and are nothing like ours. So this is a... Oh, the human brain that's the best it's gonna get. Oh wait, there's octopus brains that are donut shaped and they have the brains in their arms. And then also there's spider brains that have... It's also cell size, brain tissue or neurons or something like that. So that even if you have a giant brain, if you've got giant cells doing that work versus I think it's birds, have very small cells. So they can actually have in that tiny little brain they can actually pack in quite a few operating, yeah. And the distances between the cells, it's shorter and so things happen faster. Yeah, there's a lot of trade-offs. Levels to the whole like a brain. We're not the top of this evolutionary pyramid. Well, it's a plateau, right? There's all the sorts of stuff that got to where we're at. So I think that... I will say that I do think it's always amazing whenever I hear about another bird using a tool, innovative thing. I love those stories. I think especially COVID is super intelligent, much more so than we thought, but I've never had a power drill made by a crow. I mean, I think there's... Hey, all things are mean. We're dropping stuff on Mars. I do think there's something pretty remarkable about this human brain that's not quite plateaued from the rest of... Citations are hanging out in the water looking at us on shore going, oh, those dumb monkeys. Thinking they're going to do things again. They're just ruining things. Yeah, they're ruining everything. They're ruining their lack of anthropological knowledge. Well, we're going to keep this show going. Blair, thank you for an amazing animal corner. You got it. This is fantastic. Everyone, this is This Week in Science. Thank you. Thank you so much for joining us this week. And I hope that you join us every week because we bring you science all the time. And the only way that we're able to do that is with your support. So if you have the ability, please head over to twist.org and click on our Patreon link to choose your level of support today. You can help us bring science curiosity or sometimes random facts or arguments about how random facts may have actually come to be or what they actually tell us. But you can help us share that and keep doing what we're doing every single week by becoming a Patreon supporter. $10 and up a month, just a month, we will read your name at the end of the show. Help us grow that list. Help me just feel like I have so many names to read. Like, I want to do that. Make it longer. Micro machine voice. Micro machines, that's right. I'm going there. Thank you for your support of Twist. We really cannot do this without you. All right, Justin. Tell me a story. You got a story for us? Got two stories. Let's see. Here it is. From the Okinawa Institute of Science and Technology, they looked at some genes that can help against COVID. So some people are experiencing mild or even no symptoms whatsoever when they are confronted with COVID-19. Others are not so lucky. This is the researchers at Okinawa Institute of Science and Technology Japan teamed up with Max Planck Institute for Evolutionary Biology in Germany and they found a group of genes that reduced the risk of a person becoming seriously ill with COVID-19 by around 22%. And those genes are inherited from Neanderthals. This is Svante Pabo. Of course, other factors such as advanced age, underlying conditions such as diabetes have significant impact on how an ill and infected individual how ill and infected an individual may become. But genetic factors also play an important role. And some of these have been contributed to present day people by Neanderthals. So last year I think we talked about was it last? Oh yeah, everything's last year. Last year we talked about how Pabo and Professor Hugo Zeeberg they reported in nature that there was a greater genetic risk of developing severe COVID-19 if you had inherited Neanderthal genes. There was some set of genes there. So the latest research builds on a new study published in December from Genetics of Mortality and Critical Care Consortium in the UK which collected genome samples from 2,244 people who did develop the severe COVID-19. The UK study pinpointed additional genetic regions on four chromosomes that impact how individuals respond to the virus. Now this study published in PNAS. Professor Pabo and Professor Zeeberg show that one of the newly identified regions carries a variant that is almost identical to those found in three Neanderthals. There's a 50,000 year old Neanderthal from Croatia and two Neanderthals from southern Siberia one that's 70,000 years old, one that's 120,000 years old. So these are genes that are going way back. This second genetic factor has the opposite effect of that first one that they had discovered providing protection rather than increasing the risk to develop the severe version of COVID-19 reaction. The variant was located on chromosome 12, reduces the risk that individuals require intensive care after infection by about 22%. So this is Pabo again. It's quite amazing that despite Neanderthals becoming extinct around 40,000 years ago, their immune system still influences us both positive and negative ways today. So to try to understand how these variants affected, they took a closer look at the genes located in these regions. They found that three genes in this region called OAS code for enzymes that are produced upon viral infection and in turn activate other enzymes that then degrade the viral genomes in the infected cells. This is absolutely