Macrophage Infection by HIV: Implications for Pathogenesis and Cure: Day One
DR. JOSEPH: Welcome to the Macrophage Infection of HIV Implications for Pathogenesis and Cure meeting, jointly organized by the National Institute of Mental Health and the Ragon Institute of MGH, MIT, and Harvard. This is the second meeting on this topic that Ragon Institute is involved in. The first was organized in January 2017 in Cambridge, Massachusetts. Ragon Institute has kindly agreed to partner with NIMH on this second meeting. Thank you all for joining today's meeting. My name is Jeymohan Joseph. I'm a branch chief at the Division of AIDS Research at NIMH. I'd like to spend a few minutes talking about the background goals and structure of the meeting.
Although CD4 T cells are the main targets of HIV infection, macrophages also become infected and resist the cytopathic effects of infection, contributing potentially to HIV reservoir persistence. Furthermore, they drive inflammation and can contribute to the development of comorbidities, including HIV-associated CNS dysfunction.
So this meeting will examine emerging data relating to macrophage interactions with the immune system during HIV infection, macrophage reservoirs and approaches to their elimination, and the involvement of CNS myeloid reservoirs and associated comorbidities. The meeting will also highlight recent work on macrophage inflammation in the context of SARS-CoV-2 infection and work from recently-funded NIMH, NIDA, and NINDS investigators. A panel will discuss research gaps and priorities related to human macrophage reservoirs and inflammation/comorbidities and treatment strategies for HIV remission and cure.
So on day one, Session 1 will focus on macrophages and the immune system during HIV and SARS-CoV-2 infection, Session 2 will focus on challenges to study HIV/SIV reservoirs, and Session 3 will really have the highlights from recent awardees of the NIMH/NINDS/NIDA Myeloid Reservoir RFA. This will be one of two sessions where recently-awarded grantees from the RFA will make brief presentations of their planned work.
So on Day 2, tomorrow, we'll have Session 4 looking at macrophage reservoirs and approaches to their elimination. Session 5, we'll have CNS comorbidities in the era of ART, and finally, the second of the NIMH myeloid reservoir RFA session, and finally, the closing session tomorrow where each of the moderators will provide a brief summary of their session with a focus on challenges, gaps, and future priorities. Dr Janice Clements and Mario Stevenson will lead this concluding session.
I really want to thank the meeting organizing committee who did a lot of work on this meeting, including Dr. Janice Clements from Johns Hopkins University, Mario Stevenson from University of Miami, and Kiera Clayton who played a major role in organizing from the University of Massachusetts Medical School.
So the Journal of Leukocyte Biology has -- is interested in publishing a cluster of articles from this -- proceedings of this meeting. They are applying to solo support review papers and original investigators, so they will reach out to you after the meeting in the timeline that's listed here, and as -- and they are offering a 50 percent discount on accepted articles. Mario Stevenson, Janice Clements, and Kiera Clayton will serve as guest editors for this special group of articles.
Some housekeeping notes. Participants will be muted in listen-only mode and cameras will be turned off. Please submit your questions via the Q&A box any time during the presentation. If you have technical difficulties hearing or viewing the webinar, please note this in the Q&A box and our technicians will work to fix the problem, and you can also send an email to the email listed here. And live speakers, please be reminded that your presentations not exceed 15 minutes in length except for the plenary talk.
So it's my pleasure now to introduce Dr. Dianne Rausch, director of the NIMH Division of AIDS Research, to provide some opening comments. Over to you, Dianne.
DR. RAUSCH: Thank you, Jeymohan, and good morning, everyone. So we at the NIMH Division of AIDS Research are very happy to be co-sponsoring this conference with the Ragon Institute, recognizing the importance of macrophages in HIV pathogenesis and cure efforts. From the beginning of this epidemic, NIMH has supported a rigorous and integrated research agenda to understand the mechanisms involved in the pathophysiology of HIV-induced CNS dysfunction and the establishment and persistence of the HIV reservoir in CNS.
The study of the role of macrophages in both HIV neuropathogenesis and cure research continues to be a high priority area for our division since microglial and perivascular macrophages are important sites of HIV persistence in the CNS. The Division has issued several RFAs over the years in this area, and the most recent one, as Jeymohan mentioned, is the role of myeloid cells and persistence in the eradication of HIV reservoirs from the brain. And it received a robust response of creative approaches to better understand the myeloid-derived cells harboring virus as well as gene editing strategies to eradicate or silence these reservoirs. And as Jeymohan said, we'll hear the highlights of some of the planned work from the funded applicants during this meeting. We've also partnered over the years with the NIAID-sponsored Martin Delaney Collaboratories with co-funding to grants that had components that target these reservoirs.
It's really great to see so much interest in this area reflected by the more than 500 individuals registered for the meeting. Thank you all for joining today. I would also like to thank the Ragon Institute, particularly Drs. Bruce Walker and Kiera Clayton, for partnering NIMH on the second meeting related to the role of macrophages in HIV pathogenesis and cure.
So I would like -- now like to turn it over to Dr. Maureen Goodenow, the director of the NIH Office of AIDS Research, to provide additional comments. Dr Goodenow has been a strong supporter of this research, agenda and it's great to see you. Thank you.
DR. GOODENOW: Good morning, and thank you, Dianne, for that introduction. I'd like to thank the meeting organizers for the opportunity to talk about the OAR, the NIH HIV research priorities with a focus on cure, and how macrophages contribute to pathogenesis persistence and present obstacles for cure and vaccine development.
The Office of AIDS Research is located within the Office of the NIH Director. The vision is to advance research to end the HIV pandemic and improve health outcomes for people with HIV. The OAR mission is to ensure that NIH HIV research funding, about $3.1 billion annually, is directed at the highest priority research areas, and to facilitate maximum return on the investment. NIH HIV research funds are allocated through the OAR for distribution to the many NIH institute centers and offices with HIV research portfolios. This ensures that the NIH's HIV research portfolio is multidisciplinary, includes input from many perspectives, and leads to a robust program that has been incredibly successful over the past 30 years.
The NIH strategic plan for HIV and HIV-related research, developed by the OAR with input from a broad array of stakeholders and subject matter experts, is the major framework for the NIH HIV research agenda. The research priorities guide OAR decision-making processes related to HIV funding and are based on current data about the HIV pandemic and the science needed to reach the goals to prevent new HIV infections, develop next-generation therapies to treat and improve the health outcomes among persons with HIV, and ultimately cure HIV infection. The priorities are linked by cross-cutting research in the basic sciences, behavioral and social sciences, health disparities, implementation, training, and capacity building.
A major priority of the NIH HIV Research Program is fostering basic sciences, including lentivirology, human immunology, and cell biology, to discover fundamental knowledge that will facilitate advances in prevention, treatment, and cure of HIV. The overarching research is to understand the mechanisms of virus host cell interactions that will lead to extended viral suppression and ultimately viral elimination. Due to their long lifespan and ability to reside in virtually every tissue, macrophages are cellular candidates for a critical role in the establishment and persistence of HIV reservoirs.
Lentiviruses in general are macrophage tropic and established latent infections, with macrophages serving as viral reservoirs. A role for macrophages in HIV pathogenesis is consistent with HIV as a lentivirus. macrophages have the ability to migrate to different tissues where they can serve as reservoirs, for example, as Jeymohan mentioned, the well-studied ability to access the central nervous system that can lead to cognitive impairments and/or viral rebound. Another aspect in macrophages that supports their role as reservoirs is their resistance to the cytopathic effects of lentiviruses. monocytes and macrophages are undoubtedly challenging to study. They're heterogeneous in phenotype and pleiotropic in function. monocytes circulate in the peripheral blood and can differentiate into macrophages in vivo and ex vivo.
There's much work ahead to understand the role of macrophages and achieving HIV cure. Research is essential to discover how macrophage reservoirs contribute to HIV persistence, the factors that drive HIV macrophage tropism. What environmental cues are needed to render macrophages susceptible to viral infection and persistence. What are the interactions between monocytes, macrophages, and other arms of the immune system, and what are the critical functions for monocytes, macrophages, and dendritic cells in vaccine responses as well as long-term viral suppression.
HIV research in the area of macrophages in the extramural portfolio at NIH includes a focus on virus in the central nervous system. The upper graph in this slide shows the number of active projects or grants from fiscal year 2017 through 2021, which shows an increase during that period of about 30 percent in the number of projects. The lower graph shows the dollar amount in millions for each of those years. The total dollar amount over the five-year period is approximately $142 million, an increase of a little more than 40 percent.
Compared with basic HIV research in lymphocytes, however, for fiscal year 2021, the HIV macrophage investment of about $34 million represents about 13 percent of the NIH investment for HIV research about lymphocytes, and the number of macrophage projects is about 16 percent of the lymphocyte projects. There's clearly much to do, and this symposium is a key step in developing the next stages of research in macrophages. I'm very interested in hearing the comments and the -- and the presentations during the symposium and look forward to continuing the conversation. Thank you so much.
And now it's a pleasure to introduce the next speaker, Dr. Bruce Walker, who's the director of the Ragon Institute at Massachusetts General Hospital, MIT, and Harvard. Over to you, Bruce.
DR. WALKER: Thanks very much, Maureen, and it's really a pleasure to welcome you all and a pleasure to be partnering with the NIH in supporting this meeting, which builds off of a similar meeting in 2017. At that time, Kiera Clayton was a postdoc in my lab and was taking us in a new direction, trying to look at the role of macrophages in CTL-mediated killing, and we were sort of questioning how we would get ourselves up to speed in a new field. I suggested, well, maybe we should invite a couple of people to come and do a little mini-symposium, and Kiera took that idea and really ran with it. And out of that came a meeting with 20 leading experts in the field, a two-day workshop that was really quite successful. She recruited co-organizers, Janice Clements and Victor Garcia, and connected with Dr. Joseph at the -- at the NIH.
And the meeting was really marked by copious discussion, presentation of unpublished data. I think it helped Kiera a lot in her subsequent studies and certainly it helped me. She went on to show CTL -- macrophage-mediated resistance to CTL-mediated killing, and also, with the co-organizers, she published a summary of those -- of those proceedings of the meeting. And now five years later, Kiera again is the driving force with the co-organizers, Drs. Joseph -- Drs. Joseph, Clements, and Stevenson this time. And they've brought together really a terrific lineup of speakers to focus on critical issues related to the role of macrophages in HIV infection and, in fact, with some spillover to SARS-CoV-2 infection.
So this meeting will cover macrophages as targets for HIV infection, macrophages as mediators of inflammation, macrophages as a source of viral persistence, and also address some of the issues related to just how difficult it is to study these cells with a focus on new approaches in animal models to try and get at the -- at the underlying role of these cells in pathogenesis.
The goal of the meeting really is to catalyze discussion, catalyze critical research, and to help create a community among those of us that are interested in this particular cell, so I want to thank the NIH again for partnering with us on this meeting. I want to particularly thank Terry and Susan Reagan, who, through their philanthropy, have given us the flexibility to be able to do things like co-supporting a meeting that we feel is really critical to the field. And finally, I want to thank Kiera for the wonderful person she is, the terrific scientist she is, and the -- and the indefatigable source of energy she is for (AUDIO GLITCH).
DR. CLAYTON: Thank you for that introduction, Bruce, and for your comments. It's much appreciated. So I'm going to go ahead and introduce our plenary speaker, Fil Swirski, who was actually the plenary speaker that we had during the first macrophage meeting, and we just loved him so much that we invited him back again. So Dr. Swirski is the Arthur and Janet C. Ross Professor of Medicine, specifically cardiology, as well as a professor of diagnostic, molecular, and interventional radiology at Icahn School of Medicine at Mount Sinai in New York, and he's also the director of the Cardiovascular Research Institute. He's really a leader in the field in terms of innate immunity and inflammation in the context of disease and, specifically, cardiovascular disease.
