WEBVTT - Special Episode: Epstein-Barr Virus 0:00:43.760 --> 0:00:47.319 Hi, I'm Aaron Welsh and this is this podcast will 0:00:47.400 --> 0:00:51.400 Kill You. Welcome to another bonus episode in this mini 0:00:51.479 --> 0:00:54.319 series of bonus content that we've been putting out over 0:00:54.360 --> 0:00:57.160 the past couple of months. If this is the first 0:00:57.160 --> 0:00:59.840 time you're tuning into one of these and wondering what 0:01:00.080 --> 0:01:03.440 this is about. I've been putting together these bonus episodes 0:01:03.520 --> 0:01:06.880 to explore in more detail one aspect of the topic 0:01:06.920 --> 0:01:10.360 that we covered in our previous week's regular season episode. 0:01:10.880 --> 0:01:13.959 I've also been using this opportunity to chat with people 0:01:14.040 --> 0:01:16.760 about their jobs, what they like about them and what 0:01:16.800 --> 0:01:20.000 they don't, how much they do changes from day to day, 0:01:20.400 --> 0:01:23.240 and any words of wisdom they may have for people 0:01:23.400 --> 0:01:26.920 just starting out in their careers. So far, I've gotten 0:01:26.959 --> 0:01:31.000 to chat with some fantastic folks about hepatitis B, stigma 0:01:31.120 --> 0:01:35.920 and discrimination, a new drug for human African tripanisimiasis rabbit 0:01:35.959 --> 0:01:40.680 hemorrhagic disease virus, and it's been fascinating to see how 0:01:40.720 --> 0:01:43.520 wide ranging this work can be and how many different 0:01:43.600 --> 0:01:46.399 approaches can be used in the field of public health. 0:01:47.280 --> 0:01:50.160 This week, I'm taking a bit of a zag from 0:01:50.240 --> 0:01:54.480 last week's episode on multiple sclerosis by turning my sites 0:01:54.600 --> 0:01:58.600 to the epstein bar virus, helped along by doctor Mika Luftig, 0:01:58.800 --> 0:02:02.560 Associate Professor, Vice Chair in the Department of Molecular Genetics 0:02:02.560 --> 0:02:06.960 and Microbiology at Duke University. Last week, Aaron and I 0:02:07.040 --> 0:02:11.120 covered multiple sclerosis, which is a disease of many mysteries. 0:02:11.840 --> 0:02:15.120 Go and check out the episode if you haven't already 0:02:15.280 --> 0:02:18.560 one of these mysteries, which could be considered the central 0:02:18.720 --> 0:02:23.320 mystery really is what causes this disease. Recently, a couple 0:02:23.320 --> 0:02:25.839 of studies were released that shed a bit of light 0:02:25.919 --> 0:02:29.280 on this aspect of multiple sclerosis, especially as it relates 0:02:29.320 --> 0:02:32.520 to the epstein bar virus, a virus that has long 0:02:32.560 --> 0:02:35.320 been suspected to play a role in this and many 0:02:35.360 --> 0:02:39.280 other diseases. In the case of MS, there doesn't seem 0:02:39.320 --> 0:02:42.000 to be one single cause for what makes some people 0:02:42.040 --> 0:02:46.200 develop this disease, and it's likely many factors working together, 0:02:46.600 --> 0:02:50.160 such as a lack of vitamin D, genetic predisposition, a 0:02:50.280 --> 0:02:54.240 history of exposure to cigarette smoke, and epstein bar virus. 0:02:54.960 --> 0:02:58.720 But it does seem as though EBV is probably a 0:02:58.800 --> 0:03:02.720 crucial part in the development of this disease. In our 0:03:02.880 --> 0:03:06.040 MS episode, we talked about the implications of this recent 0:03:06.120 --> 0:03:09.839 research about EBV and MS and what it could mean 0:03:09.880 --> 0:03:13.920 for the prevention or treatment of multiple sclerosis, and that 0:03:14.040 --> 0:03:17.120 discussion it also got me thinking just more about this 0:03:17.240 --> 0:03:20.840 bizarre virus, that epstein bar virus, and what about its 0:03:20.880 --> 0:03:24.320 biology has led to it being implicated in all kinds 0:03:24.360 --> 0:03:29.080 of cancers and autoimmune diseases beyond multiple sclerosis. So I 0:03:29.160 --> 0:03:32.079 wanted to use this bonus episode to get up close 0:03:32.120 --> 0:03:37.280 and personal with this extraordinarily prevalent virus this bonus episode. 0:03:37.400 --> 0:03:40.520 It doesn't mean that EBV won't someday get the full 0:03:40.680 --> 0:03:44.440 erin squared treatment in a regular season episode, but who 0:03:44.480 --> 0:03:48.280 doesn't love a little sneak peek. Since its discovery in 0:03:48.400 --> 0:03:51.800 nineteen sixty four, the epstein bar virus has been implicated 0:03:51.920 --> 0:03:56.600 in an impressive number of different diseases, including various cancers 0:03:56.600 --> 0:04:01.680 and autoimmune diseases, just as we found in multiple sclerosis episode. 0:04:02.000 --> 0:04:05.680 There are still many mysteries and unanswered questions that surround 0:04:05.680 --> 0:04:09.080 the epstein bar virus, but over the years we have 0:04:09.240 --> 0:04:13.480 also made incredible strides in understanding how it does the 0:04:13.560 --> 0:04:17.039 things it does. One of the researchers who has helped 0:04:17.080 --> 0:04:21.520 to answer those formerly unanswerable questions is doctor Mika Luftig. 0:04:22.040 --> 0:04:26.800 Doctor Luftig has graciously agreed to submit to my many questions, 0:04:27.080 --> 0:04:30.240 not just about the epstein bar virus, but also what 0:04:30.320 --> 0:04:33.200 it's like to be a professor, what other options are 0:04:33.240 --> 0:04:37.400 out there for someone interested in viruses and microbiology, favorite 0:04:37.480 --> 0:04:41.200 virus fun facts, and so much more. I'm going to 0:04:41.240 --> 0:04:43.720 take a quick break here and then I'll let him 0:04:43.760 --> 0:04:44.640 introduce himself. 0:05:09.000 --> 0:05:12.440 I'm Nikoleptik. I'm an associate professor and the vice chair 0:05:12.520 --> 0:05:16.080 here in the Molecular Genetics and Microbology Department at Duke 0:05:16.160 --> 0:05:21.720 University School of Medicine. My lab studies EBV epstein bar virus. Primarily, 0:05:21.760 --> 0:05:26.440 we've studied how EBB infects and immortalizes human B cells 0:05:26.600 --> 0:05:30.120 and that's a model for lymphomas in immune suppressed patients. 0:05:31.400 --> 0:05:33.960 Thank you so much for joining me today. I am 0:05:34.279 --> 0:05:37.440 so thrilled to get into the nitty gritty of epstein 0:05:37.480 --> 0:05:41.880 bar virus. So what is EBV? Can you tell me 0:05:41.880 --> 0:05:44.320 a little bit more about this virus, what type of 0:05:44.400 --> 0:05:47.280 virus it is, how do people get it, and what 0:05:47.360 --> 0:05:49.240 makes this virus so special. 0:05:50.240 --> 0:05:54.279 EBV is a herpes virus, so it's in the family 0:05:54.360 --> 0:05:57.440 of We currently know there are eight human herpes viruses, 0:05:57.600 --> 0:06:02.640 and EBV is, like all herpes viruses, a large, double 0:06:02.680 --> 0:06:05.680 stranded DNA virus, and what that means is that its 0:06:05.720 --> 0:06:08.880 genome is made up of the same material as human genomes, 0:06:09.080 --> 0:06:12.719 and so that material is packaged up into a protein 0:06:12.800 --> 0:06:17.640 shell and decorated on the surface with glycoproteins, which we've 0:06:17.680 --> 0:06:19.040 heard a lot about in the news in the last 0:06:19.080 --> 0:06:23.560 two years. And this virus is complex because of its size, 0:06:23.600 --> 0:06:26.599 so it's about one hundred and seventy thousand bases long, 0:06:27.040 --> 0:06:30.360 and it can encode about eighty different proteins as well 0:06:30.400 --> 0:06:34.680 as a bunch of little RNA gene products that help 0:06:34.760 --> 0:06:38.760 take over the cell. It's special because it has an 0:06:38.760 --> 0:06:44.239 intimate relationship with humans. Virtually every adult on the planet 0:06:44.320 --> 0:06:48.600 is infected with EBB, and you're infected when you're a child, 0:06:48.760 --> 0:06:52.080 usually in the first decade of life. The virus is 0:06:52.120 --> 0:06:55.840 transmitted by saliva, so it could be your mom or 0:06:55.920 --> 0:06:59.960 dad kissing you, it could be from another kind of 0:07:00.160 --> 0:07:04.240 kiss that happens in young age, and usually the infection 0:07:04.480 --> 0:07:08.400 is relatively benign. But what happens is that the virus 0:07:08.440 --> 0:07:11.760 gets into the cells called B cells, which are the 0:07:11.920 --> 0:07:15.680 antibody producing cells in your immune system, somewhere in your 0:07:15.800 --> 0:07:20.000 oral mucosa, like your consoles or adenoids. And when that happens, 0:07:20.040 --> 0:07:23.280 the virus goes latent, and that's really the where the 0:07:23.280 --> 0:07:29.080 intimacy starts. The latently infected cell can harbor the virus 0:07:29.560 --> 0:07:31.239 more or less for your whole life. 0:07:32.160 --> 0:07:34.840 Can you talk a little more about what's going on 0:07:35.000 --> 0:07:37.520 at the cellular level with EBV infection? 0:07:38.760 --> 0:07:41.600 You know, I keep bringing up B cells, which maybe 0:07:41.640 --> 0:07:43.680 most people don't think about as much as I do, 0:07:43.760 --> 0:07:47.080 but it's sort of an important cell type to think 0:07:47.120 --> 0:07:51.040 about because the virus has evolved clearly to take advantage 0:07:51.040 --> 0:07:53.960 of being latent and living in a B cell and 0:07:54.240 --> 0:07:58.800 mimicking how B cells normally respond to antigens. So, because 0:07:58.880 --> 0:08:04.240 they're antibody producing cells of the human immune system, their 0:08:04.320 --> 0:08:07.120 goal is to have an antibody on the surface of 0:08:07.120 --> 0:08:12.040 the cell that sees an antigen from some pathogen get excited. 