immune system for this. What I kind of found also interesting is that these Neanderthals would have been sort of just coming out of an ice age in one of the cases. So this is like as people sort of reemerged back into the world after a long point of isolation or these Neanderthals reemerged out into the world after probably some decent isolation, they probably encountered a lot of these viruses. And so there's probably a culling of who had their right gene who didn't have the right defense gene. They found that the variant increased in frequency after the last ice age and then increased in frequency again during the past thousand years as a result. Today it occurs that about half of people living outside of Africa have this gene and around 30% of people in Japan which is sort of interesting because last time they looked at the gene that looked harmful nobody in Japan had it. Interesting. Yeah so it also starts to focus you back to okay so now you know that you can also sort of isolate which groups of Neanderthals intermixed with which groups of humans at some point in their previous history based on who does or does not have the vulnerability gene who does and does not have the gene that procures some sort of resistance or some sort of fight back. Yeah I wonder how it also if it also has anything to do with how COVID-19 is spreading around. So it's just it's only seems to be affecting the severe COVID-19 effects but not necessarily transmission that they can tell right. Well I mean yeah so this isn't this has nothing to do with transmissibility I don't think that was Yeah just looking at symptoms. Yeah it's about whether whether your body takes on an immune response that prevents the cascade of events that take place to get one severely ill where they're personally in danger of dying or increased danger of dying from the disease but yeah that's the whole that's the whole problem with of course yeah with something is it would almost have been better if this was just a very very very very lethal it wouldn't be much better if this is a very lethal virus that killed 50 percent of people on contact wouldn't have spread wouldn't have spread as much maybe we wouldn't have killed as many people you know what I don't want to think about whether or not it would have been better or worse you know that's where MERS got it wrong MERS pretty much killed everybody and so there was no time to spread it here's the virus and people were and people were afraid of it so they so they were like I'm gonna stay home and they stopped to spread themselves behaviorally because it was much worse serious oh yeah I don't want to talk about that psychological effect but oh okay well then let's talk about something else yeah so anyway so anyway if you have that rare variant that came from a neanderthal it might be making you 22 percent more immune to the serious effects I have like two and a half percent neanderthal genes so I but are they the right ones are they the right ones I kind of hope so got a 50-50 shot according to your study anyway if you look it up though if you did one of those genetic testing things where you send in your gear your spit and they give you genome it might tell you if you have the rare variant next study commercial genetic testing companies are using extremely unreliable technology in detecting very rare variants meaning results suggesting individuals carry a rare variant genetic variant be it disease causing or not are usually wrong and if you're usually wrong that means you're wrong most of the time so why this is important though is that people have actually gotten surgery and it doesn't go into it here but I'm assuming that this is but this is people who had the very rare genetic variations for the BRCA-1 that shows increased risk of breast cancer may have gotten mastectomies when they perhaps didn't have the variant so it's created preemptive decisions about health that are mostly unreliable this is not a good thing team of university of Exeter conducted a large-scale analysis of technology that is being used or no technology using data from nearly 50 000 people so that's a pretty decent set they found that the technology wrongly identified the presence of very rare genetic variants in the majority of cases so the team analyzed SNP chips so SNP is single nucleotide polymorphisms so this is when you have a genome and you've got the you've got all the letters and then one of the letters is switched to something else just one that's a single nucleotide switch so the so they've tested this on specific locations across the genome and they found that these chips that can test for those single changes that that have been apparently utilized when somebody's submitting their their DNA to one of these commercial sites was really good it was excellent at finding common genetic variations so something like risk of diabetes type 2 diabetes these sorts of things maybe it's something that has to do with the ear lobe or the color of your hair or something like this they were excellent at this but when there's something that was a rare SNP change or rare to happen in nature the machines were really bad at detecting it and in fact made mistakes so like the previous conversation we were getting into was talking about all of the different types of short read long read how many layers of a read you get how you can make those decisions based on algorithms that you apply to this raw data and putting these pages of these books together a lot of the commercial technology is using a sounds