He obtained his Ph.D. at McMaster University in Hamilton in Canada. He completed his postdoctoral studies at Brigham Women's Hospital in Boston. And he kind of stayed around the Boston area for a little bit as a professor of medicine at Harvard Medical School and was a principal investigator at Massachusetts General Hospital before recently joining Mount Sinai in -- earlier this year. And like I mentioned, he was one of our plenary speakers for the first macrophage symposium and really gave, you know, an interesting perspective on the autogeny of macrophages and how that relates to disease. And so today he's going to be talking about myeloid cells as inner system communicators.
DR. SWIRSKI: Thank you very much. Good morning, everyone. This is a very exciting and very important topic. Thank you, Kiera, for that introduction. It's a pleasure to be back here.
So when Kira invited me to give this plenary talk, she asked me to really provide an overview of macrophages, and that is what I really intend on doing here for the next 30 minutes. What I would like to do here as the first speaker of this exciting symposium is to introduce the cell from a historical perspective, touching on some of the major insights that we've -- that have arisen over the last 15 or so years in terms of our understanding of macrophage ontogeny as well as macrophage function.
Just to make sure that you're seeing the right screen, are you seeing my title screen here where you see the title?
SPEAKER: Yes, we are.
DR. SWIRSKI: Okay. Perfect. So we are off to a good start. All right. So let me start by showing this slide here. So we're going to go back 100 years, and we're going to make our way back to the present day.
This is a picture, probably the very first picture done with microscopy, with staining that shows us the very now-familiar morphology of monocytes. This was published in 1908, and the picture was shown in this review in Immunity. And, in fact, Simon Yona, who is the third -- the senior author on this review, went back to the original manuscript, I believe in Heidelberg, you know, found this manuscript. It was some challenge because Simon doesn't speak German and all these studies were in German, but found this image, and this is from Paul Ehrlich. And if you just look at the morphology of these cells, certainly we see our familiar lymphocytes here, but then if we look here, number two and using different stainings, what we see is very much the monocyte that we have come to know and love, and as well as other cells, of course, and very characteristic neutrophils for polymorphonuclear cells that we also know and is the subject of much investigation today.
And so this was 1908, and it was actually the year when Paul Ehrlich was awarded the Nobel Prize with Ilya Metchnikoff for their discovery in the immune system, Paul Ehrlich, of course, contributing abundantly being a German physician scientist and with many discoveries. Ilya Metchnikoff was a Russian pathologist, and he is credited to be the discoverer of phagocytosis. And really in sort of the macrophage field, we really -- the moment of birth, so to speak is 1908. It is the demonstration of phagocytosis by Ilya Metchnikoff, and since that discovery, of course, we've learned an incredible amount.
And so I'd like to just sort of put a little bit of a perspective here. I'm not a great fan of these kinds of slides because they inevitably omit more than they show, but just -- I just want to make one point here. So here we have the Nobel Prize for Medicine for the discovery of phagocytosis, and essentially, exact -- almost exactly a year later, we have the Nobel Prize here of Ralph Steinman, Bruce Buckland, Jules Hoffman, for the antigen presentation, pattern recognition receptors.
And so what has really happened is that the first 60 or so, 70 years of the 20th century, some of these individuals here really have contributed to our understanding of macrophage biology, focusing on macrophage activation, and I'll touch on some of these discoveries. And then in the 70s, what we had was Ralph Steinman's discovery of the dendritic cell which, of course, led to really a revolution in our understanding of adaptive immunity, and Bruce Butler and Jules Hoffman were key people who have contributed to our understanding of pattern recognition receptors.
But really, I think the place where I wanted to start and sort of begin looking at the history of macrophage ontogeny and function in a little bit more detail starts with this manuscript. So this is 1968. Zanvil Cohn, who you saw on the previous slide, is a senior author at Rockefeller University, and this is really one of the founding -- the key papers that in many ways has codified and imprinted in our consciousness our understanding of the monocyte/macrophage lineage that would dominate the field until very recently. So this was the first really serious attempt using tracing methods available at the time, radioactive tracing methods, to really get a handle on the life cycle of monocytes.
And the key sentence -- I think the final sentence of this manuscript, just on the bottom here, "On the basis of these studies, life history of mouse mononuclear phagocytes was formulated to be pro-monocytes in the bone marrow, giving rise to monocytes in peripheral blood, giving rise to macrophages in the tissue." So the idea here was that, first, the recognition that the bone marrow is the place where monocytes are born from pro-monocytes. This is, of course, at a time when we knew very little of the hematopoietic tree that was really a major discovery from Irv Weisman. These gave rise to monocytes which are circulating cells that repopulate macrophages in the various tissues, and this was really a dominant understanding.
And if we just go back all the way to 2005, this is a very famous review from Nature Reviews Immunology from Phillip Taylor and Simon Gordon. Simon Gordon was also on that slide, who was -- who contributed this idea of alternative macrophage activation and, of course, demonstrated F480 as a marker for macrophages. In this review, you can appreciate there's a sense that there is some precursor in the yolk sac that gives rise to primitive macrophages. The fetal liver is a place where monocytes are produced and can give rise to macrophages, and this is before, of course, the establishment of definitive hematopoiesis which occurs in the bone marrow. And this is 2005, so it's really shortly after the identification of monocyte subsets in the mouse blood, which was in 2003 with Frederic Geissmann and several years after identification of monocyte subsets in the human.
And the reason that it was important that -- the reason that monocytes subsets, their identification, was important was that prior to this, the idea was that monocytes are a homogeneous population that circulate and give rise to macrophages. Once we knew that there were different monocyte subsets that could be tracked with -- because of their various expression of surface receptors, that sort of gave the idea, or that led to the idea, that perhaps different subsets may lead to different types of cells in the tissue. And so you see this arrow here suggesting that monocytes are giving rise to macrophages, and it's pretty agnostic as to what cells and what a particular subset may give rise. But the arrow is here nevertheless despite really very little evidence that this may be the case.
Another figure which delved -- dove a little bit more deeply into this relationship between the two monocyte subsets is shown here. And so -- and here we get some arrows that are not quite filled out yet, and one of the questions at the time, so notice this is only 2005 -- it's not that long ago -- was whether one subset gives rise to another or converts. We now know that this is the case. There was a sense that monocytes, upon infiltrating inflamed tissue, can give rise to a macrophage, but still very little sense whether there are monocytes -- specific monocytes that can replenish tissue-resident dendritic cells or tissue-resident macrophages. And here we have splenic macrophages, Kupffer cells, microglia, and so on. This was still unclear.
Now this was also a time when -- as people were thinking about ontogeny of cells downstream of the monocyte, there was really abundant work that was done trying to understand processes that were upstream. One specific meeting that occurred at Le Cre in the South of France that was organized by Frederic Geissmann here, and you may see some familiar faces including Ralph Steinman, was a meeting to really start digging into those ontogenetic relationships. This was shortly after the identification of specific progenitor cells that may give rise to monocytes. And, of course, Ralph Steinman being there, there was a major discussion as to whether there are specific progenitor cells that give rise to dendritic cells.
And, again, if you look at this review that was published in Science, Kristin Mueller, the immunology editor, was there at the time listening to all of us having this discussion. There was this idea that perhaps monocytes are giving rise to macrophages in some sort of agnostic and unclear relationship. And it was really very unclear at the time -- now this is 2010 -- what cells replenish and contribute to the pool of macrophages that was clearly present in just about every cell, every tissue, maybe with the exception of cartilage.
And so there was -- with all of this in place, there was a series of landmark papers that were published between 2010 and 2014 that really complicated matters or at least allowed that exploration of ontogeny to move forward. One of these studies is right here from Miriam Merad, who was at that meeting in Le Cre, Florent Ginhoux being a postdoc at the time, using fake mapping, revealing that microglia in the brain derive from primitive macrophages, and thus, do not -- they do not require monocytes for replenishment.
There was this study in 2011 from Judith Allen, which showed that in the peritoneum, macrophages can self-renew, can replenish. So in other words, macrophages have the capacity to replicate themselves. And this was a very important observation because it suggested that perhaps macrophages do not rely -- or do not need to rely on monocytes for their replenishment. There were studies that were published at the time. Here's one from Frederic Geissmann that started to identify various transcription factors that may explain this dual origin, on the one hand, macrophages that might derive from one monocytes versus macrophages that maybe independent of monocytes or even independent of stem cells. He contributed it to some of this literature by demonstrating that proliferation of macrophages in some tissues, in this case, in the -- in the vasculature, also was a dominant feature of the replenishment of cells, requiring -- where the recruitment of monocytes was less important. And so that led to thinking about whether we just have to completely revisit this idea that monocytes give rise to macrophages in all tissues as proposed in that 1968 Journal of Experimental Medicine paper from Zanvil Cohn.
And as it turned out, that was not exactly the case, and, of course, matters were made complicated by looking at the various tissues. And so this is a review from Judith Allen and Michael Siddiqui in 2014, already building on this idea that macrophages can self-renew, and then looking at the contribution of monocytes for macrophage replenishment in various tissue. And what became very clear, and this is summarized here, is that different tissues rely on monocytes to a different extent.
So on the one hand, what we have is the CNS, the microglia, which appeared to be monocyte independent, at least in the steady state and perhaps the -- under conditions of inflammation. Certainly under conditions when there's a breakdown of the blood-brain barrier, as in MS, there may be a contribution of monocytes to macrophage or microglial pool in the -- in the brain. But under steady state conditions, it was very clear from multiple studies that microglia are monocyte independent. They colonize the brain before the establishment of definitive hematopoiesis and can self-renew throughout life.
On the other end of the spectrum, there was other tissues, dermis, and intestine probably the most well studied in this case, which showed that throughout life there is constant replenishment of macrophages by monocytes. And so really, there's this continuum, and we can take our favorite organ and sort of get a sense of which cells -- how dependent a specific organ is on monocyte replenishment. And so this, of course, led to a series of studies looking carefully at the yolk sac, at the fetal liver, and at the contribution of the various types of macrophages -- primitive microphages, yolk sac-derived macrophages, fetal macrophages, and monocytes -- to the different tissues.
And, again, just like you saw in the previous slide, on the -- on the one extreme, what we have is microglia which appear to colonize the developing brain during embryogenesis and remain there in the adult. And on the other hand, we have tissues where there is a mixed contribution, where, within a given tissue at any point in time, you may find macrophages that are monocyte independent and macrophages that may be monocyte dependent. And, of course, the picture changes under conditions of inflammation and becomes very interesting upon inflammation resolution.
And so a concept that really arose out of these studies, which is in this review for Martin Guilliams and Florent Ginhoux is this idea that if you look at different tissues and study the contribution of the yolk sac, the fetal liver, or the bone marrow to the macrophage pool, you have on the one hand closed systems, and then you have open systems that are either slow or fast. So a closed system is just what it says. It's closed to monocytes. The brain is an area where you have yolk sac macrophages with really no contribution from bone marrow, monocytes that you see in the blue. In other places, yolk sac macrophages may be replaced by fetal monocytes, and -- but in none of these closed systems, monocytes, at least in the steady state, play any considerable role, whereas in other areas -- in other tissues, like the heart or the pancreas shown here, there is evidence that over time, over age, monocytes begin to contribute.
The best of this, again, is the gut where what we see is the disappearance of these cells in the -- in the aorta, for example. It is immediately after birth that we see recruitment of monocytes that establish themselves in the vessel wall and then persist and self-renew, and no longer depend on monocytes for replenishment. Again, this is under steady state conditions. Some of these specific functions are not -- are still under debate, but, in general, there is -- this model has stood -- withstood the test of time, and, you know, we're not talking much time here, so there is much to discover.
Now, what I want to talk about now is, now that we have this idea that macrophages are coming from different sources, they can establish themselves in tissue, I want to briefly touch on macrophage functions as a consequence of their ontogeny.