0:08:12.360 --> 0:08:15.720 The cell starts to divide and make better and better 0:08:15.720 --> 0:08:20.440 antibodies that ultimately are used to fight whatever that pathogen was. Well. 0:08:20.440 --> 0:08:24.040 EBV sort of takes advantage of that process and has 0:08:24.320 --> 0:08:28.400 specific proteins that mimic the kinds of proteins that get 0:08:28.400 --> 0:08:32.360 activated in cells when they see antigen and drives that 0:08:32.440 --> 0:08:35.360 same process that B cell would have done if it 0:08:35.400 --> 0:08:39.760 had seen some foreign pathogen. And so the end goal, 0:08:39.880 --> 0:08:43.400 I'm like cutting to the chase here of why this 0:08:43.440 --> 0:08:46.080 thing is so successful and so amazing, is that the 0:08:46.240 --> 0:08:50.040 end goal is that the infected B cell that starts 0:08:50.080 --> 0:08:53.240 off in your tonsils or rev you ends up as 0:08:53.280 --> 0:08:56.440 a memory B cell in your blood, which just sits 0:08:56.440 --> 0:09:00.640 there for weeks or months or longer. When the virus 0:09:00.720 --> 0:09:04.040 is completely late, we can get into the nitty gritty 0:09:04.120 --> 0:09:06.920 of what the latent replication cycle is like, because it's 0:09:06.920 --> 0:09:09.920 not the typical replication cycle you think of a virus 0:09:09.960 --> 0:09:13.120 where you make new particles and you get out. It's 0:09:13.160 --> 0:09:18.320 actually just the viral genome is circularized as an extra 0:09:18.400 --> 0:09:21.600 chromosomal piece of DNA. Then you start with one, you 0:09:21.640 --> 0:09:25.040 wind up with about ten in the memory B cell compartment. 0:09:25.760 --> 0:09:29.960 But when say anagen comes and triggers that B cell 0:09:30.200 --> 0:09:32.760 to think that it needs to make a ton of antibody, 0:09:32.920 --> 0:09:35.240 that's a dead end for the virus and it switches 0:09:35.320 --> 0:09:38.080 to the lytus cycle, which for EBV the way it 0:09:38.120 --> 0:09:41.520 happens is that these latent infected B cells, anagen comes 0:09:42.000 --> 0:09:45.640 reactivates it. Now you make thousands of particles that are 0:09:45.720 --> 0:09:50.240 released from the cell. That starts a life cycle of 0:09:50.559 --> 0:09:54.800 then the other phase, which is in epithelial cells, so 0:09:55.040 --> 0:09:58.520 cells in the oral mucosa. When the virus gets out, 0:09:58.960 --> 0:10:01.040 it will go in and instead of doing that whole 0:10:01.080 --> 0:10:03.880 latency dance that I just described, that sort of beautiful 0:10:04.040 --> 0:10:09.199 B cell latency dance, it just replicates like any other virus, 0:10:09.240 --> 0:10:13.160 you know, the textbook example of it gets in, it replicates, 0:10:13.880 --> 0:10:18.000 produces tens of thousands of particles, kills the cell. And 0:10:18.559 --> 0:10:22.400 that amplification step is actually what's happening in all of 0:10:22.480 --> 0:10:25.400 us and why the virus is released into the saliva 0:10:26.000 --> 0:10:28.600 and getting out to be able to transmit to others, 0:10:28.840 --> 0:10:33.080 but also to infect new B cells in your oral nucosa. 0:10:34.440 --> 0:10:37.960 Okay, I see. And so in that initial infection it 0:10:38.040 --> 0:10:41.240 goes into the B cells and then eventually it will 0:10:41.480 --> 0:10:48.600 go into the epithelial cells when it is actively shedding virus, right, gotcha? Okay? 0:10:49.200 --> 0:10:53.119 And so many or even most people who get EBV 0:10:53.440 --> 0:10:57.079 may not ever know it because it doesn't produce any symptoms, 0:10:57.200 --> 0:10:59.360 But what about when it does, Like, what are the 0:10:59.440 --> 0:11:03.880 symptoms of a symptomatic EBV infection and what's going on 0:11:03.960 --> 0:11:07.319 at a cellular level that can lead to those symptoms. 0:11:08.280 --> 0:11:12.240 I'll even step back and answer the question of why 0:11:12.280 --> 0:11:15.080 don't people get sick when they're infected with EBB Because 0:11:16.960 --> 0:11:23.360 it turns out that EBV latency proteins are exquisitely well 0:11:23.440 --> 0:11:28.720 recognized by the T cell response of the human immune system, 0:11:29.280 --> 0:11:33.120 and so in adults, one to two percent of all 0:11:33.200 --> 0:11:37.520 of your T cells are specific for EBV proteins. They 0:11:37.720 --> 0:11:43.920 are activated and will eliminate those latently infected cells that 0:11:44.000 --> 0:11:49.439 are producing the viral proteins pretty efficiently for your whole life. 0:11:49.640 --> 0:11:53.800 And so it's only either in the case of immune suppression, 0:11:54.200 --> 0:11:57.880 where EBV can cause problems in the B cell compartment 0:11:57.960 --> 0:12:01.920 and where you become much more susceptible to the lymphomas 0:12:02.000 --> 0:12:04.400 that EBB can drive. We can talk more about that 0:12:04.720 --> 0:12:09.280 in a bit. But where it causes disease though, first, 0:12:09.400 --> 0:12:13.040 so to speak, in most folks life is in the 0:12:13.080 --> 0:12:15.640 second decade of life. So if you're not infected in 0:12:15.679 --> 0:12:18.280 the first decade of life, then it can be a 0:12:18.280 --> 0:12:22.640 problem because about fifty percent or so of those primary 0:12:22.640 --> 0:12:28.600 infections cause mono. So EBV causes infectious mononucleosis. And the 0:12:28.760 --> 0:12:33.800 reason that happens is that the same dance of the 0:12:33.960 --> 0:12:37.320 latent infection in the B cells happens, but the T 0:12:37.480 --> 0:12:44.559 cell response, in fact is over exuberant, and you will 0:12:44.600 --> 0:12:47.440 have on the order of half of all of your 0:12:47.480 --> 0:12:51.160 T cells in the blood will be EBV specific for 0:12:51.240 --> 0:12:55.640 a couple of weeks. And that massive systemic expansion of 0:12:55.679 --> 0:12:59.080 T cells and the cytokines that they produce is what 0:12:59.240 --> 0:13:04.000 causes the fatigue and symptoms of mono. And there is 0:13:04.040 --> 0:13:07.920 a failure of those T cells to get to the 0:13:07.920 --> 0:13:10.920 tonsils the world ecoso where the EBB infected B cells 0:13:10.960 --> 0:13:15.680 are to shut things down in essentially anyone older than 0:13:16.120 --> 0:13:20.360 an adolescent if it's your primary infection. And that's a 0:13:20.400 --> 0:13:25.320 great mystery, immunological mystery. But the idea of having a 0:13:25.400 --> 0:13:29.880 vaccine that in individuals that are not yet infected could 0:13:29.920 --> 0:13:35.720 potentially prepare your immune system to deal with that primary 0:13:35.720 --> 0:13:38.560 infection later in life could be something that prevents mono 0:13:38.640 --> 0:13:41.920 and that could have also further benefits down the road. 0:13:42.040 --> 0:13:44.560 So it's not the B cells that are infected that 0:13:44.679 --> 0:13:49.400 cause disease in mono. It's the massive expansion and failure 0:13:49.440 --> 0:13:53.520 of contraction really of the T cell response that is 0:13:53.960 --> 0:13:54.920 very interesting. 0:13:55.720 --> 0:13:59.040 So, besides the age differences in terms of when you're 0:13:59.080 --> 0:14:02.200 first exposed to eat, do we know anything more about 0:14:02.320 --> 0:14:05.200 what determines whether or not you'll have a response to 0:14:05.840 --> 0:14:08.679 EBV infection or primary EBV infection. 0:14:09.440 --> 0:14:13.400 From the standpoint of everybody is going to be exposed 0:14:13.440 --> 0:14:16.960 to this virus, right, so the vast majority of people 0:14:17.679 --> 0:14:20.800 follow the course that we just described. But because so 0:14:20.840 --> 0:14:25.880 many people are infected, turns out that there are genetic 0:14:26.000 --> 0:14:31.560 variants that families can have where the individual is not 0:14:31.680 --> 0:14:35.760 able to control that primary BV infection and B cells 0:14:35.840 --> 0:14:40.560 because they're T cells, are in some way unable to 0:14:40.600 --> 0:14:44.160 see and kill the infected B cells. And I say 0:14:44.160 --> 0:14:46.160 it that way because it turns out some of the 0:14:46.200 --> 0:14:49.240 biology and the immunology that's been done on these questions 0:14:49.800 --> 0:14:55.560 actually detect not necessarily wholesale T cell immut deficiencies, but 0:14:55.760 --> 0:15:00.720 specific defects where T cells can't recognize B cells, and 0:15:01.360 --> 0:15:05.640 if they can, if there's either a transplant, for example, 0:15:05.840 --> 0:15:08.600 of mautaquatic stem cells or T cells that can come 0:15:08.640 --> 0:15:12.320 in to preserve that function. Then they can eliminate the 0:15:12.320 --> 0:15:15.200 B cells, but the T cell response to other viruses 0:15:15.280 --> 0:15:18.440 may not be deficient. So there is now an emerging 0:15:18.760 --> 0:15:23.440 recognition and field around what we would