Dasha: [00:00:00] Welcome to the Biomedical Frontiers podcast, where we explore pivotal research projects and disruptive innovations aimed at translating scientific advancements into tangible health care solutions. I'm your host, Dasha Tyshlek 
Jonathon: If you go back to 2000, that was a turning point in genetics research because that is when we sequenced the human genome, which means we were able to lay out the ATCG sequence of our entire DNA sequence. At the time, it was sold as this idea that would just solve all diseases. We would find the genetic markers for these diseases within that sequence, and we would know how to treat it, and everything would be cured.
Dasha: What was it like for you guys going through this process where you have multiple professors partnering, you have multiple companies partnering, and you also have multiple of these technologies co-related from within one university. How did you navigate that and also address things like risk and IP?
Jonathon: One of BYU's biggest things is they want to always be focused on the idea that their research is having a positive impact in society. And that has made the university very interested with the model that we're trying to create, where we develop things in our labs, and then we are actively working with partners and being involved ourselves in order to commercialize this technology and bring it out. 
And one of the things we've done is involve students. We found students are a wonderful treasure trove of new ideas, fresh ideas. They're not jaded. They're not fixed into how things are done at this point, but they're getting far enough in their education that they have a basis to come up with a good, viable idea. 
For example, one of our students said, I think this could really help diagnose endometriosis. She was interested in woman's health and building that. She has actually now gotten investors and been able to form her own woman's health company where she is CEO. This student brought it to us and then we created the environment for her to succeed, the university wins, we win, she wins, women's health wins, and it's a benefit to so many different groups of people.
Dasha: Welcome back to another episode of Biomedical Frontiers. Today our guest is Dr. Jonathon Hill, who is an Associate Professor of Cell Biology and Physiology at Brigham Young University and the Vice President of Science and Technology at Wasatch Biolabs. Jonathon develops innovative genomic and bioinformatic methods for gene expression analysis which has tremendous applications in cancer, early detection of chronic diseases, and personalized medicine. 
His lab at BYU researches the molecular genetics of congenital heart defects by studying development of hearts and embryos. He is a Fulbright Scholar and a BYU Early Career Teaching Award recipient, having received his Master's of Science in Molecular Biology from the University of Colorado Health Sciences Center and a PhD in genetics and developmental biology from Columbia University. His company, Wasatch Biolabs, is working to move epigenetics from the lab to the clinic. Jonathon, it's great having you on the podcast today. 
Jonathon: Thanks for having me on. I'm excited to talk about what we're doing. 
Dasha: Well, I think for many of our listeners, epigenetics and genetics is a familiar term, but the details of what goes into actually sequencing and, bringing this technology and capability into the world are more mysterious.
So I'd like to start with just an overview of what is genetic sequencing and genomics, how that's different from epigenetics, and what that looks like in the lab. 
Jonathon: Yeah, I think that's a great place to start. And in a lot of ways, it's still a mystery for us too, right? This is an area of active research. It's a new area, where some of the technologies are just getting to the point where we really can ask these questions and look at them effectively. 
So, the idea here is, you know, if you go back to 2000, that was a turning point in genetics research because that is when we sequenced the human genome, which means we were able to lay out most, it turns out not quite everything, all of the ATCG sequence of our entire DNA sequence, put that together. 
And at the time, it was sold as this idea that would just solve all diseases. We would find the genetic markers for these diseases within that sequence, and we would know how to treat it, and everything would be cured.
Obviously, that has not happened and part of that is because of the other term you talked about, epigenetics. And what we've learned since that time is that the DNA sequence does not tell the whole story. There are chemical modifications, especially methyl groups, that get attached to the C's in our DNA that help control that DNA.
And those epigenetic marks will change over time. So your genetic sequence is the same. Every cell in your body has the same sequence. It's the same from birth until death, right? With a few exceptions, that is the rule. Apogenetics, these [00:05:00] chemical modifications to the DNA, change as you age. They're different in different tissues and organs.
They can change if you drink too much alcohol or if you smoke. They can change if you're out in the sun for a long time, and they can change in response to different disease states, right? And so, it's got this whole other layer of information on our DNA that we're now realizing is really important to understanding disease and the genetic basis of that disease.