Now, there has been throughout this time -- during this time as discoveries were made on the origin of macrophages, one very enduring concept that has really prevailed was this idea of M1 and M2 macrophages. Now, this is a concept that aims to categorize macrophages into these two extremes or two types of cells, on the one hand, M1 being inflammatory, and on the other hand, M2 being anti-inflammatory, irreparative. This is a concept that was proposed by Charlie Mills and he was thinking about this. He wanted to see this. He thought that there was some similarity to TH1, TH2 when we're talking about T cells. And he named the macrophages M1 and M2 on the basis of how macrophages from BALB/c mice and BL/6 mice responded to LPS.
And concurrently, Simon Gordon introduced this concept of alternative macrophage -- of alternative macrophage polarization in response to IL-4, and it seems that it was this M1/M2 designation from Charlie Mills and Simon Gordon's idea of alternative activation that those ideas got fused, and this M1/M2 paradigm was born. And what I would like to -- you know, there's one thing that I would like as a take-home message from this talk is that we really abandoned this concept and really moved beyond it. And the reason is that, on the one hand, of course, M1/M2 is a simple idea to follow and people have suggested that it's not due to substance, but there is a continuum. But I would argue that it's a very limiting concept that really puts a cage on our understanding of macrophage complexity and is, in fact, an incorrect idea of thinking about macrophages.
So, for example, if one were to say, well, M1/M2 is just a way of simplifying macrophage function, but actually macrophages exist on this continuum as we have here, and this is the work of Joachim Schultze, you can say, well, maybe that's true. But then as you add additional ways of activating the cells, various types of acids, what -- various types of stimuli, what you clearly can appreciate is that there isn't a continuum as you have certain macrophages that really have orthogonal function to this duality. So there is no continuum. If anything, there is a network and macrophages respond in very different ways, and we need to be embracing that complexity and really abandon M1/M2 altogether.
Now, of course, that complexity gave rise to thoughts about how should we name macrophages. Should we name them according to ontogeny, should we name them according to function, and there have been a number of attempts that were made. Here is a review from -- again, from Martin Guilliams, Nature Reviews Immunology, that proposed that we should be naming macrophages on the basis of ontogeny, that what we should be really thinking about is this classification. Are these cells adult or embryonic in origin, and then where are they located, and what sort of markers they express.
Another way of thinking about macrophages as a part of a consensus paper is that we should actually think of macrophages on the basis of the stimuli that they encounter. If there is a macrophage that receives IL-3 or IL-10, they will acquire certain characteristics, and we should be -- we should be naming them accordingly. And so I think that these are good ways of distancing ourselves from M1/M2 and embracing that complexity, but, of course, not -- none of these are entirely satisfying, at least not to me. On the one hand, this can be over -- very burdensome. There are so many different ways of stimulating macrophages, but I think it's a good beginning.
What I would say is that when thinking about tissue-resident macrophages, what we really need to start thinking about is big sort of ways in which these cells can be altered and can be shaped. Clearly ontogeny is important. We know that ontogeny is important, you know. That nature versus nurture question really is a perpetual one and has been very important in our understanding of macrophage function. But we also know that that the local environment really shapes, really sculpts these cells, and it depends on what they see. This is how they will respond.
Time. Time is key to a macrophage identity. We already saw that there is these closed systems, open systems. We know that in the mouse it takes up to 12 weeks for the macrophage foot to establish itself. Aging is a very important area of work in terms of understanding macrophage dynamics, macrophage function. We know that during aging, there is a myeloid bias in the bone marrow, and we know that they're -- under condition -- during aging, macrophage contributions change in various organs. And, of course, inflammation is a major stimulus that changes macrophage identity conditions of inflammation. What we find, for example, is a disappearance of tissue-resident macrophages as monocytes become dominant, then under conditions of inflammatory resolution, under some cases, resident macrophages reestablish themselves in niches as monocytes are -- monocyte-derived macrophages are out competed. We think that inflammation plays a major role in the identity of the macrophage pool.
And then, of course, we can look at this event in a broader way and ask about the various stimuli that macrophage -- macrophages encounter in the various tissues they inhabit. And we know from work from multiple labs is that if you place a macrophage -- if you take a macrophage from one tissue and put it in another, they very quickly acquire many characteristics of their new tissue. And so we know that there are very specific stimuli that can contribute to that identity.
And finally, and I would -- I would say that this is something that is now becoming very prominent in this field in investigating macrophage function, is that beyond the heterogeneity of macrophages in different tissues, we are now talking about heterogeneity of macrophages within a single tissue. Macrophages that may be close to blood vessels, macrophages that may be close to nerves, macrophages that may reside in different regions of the brain, may acquire specific characteristics that are unique or required for their specific function.
And lastly, what I would say in the last two minutes of my talk is that we're now really moving beyond immunity. You know, there was this period of time in the 90s when dendritic cells, you know, were seen as these most interesting of immune cells or of myeloid cells by virtue of their capacity to present antigen in the lymph node, and in many ways, dendritic cells are very interesting cells. They can present antigen, but they can also cross-present antigen, and they're also essential to the acquisition of adaptive immunity. One the one hand -- that as dendritic cells on the one hand. On the other hand were macrophages which were known to be phagocytes which reside -- were known to reside in tissues and which were thought to do not much else.
And what we've been learning now as we've uncovered some of the complex oncogenic relationships and functional relationships is that, in addition to these processes, such as phagocytosis, macrophages really play essential roles in the physiology of the specific tissues that they inhabit. And so they are not just immune cells, but they are really cells capable of adapting to their environment and really communicating with the stromal cells that they inhabit there, and really helping that particular organ function.
And so we are now learning that macrophages in the heart can be important to electrical conduction. We are learning that in the brain, microglia promote neuronal pruning. We are learning that macrophages are key -- we've known it already, but we are learning further that macrophages are key for iron recycling. Of course antigen presentation, but vascular function and all sorts of functions that really wouldn't be classified as immune inflammatory functions. These are some of the studies, and there's many, many of these that are really beginning to examine this very interesting of cells.
So with that, I will finish. I hope that this has been at least somewhat interesting and will -- to introduce this cell here. And thank you for your attention.
DR. CLAYTON: Hi, Fil. That was a very beautiful talk. Thank you for giving us all an overview of macrophages as well. That was really nice. So the Q&A is open, so if anyone has any questions, I'm happy to read them off, and we'll start this discussion with Fil. I'm going to start with a couple here.
So first question is, "How are the microglial cells colonized in the brain when there is the blood-brain barrier to contend with? Can HIV-infected blood macrophages migrate to the brain causing brain infection?"
DR. SWIRSKI: That may be the case. You know, that brain -- the blood-brain barrier we know can be broken down under certain conditions. Of course, you know, when we look at various diseases of neurodegeneration and neuroinflammation, you know, there are conditions where the blood-brain barrier seems to be intact. So, you know, one example of this is Alzheimer's, you know. At least in mouse models of Alzheimer's, we see very little evidence for the recruitment of monocytes or circulating cells into the brain. On the other hand, in other neurodegenerative or inflammatory diseases, I mentioned multiple sclerosis, and I also think that AML is another example where there is clearly a destruction of that barrier and a breach of borders, so to speak. And what we think is that much of that breach of borders may be the consequence of immune cells in the periphery, T cells, as well as other lymphocytes that interact in some of these strategic regions in the brain, whether it's -- and there are a number of places, like the meninges and other places, where there is a significant population of T cells and B cells that may breach those barriers.
Now, in terms of development, of course, this is developing brain, and so these primitive macrophages have their sort of own path into colonization before the blood-brain barrier is fully established. But certainly in adulthood, under -- at least under some conditions of inflammation, it's clear that the blood-brain barrier may be compromised. And then sort of the last point here is, you know, some of the work on the brain and the -- and the immune system is that we are learning that the brain, you know, contains a glymphatic system, so there is certainly recirculation of material. And there -- we are learning that there are -- is bone marrow that, of course, produces monocytes that have -- and B cells and T cells that have direct contact to the brain through vascular channels. And so there are multiple routes that cells can migrate, and, of course, that is going to be an important question to solve, considering macrophages as reservoirs for HIV.
DR. CLAYTON: Okay. Excellent. Thank you for that. So another question: "Although challenging, has there been any direct evidence reported on the presence of myeloid progenitors in the human yolk sac?"
DR. SWIRSKI: Myeloid progenitors in the human yolk sac. I am not familiar with that literature, so I can't answer that with any intelligence on this.
DR. CLAYTON: Okay. Next question: "Could you please briefly talk about the lifespan of different sources of macrophages?"
DR. SWIRSKI: That's a very interesting question. And so, first of all, let's start with the monocyte. The monocyte in the human and in the mouse, through some very careful studies, has a lifespan of approximately 20 hours, so a half-life of approximately 20 hours. Now, when we look at what happens -- so after that 20 -- you know, once a monocyte circulates for a half-life of 20 hours, it can then either convert to a different type of monocyte that that lives a few more days, patrols the vasculature. It can die, it can return to the bone marrow, or it can infiltrate a specific tissue where it could possibly become a monocyte-derived macrophage. So that happens pretty quickly, and the bone marrow continuously produces these cells and produces it according to circadian fluctuation, according to the rhythm that we have as we sleep and are awake.
Now, when it comes to macrophages in the tissue, it seems -- so the best guess is that different tissues have a different macrophage lifespan. Microglia, for example, are thought to have a very long lifespan. You know, some of this work can be done using lineage tracing, using tagging of macrophages by different means. It is thought that they can live for several months before being replaced.
Now, the problem that arises is that if, in fact, all of macrophages and tissues like the brain self-renew through proliferation and do not rely on monocytes, and if they live for two, three, four months depending on the tissue -- some of the tissues they may live for shorter periods -- the spleen, for example -- how many times can a specific macrophage self-renew. And this -- so it turns out that it doesn't seem like macrophages are akin to hematopoietic stem cells or progenitor cells that have this capacity to renew many times. And we don't actually know what is the finite number of renewal -- the number that macrophages can renew. Is it four times? Is it five times?
That's some -- that are of the best guesses for how many times these tissue-resident macrophages renew. But, of course, if it's only four or five times, when you do the math, then the question is, well, where do these cells come from. Do they come from now specific progenitors that reside in that tissue that we don't know yet? Do they come from very local sources of the bone marrow that -- which we wouldn't be able to catch by using parabiosis studies that have really been key in understanding that sort of contribution.
So there is still a lot to learn about this, but one thing I think is clear is that tissue-resident macrophages don't live forever. They live for several months, maybe longer depending on the tissue, and it doesn't seem that they can self-renew indefinitely either.
DR. CLAYTON: Okay. Thank you for that. We do have a lot of HIV-related macrophage questions which we can save for a little bit later because I think actually some of the answers are going to be there in the presentations. We do have time for one more question, but for everyone else that had questions in the Q&A, thank you very much. We're going to be following up separately with Fil, and then we can have those answers a little bit later. But I think one that's a little bit more related to your presentation, Fil, is, "Would you be more specific about your disagreement about the concept of M1 and M2 macrophages?"
DR. SWIRSKI: I think that M1 -- so I wrote a perspective on this several years where I think you can really hear my argument for why we should be abandoning M1/M2. I do believe that, you know, it is a shorthand that has persisted, but I think it's very limiting in terms of our understanding of macrophages. That is not to say that it wasn't useful, you know, and I have to say, you know, all credit here to Charlie Mills who came up with this idea as it started to get people to really think about different functionalities of macrophages. You know, they're not just plastic. They can acquire certain features, and they can produce all sorts of different mediators and products depending on the place in which they find themselves.
However, we now know that the functions of macrophages really go vastly beyond just this concept of M1/M2. So, you know, M1 and M2 are training wheels helping us to understand macrophage heterogeneity. I think we are now at a place where we can start thinking about macrophages function as -- in more sophisticated ways. And certainly, the single-cell RNA-seq data where we look at macrophage populations, when we look at their specific functions in the different organs, when we look at the functions that are independent or at least seem to be, at surface, independent of the immune system, what we quickly recognize is that the vast constellation of functions is really -- is really something that is so fascinating about these cells.