like a rather roughshod version of that now they've also a lot of them been around longer than this next generation technology has existed yeah so but this this sounds like this just means we need better genetic testing in medical use because you could get you could get your 23 and me right and you could see oh oh no it looks like I'm predisposed for xyz if I could then go to my doctor and say hey I got this scary thing on my 23 and me can you do a genetic test for this disease I think that's way but like you know your fitbit might tell you that your heartbeat's bad but you're not going to do anything about it until you go talk to a doctor first right and they they're going to hook you up and put you on the treadmill and figure it out with their better tools we need to have the better more reliable tools for medical decisions it seems like it is interesting though I think what might be happening here is that you've got it's rare variant and so what you're dealing with is something that occurs in a very low proportion of cases and so a lot of this genetic it's on the as you said just in the bio informagents did inform magicians magicians yes on that side of things it is statistics and it's probability of things popping up and so if you are layering things together and putting things together and putting them in a certain order and figuring out whether or not they exist in a certain place in a certain form all the time or only sometimes that's going to depend on how many times you're reading something and how many how many overall copies of it you have and so if it's rare the probability of either it being an error and something that was a mistake in the reading or a real signal that is a real issue so it's coming down it it's got to be because it's rare this is a statistics and probability issue yeah so so they said in and very rare variants these are variants that are present in less than one out of a hundred thousand individuals they found that the those causing rare genetic rare genetic disease ones one in a hundred thousand people would have this 84 percent were false positives in the uk biobank so they had in the data from commercial customers 20 of 21 individuals analyzed had at least one false positive at least one false positive for a rare disease causing variant that had been incorrectly genotyped now one of the things that they also point out in this study is that a lot of these a lot of the companies that that are doing this commercial genome stuff are also when they're getting when they're going back over and they are taking second third passes at the rare genetic variants when they show up and correcting them in sort of the final output however the big problem is if anybody is pulling their raw data or taking the initial information from the read they will get that that those false hits yeah i mean i think a lot of what this goes get that there are a couple of people saying this already in the chat room which is don't use any of these personalized genetics sequencing companies where you can have your genome read for medical decisions ever verify go to your doctor like you said Blair make sure that you're getting a couple of tests make sure that you are not just basing it on one data set make sure you have verification yeah yeah especially and there were like lawsuits for 23andMe like at the federal level about whether or not 23andMe and other companies could even be used to give quote unquote medical advice and now they have a whole thing where it's like this is not medical advice you should not be using this to make medical decisions and they say they have disclaimers about that entirely but yeah it was shut down completely and there you know there's lots of disclaimers because it became a very big legal thing however however that said for the common ailments the ill people it's actually shown to be quite accurate you know the it's it's uh the rare stuff the rare stuff is getting is what's getting the false hits so yeah if the rare the disease you find when you put in the diagnosis when you self diagnose on one of those web medical diagnosis tools and you go on there and you say you're feel nauseous and have some fatigue and you know a little bit of a joint ache yeah i can put that in it and next thing you know you've got the yellow fever it's every time you have cancer yeah or you've got some rare tropical disease now because cancels because some rare tropical disease like yeah it's a stretch yeah i'm gonna jump forward i've got a couple of stories before the end of the show here i want to talk about your brain my really your yeah your your brain my brain everybody's brains yes i want to have a conversation about using your brain so this is a really interesting study out of the max plonk institute for experimental medicine and also the university hospitals of Copenhagen and Hamburg Eppendorf all these researchers uh collaborated on a study looking at the effects of mental and physical demands on the brain so they discovered a while ago that hypoxia in the brain releases a compound called erythropoietin epo and this is a growth factor so shortage of oxygen releases a growth factor and in these experiments that they did with mice in the lab running in a mouse running wheel or doing mazes and having to do cognitively demanding tasks for a mouse they discovered that oxygen deficits are created little localized shortages of oxygen around your neurons that are working really hard if they're working really hard they're using up all the oxygen and the blood isn't