Dasha: How is this new revelation around epigenetics, their importance, starting to impact healthcare and medical research today? 
Jonathon: Yeah, great question. So, I think first of all, the key here is that we've known for a while about these marks and we've known that they probably had something to do with different diseases, but we just didn't have a great way to to read them, right? We can read DNA sequences, the ATCGs really easily, but until recently, we couldn't really pin down what those chemical modifications were in an efficient way. And so it just kind of sat there and we knew it was important, but we weren't really doing anything with it. Now, with the advent of third generation sequencing, both Pacbio sequencing and Nanopore sequencing can really effectively call these methylation marks or these modifications on the DNA and tell you what you have along with the sequence at the same time.
And this has really changed how we're going about this because now we have access to these marks and we can use those as new biomarkers that tell us whether someone has a disease or the state of disease or the effectiveness of treatment, right? We have something new that we can measure in these patients and gain great insights to their health and their treatments.
Dasha: So you mentioned this nanopore sequencing, and this is a technique that you guys are using at Wasatch Biolabs. Can you share a little bit about what that technique actually entails, why it's enabling this type of new research? 
Jonathon: Yeah, so nanopore sequencing is one of these third generation sequencing techniques and it was originally made because it can give really long sequencing reads. 
How it works is you prep your DNA sample. We typically fragment the pieces of DNA into 10 to 20 kilobase pieces, so really big pieces of DNA. We can ligate some adapters on the end. And then we put it in a flow cell. And what this flow cell has are these protein pore complexes that create a channel through a membrane and the DNA gets passed through that channel to the other side of the membrane. And as it does so, it disrupts the resistance and conductivity of that membrane. 
So we get an electrical signal off of that that changes depending on which base happens to be in the pore at that time, right? So if an A is in there, it'll give one electrical signal. A T will give a different one and so on, and then we can call the bases that was in that DNA sequence. But what they learned as they were doing this is the signal would sometimes be a little funky. And it turned out that that's because of these chemical modifications that was changing the signal.
And we've learned that we can actually call these modifications at the same time. And so instead of just saying it's a C, We now say it's a methylated C or it's an unmethylated C and we can get these epigenetic marks by changes in the signal as it passes through. 
It's completely kind of epigenetics for free because it actually improves the base calling accuracy as it's doing it. There's no extra preps we have to do, it just comes along with our DNA sequence as we do it. 
Dasha: Yeah, that sounds like it's really enabling a whole new field of research, as it pertains to genetics. You and your team at Wasatch Biolabs also pioneered another technique, the NESSI-SEQ. What is that technique, how does that relate to this nanopore technique, and how is it different from other processes used in the industry? 
Jonathon: So NESSI-SEQ is really about prepping the DNA for this type of sequencing, specifically what is called cell free DNA. So when cells die in our bodies, they often release their DNA into the blood.
And it's just floating around, for a while until it's eventually degraded and cleared from our system. But we can actually capture that and sequence that DNA and including get the epigenetic information off of that DNA. The problem is that that DNA is in the process of being broken down by the body, and so there are nicks and gaps and lots of damage to that DNA. It's pretty beat up, right? 
And traditional ways of getting that ready for sequencing would fill in the gaps with synthetic DNA. The problem is, synthetic DNA is always unmethylated, and so it was affecting the epigenetic [00:10:00] signal and really messing up the kind of calls that we could do with that.
And so we created this NESSI-SEQ method, which is a way to prep cell free DNA for nanopore sequencing that involves no synthesis whatsoever. And so now we can take it and put it onto the nanopore sequencing. And when it calls something as methylated or unmethylated, we can be certain that that was the actual native signal and not something that was put in as a side effect of our repair mechanism.
We then built on top of it and we created a targeted NESSI-SEQ method, which allows us to select out certain regions of the genome and focus in on and sequence just those regions. There's a lot of targeting techniques out there, but the vast majority of them involve a PCR step, which of course is going to make all synthetic DNA, and we're going to completely lose the methylation information because of that.
The alternative to that is to do something that is called a bisulfite conversion. That changes any unmethylated C's into T's and the DNA changes the sequence and you can read those changes and get an idea. That works with the PCR amplification, but it's really difficult because of that whole conversion step, which is inefficient.