call chronic active EBV, 0:15:24.520 --> 0:15:28.760 and that is an umbrella under which individuals that have, 0:15:28.880 --> 0:15:33.120 for example, excellent glympho proliferative disease XLP, which is caused 0:15:33.120 --> 0:15:36.280 by a couple of different mutations that can prevent the 0:15:36.280 --> 0:15:39.360 T cells from interacting with the B cells, and other 0:15:40.080 --> 0:15:43.960 genetic variants that prevent T cell activation and T cell 0:15:44.040 --> 0:15:48.640 killing of the EBV infected B cells. And so then 0:15:49.040 --> 0:15:54.440 there can also be spontaneous or somatic mutations like happen 0:15:54.520 --> 0:15:58.200 for example, in cancer progression, but in the immune system 0:15:58.480 --> 0:16:03.800 where those somatic variance end up causing an inability, you know, 0:16:03.800 --> 0:16:07.080 for T cells to recognize the EBV infected cells. And 0:16:07.160 --> 0:16:11.520 so in some that sort of umbrella of diseases that 0:16:11.680 --> 0:16:16.080 one could lump together as chronic active EBV are what 0:16:16.120 --> 0:16:19.800 would lead to folks basically not being able to control EBV, 0:16:19.920 --> 0:16:23.920 and the consequences of that can be pretty severe, but 0:16:24.160 --> 0:16:29.720 range from monol like symptoms recurring what can be as 0:16:29.760 --> 0:16:36.200 severe as developing lymphomas or other EBV associated cancers. 0:16:36.880 --> 0:16:41.080 EBV is involved with many different types of cancers. Can 0:16:41.120 --> 0:16:44.160 you talk a bit about how infection with EBV could 0:16:44.240 --> 0:16:45.520 lead to cancer development. 0:16:46.560 --> 0:16:52.200 By the numbers of patients, eb V associated gastric cancer 0:16:53.000 --> 0:16:56.560 is the most prevalent EBV positive cancer in the world. 0:16:57.600 --> 0:17:01.840 Almost two hundred thousand people ten percent of gastric cancers 0:17:01.840 --> 0:17:05.239 are EBB positive, And what that means is that not 0:17:05.359 --> 0:17:08.080 the person is EBB positive, the cancer is EBB positive. 0:17:08.080 --> 0:17:11.760 So every infected cell in the tumor has EBB in it. 0:17:12.119 --> 0:17:14.560 So how the heck could that happen? Turns out that 0:17:15.000 --> 0:17:19.120 EBV doesn't really like infecting epithelial cells on its own 0:17:19.240 --> 0:17:22.080 in the lab, Whereas if you take a latently infected 0:17:22.119 --> 0:17:26.479 B cell and you cocultureate with epithelial cells that are 0:17:26.520 --> 0:17:32.679 uninfected and you reactivate the B cell, that triggers reactivation 0:17:32.920 --> 0:17:36.119 and transfer of the virus through cell to cell contact 0:17:36.200 --> 0:17:39.800 to the epithelial cells a thousand times more efficient than 0:17:39.800 --> 0:17:44.080 if you did a direct infection. So piecing that all 0:17:44.119 --> 0:17:48.119 together and the fact that in gastric cancer you often 0:17:48.320 --> 0:17:53.760 have an underlying gastritis, sort of chronic infection dysbiosis in 0:17:53.800 --> 0:17:58.600 some way that is a precursor to the cancer. It 0:17:58.680 --> 0:18:02.800 is very likely that EBV infected b cells that have 0:18:02.960 --> 0:18:06.280 an antibody on their surface with a specificity for some 0:18:06.320 --> 0:18:09.960 of the bacteria that might be causing the gastritis home 0:18:10.359 --> 0:18:13.920 to the basal basolateral surface of the epithelial cells in 0:18:14.040 --> 0:18:19.040 lymphoid tissue under underneath that and essentially are reactivated right 0:18:19.080 --> 0:18:21.200 in the spot to then infect for the virus to 0:18:21.240 --> 0:18:24.880 that infect epithelial cells. Now, what I told you earlier 0:18:24.960 --> 0:18:27.800 was that when the virus infects epithelial cells, by default, 0:18:27.880 --> 0:18:30.040 it goes litic. It just replicates and it kills the cell. 0:18:30.160 --> 0:18:32.679 So why how would that cause cancer? That doesn't make 0:18:32.680 --> 0:18:37.159 any sense. Right. For viruses to cause cancer or contribute 0:18:37.160 --> 0:18:41.160 to causing cancer, they have to have something go wrong 0:18:41.560 --> 0:18:45.120 in their replication. And one of the things that needs 0:18:45.160 --> 0:18:47.720 to go wrong is that when it infects the cell, 0:18:48.160 --> 0:18:52.400 it has to have some aspect of its replication function crippled, 0:18:52.960 --> 0:18:57.159 either by mutation or by the cell having heightened antiviral 0:18:57.200 --> 0:19:02.639 responses or some other breakdown in replication. And so in 0:19:02.760 --> 0:19:06.520 EBV positive epithelial cancers, the virus is actually late so 0:19:06.600 --> 0:19:12.200 it's a Barrant process, right. Instead of replicatinglytically, it accidentally 0:19:12.720 --> 0:19:15.800 finds itself latent, and some of the latency proteins can 0:19:15.840 --> 0:19:17.560 be made, not all of the ones I described in 0:19:17.560 --> 0:19:21.640 the B cells, but usually those membrane proteins that keep 0:19:21.680 --> 0:19:26.440 the cells alive, the pro survival proteins. They're usually expressed, 0:19:26.640 --> 0:19:28.920 and then the EBNO one protein that maintains the viral 0:19:28.960 --> 0:19:33.960 genome is still expressed and together that cooperates with cellular 0:19:34.720 --> 0:19:39.840 mutations that arise in driving in this case, gastric tumor genesis. 0:19:41.240 --> 0:19:44.960 We know that this is a global virus, ninety five 0:19:45.000 --> 0:19:47.520 percent of people have it by the time they are adults. 0:19:48.080 --> 0:19:51.400 But is there geographic variation in this virus? 0:19:51.440 --> 0:19:52.360 Like are there. 0:19:52.400 --> 0:19:55.960 Different types of EBV? How much genetic variation is there 0:19:56.080 --> 0:19:57.160 in this virus? 0:19:58.000 --> 0:20:02.040 So most double stre into DNA viruses like EBB or 0:20:02.080 --> 0:20:09.360 other herpes viruses, compared to other viruses, are relatively stable genetically. 0:20:09.480 --> 0:20:14.119 They really don't mutate that much like influenza virus or 0:20:14.280 --> 0:20:18.119 sarscov two or any of the sort of acute respiratory viruses. 0:20:18.400 --> 0:20:22.160 Those RNA viruses don't tend to have the proofreading capacity 0:20:22.640 --> 0:20:26.440 typically in their polymerases when they replicate, and so they 0:20:26.600 --> 0:20:32.639 throw in errors every couple of thousand basis of nucleic acid, 0:20:32.680 --> 0:20:36.760 whereas it's much a much lower error rate in DNA 0:20:36.800 --> 0:20:41.440 replication for double strand DNA viruses. That being said, now 0:20:41.480 --> 0:20:44.120 we know as of about maybe seven or eight years ago, 0:20:44.359 --> 0:20:49.520 with genome sequencing technology developing and becoming cheaper, so we 0:20:49.720 --> 0:20:52.679 now have a couple of hundred of genomes sequenced, and 0:20:52.760 --> 0:20:55.320 what's emerged is a couple of things. So one is 0:20:55.840 --> 0:20:59.560 that the prototypical genomes we've been working with are representative 0:20:59.560 --> 0:21:02.680 actually of what you see across the world, so that's good. 0:21:03.280 --> 0:21:07.120 We know that there are two major types of EBV, 0:21:07.440 --> 0:21:10.080 so type one and type two is what they're called, 0:21:10.600 --> 0:21:15.760 and they vary in very specific genes, which is primarily 0:21:15.800 --> 0:21:19.359 the latency genes. So the majority of EBV in the 0:21:19.400 --> 0:21:22.679 world is type one. It's distributed across the world, and 0:21:22.760 --> 0:21:26.240 type two is more prevalent in Africa and in some 0:21:26.320 --> 0:21:30.400 parts of Asia, and so in some ways they're almost 0:21:30.440 --> 0:21:32.600 like two different viruses, but as far as we know, 0:21:32.680 --> 0:21:35.880 they really operate very similarly in terms of di cell 0:21:35.920 --> 0:21:40.159 infection and latency and reactivation. And everything else. So the 0:21:40.280 --> 0:21:44.360 other things that we learned from the genome sequencing experiments 0:21:44.720 --> 0:21:49.920 are that the genes that are important for virus entry, 0:21:49.960 --> 0:21:55.080 for example that could be vaccine targets, are relatively well conserved, 0:21:55.840 --> 0:22:00.800 so there's probably not a big concern about that variation 0:22:01.119 --> 0:22:05.000 like you have for flu for example, in hampering vaccine design. 0:22:05.359 --> 0:22:08.280 But there is some variation. But coming back to the 0:22:08.359 --> 0:22:11.959 geographic distribution, it turns out that one of the latency genes, 0:22:11.960 --> 0:22:15.080 called LMP one or latent number in proteen one, it 0:22:15.200 --> 0:22:20.520 varies quite a bit relatively, and one can see geographic 0:22:20.800 --> 0:22:27.400 distributions that link a particular LMP one genotype two regions 0:22:27.400 --> 0:22:30.080 of the world. We don't know what that means in 0:22:30.160 --> 0:22:34.159 terms of disease or spread or what have you, but 0:22:34.480 --> 0:22:35.360 it's been observed. 0:22:36.640 --> 0:22:39.879 So let's get into latency. Tell me more about what's 0:22:39.920 --> 0:22:42.399 going on with latency. What does it mean for a 0:22:42.520 --> 0:22:46.000 virus to go latent and what can trigger reactivation? 