necessarily keeping up with delivering it and that's a slight hypoxia they call it functional hypoxia and they discovered it leads to the formation of new nerve cells they wanted to know how and they discovered then that the hypoxia activates this growth factor erythropoietin in the brain and it leads to the development of new new connections and dendrites is a part of stimulating the brain and now the big question is is this the thing that is involved in making the connection between exercise and mood exercise and the stimulation and the effects that exercise has on the brain is this what's happening in the human brain is it functional hypoxia that creates makes you smarter running makes your brain expand this is also kind of I think also last week we talked very briefly about how stress can be good for a system so this this could be that too just any sort of stress any sort of kind of fight or flight moment any sort of challenging moment where you have to think fast it could create this stress that causes it it's like growth from hardship right yep yeah exactly and I you know I imagine that it's the opposite so this is an acute problem right so if you're running you're yeah not chronic exactly you're not always running you're running a little bit and that's good or it's you're thinking really hard you're working really hard but this isn't chronic stress right it's working your brain a little bit but not too much and so so this I think it's a really interesting mechanism and their next steps are going to be trying to discover whether or not they can put a person on a treadmill or an exercise bike and actually see if they can measure some of these changes and see if they can I don't know they're able to find in mice because they can slice the brains and check for gene expression and all sorts of stuff they're able to find a change in expression of this epogene but they have to try and make this connection in humans as well but this this could be one of those really important connections between how physical activity leads to changes in the brain or as J.G. in the chat room so Alec only points out and I like the way you think so exercise or just hold my breath that's right just everyone's not not too long hold your breath while you're studying I don't know yes breathe everybody breathe my final story for the night is about birds because I love birds and I've always wondered this about birds how do little tiny birds stay warm right how do they live down feathers they have down feathers right but how do they really stay warm like there's a difference between I mean there's got can you take a bird from the beach and put it up on the mountain and will it stay just as warm will a bird that you take from the mountain and you put it down on the beach is that going to get too hot like is what is there a difference in what's happening there and so a but Peter Buckfellow at the Smithsonian's National Museum of Natural History took a look at the Smithsonian's collection of 625,000 specimens to study the feathers of Himalayan song birds 249 species these are birds living at really high elevations and yeah she was based all on her question she was studying birds in the Himalayas and she said do they have a down jacket I have a down jacket do they do they stay warm so she looked at all these birds that were in the in the Smithsonian's collection and discovered that yes birds who live at higher elevations have more fluffy down than birds who live at lower elevations so the elevation that the song bird lives at it affects the thickness of their down jacket it's just like dog breeds from colder climates have thicker undercoats yeah and so this does kind of get at that question of where different animals can go and where they're going to be comfortable and so as we have climate change kind of moving species different places this may be an indicator of which places birds are going to be more comfortable by being able to predict how they might be able to withstand or respond to climate change very easily although this is very likely something that is a very adaptive trait and so this does this study does not get at the question of causation is this you know really a genetic issue that birds at higher elevations have like you know like people who live at higher elevations do they have just different genes that lead to more of the down they don't know that probably both or is it just adaptation I'm cold I need more feathers I would guess it's both because birds are birds are constantly losing feathers and and molting and growing new feathers and unless you're a penguin then you do it all at once but it's all at once yeah that's called a catastrophic molt but fun back that's a great name oh my god we've had so many fun facts on the show tonight yeah but but yeah I bet I bet it's both I bet they had they're they're they start out with a set of thicker feathers but that if they were hot I bet they would lose some density that would make sense to me yeah yeah so anyway down jackets on birds every time I look at a little bird in the cold cold weather outside in the winter I'm gonna make nice jacket bird looking cool in your we're looking warm in your little avian insulation jacket side is the warmth the outer side is for looking pretty or hiding or both maybe both yeah anyone have anything else we have had a wonderful show I think we've done it we have we have made it to the end of our 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Oh, Sadie loves snacks. Yes, she does. Hot rod, how dare you. She