And we should sort of shed our M1/M2 and not be afraid to leave that idea and grow on it to start talking about the macrophage function and all the different types of complexities, immune and non-immune functions, inter-organ as well as intra-organ heterogeneity. I think that's going to be very helpful, and it's going to help grow the field rather than stifle it as it can if we don't move out of this paradigm. I hope that makes some sense.
DR. CLAYTON: Okay. Thank you, Fil. So we're out of time on questions, but we do have copies of all the questions that people put in the Q&A. And we also have your names, so we'll be able to follow up with you individually because we want to make sure that your questions are answered, but unfortunately, we have to move on at this point in time. Fil, thank you very much for your time. We really appreciate it. That was a wonderful talk, and hopefully you can stay for some of the rest of the HIV talks, but thank you very much.
DR. SWIRSKI: Thank you very much, Kiera. Thank you all for listening and looking forward to this day of talks. I'll be able to join at some points, but not on all of them, but thank you very much.
DR. CLAYTON: Thanks, Fil. Okay. So I'm going to be moderating the first session, which is Macrophages and the Immune System During HIV and SARS-CoV-2 Infection. Please feel free to ask questions. What we're going to do is each person is going to have their 15-minute talk first, and then we're going to have a prolonged Q&A session at the end. So please make sure when you ask questions that you ask it to a specific speaker so that we can relay that.
So first, we're going to have Tim Hanley from the University of Utah Health Center, then we're going to follow up with Scott Sherrill-Mix from the University of Pennsylvania, then Rahm Gummuluru who's from Boston University, and then Vincent Marconi who is at the Emory Vaccine Center. And, guys, we are on a little bit of time, but I would like to ask you to stick to the 15 minutes as much as possible, but we do have a little bit of leg room. So, you know, just try to stick to it, but if we're going a little bit over, that's okay, so thank you. So I'll hand it over to Tim.
DR. HANLEY: All right. Good morning and thank you. I'd like to start by thanking the organizers of the symposium for allowing me to share some of our recent unpublished work on HIV infection and macrophages. As I'm sure I don't have to tell most people here, the major barrier toward eradication of HIV infection is the presence of small reservoirs of latently-infected cells, and these reservoirs include both CD4-positive T cells and, as a lot of recent evidence has suggested, macrophages. And although we know a lot about how the reservoir is established in CD4-positive T cells, we still don't have a great understanding of how this process occurs in macrophages. A lot of the work that I'll show you today suggests that virus-induced inflammation, specifically type I interferon production, helps to induce a state of transcriptional latency in HIV-infected macrophages.
All of my studies that I'll show today use an in vitro monocyte-derived macrophage model system where we isolate monocytes from healthy donors, incubate them in a mixture of fetal bovine serum and pooled human serum for six days, at which point they differentiate into monocyte-derived macrophages, and these macrophages have a resting or M0-like phenotype. We can then infect them with replication-competent HIV or a variety of reporter viruses and leave them in culture for an extended period of time. And during their time in culture, we can periodically harvest them to measure a viral replication, transcription, and integration.
And what we have found in most donors is that they fall into roughly two general phenotypes. The first is characterized by robust virus replication early post-infection, usually with a peak in replication between days three and 12, followed by a gradual decline in virus replication, and we refer to this as a latent phenotype. And as you can see, there's a statistically significant difference between virus replication during peak replication compared to end point of the assay. The other major phenotype we see is one characterized by less robust virus replication that persists throughout their time and culture. We refer to this as a persistent phenotype.
Now, this latent phenotype, I should mention, is not due to cell death or toxicity. We monitor cell viability throughout the course of this assay and don't see a significant difference in infected cells. And although a lot of recent evidence has shown that HIV infection in macrophages derived from male and female donors is very different, this particular effect seems to be independent of donor sex. But there is a correlation between the degree of peak virus replication and the ability to transition towards latency. Those macrophages that support very high levels of virus replication are the ones that tend to become latent, suggesting that there's some sort of threshold effect or event that needs to be reached in these cells.
Now, in T cells, latent HIV infection is characterized by a decrease-to-absent viral transcription without a change in integrated proviral DNA, and the ability to reactivate these cells with latency reversal agents, and we see a similar phenotype in our macrophages. So if you compare transcription at late timepoints after infection to early timepoints in infection, you can see that there is a significant decrease without a change in the amount of integrated HIV DNA. And importantly, if you take macrophages' latent infection after they've transitioned to latency and then stimulate them with latency reversing agents, such as TNF-alpha or PMA, you'll see a statistically significant increase in virus production.
And I should mention that the effects that we're seeing aren't a global slight decrease in virus replication in all the cells. But if we look at individual cells by flow cytometry, for example, in this one representative donor, you can see that early during infection, about 15 percent of the cells are expressing HIV, and that decreases over time and culture. So it's a subset of cells within the culture that actually turn off virus replication.
And we've confirmed this doing sorting experiments where we take macrophages, infect them with a version of HIV that expresses mirroring CD24, and then three days after infection, sort using magnetic beads directed against this molecule so that we can enrich for HIV-infected cells. When we leave those cells in culture for an additional three to four weeks, we see that a majority of them actually turn off HIV expression. And I should mention that these are terminally-differentiated cells, so it's not that the negative cells within that enriched fraction or actually expanding in culture.
So we have what appears to be a latent phenotype in macrophages, and we wanted to determine whether this latency was associated with changes in either transcription factor, recruitment to the viral promoter, or changes in Basel transcriptional machinery present at the promoter. And using chromatin immunoprecipitation assays, what we see is, in fact, yes there are changes. For example, the p65 subunit of NF-kappa B is a decreased at the HIV promoter at late points in infection compared to early infection where we have robust transcription. And this is accompanied by decreases in RNA polymerase 2 and the cyclin T1 component of pTEFb at the promoter suggesting that latency is associated with changes in transcription factor recruitment to the promoter.
Now, transcription factors are not the only thing that controls viral transcription. When HIV integrates into the host genome, it does so in a very specific way. There are nucleosomes that are precisely positioned the integrated provirus, including one located just downstream of the start site of transcription that we call Nuc-1. In order for viral transcription to occur, this nucleosome needs to be remodeled, and when it is remodeled, DNA just downstream of the start site of transcription becomes accessible to restriction enzymes, so we can use this restriction enzyme accessibility as a proxy to measure nucleosome remodeling. And what we see at Nuc-1 at early time points post-infection in our macrophages is that this DNA is accessible, suggesting that the nucleosome is remodeled, but as the cells sit longer and culture, it becomes inaccessible, suggesting that the nucleosome is no longer remodeled.
Now, viral transcription is also a very tightly controlled at the level of both transcription initiation and transcription elongation. We can measure this using primer specific for early RNA products or late RNA products, such as from the gag region of the genome. And what we see in our macrophages is that during early timepoints after infection where we have robust replication, there is efficient transcription initiation and elongation. But as the cells live longer and culture, you can see that there is a block to transcription initiation, suggesting that latency is associated with block transcription initiation in this context. And this is actually distinct from what is thought to occur in lately-infected T cells where in those cells latency is associated with paused elongation.
So we have what appears to be a latent HIV phenotype in macrophages. We wanted to next determine what cellular pathways and viral constituents for contributing to the transition towards latency. So what we did was take a macrophages at day seven post-infection, so as they're beginning that transition towards latency, and submitted them for single-cell RNA sequencing. And what we found is that there were a number of differentially expressed genes, upregulated in red here, downregulated in blue. These orange genes are actually HIV-associated genes. And what we found is that interferon-regulated genes are actually increased in this subset of differentially-expressed genes. So about two-thirds of the significantly upregulated genes are bona fide interferon regulated genes, whereas all of the downregulated genes are interferon regulated genes, suggesting that type I interferon signaling plays a role in this transition to latency.
We've also shown in a recent publication that if you treat HIV-infected macrophages with a single dose of type I interferons, you get this pronounced and sustained decrease in virus replication suggestive of latency. So it seems like treating with type I interferons can actually induce latency in macrophages. And we've confirmed this using a number of different inhibitors of interferon signaling. These include a soluble type I interferon receptor as well as JAK1 and JAK2 inhibitors, such as ruxolitinib, and if you treat HIV-infected macrophages with these type I Inhibitors -- type I interferon inhibitors, you can actually prevent that progression to viral latency. Interestingly, treatment with these type I interferon inhibitors also prevents the loss of NF-kappa B from the viral promoter and RNA polymerase II, and allows for Nuc-1 to be remodeled, which all correlates with higher levels of HIV transcription and replication when you block type I interferon signaling.
So we know that type I interferon signaling seems to be important for the creation of this latency phenotype in macrophages. We next wanted to determine what cellular signaling pathways might be contributing to that. HIV is sensed by a number of different innate immune receptors within the cell. These include toll-like receptors, RIG-I, MDA5, and cGAS, which all recognize viral nucleic acids to some extent. In the interest of time, I'll just tell you that using a number of specific inhibitors for toll-like receptors and cGAS had no effect on the transition to latency in macrophages. But if we culture the macrophages with inhibitors for TBK1, a kinase that is a common downstream molecule in all of these pathways, you actually could prevent the transition to latency, suggesting that perhaps RIG-I, MDA5, and MAVS might be involved in inducing latency.
So we went on to determine whether MAVS was involved, and we did this by infecting our macrophages with short hairpin RNA encoding retroviruses in the presence of VPX. These happen to also express an antibiotic resistance gene, so we could select for infected cells over the course of five days, then infect them with HIV and harvest them later. And we get good knockdown of MAVS in this case without affecting infection too much. And as you can see, if you -- if you knock down MAVS in this one representative donor, you can actually prevent the progression of these cells towards a latent phenotype, suggesting that inducing latency requires MAVS TBK1 signaling. And it's most likely that there is a viral RNA species that's being recognized in this pathway, and now we're working on trying to identify exactly what kind of RNA -- viral RNA species is involved.
The last bit of data I'll show you was to determine what role, if any, HIV accessory proteins play in inducing viral latency. And some of this work was done by Laura Martins, a postdoctoral fellow in the lab of my close collaborator, Vicente Planelles. And what Laura did was to infect macrophages with wild-type HIV-1 val and submit it for RNA sequencing. And there were hundreds of differentially-expressed genes in these HIV-infected macrophages compared to uninfected controls, a large proportion of which were interferon-regulated genes. And I'm showing you a subset of those here in the orange bars.
And what I'd like you to notice is that the degree of the effect induced by wild-type HIV is actually blunted when compared to treating macrophages with a type I interferon shown in the gray bars here where they were treated with interferon epsilon, a type I interferon. So it seems like HIV infection and macrophages induces a suboptimal interferon response. Laura went on to infect these macrophages with a version of HIV val that has a deletion in VPR, and what she found is that the interferon response was even further blunted in the case, suggesting that VPR itself is capable of inducing a suboptimal type I interferon response.
So what we did is we took those mutant viruses and infected monocyte-derived macrophages. And as you can see in the open circles here, infection with that delta VPR virus actually prevents a transition towards a latent phenotype when compared to the wild-type virus shown here in black, suggesting that VPR actually contributes to the induction of latency in macrophages. We also used a virus that included a mutated version of VPR, the R80A mutation, which is involved in cell cycle checkpoint activation, and we still saw a transition to latency, suggesting that at least that function of VPR is not required for this effect.
So in conclusion, what I've shown you is that macrophages from a subset of donors enter a state reminiscent of viral latency, and I should mention that we see this in about two-thirds to three-quarters of the donors that we test. This transition to latency is associated with decreased NF-kappa B recruitment to the viral promoter, that type I interferon signaling induces latency by blocking NF-kappa B in RNA polymerase to recruitment to the promoter, and that latency requires MAVS TBK1 signaling, likely through recognition of some viral RNA species, and finally, that HIV-1 VPR contributes to the induction of latency in macrophages in an as yet undetermined mechanism. So our lab is currently looking at a number of follow-up studies to see whether this phenotype actually can be recapitulated using tissue macrophages from surgical specimens and looking at some of the further cellular and viral contributions to the transition to latency.