It itself damages the DNA, it has batch effects associated with it, and it's just as hard to target regions when it may be a T, it may be a C depending on the methylation state. So we can grab the native DNA using this targeted method, use our NESSI-SEQ protocol to make sure that there's no synthesis during the repair steps, and then do the sequencing and get a really great targeted epigenetic signature on this DNA. 
Dasha: So how does this impact the potential of this field of epigenetic research? 
Jonathon: I think in the big picture, it really opens up new avenues. Like I mentioned, until five or six years ago, when these third generation sequencing technologies were really coming on, we were very limited in our ability to look at these epigenetic marks.
The most common method and still today, probably the most common method is what is called a methylation array. The Illumina Epic array would be the biggest example of this, and it hits about 800,000 to 900,000 methylated C's throughout the genome. Well, it turns out that there's 28.1 million places that this methylation can occur.
So we're missing out on the vast majority of data. Now, with our NESSI-SEQ protocol and with nanopore sequencing, in a typical run, we usually get about 27 and a half million sites. So we're getting about 30 times the amount of data that we were getting before, right? A multiple of 30.
And so, for the first time ever, we can really get that comprehensive picture of what is happening across the entire genome, in an accurate way, that is inexpensive and straightforward to do. So this is now a viable biomarker, both in research and in the clinic. We can now really start looking at these and make confident calls about what is happening biologically.
Dasha: That's so fantastic. When you were describing some of the causes of this methylation and you were saying, like, you can detect somebody was smoking or particular tumors. Is it, just like negative and destructive things to your body that the methylation enables us to see? Are there also positive health markers that have been discovered as well?
Jonathon: Yeah, I mean, it's interesting. You think about the negative and we tend to focus on that in medicine, right? But for every negative methylation mark, that means the opposite is the healthy methylation mark. So we have those, right? Most commonly, what we're looking at is not you couldn't classify it as positive or negative, but we're just looking at the differences between cell types.
And one use that we have for that is to identify different cell types within a sample. To give an application that we're working on right now, someone who has neurodegeneration has cells dying in the brain, right? Neurons are dying and their DNA is getting released into the blood, so we can look for those neurons specific methylation marks and identify cell free DNA in the blood as having come from dying neurons.
And we can let that person know, hey, you have an elevated amount of neuron death. This might be early stage Alzheimer's or Parkinson's disease, depending on the exact population that's dying, etc. Or the opposite, of course, is true as well, right? Meaning we can tell someone that's worried about it, hey, you're fine.
We don't see any of that. You have a healthy mix, if you will, of cell free DNA in your blood. And so, you know, we can do that for identification. We can do it for disease state. We can do it for any number of things. 
Dasha: That is [00:15:00] so promising and encouraging. I want to talk a little bit about the story of the founding of your company.
How did you end up going from developing a novel sequencing methodology or a preparation step into building into a flourishing company? 
Jonathon: Yeah, I mean, to do that, let's step back a little bit. Our kind of motivations, I think, are an important part of this story. I'm kind of a typical story, I think, if you look at it. I was pre med as an undergraduate at university, decided my junior year, I was TAing a class.
I was doing research in a lab, just fell in love with that life and said, I'm going to go be a professor instead. So I went through graduate school, postdoc, got my professor position. And what I found along the way is I was learning all these really cool things about how our bodies work and about biology in general.
And yet, I would publish, I'd get a grant, then I'd publish and get a grant. And I felt like a loop, right? It kind of an infinite loop cycle. And I kept thinking, there's gotta be a way to make sure that this stuff I'm learning can actually get into the clinic and help people. 
At the same time, a colleague of mine who works on epigenetic methylation marks as well, came to me and he said, you know what? We have this technique we just figured out in the lab, where we can see dying neurons in the cell free DNA in the blood, right? But we're running into issues. Can you help us? And I have a genomic sequencing bioinformatics background, so I was the one that suggested we use nanopore sequencing and we kind of solved these problems together.
 Then, their idea was, okay, we figured this out. Let's go license this to somebody and have them run it kind of thing. And when they did, they found out there was nobody in the country that had a clinically oriented nanopore sequencing lab. It did not exist. And we realized that if we were going to get this out there to where it could help people, we had to do it ourselves.