is not chunky. That is, yes. Don't comment on that stuff. That's, first of all, I body score her daily. Do you? I was a zookeeper and I know what to look for. Could she lose like a pound or two, probably, but also corgis are chunks are chunks. And so she's not a chunk. She doesn't, her tummy's not like hanging down. She still has a whoop, you know, behind her rib cage, which is good. She still goes in, if you look down from above, goes in behind her rib cage, which is what you want. So she knows she's okay. She's fine. But right now we're not running. So she actually might get back to not running right now. I just take a break. You're moving. Yeah. Yeah. On my first run in my neighborhood, I tripped on a root that like was poking through the cement and just ate it in the worst way possible. Ow. Yeah. Yeah. Are you okay? You're not okay. Yeah. I think I'll be okay. I'm like hobbling around with a cane right now, but I can like bend it and I can like gingerly put weight on my leg. It's just, yeah. I think it just, it really needs to heal. Did you break your patella? I don't think so. I don't think anything's broken. I feel like I'd be way worse off if anything was broken. Yeah. I feel like I just hit it. So it was just like pure brute force on my kneecap. Ow. Just my entire body weight pretty much went on my kneecap. Ow. That sounds terrible. Yeah. On cement. And I was like trying to dodge her because I didn't want to fall onto her. Oh, I'll fall on the dog. So, yeah. Anyway, yeah. So we won't be running for a while. I'm sorry. But that's okay. That's the thing is like as you get older, the bounce back for injuring yourself gets longer and longer. It does. Let me tell you. I'm sorry. I'm already experiencing it. I'm definitely. Oh my goodness. You know, just a fall is a thing now that can change your life. A crazy life. Just not putting your feet in front of each other correctly. Change everything. Well, I mean, at least it'll change your perspective. You'll be like, hey, how'd I get down here? World looks different. Hang on a sec. Did I miss the explanation of what the injury seems to be? Wow. You fell. I wanged my knee. Technical term. Do you think it's a little muscle tear? Yeah, I don't know. ACLs or? I don't know a lot about knees. This is my son tore his ACL. In a weird freak accident where he was at a dog park. Dogs are always responsible for this. All right, you dog hater. He doesn't like animals. He was running and a dog ran in front of him. He stopped to not run into the dog. Now that interaction tore that muscle. He was in a leg brace for months and months. There was talk about maybe he might need a surgery. He was young enough to be able to restore it without. It's very small muscles that are involved in this. This is one of those things. Perfect example of technology we've gotten from sports. It is a very common sports injury. There have been so many procedures done over the years that it's almost a routine thing now if it came down to a surgery. I'm not trying to set you up for surgery, but I'm telling you you need to go get it looked at really soon. Yeah, it's tough because I can't drive myself to a doctor right now. There's that because it's my right leg. Also, I have a new job, so I don't really have any six-time. So there's that. I'm not understanding any of what you're saying. You're going to put off what could potentially be a catastrophic injury that lasts your entire life. For some of these short term... Have you heard of Uber? Is that still a thing in COVID-19? It's COVID, man. Did they shut it down? I don't know. I don't leave the house anymore. Uber's so gross during COVID-19. You can have the windows open. All the windows open. I'll get it taken care of. I'm giving it a couple days so that I actually know what's wrong with it a little bit better because I went to a doctor yesterday and just be like, everything hurts. I'm elevating it. I'm icing it. I'm working from home. Sometimes it's just a bad fall. Yeah, and it could just be a bad fall. Yesterday I couldn't stand it all and today I can hobble around the house. I'm already healing a lot faster than I would think if it was something bad. But yes, if I am still in pain in a few days, I am going to go to a doctor. Good. Yes. No, no. I'm not going to have irreparable damage to my knee. I need it. Don't do irreparable. Yeah. Reparable. The need is important. Yes. Yes. No, no. I'm definitely going to... No playing. You want to be able to play soccer on a sandy beach for as long as you want. Soccer is gross. My hair is not. Why is soccer gross? Because I played it as a child. I didn't have very much fun. Okay. I was a casualty of the Viking Soccer League of the 90s. Okay. Soccer, by the way, is one of those sports that America, the female soccer players, excel at that sport better than we excel at most international sports. They're like the best team. Just saying. Yeah. Let's take a second look at your soccer's gross comment. Well, I don't think we should force small children to play soccer en masse. You know what's funny? Because America, I mean, doesn't have a lot of professional or well-publicized soccer leagues. It's like everybody has soccer moms. It's the thing. Everybody's going taking kids to play soccer and then they just stop when they get to college, apparently. Because we never see the televised. It just becomes an unpopular sport in this country. It's because you force children to play it and then they're sick of it. That's why. Yeah. But you would think like with the amount of emphasis