0:22:47.119 --> 0:22:53.280 Yes, awesome, Okay, it's my favorite topic. So latency in 0:22:53.560 --> 0:22:56.639 the case of EBV is sort of an active latency. 0:22:56.880 --> 0:22:58.720 It's not the kind of latency you might think of 0:22:58.800 --> 0:23:02.320 as the virus is sleeping and you know, don't wake 0:23:02.359 --> 0:23:07.560 it up. It is a form of infection in B 0:23:07.680 --> 0:23:12.400 cells that is the default form that when you acquire 0:23:12.400 --> 0:23:15.000 your EVV in the saliva. The initial infection in B 0:23:15.119 --> 0:23:20.240 cells leads to a series of eight viral proteins being expressed, 0:23:20.800 --> 0:23:24.480 and they're called latency proteins. Six of them are transcription factors, 0:23:24.520 --> 0:23:27.199 so they go into the nucleus and they turn on 0:23:27.359 --> 0:23:30.679 genes and turn off genes in the host genome, and 0:23:30.800 --> 0:23:33.720 two of them are membring proteins at the cell surface 0:23:34.240 --> 0:23:40.080 that activate cellular signaling pathways, and that mimics how that 0:23:40.160 --> 0:23:43.560 B cell would normally have responded to antigen or a 0:23:43.600 --> 0:23:46.680 foreign pathogen if it were normally doing its job. But 0:23:46.760 --> 0:23:49.480 EBB is sort of co opting that. So when the 0:23:49.680 --> 0:23:53.520 latency proteins are expressed, the cell that it infects, a 0:23:53.560 --> 0:23:56.680 B cell is just a resting cell. It doesn't divide 0:23:56.720 --> 0:24:02.159 unless it gets signals to divide. And so those nuclear proteins, 0:24:01.920 --> 0:24:06.440 the so called ebna's epstein bar nuclear energens, when they're expressed, 0:24:06.840 --> 0:24:09.000 the cells will start dividing, and they actually do so 0:24:09.160 --> 0:24:13.000 very rapidly, and that's mimicking what happens when a B 0:24:13.119 --> 0:24:16.760 cell would normally have seen some foreign antigen, and so 0:24:16.840 --> 0:24:21.400 that rapid proliferation occurs for a number of divisions. And 0:24:22.040 --> 0:24:25.240 at the same time, these membrane proteins that are activating 0:24:25.280 --> 0:24:29.680 the signaling pathways are telling the cells at all costs 0:24:29.960 --> 0:24:34.600 stay alive. And the reason that's important is that the 0:24:34.680 --> 0:24:39.239 process from a naive B cell maturing to becoming a 0:24:39.520 --> 0:24:41.879 plasma cell or a plasma blast, which is one of 0:24:41.960 --> 0:24:44.960 these antibodies secreting B cells or a memory B cell, 0:24:45.480 --> 0:24:49.560 that process is one in which the B cell is 0:24:49.600 --> 0:24:52.800 activated and rapidly proliferates, so like you have a lot 0:24:52.840 --> 0:24:55.520 of B cells around to ultimately be able to make 0:24:55.560 --> 0:25:01.520 antibodies to stop some pathogen from taking over. In that process, 0:25:02.080 --> 0:25:06.720 it's a little sloppy, so an enzyme comes on that 0:25:06.920 --> 0:25:11.000 actually damages the DNA, cuts the DNA and causes mutations 0:25:11.000 --> 0:25:15.600 in the DNA in the so called immunoglobular locus. So 0:25:15.720 --> 0:25:19.960 the genes that are going to make the antibodies get mutated, 0:25:20.560 --> 0:25:23.960 and that is the selection process by which the B 0:25:24.119 --> 0:25:27.199 cells go from having an antibody that initially recognized the 0:25:27.240 --> 0:25:32.080 pathogen to making a better and better, higher affinity antibody. 0:25:32.840 --> 0:25:36.119 That process is dangerous, right, there's all this DNA damage, 0:25:36.119 --> 0:25:40.240 there's all this churn and everything. So EBV actually mimics 0:25:40.480 --> 0:25:43.520 that process. And so if that cell is going to 0:25:43.520 --> 0:25:46.120 stay alive and still be an EBV infected cell when 0:25:46.119 --> 0:25:48.359 it comes out of it, it needs to tell the 0:25:48.400 --> 0:25:51.240 cells not to die. And then after a couple of 0:25:51.280 --> 0:25:54.960 rounds of division, it gets out into the proiffery into 0:25:55.000 --> 0:25:58.080 the blood as a memory B cell, and it shuts 0:25:58.119 --> 0:26:02.439 everything off and it becomes truly latent and quiescent. And 0:26:02.480 --> 0:26:04.800 the reason it does that is that all of those 0:26:04.800 --> 0:26:07.280 proteins that I told you about, the ebnas and the 0:26:07.320 --> 0:26:12.840 membrane proteins so called LMPs, those are highly immune dominant, 0:26:12.840 --> 0:26:16.000 and T cells are going to recognize them and kill 0:26:16.040 --> 0:26:20.240 those EBB infected cells. So it shuts everything off, gets 0:26:20.240 --> 0:26:24.480 into the blood and sits there. When that cell divides, 0:26:24.880 --> 0:26:28.520 it makes one protein, and the one protein is a 0:26:28.520 --> 0:26:33.720 protein called VNA, one that can facilitate the DNA replication 0:26:34.359 --> 0:26:38.560 just of the EBV genome, which is actually represented at 0:26:38.560 --> 0:26:41.480 this point as probably eight to ten copies so extra 0:26:41.560 --> 0:26:46.919 chromosomal circular copies of BBVDNA and then partitions them to 0:26:47.000 --> 0:26:53.640 daughter cells. Then if those cells find themselves in lumphoid 0:26:53.640 --> 0:26:57.560 tissue in the oral mucosa, and the actual antibody on 0:26:57.600 --> 0:27:00.800 the surface of that B cell recognize as an anigen 0:27:01.600 --> 0:27:04.960 that triggers the differentiation of the cell and the switch 0:27:05.040 --> 0:27:08.000 to litic replication, and so then the virus makes tons 0:27:08.040 --> 0:27:11.480 of particles and gets out. Now, it turns out that's 0:27:11.560 --> 0:27:15.240 not the only way it can happen. Like most herpes viruses, 0:27:15.680 --> 0:27:19.480 we often say stress can induce reactivation. What is stressed, 0:27:19.520 --> 0:27:25.480 so DNA damage from radiation as a stress, hypoxic environments so, 0:27:25.560 --> 0:27:30.159 low oxygen environments as a stress. In fact, some small 0:27:30.200 --> 0:27:32.840 molecules that are secreted by bacteria that might be in 0:27:32.880 --> 0:27:38.119 our oral microbiome as a stress can reactivate latent DBB. 0:27:38.960 --> 0:27:41.480 So it's not just the B cell receptor or the 0:27:41.520 --> 0:27:43.800 antibody on the surface of the B cells that needs 0:27:43.800 --> 0:27:48.480 to signal or recognize anagen to trigger reactivation. All of 0:27:48.520 --> 0:27:51.320 those different kinds of stresses can do it. A lot 0:27:51.320 --> 0:27:54.679 of this comes back to the idea that EBV is 0:27:54.960 --> 0:27:58.359 latently in all of us, in our B cells, and 0:27:58.440 --> 0:28:01.600 because it's in our B cells, those cells have a 0:28:01.720 --> 0:28:05.840 very specific function, which is that they have antibodies on 0:28:05.880 --> 0:28:11.080 the surface, and those antibodies could recognize other pathogens, they 0:28:11.080 --> 0:28:17.000 could recognize auto antigens, they could recognize nothing, And if 0:28:17.040 --> 0:28:20.200 they recognize nothing, that cell should have died, but EBV 0:28:20.359 --> 0:28:24.520 keeps it alive. And so that sort of central principle 0:28:25.440 --> 0:28:30.920 is what underlies the relationship between EBV and I think 0:28:30.960 --> 0:28:35.080 some of the cancers it's associated with, probably autoimmune diseases, 0:28:35.400 --> 0:28:41.720 and certainly how this symbiosis between EBV and the B 0:28:41.880 --> 0:28:47.400 cell why it works. Basically, so one about one in 0:28:47.400 --> 0:28:51.360 one hundred thousand of our memory B cells in our 0:28:51.400 --> 0:28:55.320 blood at any given time is EBB positive, So that 0:28:55.440 --> 0:28:59.320 ends up being probably tens of thousands of cells. And 0:28:59.400 --> 0:29:03.200 each of those else has a different specificity the B 0:29:03.280 --> 0:29:05.320 cell receptor on the surface of each of those cells. 0:29:05.560 --> 0:29:08.040 They might be for an E. Coli in your gut, 0:29:08.400 --> 0:29:11.200 They might be for the cold virus you had when 0:29:11.240 --> 0:29:15.040 you were for they might be for tetanus, vaccine anigen, 0:29:15.280 --> 0:29:19.200 they might be for some autoanigen. But because the virus 0:29:19.200 --> 0:29:22.160 is clas and most of the time everything's fine. So 0:29:22.480 --> 0:29:25.200 when we talk about EBV flaring up and this kind 0:29:25.240 --> 0:29:29.320 of thing, EBED is a barometer of our humoral immune response. 0:29:29.840 --> 0:29:36.200 It's like a little gauge of when things are okay 0:29:36.800 --> 0:29:41.880 and when things are imbalanced. And that's vague, but you 0:29:41.920 --> 0:29:45.000 can imagine that you could put specificity on it if, 0:29:45.040 --> 0:29:48.480 for example, it was a particular pathogen driving a particular 0:29:48.480 --> 0:29:54.200 clone of EBB that mimicked an autoanigen, like maybe that's 0:29:54.200 --> 0:29:57.719 what causes chogrin syndrome sometimes, or maybe that's what promotes 0:29:57.840 --> 0:30:01.440 ms sometimes. Right, it's all about the B cell. 0:30:01.560 --> 0:30:06.320 Talking more about autoimmune diseases and the potential role of EBV. 0:30:07.040 --> 0:30:10.000 What are the conditions that seem to have the highest 0:30:10.040 --> 0:30:14.760 support for an involvement of EBV And is it sort 0:30:14.800 --> 0:30:17.960 of that mechanism that you described or are there different 0:30:18.000 --> 0:30:19.280 mechanisms that are involved. 