So we got some partners together, some early investors, you know, the whole thing that you need. And we decided to set up this lab, and so we created Wasatch BioLabs out of that, partly to run some of our own tests, but once we did that, we realized, hey, we've got this neat platform where we can do this epigenetic sequencing, and we're getting really good at it, and this is something that other people can use, right? 
One of the things we realized early on is we are not experts in all the fields. We don't know everything. We know we have a hunch that epigenetic marks can be important in a wide range of uses, but we don't know what those are. We don't know what diseases they can be applied to.
We don't have access to samples, all those kinds of things. So what the company has started to do is really try to bring in partners who have those expertise and say, hey, work with us. We've got the platform. You've got the domain knowledge for this particular application. Let's work together to create a test.
And we have three or four partners right now that we're working with in order to get their tests up and running as well, in addition to our own. So it's been a fun adventure. It's really neat to see different people thinking about these questions and coming together and creating awesome solutions.
Dasha: That is such a beautiful story, and I love also this thread of partnership that's running through it, where you're partnering with other faculty, you're partnering with other students, clinicians. And so, you're really working on something that is enabling other people to also realize ideas and potential directions in both research and translational research for clinical applications.
What was it like for you guys going through this process where you have multiple professors partnering, you have multiple companies partnering, and you also have multiple of these technologies co-related from within one university. How did you navigate that and also address things like risk and IP?
Jonathon: Yeah, let me tell you, I've learned so much about new areas that I didn't know about before, right? I was very focused into the biology and the research, and I've now seen the side of patent law, IP protections, working with tech transfer, working with the VP of research at BYU. And then, of course, the business and the investment rounds and all of these kinds of things that we don't think about all the time, and it really shows that you need a team effort. 
Luckily for us, one of BYU's biggest things is they want to always be focused on the idea that their research is having a positive impact in society. And that has made the university very interested with the model that we're trying to create, where we develop things in our labs, and then we are actively working with partners and being involved ourselves in order [00:20:00] to commercialize this technology and bring it out. 
And so the tech transfer office has been very great to work with. They've been very flexible on things. They've been willing to try out new things with us, those kinds of things. We've actually set it up to using the normal university channels where the company gives us what's called a sponsored research agreement. It's kind of like a grant from a company, if you will. And that allows us in our labs to independently research new technologies and new applications that we can think of.
The company has to kind of stay out of those by rule, but it gives us the funds where we can focus on that and then help that. And one of the things we've done with those funds, like you mentioned, is involve students. We found students are a wonderful treasure trove of new ideas, fresh ideas.
They're not jaded. They're not fixed into how things are done at this point, right? But they're getting far enough in their education that they have a basis to come up with a good, viable idea. And they need some mentorship to help bring it about, but they're there. So we've had a couple of students come to us and say, hey, I learned about your technology. I think I know a new application. 
For example, one of our students said, I think this could really help diagnose endometriosis. She was interested in woman's health and building that. And so we said, hey, okay, we think this will work as well. Why don't you work on this project? She's been working on it.
She has actually now gotten investors and been able to form her own woman's health company where she is CEO. And building this platform and working with Wasatch Biolabs to help finish up the research and bring her technology out, right? And this is an idea that I never would have had. This student brought it to us and then we created the environment for her to succeed, and be able to pull that through, and it becomes a win win situation. The university wins, we win, she wins, women's health wins, and it's a benefit to so many different groups of people. 
Dasha: I love that and that spirit of partnership. Since you're providing kind of a technique and a co-development of research, what is it like to kind of come up with an idea and start working with you guys?
And what do you do versus what does the partner do who develops the diagnostic for their particular diagnostic concept? 
Jonathon: Yeah, that will vary a lot case by case, depending on what expertise they're coming with. And so we sit down with them and usually over the course of several weeks, we talk through these things.
First of all, we need to know, does it fit our platform? Are we a good fit on our end technologically? We're still pretty small. We're getting started and so we can't go into completely new areas. We need to focus on what we know right now. But if we feel like we have something to contribute, then the next step is to decide where the research is.
