TGen Talks: PepSeq
Karie Dozer [00:00:03] I’m Karie Dozer and this is TGen talks. You’ve probably heard claims that very soon your doctor will be able to diagnose anything using not multiple vials, but a single drop of blood. While much of the hype around such technology is just that, you can tell a lot about your immune system from a very small blood sample. Ten researchers are using this technology to help determine immune response to not just one, but multiple viruses and pathogens. And they’re hoping to not only measure individual risk, but prevent public health emergencies in places where a population has little to no immunity to a virus on the rise. Today on the podcast we’re talking with Jon Altin at TGen North about what this breakthrough technology could mean for not just public health but the prevention and treatment of diseases with viral triggers. John, that’s a lot. Thanks for taking the time to talk.
John Altin, PhD [00:00:56] Thanks. It’s great to be here
Karie Dozer [00:00:58] Tell me about what you do here at TGen and what’s the focus of your research.
John Altin, PhD [00:01:02] So I’m an assistant professor at TGen North and I actually work between two programs, the Division of Pathogen Genomics, as well as the Integrated Cancer Genomics Division in Phenix. And the reason I’m sort of straddling these two worlds is because I’m an immunologist by background. And what we’re learning every day is that the immune system is important in more and more things. And it really has a role against cancer, against pathogens in other sorts of settings as well. So my research is focused on trying to understand the immune response both to tumors and to pathogens, and specifically to understand which parts of those are those agents that can cause, you know, disease and death. Which parts are being recognized by the immune response?
Karie Dozer [00:01:45] Your latest research involves something called PepSeq. What is PepSeq and what’s the subject of your paper, in a nutshell?
John Altin, PhD [00:01:52] PepSeq is a technology that we have been working on for a decade or so now, which allows us to run an analysis of antibodies in a very high dimensional way. So normally, if we get an antibody analysis done, let’s say, for example, clinical tests measuring antibodies against a particular target, a virus or something. We’re measuring one thing. We’re seeing how much antibody is there against Target X in the case of PepSeq. What we’re doing is attacking that same principle, but we’re applying it across thousands, hundreds of thousands of different dimensions. So instead of doing one measurement at a time, we’re making hundreds of thousands of measurements, all from a very small sample. And so what that lets us do is instead of looking at how much antibody you have against Target X, now you can look at your antibody profile across, for example, the entire human virus, which is what we did in this paper in the virus is really the word that we used to represent all viruses that can infect humans, which is which is many. You know, we had 80 different viral species included in this. That will include things that you’re very familiar with, COVID 19 virus that causes COVID 19, HIV, those kinds of very high-profile viruses, but also many kind of garden variety, low pathogenicity viruses like the common cold. So we can look, you know, across that whole universe of space all at once from a small sample using this tool in a way that we couldn’t do using traditional approaches.
Karie Dozer [00:03:15] You use the word virome. That in itself is sort of if you had a walk-in closet, if you will, of all viruses and pathogens that could affect a human immune system. Is that what that is?
John Altin, PhD [00:03:25] That’s right. It’s really the full repertoire is everything. Now, the virus can mean different things to different people, but in the case of the human virus, we’re thinking about all the different viruses that can infect a human. And as I say, this can include things that are very well known, high profile, well-studied things that are emerging, you know, in populations that we don’t really know much about, things that, you know, come from animals, viruses that cause common disease, viruses that cause, you know, severe disease. Some species like Epstein-Barr virus, for example, we’re basically all infected with. But in some cases, that can lead to a disease like multiple sclerosis. So there are all sorts of effects that these viruses can have on our health.
Karie Dozer [00:04:04] And you talked about the ability to test a human against all of these possible pathogens. Is that the best part about PepSeq or is the best part about it the small amount of blood sample that you need to make it work?
John Altin, PhD [00:04:20] I think it’s both of those things. And also another which is that, you know, we’re looking across these viruses, but we’re not just treating each virus as sort of a monolith. We’re able to actually say very specifically which parts of each of these viruses is the immune system seeing. And that’s important for a few reasons. It can help us to get more precise, specific diagnostic approaches. But what it can also do is identify regions that are the same between many viruses. And this has become an area of great interest against the coronavirus, for example, where there are regions of the coronavirus, the pandemic virus that are very similar to other, let’s call them cousin coronaviruses that are endemic and those. Regions can be very important as far as developing very broad across protective escape resistant immunity, because obviously we know that these variants can come along and escape our prior immunity. So it’s that kind of breadth as well as the high-resolution view that PepSeq is able to give us.
Karie Dozer [00:05:19] We’re talking with John Altin at TGen North about technology called PepSeq. Simply put, did you and TGen North create PepSeq or did you advance it in some way from something that existed before?