0:30:20.480 --> 0:30:23.720 I think there can really be two likely two mechanisms. 0:30:24.200 --> 0:30:27.000 One is what I just described, which is that because 0:30:27.040 --> 0:30:30.280 EBV finds itself in B cells, that's where it lives, 0:30:30.640 --> 0:30:34.040 if one of those B cells has an antibody that 0:30:34.320 --> 0:30:39.600 on its surface that is autoreactive, and that autoreactivity is pathogenic, 0:30:40.080 --> 0:30:43.800 then that would be a mechanism where the process that 0:30:43.840 --> 0:30:48.400 I described of how EBV latency proteins tell cells to 0:30:48.520 --> 0:30:53.040 proliferate keep them from dying expand clones. Right, that cell 0:30:53.080 --> 0:30:56.280 may actually come back through the lymphoid tissue and need 0:30:56.320 --> 0:30:59.000 to expand again, and if that happens, EBV is there 0:30:59.080 --> 0:31:02.160 to keep it alive. So that's for example, that's something 0:31:02.200 --> 0:31:05.880 that goes awry in Honchkin's umphoma. In this case, it 0:31:05.960 --> 0:31:08.560 could be in the case of certain autoimmune diseases. You 0:31:08.560 --> 0:31:12.560 can have B cells that are infected with an auto antibody. 0:31:13.160 --> 0:31:17.720 They expand, and perhaps they expand to becolm plasma cells 0:31:17.720 --> 0:31:19.720 that go to the bone marrow and just secrete antibody 0:31:19.880 --> 0:31:22.240 for a long period of time. And that could be 0:31:22.640 --> 0:31:25.480 this just a pathogenic auto antibody that you need to 0:31:25.480 --> 0:31:29.560 get rid of because that's what's causing a particular autoimmune condition. 0:31:30.040 --> 0:31:34.120 So that's one possible mechanism for how EBV could be 0:31:34.160 --> 0:31:38.920 involved in variety of autoimmune diseases. Another is what was 0:31:39.000 --> 0:31:44.720 proposed in the recent Nature paper about EBD's association with 0:31:44.960 --> 0:31:48.680 MS and molecular mimicry. What they found was that if 0:31:48.720 --> 0:31:52.720 they looked in the cerebral spinal fluid of MS patients 0:31:53.360 --> 0:31:56.800 where B cells should not be hanging out, but they 0:31:57.560 --> 0:32:00.680 found some, you know, enough to be able to then 0:32:00.800 --> 0:32:04.960 isolate them and pull out the antibody genes that are 0:32:05.400 --> 0:32:08.640 in each individual B cell express them, so make them 0:32:09.240 --> 0:32:11.959 in vitro in the lab and then ask well, what 0:32:11.960 --> 0:32:14.680 are these antibodies buying? And what they found was that 0:32:15.120 --> 0:32:18.360 about thirty percent of patients had antibodies that reacted with 0:32:18.520 --> 0:32:23.960 EBV antigens. And when they drilled down into which antigens 0:32:24.680 --> 0:32:28.600 were recognized, more often than not, it was this viral 0:32:28.640 --> 0:32:32.440 proteinv No one and that protein is known to play 0:32:32.480 --> 0:32:35.400 all sorts of games to avoid the immune system. So 0:32:36.200 --> 0:32:38.480 what does that mean? Why does that cause it? Why 0:32:38.520 --> 0:32:42.000 would that or could that cause ms? And it turns 0:32:42.040 --> 0:32:44.360 out that the small peptide region of v No one 0:32:44.480 --> 0:32:48.640 that's recognized by the antibody is virtually identical to a 0:32:48.680 --> 0:32:52.640 region of a protein that's expressed in neurons called gliocam, 0:32:53.320 --> 0:32:59.280 and that indicates that that specificity is one where just 0:32:59.720 --> 0:33:03.880 one amino acid difference is enough to shift you from 0:33:04.040 --> 0:33:07.920 recognizing a pathogen to recognizing your own protein. And so 0:33:08.560 --> 0:33:12.360 I think those are the two favored and plausible mechanisms. 0:33:12.920 --> 0:33:16.120 Is it the EBV positive B cells that are playing 0:33:16.120 --> 0:33:18.520 a role here, or is it this other mechanism of 0:33:18.560 --> 0:33:23.360 molecular mimicry, where the antibody response to an EBB protein 0:33:23.920 --> 0:33:29.840 could end up being what triggers reactivity with your neurons, 0:33:30.000 --> 0:33:35.200 which is bad. The question of how much in every 0:33:35.280 --> 0:33:38.920 case of MS or any other autoimmune disease does this contribute. 0:33:39.240 --> 0:33:42.440 I think that the serum in MS patients from the 0:33:42.840 --> 0:33:48.400 large military study is the strongest evidence yet of the 0:33:48.440 --> 0:33:52.720 requirement of EBV infection for developing MS, and I think 0:33:52.760 --> 0:33:57.520 that the Nature paper really strongly supports a potential pathogenetic 0:33:57.560 --> 0:34:02.640 mechanism of molecular mimicry could support the development of MS 0:34:02.680 --> 0:34:09.040 in some individuals. I think the idea that preventing EBV 0:34:09.160 --> 0:34:14.759 will prevent MS is going to require doing that experiment right, 0:34:14.880 --> 0:34:18.879 But I think the chances of that preventing MS are low. 0:34:19.920 --> 0:34:23.200 It may be that a subset of MS is EBV 0:34:23.560 --> 0:34:26.880 driven in some way, or is it really does require 0:34:27.280 --> 0:34:34.640 continued EBV infection, And again, whether it's related to how 0:34:34.800 --> 0:34:38.560 strongly you're able to prevent autoreactive T cells and B 0:34:38.680 --> 0:34:43.200 cells from developing versus how well you keep your EBV 0:34:43.320 --> 0:34:47.360 in check. That's something that the field is really deeply 0:34:47.400 --> 0:34:50.560 interested in figuring out over the next five to ten years. 0:34:51.400 --> 0:34:55.680 So besides this MS research that's been in the news lately, 0:34:56.000 --> 0:34:59.480 EBV has also, I feel like, made headlines for its 0:34:59.520 --> 0:35:03.640 potential involvement in long COVID. What do you think about that, 0:35:04.000 --> 0:35:07.360 what research has been done on that, and do you 0:35:07.360 --> 0:35:09.320 think that it's a plausible link. 0:35:10.480 --> 0:35:14.280 I think that the link between EBV and long COVID 0:35:14.880 --> 0:35:19.480 likely has to do with this idea that EBV infection 0:35:20.120 --> 0:35:23.520 latent infection in B cells is sort of a barometer 0:35:23.880 --> 0:35:27.879 of your humoral immune system, and so when things are. 0:35:27.760 --> 0:35:33.440 A little off balance, either because you've got coinfection and 0:35:33.920 --> 0:35:37.560 huge amount of cytokine is being released either systemically or 0:35:38.520 --> 0:35:44.440 locally in some lymphoid tissue, that this can trigger EBV reactoration, 0:35:45.000 --> 0:35:49.480 and depending on how well the patient is doing in 0:35:49.560 --> 0:35:53.960 terms of maintaining their EBV specific T cell responses in 0:35:54.000 --> 0:35:59.320 EBV immunity, that can essentially be a mono like situation 0:35:59.680 --> 0:36:06.480 or in any event, can cause a lympho proliferation and ultimately, 0:36:06.719 --> 0:36:11.160 you know, some disease associated with that that could overlap 0:36:11.239 --> 0:36:13.239 with some of the long COVID symptoms. So I think 0:36:13.360 --> 0:36:17.719 fatigue being the major one that has been linked when 0:36:18.280 --> 0:36:21.719 EBV DNA is detected in the blood. That indicates that 0:36:21.800 --> 0:36:27.160 there's really a significant imbalance in these EBV infected B cells. 0:36:27.600 --> 0:36:32.920 And so whether that is again simply a barometer of 0:36:33.120 --> 0:36:39.520 the underlying immune health of that individual, or is contributing 0:36:39.560 --> 0:36:42.720 to some of the symptoms like fatigue in long COVID, 0:36:43.200 --> 0:36:45.600 I think just warrants further study. 0:36:46.800 --> 0:36:49.440 So I want to end the part one of this 0:36:49.520 --> 0:36:54.000 interview with a question that is very general and hopefully 0:36:54.120 --> 0:36:57.920 very fun. Do you have a piece of favorite trivia 0:36:58.120 --> 0:37:00.920 for either EBV or justviruses in general? 0:37:01.800 --> 0:37:08.040 Yes, okay. EBV was discovered in nineteen sixty three to 0:37:08.160 --> 0:37:11.719 nineteen sixty four by Anthony Epstein, who was an assistant 0:37:11.719 --> 0:37:15.480 professor in the UK and his graduate student, yvon bar 0:37:16.440 --> 0:37:19.800 and he had seen a talk in sixty three from 0:37:20.360 --> 0:37:25.080 Dennis Burkett, who was an Irish missionary surgeon working in Uganda, 0:37:25.400 --> 0:37:30.239 who had characterized this large draw tumor that is the 0:37:30.280 --> 0:37:34.480 most prevalent pediatric tumor in subsern Africa. And at the 0:37:34.560 --> 0:37:38.560 time we knew that other animals could be infected with 0:37:38.560 --> 0:37:41.359 certain viruses that caused cancer, but no human tumor virus 0:37:41.400 --> 0:37:46.040 had been discovered, and so Dennis Burkett presented this study 0:37:46.120 --> 0:37:50.439 where he mapped the epidemiology of this cancer. This burke 0:37:50.480 --> 0:37:56.200 at lymphoma across Africa and it was almost coincident with 0:37:56.239 --> 0:38:02.120 where malaria was holoandemic. Epstein was wrapped and was certain 0:38:02.520 --> 0:38:06.760 that there was a virus, probably transmitted by the mosquito 0:38:06.840 --> 0:38:11.360 that was also transmitting hilaria that would cause this lymphoma, 0:38:11.920 --> 0:38:16.040 and so they set up a collaboration where specimens from 0:38:16.120 --> 0:38:20.279 the lymphoma will be sent from Kampala to London, and 0:38:20.800 --> 0:38:26.440 over months and months of investigation, no virus was found. 