So with that, I'd just like to thank the members of my lab and the members of the Planelles lab for all of their help with this project, and I'm happy to take questions at the end of the session. And now I'd like to turn it over to Scott Sherrill-Mix.
DR. SHERRILL-MIX: Yeah, that's going to be a nice introduction to my talk, too. Thank you. So I'd like to talk about the phenotypic properties of HIV-1 at transmission and rebound. So this is going to be a two-part talk, first talking about some of the longitudinal dynamics of interferon resistance. As we were just hearing, interferon plays an important part in HIV infection, and we've been seeing really strong effects at transmission and rebounding that I think are important to keep in mind. And then following up on that, some more preliminary work looking at growth in macrophages that I thought would be pretty relevant for this conference.
So we're interested in interferon resistance in HIV, largely because of a project a couple -- that we published a couple years ago looking at transmission pairs. So we identified a person who had just been infected with HIV, then contact traced back to the likely donor, and identified the donor, isolated virus from the donor and recipient, and compared the viral phenotypes -- different viral phenotypes, like replication capacity, infectivity, interferon resistance, and we found there's a really strong signal in interferon existence.
So on the plot on the left here I'm showing each transmission pair as a different color. And so in the leftmost in gray, that's a donor who we isolated the virus from serum in gray or from genital secretions in hash marks, and the lines are spanning the range of interferon resistance. So if it was -- if a virus was interferon sensitive, it's low on the y axis. If it's interferon resistant, it's high on the y-axis. And so this donor transmitted to two different recipients, these small gray boxes up here, and those recipients all have viruses that were highly interferon resistant, much higher than what we saw in the donor that transmitted it to them. And this was true across many different transmission pairs in green. We see the same thing, donor interferon sensitive recipient, highly interferon resistant. Same, same, same. And so it seems like this is a general phenotype where interferon resistance is essential for transmission or the establishment of infection in the new host.
And so just as a really quick refresher, interferons at cytokine that induces antiviral innate immune response, so cells detect something's going wrong in the cells. That induces the expression of interferon. It's picked up by the interferon receptor, activates the JAG-step pathway, and induces interferon stimulated genes that target different aspects of the viral life cycle, trying to inhibit replication.
And so we measure interferon resistance in primary CD4 T cells, so we get healthy donor primary CD4 T cells. We have differing amounts of interferon, then we had a defined amount of virus and monitored replication over a seven-week infection. And then we measure how much virus we get out by p24 in the supernatant. And so, for example, the top left here, this is viruses isolated at 12 days post-infection from a single patient, and when there's no interferon, we get maximal replication. As we add more and more interferon, we see replication drop by a replication drop. And so to quantify these curves as like a single measurement, we use IC50, so that's much interferon we need to drop replication by 50 percent. So here's 50 percent in these viruses. The IC50 is around 1 picogram per mil.
In more sensitive viruses like those isolated at 1,000 days after the onset of symptoms, we see that that much less interferon is needed to drop replication 50 percent. In these viruses, it was around .001 to .01 picograms per mil, so sensitive virus, more resistant virus.
And we also -- so interferons are a bit complex. There's a bunch of different types. Here we're just talking about type I interferon, and within type I interferon there's several different subtypes. So we measure interferon alpha-2 and interferon beta resistance because those are well characterized and they've been used in human patients in clinical trials. And so, in general, we see a really high correlation between interferon alpha-2 and interferon beta resistance. So here on the x-axis, I'm showing interferon alpha-2 resistance, on the y-axis, interferon beta resistance, and as you can see, there's a really nice correlation. So I'm just going to show you interferon beta resistance for most of this talk, but we measured it in both and they were highly correlated.
And so we saw that that stark difference between the acute recipients who had strong -- strongly interferon-resistant virus and the chronic donors that transmitted to them where there was much, much less interferon-resistant virus, and so we wanted to try to figure out what was going on there. So we've got a longitudinal cohort where patients were identified shortly after HIV infection and then were tracked for years of untreated infection, then the patients were put on, by their primary care doctor -- antiviral therapy by their primary care doctor and were tracked for several more years.
And so we had six patients that followed pretty typical standard progression of HIV, and so that's a high viral load, so in red we're showing viral load. You see a high peak of acute infection that drops off to a set point over the course of infection, then the patient is started on antiretrovirals. The gray indicates antiretroviral therapy, and the viral load drops down to detectable levels. Similarly, the CD4 cells count in blue start at healthy levels and then slowly trickle down over the course of infection down to levels that are defined as AIDS-related.
And so we saw that sort of standard progression in six patients. We saw two patients that didn't progress to AIDS over the course of the infection, so in blue their CD4 counts were healthy when they came into the study and maintained healthy levels over the course of the five years we were tracking them. And then we have two patients that rapidly progressed to AIDS, so they started at healthy CD4 counts, then their CD4 counts dropped within one to two years of infection.
And so we had samples longitudinally across the untreated infection plasma samples. We also had PBMC samples during ART treatment so we could isolate virus from these samples and assess their interferon resistance. And so on the right here I'm showing interferon resistance on the y-axis, again, weeks from onset of symptoms on the x-axis. So as you can see, during acute infection, interferon resistance was high in every patient we saw matching what we had seen in the transmission pair studies. We saw that interferon resistance dropped rapidly within the first six months to a year. These virus -- the viruses were able to isolate hundreds to a thousand times more sensitive to interferon -- to interferon. We also saw that as the patient progressed to AIDS as CD4 counts dropped, interferon resistance started to rise to higher levels.
And interestingly, in the two fast-progressing patients, we didn't see the big interferon drop that we saw in every other patient. It seems like there's something about fast progression that maintains interferon resistance at a high level, and so that's over the course of an untreated infection. We were also to get PBMCs after years of ART treatment, do viral outgrowth, and obtain virus from those PMBC from outgrowth and compare their interferon resistance. So and the blue dots in these patients indicate where we are able to get viral outgrowth from PBMC, and in every case, the interferon resistance of these viruses was really similar to what we saw just before the initiation of ART. So the interferon resistance is similar to the last timepoint before ART in all these patients.
Interestingly, we were able to get one outgrowth virus from the fast-progressing patient, and his outgrowth -- the outgrowth virus was very similar to the last timepoint there, too, but that was pretty interferon resistant because there was little drop from interferon resistance. And so we can -- we can try to distill all that data down into one plot to take all the cute viruses from the 10 patients and condense it all together, take all the chronic isolates from those 10 patients, condense it together. And we -- you can see, as I was saying, all the acute viruses are highly interferon resistant. All chronic viruses are interferon sensitive. Interferon resistance is on the y-axis again with top -- high values up at the top. And you can see there's also that subset of virus from fast progressors that maintain their interferon resistance even in chronic infection.
We can also pull in the data that I led off the talk with, the transmission pair study where acute recipients were highly interferon resistant, chronic donors were interferon sensitive, and then we can compare that to the outgrowth viruses we got in blue. So you can see all the outgrowth viruses really resembled chronic virus, except for that one outgrowth virus from a -- from a fast progressor that had a pretty high interferon resistance.
And so we wanted to see is this a general characteristic across other studies. So we collaborated with the Bier Lab, Montaner Lab, Nussenzweig Lab, and Siciliano Lab and collaborators to get many different patients' outgrowth virus. So on the x-axis here, I'm indicating each patient. The dashed lines indicate different clinical studies or clinical trials or studies that we're getting these from. And so in blue -- in cyan here, I'm showing all the different outgrowth viruses we got from these different patients, different studies. And consistently, the interferon resistance was really similar to what we see in chronic interferon -- to chronic viruses, so sort of a middling level of interferon resistance.
And so some of these patients had also volunteered to undergo analytical treatment interruption, so they paused their antiretroviral therapy and then were monitored for viral rebound. And as soon as they could detect viral rebound, we isolated virus from that serum and assessed what the interferon resistance looked like in those rebound viruses that you're actually getting from rebound patients.
So in red here, I'm indicating rebound viruses. We were able to isolate quite a few from these patients, and in every case, in every patient, in every study, these were highly interferon resistant, very interferon resistant, even more interferon resistant than what we had seen in acute infection earlier. So these rebound viruses, key characteristic seems to be their interferon resistance, and worrisomely, that doesn't seem to match what we are able to get from viral outgrowths. The viral outgrowths, one of the primary ways to assess the latent reservoir, it looks like our assessments, at least on outgrowths from primary CD4 T cells, don't seem to match up with the virus that we actually see replicate in rebound, in actually in vivo replication in rebound.
And so just to summarize the dynamics of interferon resistance part of the talk, we saw interferon resistance is high during acute infection. It drops rapidly. It starts to rise as CD4 counts drop. We saw that outgrowth viruses were interferon sensitive. That was similar to late timepoint chronic viruses. I should also say we sequenced outgrowth viruses from our longitudinal cohort, and they were phylogenetically similar to the late timepoint viruses, similar to other reports that a lot of the latent reservoir seems to be seeded right around the time of ART initiation. And in contrast to the outgrowth viruses, the rebound virus, the viruses that we actually saw replicating in patients, were highly interferon resistant.
And so a lot of the research in the lab now is trying to figure out this disconnect. Why are the outgrowth viruses so different from the viruses we can actually see replicating in patients? And so one aspect that we're investigating is growth in macrophages. So we've been assessing the growth of these rebound and outgrowth viruses in macrophages. We do that by isolating monocytes from healthy donors, differentiating into macrophages, then putting them in culture, adding a defined amount of virus, and just tracking over a 21-day infection to see if we get viral growth.
And so YU2 is sort of a positive control virus. It's known to replicate macrophages, and when we -- in this example, you can see that it rapidly produces P24. In the supernatant, you see a robust fighting of infection over the 20-, 21-day infection.
And so we assessed the macrophage replication in many different donors. So in this heat map, I'm showing different healthy donors as columns and different viruses as rows. And you can see -- and I should say that the red indicates a high area on the curve, so we just distilled this replication curve down into a single value area under the curve just to add up all the -- all the colored bit here. And so if you're -- if you have a strong replication of macrophages, you'll be bright red on this plot here.
And so you can see that different donors -- different healthy donors on the -- in the columns have different amounts of macrophage replication or different -- differently permissive type. Donor 3 here was very non-permissive for macrophage growth. And so we control for that by measuring on many different donors. Each virus -- each row is a virus measuring many different donors. We average across the row or across the different healthy donors, taking into account how permissive each donor is, and that gives us a single score for macrophage replication. The average p24 area under the curve for these patients -- for these viruses, accounting for the different permissivity of the donor cells.
And when we do that and compare rebound virus, outgrowth virus, transmitted founder virus, and chronic virus, we see that many, many rebound viruses do exhibit spreading infection in macrophages. That's also true. We saw some in outgrowth viruses and in transmitted founders, I should say. The orange are positive controls, so YU2, TGO 21, and TYPE, that are known to replicate a macrophage, so we set up replication where we expected it. And so we can see that many, many of the viruses that rebound in patients are able to replicate a macrophage -- many, but not all -- and we're still trying to quantify this. Is there a difference between rebound and outgrowth, between rebound and any of the other categories, so that's work in progress. But at least as a preliminary finding, we can observe in our system some rebound virus replicating in macrophages.
And so while we're still working on that, there is one anecdote that I thought would be interesting to share here. So in a -- in a single patient, we had -- we isolated virus from -- by a viral outgrowth in green prior to anti -- through ATI to cessation of antiretrovirals treatment interruption -- during treatment interruption in red so the rebound virus, the active virus that actually reappear in patients when they stop their medicine. And in blue, after six months of antiretroviral therapy, after the treatment interruption, we can isolate virus by outgrowth.