John Altin, PhD [00:05:33] Yeah, the origins of PepSeq came about when I was working actually in biotech before I joined TGen, and so we sort of took that approach to TGen and we’ve really, I think, expanded it in all sorts of ways. So you know, that basic principle was there, but what wasn’t there was what its application was and the design of these very complex libraries. All of that has happened, you know, in the last four or five years at TGen.
Karie Dozer [00:05:58] You talked about a small sample and there have been recent news stories about technology that purportedly used a drop of blood to diagnose all sorts of diseases. Is that truly what we’re talking about? Like a single drop of blood? And if so, how revolutionary is that? What did we used to use?
John Altin, PhD [00:06:15] Often a blood test will be a large volume draws, as you know. So what we’re talking about here is literally a drop in this particular paper. We had some work that used dried blood spots, which is where someone can actually collect the sample themselves using a lancet to prick the tip of the finger and then put a drop of blood on to fill out filter paper. And so we know that that’s enough sample to generate these insights. And I think that is it. That is a big advance and that’s not one that we alone have made. Others recently have done the same thing. So I think this is this is really pointing to a direction that the field I think is moving and will move as the sample requirements go down. Because, you know, do we really need to be collecting, you know, a tube full of blood from your arm? And we could do it all from a drop, especially for kids, You know, during blood can be challenging for people who are frail Ill went to one of our NIH programs actually that we’re closely involved in is all about developing what they call samples bearing assays. And it’s all about these kind of populations where a large volume of material is just not non-viable and a smaller volume is really all you can get. So I think there’s absolutely a need for that.
Karie Dozer [00:07:20] So this technology has advanced something that you were able to do several years ago by leaps and bounds and in two different directions, really in two different ways. Globally speaking. What’s so great about PepSeq and what you’ve developed here?
John Altin, PhD [00:07:36] I think there are a number of avenues that we can we can take this and that can have an impact. One of them relates to their high-resolution view. So looking at these very specific regions of a virus or a tumor that we want to target, and then developing therapies that are directed to those regions at that. Certainly one sort of therapeutic angle that I think PepSeq is opening up for us in a really exciting way. The other relates to the breadth and looking across all of these, for example, different viral species. One of the areas that we think this could have real promise in application is in population level epidemiological surveillance. So right now we don’t really do a great job of understanding at a population level what is happening where and when people are getting infected with what. And so what we’re really excited in doing is scaling this approach to that level, using, for example, blood donor samples which are collected, you know, thousands and thousands at a time, hundreds of thousands every year. And we can we can tap into that. We have we have some avenues that we can potentially generate something that I would I would analogize to a weather forecast where we’re looking across space and time across the country ultimately, you know, globally and understanding who is getting infected with what, where and when that is going to be just called for, for public health people who want to understand how do we go in and prevent and control and understand the incidence of disease. Right now, the way we do that is through pretty basic surveillance approaches that often involve, you know, reporting from clinicians and things like that. So to be able to do this using this technology, which has now become cost effective at that scale, I think could open up real opportunities in modeling and surveilling for disease quite globally.
Karie Dozer [00:09:17] What about at the individual level? What does this mean for someone who may be looking at their risk of contracting certain diseases? They’re traveling to a certain region. They know that they are genetically predisposed to a particular cancer or a particular disease. Is this technology useful in those instances?
John Altin, PhD [00:09:36] I think it can be. You know, one of the things that we’re learning is that many diseases that we didn’t even think were related to a virus actually do have a viral trigger. Multiple sclerosis, I mentioned before is a great example of this, where it looks pretty clear now that infection by this very common virus, Epstein-Barr virus, is strongly associated with the development of M.S., which is, you know, debilitating neurological disease. Now, not everyone who gets infected with EBV develops mean. But there is this association. So if we can track, you know, how these infections are looking, where and when people are being infected. And some viruses like EBV, can actually reactivate in our bodies over time and sort of go up and down. And if we can track that, too, I think there’s really an opportunity to understand how that informs people’s health and the development of other chronic diseases that may be closely related.
Karie Dozer [00:10:24] Is this all about immunology and risk or is this it? Can this technology also be used to treat a particular disease in a particular person?
John Altin, PhD [00:10:34] For treatment, I think this technology opens the door and what it does is it says here are the regions that we want to look at and focus in on. And then there are pathways to developing therapeutics that are very tailored to those are very directed. So I think it opens the door to therapeutics is not directly a therapeutic assay, but I think it has, you know, real potential there in terms of the diagnostic aspect. I think that’s much, much closer even because we already have an assay that basically gives us information about someone’s immune profile and viral profile today.