0:38:27.000 --> 0:38:32.400 And so the twenty sixth biopsy was being flown to 0:38:32.800 --> 0:38:37.160 London and there was fog in the city and the 0:38:37.239 --> 0:38:42.880 flight was diverted to Manchester and the sample sat overnight 0:38:43.440 --> 0:38:46.799 and was brought to the lab and the liquid that 0:38:46.840 --> 0:38:51.680 it was in was cloudy, and so he thought, oh gosh, 0:38:51.880 --> 0:38:55.160 it must have been contaminated with bacteria. But let's take 0:38:55.200 --> 0:38:58.640 a look anyway, and when you look under the microscope 0:38:59.480 --> 0:39:01.920 he saw that the cloudy stuff wasn't bacteria, but it 0:39:01.960 --> 0:39:06.560 was cells and some cells had been had sloughed off 0:39:06.600 --> 0:39:08.719 of the tumor. And at the time, nobody knew how 0:39:08.719 --> 0:39:13.000 to grow lymphocytes, so there was no culture system for lymphocytes. 0:39:13.040 --> 0:39:17.319 But nevertheless, Yvonne bar tried a bunch of different conditions 0:39:17.600 --> 0:39:20.839 and was able to successfully grow the cells that had 0:39:20.880 --> 0:39:23.439 slept off from the tumor, and a couple of weeks 0:39:23.520 --> 0:39:26.560 later they had enough cells, and sure enough, in about 0:39:26.560 --> 0:39:30.320 one out of one hundred cells chalk full of herpes 0:39:30.400 --> 0:39:34.520 virus like particles. And that was it, that was the discovery. 0:39:34.719 --> 0:39:39.160 And he got up and went outside and walked around 0:39:39.200 --> 0:39:42.479 the building and came back and looked again, and sure enough, 0:39:42.880 --> 0:39:46.240 the cell cells are chock full of herpes virus like particles. 0:39:46.280 --> 0:39:49.360 So he was wrong about what kind of virus it 0:39:49.400 --> 0:39:52.640 would be. It wasn't transmitted by the mosquitos, but he 0:39:52.719 --> 0:39:56.200 was absolutely right that there was a virus in those cancers. 0:39:57.040 --> 0:40:00.600 That story of the discovery of the virus, as told 0:40:00.600 --> 0:40:03.440 by Anthony Epstein at the fiftieth anniversary of the discovery 0:40:03.760 --> 0:40:08.560 about eight years ago, is my favorite piece of virology trivia. 0:40:09.719 --> 0:40:12.560 That is such a fantastic story, and it must have 0:40:12.640 --> 0:40:15.560 been so cool to get to hear it directly told 0:40:15.640 --> 0:40:18.480 by the man himself. So we're going to take a 0:40:18.560 --> 0:40:21.040 quick break here, and then when we get back. I 0:40:21.080 --> 0:40:23.960 want to hear all about what virology as a career 0:40:24.080 --> 0:40:27.040 is like and any words of wisdom you may have 0:40:27.160 --> 0:40:48.160 for people who might just be starting out on this journey. 0:40:55.640 --> 0:41:00.000 Welcome back everyone, All right, so let's talk about virology 0:41:00.600 --> 0:41:03.680 as a career. What it's like to be a virologist. 0:41:04.160 --> 0:41:07.759 What got you interested in EBV? Did you know all 0:41:07.800 --> 0:41:10.200 along that you wanted to study viruses? 0:41:11.280 --> 0:41:13.560 I knew I wanted to study viruses, and I was 0:41:13.600 --> 0:41:17.279 always interested in studying viruses that caused cancer. So it 0:41:17.280 --> 0:41:24.520 turns out my dad's a virologist, which is maybe not 0:41:24.640 --> 0:41:28.040 the most common route that people get into the field, 0:41:28.120 --> 0:41:30.480 but in my case, when I was a kid, I 0:41:30.560 --> 0:41:33.640 used to go to American Society for Virology meetings on 0:41:33.719 --> 0:41:37.680 college campuses in the summer and hang out and eat 0:41:37.719 --> 0:41:43.480 pizza and you know, meet graduate students and then meet virologists. 0:41:43.520 --> 0:41:46.040 And then as I got older, I would go as 0:41:46.040 --> 0:41:48.360 a high school student, and I started getting into the science. 0:41:48.440 --> 0:41:50.960 I was always a math and science nerd, and so 0:41:52.239 --> 0:41:55.839 I really became interested in biology and started to ask 0:41:55.920 --> 0:41:59.200 questions at these meetings. And then late in my high 0:41:59.239 --> 0:42:04.800 school career had some experience in doing some microbiology research. 0:42:04.880 --> 0:42:08.080 And then when I started in college, knew I wanted 0:42:08.120 --> 0:42:11.359 to work on viruses, and so found the virology lab 0:42:11.400 --> 0:42:14.600 on campus, and actually it was a herpe simplex virus lab. 0:42:14.680 --> 0:42:20.480 So I started working with HSV from early on and 0:42:20.880 --> 0:42:24.960 how the virus inter cells and the glycoproteins that uses 0:42:25.080 --> 0:42:29.440 the receptors and this kind of thing. And so junior 0:42:29.480 --> 0:42:33.239 to senior year transition I worked at the CDC. I 0:42:33.280 --> 0:42:36.680 had an opportunity to do an internship there and worked 0:42:36.680 --> 0:42:39.920 in the herpes virus section with the chief named Phil Pellett. 0:42:40.080 --> 0:42:43.240 The lab was studying all different herpes viruses and around 0:42:43.239 --> 0:42:46.239 that time a new virus had been discovered called KSHB 0:42:46.440 --> 0:42:49.920 or capcy sarcoma associated herpes virus, and so they were 0:42:49.960 --> 0:42:52.880 really keen to just understand the basics, you know, like 0:42:52.960 --> 0:42:55.319 let's grow this virus and let's purify it, and let's 0:42:55.360 --> 0:42:57.400 figure out what proteins are in it and how it 0:42:57.480 --> 0:43:01.520 inter cells and all this basic stuff. And so I 0:43:01.560 --> 0:43:07.160 had a hugely impactful experience there, not just from the 0:43:07.200 --> 0:43:10.240 science and the kind of science we're doing, but Phil, 0:43:10.719 --> 0:43:13.800 after you know, we finished in the lab, would would 0:43:13.840 --> 0:43:16.640 stay and we'd chat about the future, you know, what 0:43:16.680 --> 0:43:19.120 I was going to do, and where I might be 0:43:19.160 --> 0:43:21.400 interested in going to graduate school, and what questions to 0:43:21.480 --> 0:43:25.040 work on, and really had an opportunity to think about 0:43:25.600 --> 0:43:30.759 that carefully, and so he suggested EBV. He said, this 0:43:30.840 --> 0:43:33.960 is if you want a big challenge and you want 0:43:34.280 --> 0:43:37.399 to understand viruses that can cause cancer, you should work 0:43:37.400 --> 0:43:40.040 on EBV. There number of labs in the country that 0:43:40.080 --> 0:43:43.120 were really exceptional in studying it. So I wrote to 0:43:43.160 --> 0:43:47.040 them and applied to graduate schools and ended up going 0:43:47.080 --> 0:43:49.000 to graduate school to work on EBV. 0:43:49.239 --> 0:43:54.080 Basically, so, as a professor, you have to do so 0:43:54.320 --> 0:43:57.560 many things like that that one word covers a lot 0:43:57.600 --> 0:44:00.279 of different you know, responsibilities you have to do each 0:44:00.360 --> 0:44:02.680 You have to write grants, you have to do the research, 0:44:02.680 --> 0:44:04.280 you have to manage a lab, you have to advise 0:44:04.320 --> 0:44:08.279 grad students and everything you know in between. Are there 0:44:08.280 --> 0:44:11.480 any parts of your job that you absolutely love or 0:44:11.920 --> 0:44:15.080 parts that you could easily give up and not look back. 0:44:16.280 --> 0:44:18.880 The part that I absolutely love is what got me 0:44:18.920 --> 0:44:22.480 into it from the beginning, and it's seeing new data 0:44:22.960 --> 0:44:27.600 and seeing new discoveries made that no one's ever seen before. Right, 0:44:27.840 --> 0:44:31.160 So that bug that sort of fire in the belly 0:44:31.280 --> 0:44:34.680 to be able to see this new discovery and want 0:44:34.719 --> 0:44:37.600 to ask the next questions and figure out the mechanism 0:44:37.680 --> 0:44:41.960 and just develop a project. That that's really what I love. 0:44:42.280 --> 0:44:46.400 And like you said, though, along the way, all of 0:44:46.440 --> 0:44:52.040 the other benefits features of being a professor, you know, 0:44:52.680 --> 0:44:56.200 come with you. And I have to say I, in 0:44:56.280 --> 0:44:59.600 my training, I did not have an opportunity to do 0:44:59.640 --> 0:45:03.360 as much mentoring as maybe others, and that is something 0:45:03.440 --> 0:45:06.880 that I do really love. I love doing that in 0:45:06.920 --> 0:45:09.880 the context of the lab, you know, so training graduate 0:45:09.920 --> 0:45:12.680 students or undergraduates that come in the law post docs, 0:45:12.719 --> 0:45:15.880 and also doing that the context of faculty mentoring, and 0:45:16.800 --> 0:45:20.000 you know, really helping junior faculty get get started and 0:45:20.040 --> 0:45:23.719 transition through tenure and all of those challenging spots in 0:45:23.760 --> 0:45:27.719 their career. And you know, teaching is something that I 0:45:28.160 --> 0:45:31.320 love when I'm doing it, but I don't love thinking 0:45:31.320 --> 0:45:34.320 about having to do it. I'm telling you about a 0:45:34.320 --> 0:45:37.800 lot of things I love. What do I hate about 0:45:37.800 --> 0:45:40.080 this job? I thought I've been thinking a little bit 0:45:40.080 --> 0:45:44.279 about that. I don't. I don't hate writing grants. I 0:45:44.280 --> 0:45:47.120 think I actually think writing grants are really useful as 0:45:47.120 --> 0:45:53.480 an exercise to uh distill your ideas into a digestible 0:45:53.840 --> 0:45:57.000 set of uh, you know, future experiments and you know, 0:45:57.040 --> 0:45:59.439 setting up rationale for why you're doing what you're doing. 