If we feel like they have something, maybe they've been doing research on it. They already have the epigenetic markers, et cetera, right? It's fairly far along. Then they might partner directly with Wasatch Biolabs to move it onto our platform to do some clinical validation. We have an HCLD, we have support staff to help with the clinical validation and the clinical approvals, right?
CLIA. FDA, whatever it might be to help them move that out to the market. If it's earlier and they're like, I think there's something here, but there's some research that still needs to be done. Then that comes to the university side and in a couple of cases, we've said, hey, this is too early for the commercialization, but we think it's super intriguing.
We want to look at it. Let's use some of these sponsored research agreement funds that we have and do a partnership between universities, usually, and do that research first. And then we get it to a point that either it doesn't work or it might be commercializable and then we can start talking to the company.
Now at that point, because of the, you know, conflicts of interest, et cetera, Wasatch isn't obligated to take it on. The company isn't obligated to take it to Wasatch, right? It's independent, but there is that avenue there ready to go that we can go down if it goes to commercialization. And so, yeah, it just depends on where we're at and what we need to do, but we're willing to work with a wide range of people, to help develop out this platform and apply it to new cases.
Dasha: I think that research partnership between the company and the university, as you just illustrated, creates this opportunity for somebody to work with you at multiple levels, different levels of readiness, because I think when you're working in the commercial firm, you sometimes have that limitation. You really got to be really risk averse and so something that maybe isn't quite ready for commercialization. 
Those projects sometimes kind of get a little bit stuck in that pre-commercialization phase, but because of that university partnership you developed through [00:25:00] this process, I can see you've solved for that by having a place for these projects to also benefit from your expertise in your labs and the team without it necessarily to to be shut down because of the business risk.
So, I think that's super clever and just shows how well that translational research partnership, the tech transfer offices working with the businesses, how well that can work together. One question I kind of have on that is you mentioned that as you walked into, stepped into a new role, kind of more commercial role, you've had to learn a lot about entrepreneurship, and I'm just wondering if you can share some lessons from the business side that you've learned, when commercializing.
Jonathon: There's myriad ones. And most of them are little details, right? Like I've learned what series a funding means, things like that, because it's a different world. But I think the biggest one, take home message is that commercializing a product is different then researching something. We have a paradigm in academia where we are more interested in the question and the biology that we can learn, than the idea of a product that is usable.
And I've actually found that this can be a major break, a major issue in commercialization in general. an example I can come up with is I remember reading through the literature, trying to keep up on things and, for a colleague I was looking for insulin detection mechanisms. And I found that people have been working on this and some university labs had developed methods, and when you go look, they're really complicated. 
I remember one actually involved like gold plated glass slides, and you know, hours and hours of work and all this labor. And you just realize that that was never going to get to a place where it was actually viable on the market. So the biggest lesson I've learned is that early on in the research process, when we're looking at something that can be translated to the market, we already have to be thinking about the business case, the costs, the scalability, those kinds of things.
Our early proof of concepts may not be there yet, right? We can get overly focused on that, but we need to have that in mind and at least see a path for it to get there. And, if us as researchers can do that, then I think we're going to see a lot more technologies move from the university space out into the commercial space and start impacting people's lives.
Dasha: Yeah, that makes that makes perfect sense. So you mentioned a couple of the promising applications that you guys are already working on. What are some other potential future applications and sort of a call out into the world for things that could fit this type of technologies application where it could accelerate some sort of health outcomes that you foresee developing over time.
Jonathon: Yeah, I think in a lot of ways, we're just finding out what these applications are. Some of our partners right now, I can't give too many details, but are looking in the fertility space, predicting if certain fertility treatments will be successful or not based on epigenetic marks. We have people interested in the forensic space, being able to identify tissue types in a sample from a crime scene or identify perpetrators, et cetera, based on these methods.
We have people that are looking at neurodegeneration. We have people looking at cancer. We have people who are trying to make diagnostics for a specific use case and others who are just trying to create a large body of data so that hopefully we can find patterns that we don't even know are there.
And so there's so many different uses. One of the big ones that we'd like to start moving into is drug companies who are developing new medications, new pharmaceuticals. And either to predict who's going to respond to those drugs and how, or to look at the efficacy of those drugs, et cetera, using epigenetic marks.