And so when we look -- when we sequence the virus and look at the phylogenetic tree, like I'm showing here, there's a -- there's a single clade where we see rebound and outgrowth virus very highly related, very, very closely clustered, and these are outgrowth virus after the treatment interruption. So it's unclear if these were -- already existed in the latent reservoir or if they're receded during rebound.
But when we look at the virus and we assess interferon resistance, tropism, and replication in the macrophages, we see kind of an interesting story. So in interferon resistance, the outgrowth viruses have similar interferon alpha resistance, but they had -- the rebound viruses have higher interferon resistance within this clade than the outgrowth viruses. So these outgrowth viruses had a decent interferon resistance, but they weren't as resistant as the closely-related rebound viruses.
And so all these viruses in the single clade were CCR5-tropic. All the other viruses were dual or CXCR4-tropic, and only within this clade did we see replication in macrophages. So all the rebound -- all four out of four viruses within this clade showed low, but detectable, macrophage replication, while the two closely-related outgrowth viruses did not show any detectable replication in macrophages. And so this is just one anecdote, but it's an interesting phenomenon where rebound viruses did show spreading infection in macrophages while the outgrowth viruses, the less-resistant outgrowth viruses, did not.
And so just summarizing the macrophage part of the talk, just to remind you, rebound viruses were highly interferon resistant while outgrowth viruses were interferon sensitive. We're trying to find out why that could be. And so we saw many rebound viruses exhibit spreading infection in macrophages, but we also see replication and outgrowth in transmitted founder viruses. We're still trying to distill that down into a clearer picture. Part of the problems there are that cell donors have a strong effect. Also we're doing all this with fetal bovine serum, FBS, and a study in 2017 by Micochova et al., reported that FBS makes macrophages more permissive to HIV replication than the human serum that's often used in other studies. So we're digging down on this further to figure out exactly what's going on.
And I also told you about that single N of 1 anecdote where we saw, within a highly-related clade, the more interferon-resistant virus showed replication. More interferon-resistant rebound virus showed replication in macrophages, while the less interferon-resistant outgrowth viruses did not. And so this kind of raises the question, could macrophages be part of the story here. So with these highly-interferon rebound viruses, we don't get an outgrowth, so it seems like there's some reservoir that we're not -- we're not identifying by our standard outgrowth assays, or there's some sort of rapid evolution towards interferon resistance maybe in some hosts that has strong interferon-stimulated, gene-strong interferon response, and so trying to dig into that. Macrophages could be an interesting host there, and I'm really interested to hear the rest of the talks today and tomorrow.
And so all the longitudinal work was a collaboration with Marvin Gondim. Fred Bibollet-Ruche led the macrophage stuff. This is all from the lab of Beatrice Hahn. We have many collaborators, and, of course, thanks to all those study volunteers who contributed samples in their time. Thank you for listening. And I guess now I'm supposed to hand over to Dr. Gummuluru for his talk, and I'd be happy to answer any questions later in the question and answer period.
DR. GUMMULURU: Good morning, everybody, and thank you to the organizers as well as NIMH for this opportunity to present our work. I realize that I am the -- it looks like the only one who's going to be presenting some work on SARS-CoV-2, so just bear with me as I present a little brief primer on SARS and its -- and the roles of macrophages in SARS-CoV-2 pathogenesis. Some of our work on HIV and macrophages will be presented in the next session tomorrow, so stay tuned for that.
So it's been -- since the -- since the start of the pandemic, it's been well appreciated that there is a very strong correlation to -- sorry -- strong correlation to the presence of consistently high levels of inflammatory cytokines in patients who have severe disease. So as opposed -- shown here in this schematic is a difference between a mild and severe disease, and as opposed to in the mild disease where infection most often occurs in these ACE2 positive type I and type II pneumocytes, infection is resolved very quickly and very low inflammation is observed. Contrast to that is the severe disease phenotype where we see recruitment of large numbers of inflammatory monocytes and macrophages to the bronchial alveolar space, and there is persistent production of proinflammatory cytokines. And the cellular source of these cytokines have also been debated, but what has been clear is that there are high levels -- correlation to a macrophage-intrinsic inflammatory cytokines signature in COVID-19 patients.
But the questions that remain that are unanswered include whether macrophages themselves are susceptible to SARS-CoV-2 infection, and this is -- and then lots of elegant single-cell RNA-seq data studies have shown that indeed there's not only activation of alveolar macrophages -- those are tissue-resident macrophages in the lung -- as well as recruitment of large numbers of inflammatory monocytes in monocyte-derived macrophages into the space. And interestingly, if you map the viral RNA reads to the cells in these tissue sites, we find that mostly myeloid cells are the ones which are RNA positive. This has also been corroborated with independent RNA scope analysis. Shown here is an alveolar macrophage that is T206 positive, that shows RNA positivity in this tissue environment. But the question that still remains is whether these cells themselves are susceptible to infection because these cells themselves could just be phagocytic in the virally-infected cells in their immediate environment. So we set out to answer that question.
And the next question we wanted to ask was whether this infection or potential virus exposure of these -- to these cells induces an innate immune activation phenotype, and, if so, what are the viral determinants that govern this and what are the innate immune surveillance mechanisms that sense virus infection in these cells. The third question that I'm not going to get today is the question of whether there is a dysfunctional macrophage response and whether that contributes to COVID-19 severity, and this is work in progress as well.
All right. So the first question of whether macrophages are susceptible to CoV-2 infection, we went about doing this using monocyte-derived macrophages for our all of these studies that I'm going to show you today. These are, again, peripheral blood, CD14-positive monocytes differentiated into macrophages using MTSF and human AB serum. So there has been some controversy in the literature about whether or not these cells are ACE2 positive, and ACE2, as you remember, is the primary receptor for SARS-CoV-2 entry to susceptible cells.
What we find is that, as opposed to a cell line which has been engineered to exogenously overexpress ACE2, in this case, HEK293 cells, the macrophages or quantitative RT-PCR show no expression of a ACE2. And if one was to look for FACS expression, you again fail to see any cell surface expression of a ACE2 in these macrophages. But are they permissive -- to permissive to infection? To ask that, we used antivirus phenotypes. In this case, we use CoV-2 S-pseudotyped lentivirus particles and carried out infections, again, of these monocyte-derived macrophages.
Shown here is the data from cells derived from three independent donors, and I'm comparing this to infections of HEK293 cells, again, which are overexpressing ACE2 in the orange histograms, which show robust infections with these S-pseudotyped lentiviruses. Surprisingly, macrophages which do not express ACE2 were susceptible to infection by these S-pseudotyped lentiviruses shown here in the red, these red histograms. And interestingly, the entry of these S-pseudotyped lentiviruses was blocked by inhibitors of the cathepsin proteases that are present in the endosomal compartment, while it was not inhibited by protease inhibitors that target the TMPRSS2 protease inhibitor that is present in the cell surface.
So SARS-CoV-2 as entry in ACE2 positive pneumocytes or epithelial cells is dependent on ACE2 and TMPRSS2 predominantly, while in macrophages it seems to be progressing to an ACE2 independent manner via an endosomal entry pathway dependent on cathepsin present for S-proteolytic cleavage and priming of fusion event. We are confident that this is indeed dependent on S-mediated entry because we're using antibodies that either target the receptor binding domain of CoV-2 S or those antibodies that specifically target the N-terminable domain of S. We find that, specifically, antibodies that target the N-terminal domain of CoV-2 S are the ones which are inhibitory to entry of lentiviruses pseudotyped with CoV-2 S, again highlighting that this is ACE2 independent entry mechanism that is utilizing alternative entry receptors to gain access into macrophages.
A number of findings in the literature have already argued that attachment factors and various lectins are what are responsible for recognizing the N-terminal domain of CoV-2 S, and so that immediately was our interest as well as we were interested in what are the other attachment factors or receptors that might facilitate CoV-2 S entry in macrophages. Our interest has been for a long time on a specific lectin molecule called CD169, or Siglec1, and I'm going to get into the reasons why we think this is also relevant for CoV-2 S entry in macrophages.
It is constitutively expressed on alveolar macrophages. Shown here is a -- is a staining -- lung interstitium in alveolar macrophages and the brown staining represents CD169 positivity, which is extensive. This protein is inducible by type I and type III interferons on monocytes/macrophages and also dendritic cells. Shown here is some of our previous work on this where MBMs stimulated with type I interferon show robust upregulation of this protein on their cell surface.
And our previous work among -- as well as others have also shown that Siglec1 captures, for example, HIV-1 amongst other viruses as well and use -- by recognizing alpha-2,3-sialyated acid residues either on glycosphingolipids or on envelope glycoproteins, and targets virus particles to the cis and trans-infection pathway. Interestingly, three weeks ago, there's already a paper in the literature that has argued that SARS-CoV-2 infection is -- can be enhanced by the CD169 and ACE2 positive cells as well.
Importantly for this talk, we can all -- it's been reported as well is that upregulated expression of peripheral blood CD14-positive monocytes has been observed, and Siglec1 expression on alveolar macrophages is dramatically upregulated in COVID-19 patients. So shown here is these alveolar macrophages, and the green staining represents CD169.
So all of this points to the fact that this receptor might be playing a role in facilitating entry. To get at this question, we established cell lines, in this case, human myeloid cell lines, THP1, that either stably express or considerably -- stably express CD169 where the controlled also expressed ACE2 or both receptors. And we asked whether they were able to recognize the CoV-2 S or the spike -- recombinant CoV-2 spike. Shown here is an example of this analysis. In blue histograms is the binding of the CoV-2 S recombinant protein to THP CD169 cells, and we see robust binding to these cells to levels similar to that we find with the ACE2 expressions. Note that there is a significant enhancement of CoV-2 S binding to when both receptors are expressed on these cells.
As an important control, we established our THP1 cell line, which expresses a mutant CD169 -- this is R1168 mutation -- that disrupts its ability to recognize sialic acid residues that completely abrogates its ability to recognize CoV-2 S. This binding is expressly correlated with the infection data, again, with the CoV-2 S pseudotyped lentiviruses where we find that the CD169 positive cells facilitate entry and infection with the pseudotyped lentiviruses to levels that we see with the ACE2 positive THP1 cells, and that this infection is enhanced again when both receptors are expressed.
So this is our CoV-2 S pseudotyped lentiviruses. So the question that we were at -- we were next interested is whether this is also true for a replication competent CoV-2 -- SARS-CoV-2, and we used the Washington isolate of this and challenged these THB2 cell lines that expressed the various different receptors on the cell surface, including CD169, ACE2 alone, or the double positive cells.
So shown here is a staining for the nucleocapsid protein of CoV-2 to indicate productive infection and double-stranded RNA to indicate RNA replication in these cells. To our great surprise, there was absolutely no infection that was detectable in these either parental cells or CD169 positive cells alone. In contrast, when we expressed ACE2 in these cells, we were able to rescue infection robustly, and this infection was greatly enhanced when both receptors were present. In fact, every cell in the culture was, in essence, infected by the -- by replication of CoV-2. This is also true for primary cells, in this case, MDMs, which are either considerably expressing CD169 or overexpressing CD169, and they both fail to support CoV-2 replication. Interestingly again, ACE2 expression and restoration of ACE2 expression in an MDM restores virus replication.
So we next asked if, indeed, virus production is also seen in these cells, and, indeed, the staining that we see within reflects -- is also reflective in the virus production. In green are the ACE2 positive cells and in purple are the double positive cells, and those are the only two cultures that result -- whose infection results in production of replication-competent CoV-2, which can titered on permissive cells, and they produce very high titers of virus only when ACE2 is present. So in the absence of ACE2, which is the case for most macrophages, there is no productive infection.