Karie Dozer [00:11:05] When it comes to using this technology to look at viruses worldwide, say something that affects people in Africa but doesn’t generally affect people in the United States. How does this technology give us more knowledge about perhaps preventing these diseases or stopping a spread or pandemic like the one we just went through with COVID 19?
John Altin, PhD [00:11:27] One of the things I think we learned through the pandemic is that problems that look like they are just distant from us aren’t always distant from us. So that virus that was affecting people in Wuhan in early 2020, late 2019 didn’t seem like a problem for us until it was a problem. And now obviously it’s been let’s hope we’re past that phase of global life. But, you know, I guess the point is that we’re in a very globalized world, an increasingly globalized world. And so there is a lot of interconnection, a lot of potential for things that are local to become global. So I think by sort of setting up networks of surveillance that are trying to pick these things up early and once they arrive, you know, in the U.S. or elsewhere, for example, to see how they’re spreading state to state, region to region, has real potential to give us a jump start on, you know, tackling a pandemic or even something that’s less than a pandemic, but still causing, you know, disease.
Karie Dozer [00:12:22] If the pandemic had started today and you had this technology in hand and it was something that you were learning how to use. Would science have had a quicker, better handle on COVID 19 and it spread? Would we have known more sooner if we had this?
John Altin, PhD [00:12:37] I think if we had this kind of surveillance, this nationwide or even global surveillance system in place, we would have seen this virus early and we would have seen how it was spreading earlier than we did. We would have had a pretty significant head start in understanding where it was and who was being affected, not to mention an understanding of what are the therapeutic opportunities or targets that may flow from that.
Karie Dozer [00:13:01] As an immunologist, does the scientific world have a handle on every virus and pathogen that is out there, or is there something in this closet, in this virus, in that that we don’t have a name for yet that we haven’t truly found?
John Altin, PhD [00:13:16] There are a lot of blind spots. There are viruses that we either don’t know about or don’t realize are actually as pathogenic as they are. One example would be an enterovirus that we have worked on here at TGen North, which is really sort of a common garden variety virus, doesn’t really cause much disease. You know, pretty mild symptoms generally. But recently it was found to be associated with a very debilitating disease, much like polio, actually, that had these neurological symptoms that was causing kids to become paralyzed, you know, in a very small percentage of cases. But, you know, we didn’t really understand that association until recently. But it’s an example of how there is a lot of, let’s call it dark matter in this space that we don’t understand that, you know, may or may not be a serious we don’t really know. Maybe it’s one in a thousand, one in 10,000 people who get infected develop some kind of complication that may not even be tracked back to that viral species. So I think there’s a lot of opportunity to, you know, shine some light on that dark matter.
Karie Dozer [00:14:16] Have you ever speculated how much dark matter there is, how much we know, as opposed to how much we don’t know?
John Altin, PhD [00:14:22] It’s a great question. You know, we know that in other spheres, the number of viruses is just is just astronomical, you know, millions and millions in terms of what we know infects humans. It’s more in the hundreds, but that’s really based on what we know. And so there are opportunities with this type of technology to do surveillance that’s more general than that. And actually we’re collaborating to really extend what we’ve done in the human case to the mammalian virus. Viruses is looking across all mammals and we’re really interested to see what that’s going to teach us both in other mammals and humans, because there’s a lot of space there that just hasn’t been explored.
Karie Dozer [00:14:59] COVID 19 is obviously so. Forefront in our mind in the United States. Is there a global disease or pathogen that you think this technology will be the most helpful in addressing, treating, diagnosing worldwide?
John Altin, PhD [00:15:14] I think influenza is maybe not the only example, but is an example of a virus that we know kills, you know, tens of thousands of people a year. Often people who are immunosuppressed or frail. But that is obviously surfacing in different places in different ways with different variants. And I expect COVID 19, SARS-CoV-2, to do much the same thing going forward. Unfortunately, we’re not going to be, you know, fully past this virus as much as we want to be. And it’s going to predominantly affect people who are who are frail or have weakened immune systems, I think. But these are both examples of things that are probably here to stay, are not going to be kind of static. They’re going to keep changing. And if we can stay a step ahead of that game and track them and understand them, I think we’re going to be in a better position to address them.
Karie Dozer [00:16:00] Thank you, John Altin, for your time. Interesting technology. I hope you help find the next great thing to do with it.
John Altin, PhD [00:16:05] Good talking with you. Thank you.
Karie Dozer [00:16:07] For more on TGen’s research, go to TGen dot org slash news. The Translational Genomics Research Institute, part of City of Hope, is an Arizona based nonprofit medical research institution dedicated to conducting groundbreaking research with life changing results. You can find more of these podcasts at TGen dot org slash TGen Talks, Apple, Spotify and most podcast platforms. For TGen Talks, I’m Karie Dozer.