And I think this is an area kind of pharmacogenomics, but it's epi pharmacogenomics, if you will, trying to look at these and see what effects on the epigenome these drugs are having and what they can tell us about their mechanism or efficacy in different use cases. I think it's wide open. There's a lot that we can learn there.
Dasha: It's really amazing to be kind of at a starting point in a field where now like the doors open up and so much new potential is created in terms of understanding and also practical application. So that's really interesting and one question that sort of pops up for me is you also mentioned cancer and I think a lot of people think about cancer detection, but you're also saying something about treatment monitoring, could you kind of dive into that a little bit more. 
Jonathon: Yeah, there's lots of different applications here. First of all, you know, one of the things we're really good at, and I used the example of neurodegeneration, but it could be any cell type, is monitoring cell death [00:30:00] in the bloodstream.
People have looked at epigenetic marks and cell free DNA sequencing as a cancer diagnostic for a long time. But what we're beginning to appreciate is that that these opportunities may extend beyond that. If we're doing a chemotherapeutic, for example, we expect increased cell death.
That's part of it. Part of that's going to be on target and we would hope to see actually increased cell free DNA from tumor cells, right? And some of it is side effects, other tissues that are getting damaged in the process. And both of those can be monitored by sequencing and looking at epigenetic marks on cell free DNA.
And so we can help identify why someone's having severe reactions to a chemotherapeutic, or we can say, hey, your tumor is responding to the chemotherapeutic or not, and maybe allow us to pivot our treatment plan earlier than we currently can. And so I think these are great things that we'll have in the near future that will help us just kind of treat people more effectively rather than just purely do a diagnostic, right?
Dasha: It's a really fascinating topic. I love this idea that we can also monitor the effectiveness of the disease, not just symptomatically, but through these biomarkers. And, for those who are listening, our very first episode of the podcast, with Dr. Nathan Price, we discussed the application of AI with genetics and epigenetics to creating a more personalized healthcare approach, kind of a big picture view of what this could mean for the healthcare system.
So, if you haven't listened to that episode, follow on to this one with that one to kind of take the story all the way through to what that might do in terms of transforming healthcare to be more personalized overall.
I want to pivot to a different topic, which is your research in your lab at BYU, focusing on congenital heart defects. Can you share a little bit of the background, the interest, where did it originate, and what you're doing now? 
Jonathon: Yeah, so, my interest goes back to that pivot that I did as an undergrad when I decided I'm not going to go be a doctor, I'm going to go do research and be a professor, right? And at the time I thought, well, the one thing I got to figure out if I'm going to do this is what am I going to research?
And I got exposed, this is early 2000s, right? So everything was about embryonic stem cells. And I got exposed to that idea that we all started as a single cell, and the DNA sequence forms kind of an instruction set or a program that runs, and we build a person out of that, right? A full human being and I just thought that was the most fascinating thing I'd ever heard of.
The idea that DNA could give us all the instructions to really have an embryo build itself. Right? And build it out. And so I decided I wanted to go into understanding those gene regulatory mechanisms that help differentiate cells and build tissues and build organs during my graduate work actually worked in a lab looking at the development and differentiation of pancreatic islet cells, the insulin and glucagon producing cells that are affected in diabetics.
Right? The idea was, could we come up with the path you needed to take to differentiate embryonic stem cells into these pancreatic islet cells and replace the cells that were lost in type one diabetes, right? Very kind of applied kind of thing, and it was a really cool process to go through, but as a postdoc, I decided to pivot a little bit in an area that had always fascinated me.
In fact, when I was going to be a doctor, I wanted to be a pediatric cardiologist and help children who are born with congenital heart defects, which happens to be the most common type of birth defects that we see in the clinic. In fact, some statistics say it affects as high as 1 percent of births.
It's very, very common. So, I wanted to understand, okay, first of all, we don't even know how the heart forms normally. How does that happen and what is going wrong in these patients? Why does it not always work correctly? What's happening? And so, for the last 15 years, I've really been looking at the genetics and gene regulatory mechanisms to help drive heart formation.