0:46:00.040 --> 0:46:02.680 Don't like the process of you know, waiting and you 0:46:02.840 --> 0:46:05.680 having it reviewed and biting your nails and all that stuff. 0:46:05.719 --> 0:46:08.279 But I do like writing the grants because of what 0:46:08.320 --> 0:46:12.359 it does for the science. I don't love where things 0:46:12.360 --> 0:46:15.120 are right now with academic publishing. I think they could 0:46:15.160 --> 0:46:18.000 be improved in a number of ways. I think that 0:46:19.360 --> 0:46:21.680 one of the aspects that you know, a lot of 0:46:21.680 --> 0:46:24.080 folks talk about, and I agree with this, is that, 0:46:24.200 --> 0:46:28.960 you know, really linking our sort of productivity and our 0:46:29.960 --> 0:46:33.600 worth to the impact factor of the journal that we 0:46:33.640 --> 0:46:37.479 publish our papers in is not not appropriate. And how 0:46:37.520 --> 0:46:40.960 to get away from that when we evaluate faculty candidates 0:46:41.080 --> 0:46:43.719 or people coming up for ten year promotion or have 0:46:43.800 --> 0:46:47.160 you is tough, but I think we try our best 0:46:47.239 --> 0:46:50.760 to do that in terms of evaluating the actual impact 0:46:50.760 --> 0:46:52.759 of the work and the you know, the rigor of 0:46:52.760 --> 0:46:55.560 the science and the reproducibility of the science was often 0:46:55.600 --> 0:46:59.880 isn't something that that comes into play, despite how challenging 0:47:00.600 --> 0:47:02.880 that issue can be. So I think if there was 0:47:02.880 --> 0:47:05.600 one area that I don't love. It's kind of the 0:47:05.680 --> 0:47:09.960 space of navigating the publication system. 0:47:11.239 --> 0:47:14.239 So on the alumni section of your lab website, I 0:47:14.280 --> 0:47:17.040 see that you've graduated students that have gone into very 0:47:17.080 --> 0:47:21.800 different careers, from government positions to industry, to medicine and others. 0:47:22.280 --> 0:47:26.080 So besides academia, what other careers do you think that 0:47:26.160 --> 0:47:30.120 a master's of science or a PhD in microbiology would 0:47:30.200 --> 0:47:31.120 set you up for? 0:47:32.280 --> 0:47:35.880 Yeah? Absolutely, I think a lot of different careers. I 0:47:35.920 --> 0:47:41.640 think that we train critical thinkers, we train effective communicators, 0:47:42.200 --> 0:47:47.560 We train folks to solve difficult problems by working in 0:47:47.640 --> 0:47:52.600 and valuing diverse perspectives on teams that will get you there. 0:47:52.840 --> 0:47:57.440 And that skill set describes as you can imagine a 0:47:57.440 --> 0:48:00.879 lot of different industries, right, so obviously or learning how 0:48:00.880 --> 0:48:03.640 to do that in the context of pipetting and whatnot. 0:48:04.239 --> 0:48:08.960 So doing that in science in industry, you know, is 0:48:09.000 --> 0:48:12.120 the most logical place to go next from the point 0:48:12.160 --> 0:48:15.000 of view of if you love the science right aspect 0:48:15.080 --> 0:48:18.160 of it, if you love the communications aspect of it, 0:48:18.320 --> 0:48:21.640 or if you love the entrepreneurship aspects of it, then 0:48:21.640 --> 0:48:23.759 there are sort of slightly different paths that you can take. 0:48:23.840 --> 0:48:26.480 So I mean the industry now. You know, it's interesting 0:48:26.520 --> 0:48:28.840 when I think back to even my time as a 0:48:28.840 --> 0:48:34.160 post doc, the opportunities in industry were relatively limited to 0:48:34.280 --> 0:48:40.040 sort of big pharma or basically big biotech or startups, 0:48:40.040 --> 0:48:43.520 but you know, the relative risk there was still pretty high. 0:48:43.920 --> 0:48:49.239 And that array of opportunities to be a PhD or 0:48:49.320 --> 0:48:55.720 master's level scientist in biomedical research in industry is now 0:48:55.840 --> 0:49:01.719 incredibly diverse. And it's not restricted only to Boston and 0:49:01.760 --> 0:49:05.759 the Bay Area OURTP where we are here obviously, you know, 0:49:05.920 --> 0:49:09.400 is full of companies developing all through that spectrum. So 0:49:09.760 --> 0:49:13.120 I think a lot of folks are really excited about 0:49:13.160 --> 0:49:16.319 moving into industry where they can sort of see the 0:49:16.400 --> 0:49:19.520 kinds of basic discovery type work we do here translated 0:49:19.560 --> 0:49:23.560 into drugs or therapies in some way, and when you're there, 0:49:23.600 --> 0:49:27.919 you have an opportunity to really expand and explore other 0:49:28.000 --> 0:49:31.719 aspects of that process. Right, So, whether it be liaising 0:49:31.760 --> 0:49:34.600 with clinicians as a medical science lise on, whether it 0:49:34.680 --> 0:49:38.840 be developing writing nbas and doing really more science communication, 0:49:39.200 --> 0:49:42.480 or having an opportunity to shift and do more business 0:49:42.480 --> 0:49:45.360 development and entrepreneurship, you know, there are a lot of 0:49:46.400 --> 0:49:49.440 opportunities just in you know what now is kind of 0:49:49.440 --> 0:49:53.319 biotech and pharma that really broad industry. And then, like 0:49:53.360 --> 0:49:55.200 you said, some of the folks from my lab have 0:49:55.280 --> 0:49:59.120 gone on to policy fellowships and really working to impact 0:49:59.239 --> 0:50:01.919 the way that our government and you know, at any 0:50:02.000 --> 0:50:04.879 level really thinks about and communicate science. And I think 0:50:04.920 --> 0:50:08.960 that's obviously very much needed these days. And you know, 0:50:09.040 --> 0:50:12.640 I think there are certainly still other areas that you're 0:50:12.680 --> 0:50:17.960 competitive for consulting or patent law or what have you. So, 0:50:18.120 --> 0:50:21.960 so really a wide range of you know, of opportunities 0:50:22.120 --> 0:50:24.800 in what you can do with their master's or a PhD, 0:50:24.960 --> 0:50:30.200 and the sort of resilience and you know, other things 0:50:30.239 --> 0:50:33.920 that come from doing your PhD really set you up 0:50:34.000 --> 0:50:37.000 nicely for any of those kinds of careers. 0:50:37.719 --> 0:50:41.120 What advice would you give someone who is interested in 0:50:41.120 --> 0:50:44.840 biology broadly but isn't sure exactly what they want to 0:50:44.880 --> 0:50:47.520 do or what's available to them, And what do you 0:50:47.520 --> 0:50:50.760 think are the most important factors to consider when thinking 0:50:50.800 --> 0:50:54.280 about the career that you want to have whatever relates 0:50:54.320 --> 0:50:55.359 to in biology. 0:50:56.440 --> 0:50:59.560 Yeah, so I think even starting to think about this 0:51:00.120 --> 0:51:03.720 at an early age, you know, high school or even before, 0:51:04.239 --> 0:51:06.880 I would say seek out a mentor seek out someone 0:51:07.040 --> 0:51:11.440 that you can talk to about science, about being a scientist. 0:51:11.480 --> 0:51:15.040 There are a lot of especially in the COVID era, 0:51:15.520 --> 0:51:18.640 a lot of societies like ASB and ASM have been 0:51:18.640 --> 0:51:24.240 doing really like open webinars and podcasts and communication events 0:51:24.560 --> 0:51:28.080 to encourage young people that are interested in biology and 0:51:28.120 --> 0:51:30.839 interested in science to come not just learn about what 0:51:31.000 --> 0:51:33.000 science we do in the lab every day, but like 0:51:33.040 --> 0:51:35.759 what you know, what the field really is like and 0:51:35.800 --> 0:51:37.879 what the path is going to look like, right, because 0:51:37.880 --> 0:51:40.160 I think a lot of folks don't know what for example, 0:51:40.160 --> 0:51:43.400 graduate school is like you know from high school or 0:51:43.400 --> 0:51:46.080 even college. It's like some people think it's just the 0:51:46.080 --> 0:51:50.080 alternative to medical school or something, whereas you know, what 0:51:50.640 --> 0:51:53.600 I would suggest is that if you can find a scientist, 0:51:54.160 --> 0:51:57.560 try to find an opportunity to do research in some way. 0:51:57.960 --> 0:52:01.880 They're more and more even virtual options for this because 0:52:01.920 --> 0:52:05.120 of what's happened with the pandemic, where where you can 0:52:05.160 --> 0:52:07.520 engage with the scientists in the lab and maybe do 0:52:07.560 --> 0:52:10.880 a computational project or just reading and learning about a topic. 