there is on youth soccer, we would have college games being played like we have NBA college or NCAA football and basketball college athletics. But you don't see soccer represented there on that level. Even though I think more people play that as a youth than any other sport. And I'm telling you that's why. Everyone's had it up. People love soccer in the Pacific Northwest. Oh, good. Yeah. Huge up here. Yeah, it's huge here too. It's huge everywhere. It's huge. Huge youth soccer. Huge. So Blair was saying that she wanted, because she's in pain. Hey, Blair. Not to stay and hang out all night long. I'm kind of getting tired of hearing you complain. But once that physical. Oh, but one moment before we dive to set up the. I was, I was, but I was just sitting up and it kind of slow, long, long, slow way. But I was thinking tomorrow I'm going to be working and doing some stuff. But I was thinking of throwing on if you're going to be watching the NASA lander. Well, I mean, can't watch it land, but watching some of the coverage to make sure it is landing and then they get signal back and all that kind of stuff. The crew go like, huh? Yes, we can watch. It would be really funny if we can watch that. We got footage from Mars of it landing. And we all watched it. And then afterwards went. Wait. I mean, they've got Mars orbiters and things that have cameras, both those cameras for a second. Watch it go in. Anyway, I was thinking of doing a little, just doing a Twitch stream to talk to chat with people, other people. I think it's at 1115 a.m. Pacific time. That works. When coverage starts and then 1215, they're supposed to get a confirmation of it hitting the atmosphere of Mars. And so then it'll be somewhere. It's somewhere between the noon and one o'clock hour. Just tell me when to show up. I'll text, should I text you? Yeah, just text me when to show up. I'll send you, I'll send you a, I'll send you an invitation and we'll do, we'll do a stream yardy thing and we can hang out and talk and watch the NASA coverage and be like, dude, what? And stream to Twitch and it'll be fun. Although the last NASA thing I watched live was the Challenger. Just saying it might be bad luck. Just you might be bad luck. I'm one for one. That's all I'm saying. Yeah, one point is, it's just a point. It's not even a line yet. I understand. I understand. I'm still one for one. That's all. That's all I'm saying. You're also one for one on predicting the Super Bowl. Oh yeah. Oh no, that was fantastic. No, I made a lot of other predictions that didn't, but what was, if you recall that prediction though, that was something like even frighteningly. Oh, I actually, I actually just looked at it because it was 10 years ago. Okay. It was 10 years ago last week. New Orleans Saints versus the Indianapolis Colts. Yeah. And I didn't just predict who won. You predicted the point spread. And the final play, I was like, paint manning, who doesn't throw interceptions? Those interceptions. Oh no, he's got, he's taking them out. And that's how they, that's what happened. And it was really scary to watch the game unfold the way you predicted it. Yeah. Did you even remember? No, I totally, I totally did. Cause I was watching the game. And then somebody in my Twitter feed or the Facebook feed, cause I used to watch those things once upon a time was freaking out because they knew the prediction and just watched it happen. So yeah, then I, the next year I sold a sports pick and book picks for the first, I think three weeks, but I got like everything wrong. So that ended that. Yeah. That ended, like I said, one for, well it was one for one for a hot second. Yeah. There's a, it's actually, this is an ancient scam. Where you would use mass mail to predict the outcome of a sports game. And so you send the, you send a different picks. Sometimes they conflict to a thousand people. And at some point you've got a subpopulation there where you've been right every week. It's, it's, it's like picking every box in, in one of those, one of those, what the scores are at the thing. But you send it to every, a thousand people. And after the first week, maybe you're down to 500 people. Maybe after the second week, you're down to 250. Third week, three week, four, you're down to 50 people. But to those 50 people, you've been right every time. So now you're like, 50 bucks. I'll give you the next answer. Then everybody sends you 50 bucks. Half of those, maybe a third of those, quarter of those, you get, you get three or four games right. Those people are going to be down for a hundred bucks next time. Cause they bet on the game with your 50 bucks and they won. I like your, I like your math. I like your math here. It's the greatest, like, uh, it's one of my favorite scams of all time. Cause somebody at some point figured out like, yeah, we can predict all of the different outcomes. I could use math to make money honestly, or I could use math to ski. Well, that's what, okay. Yeah. Well, well, no, to be fair, to be fair, when it comes to Wall Street, is there a difference? Yeah, no, that's steaming for sure. Yeah. Hey Blair, I wish you speedy recovery. Thank you. Go ice that knee. Yup. And say good night, Blair. It's right here. Good night, Blair. Say good night, Justin. Good night, Justin. Good night. Good night, everyone. Thank you for another great show. And hey, maybe we'll see you tomorrow watching to watch, to watch the NASA stuff. But for sure we'll see you next Wednesday cause we'll be back. And I hope that you are too. Have a wonderful week. Bye.