Dasha: Can you share a little bit about what is already known versus what's not yet known, particularly about the development of hearts, but also maybe broadly about the development from that first single cell into a full human being. 
Jonathon: Yeah. So one of the things that is known is that the DNA is the major driver here, right?
It is the instruction set. That's going to do that. What we're trying to learn is how that works. How do you turn those instructions into action and actually be able to put the embryo together. As an example for the heart, it's a fascinating process. So, the heart actually starts forming as two populations of cells on either side of the embryo.
And those cells start migrating to the ventral midline, so [00:35:00] the front of the embryo right in the middle. And when they meet each other, they know to attach to each other and form and kind of elongate into a tube, okay? That tube actually hooks into the vasculature and doing peristaltic contractions actually starts moving blood through the embryo.
So the heart's not even formed yet and it's already functioning. Then we go through what is called heart looping morphogenesis. What happens is that tube kind of wraps around on itself. I like to think of it as it ties a knot on itself and forms the ball that we think of as the heart through that process.
And that's how you have a continuous flow, kind of snakes its way through the heart. In humans and other mammals, the last step of that is to build a wall down the middle to septate the left and the right heart, from each other. In some other animals, you know, fish, et cetera, they have two chambers, that last process never happens.
But all animals share that initial heart looping morphogenesis. As we look at it, we think that most of our congenital heart defects come from defects in that heart looping process, because if it fails earlier, you're not even going to have blood flow. You can't feed off the placenta. There's no nutrient going to the embryo and the embryo will fail quite early.
But if those late processes just don't quite happen, right, then maybe we have a murmur in the heart, or maybe the vasculature didn't hook up right. Or maybe the left side of the heart is weaker than the right side. Or you have issues with the valves that form during this process.
All of these processes that we see in the clinic go back to that stage of heart development. And so really what we're trying to understand is how do you turn on and turn off genes in just the right place at the right time to tie a knot? How do you make it so it can move around like that and create that amazing shape and function?
And I think one of the most amazing things that my lab is starting to look into is it turns out that it's not just gene A turns on gene B, which turns on gene C, what we call a regulatory cascade, but it is sensing its environment and making decisions based on those stresses all along the process. 
So, for example, if you stop, we work in zebrafish embryos, you can stop the heart from beating and because they can absorb nutrients from the water, they can live for a while, but the heart will stop developing in order to have that process complete correctly, you have to have the beating action. And what it looks like, this isn't my lab, but another lab modeled it out and showed that the cells are measuring the forces of the blood on the walls to designate where certain features in the heart should be, particularly the valve.
You find the place where the blood is moving the fastest through the heart and that's where the valve should go, things like that. And so, we have some work that looks like that can affect relative atrium and ventricle size. Things like that. And so it's a really cool process where the embryo isn't just building things in a preset program, but it actually is adapting and trying to adjust as it goes.
And we think this could have big impacts in congenital heart disease treatment and identification, because we know that, for example, individuals who are obese, are more likely to have a child with a congenital heart defect. We know that there's certain environmental exposures that can make you more likely to have a congenital heart defect.
And we know sometimes those exposures depend on certain genetic predispositions, right? And so we're seeing this interplay between genetics and environment and seeing that it can affect something as basic as forming a heart inside an embryo, we're trying to understand those mechanisms and how that works.
Dasha: Yeah, that's a very different thought process thinking that the genetics just sort of unfold in a particular program, kind of like from start to finish, that it's just preset and that's just cause how it's going to go versus to be thinking of the cells as being responsive and adaptive the entire time and that every person is formed, not just from that DNA, but also from that sensing and adapting that was happening at these early stages of development. 
That's really powerful. Do you see this as a kind of paradigm shift for kind of overall view of embryonic development and having broader impact beyond the heart?
Jonathon: I hope so. When I went through my education, we were taught these genetic cascades and the idea was gene A turns on gene B turns on gene C. And as you think about it, that's a really fragile system. Because you might have a thousand genes in that cascade from single cell all the way to finished heart, for example.
And if any one of those breaks along [00:40:00] the way, then it doesn't work right. But if you have genes that are just telling cells, hey, if you sense this environmental factor respond in this way, you get more robustness, you can have more cells that are that way. 