0:52:10.960 --> 0:52:14.759 And ultimately I think what you want to try to 0:52:14.800 --> 0:52:18.880 get to is to be involved in doing an experiment 0:52:19.480 --> 0:52:24.920 and seeing the discovery. If that bites you, if you 0:52:25.040 --> 0:52:27.400 see something no one's ever seen before, whether you did 0:52:27.440 --> 0:52:29.600 it with your own hands or you're working with a 0:52:29.640 --> 0:52:31.880 graduate student or somebody you know in the lab and 0:52:31.920 --> 0:52:35.560 you see something, and if that bites you and you realize, oh, 0:52:36.480 --> 0:52:39.600 I could do this and see things nobody's ever seen 0:52:39.640 --> 0:52:44.160 before and really develop that and come up with new 0:52:44.200 --> 0:52:47.840 experiments to test new hypotheses. You know, that is when 0:52:47.880 --> 0:52:51.120 you know that being a scientist might be for you. 0:52:52.239 --> 0:52:54.600 So you talked about one way that you wish academia 0:52:54.680 --> 0:52:58.279 could be better, right in the context of publishing and 0:52:58.320 --> 0:53:01.319 the way that we evaluate certain candidates or the way 0:53:01.320 --> 0:53:06.160 that people maybe evaluate their own self worth in academia. 0:53:06.400 --> 0:53:08.480 What would you say about grad school? What are the 0:53:08.480 --> 0:53:12.440 ways that in general graduate school in biology or microbiology 0:53:12.920 --> 0:53:14.000 could do better. 0:53:15.040 --> 0:53:19.040 Graduate school is changing a lot in front of our eyes. 0:53:19.400 --> 0:53:24.160 And when I got to do about fifteen years ago, 0:53:24.640 --> 0:53:30.560 most of the programs, I would say were relatively conservative 0:53:30.640 --> 0:53:33.359 and kind of old school and their approach, which was 0:53:34.320 --> 0:53:39.319 the mentality that students were workers that had to have 0:53:39.480 --> 0:53:45.240 pressure sort of applied to have them perform and produce things. 0:53:45.280 --> 0:53:49.080 And that is for obvious reasons. The kind of thing 0:53:49.120 --> 0:53:54.239 that leads to really significant burnout and mental health challenges 0:53:54.280 --> 0:53:58.520 that certainly still exist in graduate education today. But I 0:53:58.520 --> 0:54:01.440 think what I'll say is we're we're a number of 0:54:01.440 --> 0:54:03.560 things have happened over the years, at least here at Duke, 0:54:03.600 --> 0:54:08.600 where we've recognized a lot of how we were training 0:54:09.000 --> 0:54:13.440 students and basically blind spots and what we were missing, 0:54:13.960 --> 0:54:16.840 especially in terms of what we were just talking about before, 0:54:16.840 --> 0:54:18.680 which is where are you going to go? Right? Are 0:54:18.719 --> 0:54:20.400 you going to go into academia? Are you going to go, 0:54:21.160 --> 0:54:22.960 you know, into industry, You're going to be a scientist, 0:54:22.960 --> 0:54:25.399 You're going to have a different career path. And when 0:54:25.440 --> 0:54:28.800 you simply look at the numbers, you see that about 0:54:28.800 --> 0:54:31.160 fifteen to twenty percent of our graduates wind up in 0:54:31.160 --> 0:54:36.680 academia and fifty percent are in industry. Right, So there 0:54:36.760 --> 0:54:39.080 was at the time, you know, would people would say 0:54:39.360 --> 0:54:44.520 alternative careers or something like that to academia, which is ridiculous, 0:54:44.600 --> 0:54:48.239 right with the majority of people are going into other careers. 0:54:48.520 --> 0:54:52.080 So it was that realization that happened maybe ten or 0:54:52.080 --> 0:54:55.040 so years ago here at the graduate school. A lot 0:54:55.040 --> 0:54:59.960 of effort was put into rethinking, reimagining graduate education around 0:55:00.000 --> 0:55:02.480 and you know, having a PhD, what what you need 0:55:02.560 --> 0:55:06.000 to be trained for in the biomedical research you know, 0:55:06.680 --> 0:55:11.919 workforce and and what are the skills that are most 0:55:11.960 --> 0:55:18.480 important broadly? And number one is problem solving, creative thinking, resilience, communication, 0:55:19.520 --> 0:55:23.000 to a broad audience, to an arrow audience, uh, writing, 0:55:23.920 --> 0:55:28.000 All of these things really are are the foundation being 0:55:28.040 --> 0:55:33.680 able to do this in an environment that is respectful, diverse, 0:55:34.400 --> 0:55:39.160 pro student. But you know, it's just a rethinking of 0:55:39.760 --> 0:55:41.960 uh you know, what the goals are and how and 0:55:42.000 --> 0:55:45.320 how you get there and I think you know, partnering 0:55:45.760 --> 0:55:49.160 with one another as you know, it's a mentor mentee relationship, 0:55:49.200 --> 0:55:52.640 but it's also one where we're colleagues, right, and seeing 0:55:52.680 --> 0:55:55.520 each other in that way and being respectful and and 0:55:55.800 --> 0:55:58.120 and challenging each other, right, I mean that is part 0:55:58.120 --> 0:56:00.560 of the process, but you know, seckful way. 0:56:01.640 --> 0:56:04.279 I have one last question for you, and that is 0:56:04.320 --> 0:56:07.320 to ask you what you hope this next year brings 0:56:07.400 --> 0:56:12.319 in terms of EBV research or other research or just 0:56:12.520 --> 0:56:16.479 general personal goals for you and or for your lab. 0:56:19.640 --> 0:56:24.880 So for the lab, I'm really excited about the area 0:56:24.920 --> 0:56:27.400 of science that we've been in for a couple of 0:56:27.440 --> 0:56:31.880 years now, which is I would generally call a heterogene 0:56:32.120 --> 0:56:37.160 heterogeneity of infection. So if you infect cells, they don't 0:56:37.200 --> 0:56:41.560 all behave the same way, So we generally lump things 0:56:41.560 --> 0:56:46.000 together sometimes and say infected and uninfected, or you know 0:56:46.040 --> 0:56:49.200 that kind of thing. And I've always been really interested 0:56:49.239 --> 0:56:53.919 in temporal dynamics, like how things change over time after infections, 0:56:54.280 --> 0:56:57.080 but also what's the difference between cell A and cell 0:56:57.160 --> 0:56:59.600 B And if you infect a million cells, are they 0:56:59.640 --> 0:57:02.440 all bonding the same way? The answer, the short answer 0:57:02.480 --> 0:57:06.040 is no, not at all. And so we've been using 0:57:06.960 --> 0:57:11.840 technology called single cell RNA sequencing as one method to 0:57:11.880 --> 0:57:14.359 be able to see those differences, whether it be during 0:57:14.400 --> 0:57:17.440 latency or liticcary activation of the virus, or different tumor 0:57:17.480 --> 0:57:21.680 cell lines and different settings. And we've we've published a 0:57:21.720 --> 0:57:24.360 paper on this already and have a couple more coming 0:57:24.400 --> 0:57:27.680 out this year that are really telling us just about 0:57:27.720 --> 0:57:31.080 how different the outcomes of viral infection can be at 0:57:31.080 --> 0:57:33.880 the single cell level and what that might mean then 0:57:34.200 --> 0:57:42.120 for disease, for latency, establishment, for therapeutic approaches, and and 0:57:42.240 --> 0:57:44.960 you know, I think is uh, it's really an exciting 0:57:45.040 --> 0:57:48.680 time to be studying UBV. As you know, the first 0:57:49.640 --> 0:57:54.000 doses of the moderna EVV vaccine have have gone into arms, 0:57:54.040 --> 0:57:58.200 and so everybody's excited to see how how that does 0:57:58.280 --> 0:58:05.520 in terms of impact mono and also EBV replication and development. 0:58:25.080 --> 0:58:28.920 Thank you so much, doctor Leftig. That was such a 0:58:28.920 --> 0:58:33.080 fascinating interview and I definitely gained a lot more respect 0:58:33.160 --> 0:58:35.720 and awe for this virus and what it can do. 0:58:36.480 --> 0:58:38.600 If you would like to learn more about the super 0:58:38.600 --> 0:58:41.240 cool work that doctor Leftig and his lab is doing, 0:58:41.600 --> 0:58:43.840 I will post a link to his lab website on 0:58:43.840 --> 0:58:47.640 our website This podcast will kill You dot com. Speaking 0:58:47.680 --> 0:58:51.120 of websites, our website is also where you can find 0:58:51.240 --> 0:58:54.440 all kinds of things like the sources for all of 0:58:54.440 --> 0:58:59.400 our episodes, transcripts, Quarantini and place Berta recipes, our bookshop, 0:58:59.440 --> 0:59:03.040 dot org account, links to music by Bloodmobile, links to 0:59:03.120 --> 0:59:07.680 merchant Patreon, and so much more. Thanks again to Bloodmobile 0:59:07.720 --> 0:59:10.560 for providing the music for this episode and all of 0:59:10.600 --> 0:59:13.920 our episodes, and thank you to you listeners. I hope 0:59:13.920 --> 0:59:17.959 you enjoyed this fora into EBV, and a special thank 0:59:17.960 --> 0:59:22.520 you to our wonderful, generous patrons. We appreciate you so much. 0:59:23.520 --> 0:59:26.560 We have got a brand new episode on a brand 0:59:26.560 --> 0:59:30.840 new topic coming out next week, so until then, keep 0:59:31.000 --> 0:59:45.440 washing those hands.