So we can conclude from this part is that there is a post-entry block to SARS-CoV-2 replication in CD169-positive macrophages, but there is entry and fusion, and that ACE2 expression in these macrophages can rescue CoV-2 replication, and that co-expression of both these receptors significantly enhances replication. But the question remains as to whether these CD169-positive macrophages and these are the macrophages that are present in vivo which lack ACE2 expressions, whether they interact with the virus and whether there's a consequence of that virus interaction of these cells, and the short answer is yes.
If you take a look at the ACE2 deficient CD169 positive macrophages and again expose them to this replication of SARS-CoV-2, we find robust induction of cytokines, in this case, proinflammatory cytokines, IL-6, TNF-alpha, IL-1-beta, and the type III interferon IL-29, and this occurs within 24 hours post-infection. So these are cells which are refractory to productive infection but are still responding to this restricted infection by producing these proinflammatory cytokines.
So what is the mechanism for this? What triggers this process? As I briefly mentioned, entry is occurring through this endosomal compartment, and a CoV-2 lifecycle is dependent on the -- on the release of this cluster and genomic RNA to the cytoplasm which is translationally component, that immediately is translated to form the viral replicase complex that includes the RNA-dependent RNA polymerase, which then is responsible for generating both the negative strand genomic RNA, cluster in genomic RNA, and the subcluster and subgenomic RNAs that are responsible for production of viral proteins and for new infectious particles. And, in fact, most of these subgenomic RNA transcripts are quite abundantly detected within six hours post-infection, so extremely fast kinetics.
So we set out to detect these RNAs in these CD169-positive macrophages exposed to SARS-CoV-2, and we used two different approaches. We used single molecule fish to look at individual RNA transcripts to not only look at productively-infected cells, but also to visualize the spatial distribution of these RNA species in these cells. This SM fish was used for detecting not only genomic RNAs, both plus-strand and negative-strand, but also the plus-strand subgenomic RNAs. So shown here is the distribution of the plus-strand genomic RNA in these various cells. And, indeed, all cells, even in the absence of ACE2, are RNA positive and this is reflected by this quantification shown here. But there seemed to be some differences in the spatial localization of these RNA species.
And this is better visualized in this next slide where you can clearly see that there is a perinuclear localization of RNA transcripts in these ACE2 positive or the double positive cells, while the CD169 alone cells have these unique puncta-like RNA, which are much more diffused and never approach the distinct peripheral subset of -- subset nuclearization that you see in the ACE2 positive cells. This argues that presumably the replication complex establishment has been somehow deterred in these ACE2-negative CD169-positive cells.
We can corroborate this with also quantitative PCR shown here as a time-dependent measurement for genomic RNA in these various cells of THP1s exposed to SARS-CoV-2. And unlike the parental THP1 cells, the THP CD169 cells show a robust increase in the genomic RNA expression, up to six hours, and then there seems to be an attenuation that progressively results in a decrease in the total RNA transcript of levels, unlike the ACE2 positive cells where there's progressive increase in RNA transcript, suggestive of robust replication. This is also reflective in the negative-strand RNA that we can measure in these cells. Again, there is an initial burst of replication and increase in negative-strand RNA expression, but which again is capped and attenuated, which is not so the case in ACE2-positive cells.
And if one was to look at the subgenomic RNAs, which are responsible for viral peptide synthesis and viral protein synthesis, we find, again, that there is initial production of these subgenomic RNAs, whose expression is completely blocked if one was to pretreat with Remdesivir, which I remind you is a nucleoside analog that blocks chain elongation, so it blocks RNA-dependent RNA polymerase activity and function.
So these data are -- would argue that indeed that there is viral entry fusion and initial burst of virus replication, which is then attenuated in the CD169-positive macrophages. And this is not only true for THP1 cells, but also true for the monocyte-derived macrophages, which we find similar kinetics of increase of these genomic RNAs and subgenomic RNAs whose expression is impeded when you have SARS-CoV-2 present -- when you have Remdesivir pre-treatment.
All right. So what is the consequence of this RNA expression in these cells? Interestingly, when we look for cytokine expression, we find that IL-6, TNF-alpha, IL-beta, and IL-29 expression are all observed in these THP CD169 cells, and I'll remind you these are the cells where there is no productive infection. And interestingly again, Remdesivir pre-treatment completely attenuates this induction of proinflammatory cytokines, suggesting that, indeed, it is the RNA synthesis expression in these virally-infected macrophages that is triggering the cytokine responses.
This is again true not only for THP1s, but also true for monocyte-derived macrophages. Remdesivir pretreatment completely shuts down this induction of proinflammatory cytokines, suggesting that it's not an entry event that is triggering, but it's a post-entry entry event in these cells, and this is a very rapid event. Within six hours post-infection, we start seeing induction of these proinflammatory cytokines messages that reaches a peak at 24 hours post-infection.
So what are the sensing mechanisms that are -- that are triggering this RNA-dependent innate immune activation? There's a considerable amount of literature already that has argued that numerous sensors, including the cytoplasmic RIG-I MDA5 pathway as well as endosomal TLR pathways are responsible for the sensing -- for detecting SARS-CoV-2 RNA, and we set out to identify which of these pathways are necessary for the detecting these virally-expressed transcripts.
So we established cell lines, in this case, THPs, with selective knockdowns in either RIG-I -- or knockdowns in RIG-I, MDA05 maps, or stained and blocked the DNA sensing pathways, which my hypothesis also turned on in SARS-CoV-2 infection. We knocked out UNC93B1. This is our host chaperone protein that is required for TLR -- proper TLR localization in the endosomal compartment, so knockdown of UNC93B1 abrogates TLR-based sensing pathways. We also knocked down IRF-1, which has been hypothesized to induce inflammatory gene expression. We established these stable cell lines and showed robust knockdown of all of these adapters or sensing molecules in THP CD169 cells. We then infected these cells with SARS-CoV-2 and measured the ability of these -- variably knockdown cells for supporting replication. And indeed this -- all reported similar levels of infection to vaccine with the parental cell types as measured by genomic RNA, PCR, or subgenomic RNA PCR.
Interestingly, when we look for cytokine expression in these cells, cell lines where there were selective knockdowns of MAVS, RIG-I, and MDA5 -- or MDA5 are the ones which are -- which show absolutely no induction of any of the proinflammatory cytokine, including IL-6, TNF-alpha, IL-1 beta, or IL-29. So this is -- in contract, knockdown of UNC93B1, shown here in red, which abrogates the TLR sensing pathway, had no impact on this, suggesting that it is the cytoplasmic exposure of these RNA transcripts, and detection by the cytoplasmic nucleic acid sensing mechanisms are what are required for the induction of innate immune activation in macrophages.
So to conclude this, I've shown you that there is a fusion and entry mechanism in macrophages that is occurring in ACE2 in an independent manner that is being -- that is facilitated by this ITAC called Siglec1 or CD169, and that this entry pathway can result in restricted expression of viral genomic and subgenomic RNAs, which are -- then can be detected in a RIG-I, MDA5 in a MAVS-dependent manner, and that this can result in amplification via hypothesized or proinflammatory responses by SARS-CoV-2 infection macrophages in bronchial alveolar space. We are currently testing the hypothesis that these macrophage-intrinsic differences might contribute -- especially in these signaling pathways, might contribute to the disease severity in COVID-19 patients.
And finally, the work in my -- this is a very nice collaboration between my lab and Elke Muhlberger's lab at the NEIDL at Boston University. In my lab, I have very talented graduate students. Sallieu Jalloh has carried out this work assisted by our technician, Jacob Berrigan. In Elke's lab, it's a senior research scientist, Judith Olejnik, who's done a lot of these infections studies for us. We've collaborated with Sanjay Tyagi and Yuri Bushkin at the Public Health Research Institute at Rutgers for the single-molecule analysis, and these is our funding sources. Thank you for your attention.
Our next speaker is Vincent Marconi, who's coming to us from Emory Vaccine Research Center, and I see him. Take it away, Vincent.
DR. MARCONI: Thank you, Rahm. I hope you can hear me and you can see my full screen on the slides. I'd first like to thank the organizers of this meeting and NIMH for inviting me and giving me the opportunity to talk on behalf of Boghuma Titanji, a fellow in my lab who largely produced these data that I'm going to share with you today. These are my disclosures, none of which are directly relevant to the data I'm going to present here.
So with a population of just under 38 million people worldwide living with HIV, more than half will be over 50 by 2030. HIV has been shown to independently increase the risk of age-related conditions, including cardiovascular disease, which is similar to other risk factors in magnitude. Activation of especially monocytes and macrophages from microbial translocation and lipid particles are a major driver of cardiovascular disease for people with HIV. To date, however, there no specific strategies to target this mechanism of disease for this population.
So the objective of this series of studies I'm going to show you was to assess the in vitro impact of several therapeutic strategies that target various aspects of the cardiovascular disease inflammatory cascade, particularly affecting people with HIV, including JAK stat inhibitors, and, in this case, baricitinib, colchicine statins, in this case atorvastatin, and antiretrovirals, which we'll show you intrasividan.
Using each drug combination or combinations of drugs, we can assess the impact of these strategies on various triggers of cardiovascular disease, and in this case includes HIV infection itself, lipids, and lipopolysaccharide-mediated inflammation. Our in vitro model involves pre-treating monocyte-derived macrophages with each drug of interest for two hours, then each stimulus is applied for various times prior to collecting supernatants for either cytokine or p24 quantification. For HIV infection, this his is done for five days, and for the other experiments we follow after 24 hours of stimulation. All of the cytokines seen here are measured using multiplex flow.
Because JAK inhibitors have demonstrated an in vitro inhibitory effect on HIV replication in T cells and macrophages via multiple mechanisms, and these include co-receptor binding, transcription, homeostatic proliferation, cell lifespan, and trafficking of target cells, we incubated various concentrations of baricitinib with HIV P89.6 and replenished with fresh drug daily for five days. As shown here, there was actually a dose-response effect on p24 production when compared to the positive control.
Additionally, we see a dose response effect on multiple cytokines, including IL-1 beta, IL-6, and tumor necrosis factor alpha with a threshold response for IL-10, and a very potent categorical response for IL-8. And this is about equivalent to a four milligram dose when you use the .12 micromolar concentration.
Now, when we looked at colchicine, we saw a similar dose response curve, and this has been shown, at least in T cell infections, potentially via likely microtubular trafficking disruption but has not been shown in macrophages as we're showing here. Similarly, a dose response was also observed with all cytokines, except for interferon alpha. The anti-inflammatory activity of colchicine involves, in most cases, inhibition of NLRP3 inflammasome. The effects here are, although potent, not as broadly potent and as significant as was shown with baricitinib. Now, in the literature, there's is very inconsistent in vitro data on the antiviral effect of statins against HIV despite multiple proposed mechanisms that we've listed here. There's no robust clinical data at this point supporting an antiviral effect against HIV, and in our case, we did not observe any inhibitory effect of atorvastatin against HIV infection in monocyte-derived macrophages.
During the early stage of atherosclerosis, macrophage autophagy is intact and it exerts its normal effects. However, when exposed to excessive oxidated LDL, autophagy flux is blocked through mechanisms that might involve cholesterol crystal overload or lysosomal leakage. Impaired autophagy results in lipid accumulation and activated inflammasomes, both of which, in turn, exacerbate atherosclerosis. Meanwhile, atorvastatin could upregulate autophagic activity through the mTOR pathway to inhibit NLP3 inflammasome activity and alleviate lipid deposition. This would subsequently mitigate inflammation and stabilize vulnerable atherosclerotic plaques.
Again, although there are mixed reports of the impact of statins on inflammation and cardiovascular disease risk in HIV, the role of statins is being investigated in cardiovascular risk in the large, randomized control trial REPRIEVE, which should be out soon, following 7,500 participants worldwide. In our case, we found no significant effect on cytokines in this particular model. And for us, although emtricitabine has effect -- antiviral effect that's quite potent, we did not see any inhibition of cytokine production in HIV-infected monocyte-derived macrophages.