And, you get a natural adaptation to the natural variability between each individual, each mother of that individual,different environments, different exposures. And so you start to see how an embryo can actually make it through that whole process successfully as often as it does, which I think is amazing. 
Dasha: And how do you see this field of epigenetics and embryonic development evolving kind of in the long term, next 10 years, predictions for where this research might take us broadly?
Jonathon: Yeah, I think it's many fold. whenever you have a new technology as enabling as third generation sequencing that can give us epigenetic marks, I think for the next decade or so, you tend to see an explosion of different applications of that. Pile on top of that, concurrently, we're seeing a new revolution in AI that's allowing us. 
And so you've got these two technologies coming together, working together to create kind of a double explosion in this field. And I think as we go through, we're going to find there are links to these developmental pathways and various disease states, even if these disease states show up in adults, right?
One of the major ways that the genes are being regulated during embryogenesis to decide to become a heart cell or an eye cell or a hair cell, et cetera, is through changing methylation patterns. That's what helps identify these cells. It's those same methylation marks that were put down during embryogenesis that we use in the clinical lab to identify dying neurons in an elderly patient.
And so there's this huge link between the different processes. We also know that there's certain processes like your heart regeneration that people are looking at. That embryonic cells have the ability to do that, adult cells do not, and perhaps it has to do with the epigenetic changes. And if we can reverse some of those, we can reestablish that ability to regenerate, et cetera.
Right? So we're going to see these kinds of applications just explode over the next decade. Some of them will pan out, some of them will not, but we're going to learn a ton along that process and it's going to be really cool to watch. 
Dasha: Yeah, wow. Epigenetics seems like a very exciting field of research with so much potential for, innovation, new discoveries in the coming decades.
What would you give as advice to early career scientists, those who might be interested in pursuing research in similar fields? 
Jonathon: So, yeah, the first thing I tell my students is find something that you are really passionate to research about. We in the university constantly have this debate between following your dreams and the practicality of getting a job and building a career, right?
I think in biotechnology and in biology in general, we're at a really cool place where those can be the same thing, where there are careers in creating these great new technologies and really expanding our field of knowledge, but the research is always hard, regardless of what you're doing, right? I tell my students all the time in science, by definition, we don't know what we're doing.
We make mistakes. We're kind of feeling around in the dark and there's a lot of long nights and hard times and failure along the way. But if you are passionate about that question, you really want to know the answer, you're going to fight through those things and you're going to find that answer. If it's just something you're doing because, well, what else would I do? You're going to give up on that question, right? So you need to find something passionate. 
The second one is much more practical advice, and that is get data analysis skills. In the university, we are a little bit slow to adapt these sometimes our education, our curricula to this, but biology is no longer the science where you can get away with hiding from math, hiding from big data, and just kind of doing science without the math, if you will, right?
That used to be biology. That is not the case anymore. We need to be able to look at large data sets, make sense of this program, neural net models, all of these kinds of things. And those are valuable skills for the students to get.
And then the last thing is never lose track of why you're doing what you're doing. Make sure that you are able to keep that vision of, if it's to help people, for example, that you're able to keep that vision and keep going forward and never lose sight of that. Never let it just become a job that you do nine to five and don't really care about. 
Dasha: Well, Jonathon, it was so great having you on the podcast. We learned so much and have such an amazing, new area of science to be [00:45:00] thinking about and all the potential it has for human health. 
I want to call out specific call to action, which is that if you are interested in developing your own epigenetic diagnostic tools, you have ideas for unique clinical applications or your research is already rolling in this direction, you can reach out to Wasatch Biolabs to partner with them to develop it further.
And you can do that by reaching Jonathon directly on LinkedIn or through the company website, all of these things are linked down in the description. So, really a call to partnership and innovation for all.
David: Thank you for listening to biomedical frontiers stories with innovators in healthcare. My name is David Chen and I am the managing director of the Wallace H. Coulter Center for Translational Research at the University of Virginia. Our mission is to help bring promising new biomedical research and technology into the hands of the provider and the patient.
If you found this episode valuable, please let us know by subscribing. You can learn more about our promising translational research projects on our website. See links in the show notes.