So in conclusion, baricitinib inhibits production of proinflammatory cytokines in monocyte-derived macrophage cultures infected with HIV. Similarly, colchicine inhibits this as well, but the effects of colchicine on these proinflammatory cytokines are less impactful than baricitinib. Baricitinib and colchicine both exhibit antiviral effects against HIV in monocyte-derived macrophage cultures as well as been shown in T cell models. Atorvastatin and emtricitabine did not impact the production of proinflammatory cytokines in the same model using infection with HIV.
So I would like to thank again Boghuma Titanji, whose work this comes from working in the lab of Dr. Raymond Schinazi of Biochemical Pharmacology with assistance and support from Christina Gavegnano. And I think we've wrapped this up on time, so happy to follow with the panel with Kiera Clayton.
DR. CLAYTON: Okay. Thanks, everyone. Those were some great presentations. So we'll continue on. We have quite a few questions in the chat here, so we'll try and get through as many as we can. So let's see here. Okay. So I'm going to post questions to each of the panelists. If everyone could turn on their video right now and to answer the question, obviously unmute yourself. So question -- okay. So question for Tim. "Does infection with distinct strains of HIV alter the phenotype of infection in macrophages from a particular donor?"
DR. HANLEY: So we've actually tested a number of different strains, including lab-adapted strains and primary strains, and have seen a similar phenotype. We're planning to look at transmitted or founder viruses as well that are thought to be interferon resistant to see if there's a different phenotype there. But to date we haven't noticed a difference depending upon whether we use lab-adapted or primary viruses.
DR. CLAYTON: Okay. We have another comment/question here. "Nice data" -- again for Tim. "Nice data on how high and low differential transcriptional patterns, but use of latency term is unexpected as transcription is still present." Sorry, I'm just reading verbatim. "Also giant cell formation follows long-term cultures of infected MDM, so it's unclear how giant cell formation relates to transcriptional state in vitro." Is that a kind of phenotype that you see in your longer-term cultures as the giant cell formation?
DR. HANLEY: So to answer that part first, we do a lot of our studies using envelope-deficient reporter viruses, so we don't actually see syncytia formation in long-term cultures when we use those viruses. We do see some sensa syncytia formation when we use replication-competent strains that have envelope glycoproteins, but it's actually not that pronounced in these cultures. So we don't see a large number of multinucleated giant cells.
And as for the first part of that question about use of the term "latency," I think the thing to remember here is that not every cell in the culture actually turns off HIV replication, so -- it's the majority of them, but not all of them. So if you're looking at RNA in the bulk population, you're still going to see some transcripts present. I think looking at the single-cell level which we -- which we've started to do, you can actually really see the differences between cells that express high levels of transcripts and cells that express little to no transcripts.
DR. CLAYTON: Okay. Thank you. Another question for Tim. "Do JAK inhibitors affect NFAT the way that they would NF-kappa B?"
DR. HANLEY: We haven't actually looked at that specifically doing chips for NFAT at the HIV LTR and those cells treated with type I interferon inhibitors, but we've looked at NFAT occupancy at the LTR without the presence of those inhibitors. And what we actually see is that there's very little NFAT present at the viral promoter in macrophages, and that's likely because the NFAT sites overlap with the NF-kappa B binding sites, and those seem to be constitutively occupied in these cells, and it's probably preventing NFAT occupancy.
DR. CLAYTON: Okay. And one more question, then I'll move one to the other speakers. "Do you see changes in the transcription factor binding at the ISREs within HIV?
DR. HANLEY: All right. So that's a great question. We haven't actually looked at it in this latency model, but we've looked at it in other contexts. So in the context of co-infection with bacteria that induce strong type I interferon responses, we actually do see changes in IRF binding at the ISRE that is associated with decreased transcription, but we haven't actually looked at that yet in this system where we're really focusing on virus-induced inflammation and its effects on latency.
DR. CLAYTON: Okay. Thank you, Tim. There are additional questions for Tim, but like I said with Fil's talk, we are going to follow up with people individually just to make sure that their questions are answered. But just in the -- to keep time here, we're just going to move on to some questions for Scott. So, Scott, "Does the time of initiation of ART have an impact on interferon resistance?"
DR. SHERRILL-MIX: We don't have direct data on that, but it sure seems like it would. If you initiated ART really, like, during the acute phase, then the only viruses that are circulating are interferon resistant. So it seems like all the outgrowth viruses you get from that patient would likely be interferon resistant, but we don't have direct data on that yet.
DR. CLAYTON: Okay. Another question for you: "Are there any unique features within the genomic sequence of interferon resistance viruses?"
DR. SHERRILL-MIX: Yeah, that's a really good question we've been trying to dig into. It's been tough. It seems like it's not, like, a single signature here that's doing -- like driving everything. It seems like different virus have different ways to escape the innate immune pressure. There's been reports of IFITM resistance and, like, a signature in VPU, but it seems like that's probably just for one or two viruses and not, like, the general -- the general picture. So we've been making infectious molecular clones from a bunch of these viruses so we can start digging in a little deeper doing CRISPR screens and, you know, swapping genes around to try to narrow things down. But it's still a big question, like, what actually is driving this in the genome.
DR. CLAYTON: Yeah, absolutely. Another question for you: "What fraction of MDM sample support replication of standard macrophage-tropic strains, such as YU2 or the GRC SF-like viruses?"
DR. SHERRILL-MIX: Yeah, we're still warming up on our macrophage stuff, but at least in our samples, we had we had healthy -- we had seven healthy donors. Two of them were really resistant to growth even by YU2. Like, three of them were, you know, middling growth, and then two were really permissive where you could just see, you know, a whole bunch of viruses were able to replicate really easily. So I guess maybe two out of seven with our initial data being resistant to growth.
DR. CLAYTON: Okay. And I had a question for you as well. So when you talk about your outgrowth assays, of course, these are all CD4-based outgrowth assays, and I think there's going to be some work highlighted a little bit later on in terms of potential ways to get virus out of myeloid cells from people. So do you think you would see something different with the viruses that are derived from myeloid cells versus CD4 T cells?
DR. SHERRILL-MIX: We might. It would be really interesting to see. I don't know what to predict there. We haven't been able to -- we haven't isolated from macrophages, so it'd be really interesting. We're starting to look into that ourselves, but it'd be great to hear somebody actually doing it. That's going to be a cool talk.
DR. CLAYTON: Yeah, for a little bit later on. I don't want to give anything away at this point.
DR. GUMMULURU: Can I ask a question, Kiera? Is that all right?
DR. CLAYTON: Yeah, go ahead.
DR. GUMMULURU: Scott, so this out -- these rebound viruses that you're seeing that are resistant to interferon, is there temporal differences? So if you were to isolate viruses from earlier in the chronic infection versus later, so is there differences in their susceptibility or is it resistance to interferon? The reason I'm asking is that -- is this a continuum here? Is that what is happening here?
DR. SHERRILL-MIX: Mm-hmm. Yeah, so there's definitely -- when the virus gets seeded, it seems like most of the virus we see in the latent reservoir similar to whatever was circulating just before the initiation of ART, and it seems like we see highly interferon-resistant and acute, it drops and then starts to rise as the patients progress towards AIDS. I don't know -- all these patients were started on ART, but I don't know what would happen in an untreated individual where they really progressed into AIDS, so it'd be interesting to see there.
There was something -- yeah, so I guess that's about it. We're trying to follow up and get more diversity -- oh, that's what I was going to say. So we also have some samples where they let the patients go longer on treatment interruption, so like months of treatment interruption where the virus wasn't going crazy but you could see it replicating. And there -- this is very preliminary data, but it looked like interferon resistance was dropping over the course of the long treatment interruptions, but that's still very preliminary data.
DR. CLAYTON: Okay. Thank you. So we're going to move on to you, Rahm. Okay. "So there is a Nature immunology paper by Kanneganti," that lab "and other work by Hasan Zaki. They've shown that SARS-CoV-2 envelope and spike protein could activate the TLR2 pathways. In your THP1 cells, did you knock down TLR2 to eliminate the effects of engaging this pathway?"
DR. GUMMULURU: Yeah. Also I just want to apologize that text messages are going off, so it's just my kids texting me. Sorry. I can't turn it off right now. But to answer that question, so we looked at the spike activation of these cells, and I didn't show that data -- I apologize for that -- but the spike by itself did not activate these cells, so we don't think it is spike dependent activation of macrophages. Yes, there is data not only from the Kanneganti lab, from other labs as well that have argued that maybe spike is binding to some other lectin receptors, like even DC-SIGN or other sign molecules that might lead to activation of these myeloid cells, like dendritic cells as well, but we failed to observe that. That does mean that this might not be another pathway of immune activation of myeloid cells, but in our hands, we've seen -- almost all of it seems to be dependent on RNA expression in RNA-dependent sensory pathways.
DR. CLAYTON: Okay. Excellent. So we have another question here. "Even low expression of ACE2 could contribute to SARS-CoV-2 infection. Have you treated macrophages with an anti-ACE2 antibody to see if the infection could be inhibited?"
DR. GUMMULURU: Yeah. Yeah, we did that pretty early on, and we failed to see any difference, at least for the lenti pseudotypes. We've really tried hard to look for ACE2 expression on these cells, and this is an ongoing controversy because there is some in the -- there are some reports in the literature already that have claimed to show ACE2 expression in macrophages. Maybe it depends on the type of experimental conditions that you are pursuing in order to differentiate these cells. It's entirely possible. But the ones that we have at this point failed to show any ACE2 expression on the surface.
DR. CLAYTON: Okay. And actually I'm going to follow up with that because that's something that we have looked at, you know, right after the lockdown just out of curiosity. And so how long did you mature your monocytes into macrophages before you looked at ACE2 expression, number one. And do you think it would -- did you have any reason to think that it would go up the longer you left them in culture?
DR. GUMMULURU: Right. So our cultures are all six to eight days post-differentiation from monocytes and presence of human AB serum and MCSF. We have looked at it beyond up to 12 days, but no more than that. We tend to not to use macrophages beyond that in our culture conditions. So there's also reports that ACE2 is an ISG, that it can be inducible by type I interferon, and that is also being questioned now because it looks like maybe it's much more of the -- one of the spliced isoforms that fails to bind CoV-2 S that is inducible by type I interferons. So that's also something that is under consideration. But as -- but, again, as you point out, Kiera, it's possible that longer culture conditions might contribute to ACE2 positivity, but we've only taken it out to two weeks and no more.
DR. CLAYTON: Okay. Excellent. So another question for you, Rahm: "Any ideas how ACE2 -- what the ACE2 independent mechanism of infection," like what's mediating that?
DR. GUMMULURU: Right. So, I mean, so we would argue that this is -- it is this lectin CD169 that is binding to sialylated-S on the surface of SARS-CoV-2 that endocytosis it into an endosomal compartment where fusion can be -- occur through a cathepsin-dependent manner, and that fusion can then result in exposure of and release of RNA into the cytoplasm, which for some reason at this point we are still unclear as to why that does not progress to productive infections. So very interested in identifying what that block to later steps in the virus lifecycle are in these cells.
DR. CLAYTON: Okay. Excellent. So kind of related to your experimental setup here, "How did you select ACE2 expressing MDMs in primary cells," or I guess this would be the monocytes maybe. Is it sorting that you -- that you used, or did you just have a hetero culture?
DR. GUMMULURU: This is a hetero culture. We didn't sort. These were lenti suited -- ACE2 expressed from a lenti vector that was then transduced into MDMs and then looked for ACE2 expression on them. On the THPs, those were sorted for high ACE2 expressors. Those you can make stable cell lines relatively easily.
DR. CLAYTON: Yep. Okay. And then one final question, which I think is pretty interesting. "Are there established CD169 null or SNIP patients, and I was wondering if you were able to assess those MDMs."
DR. GUMMULURU: Yeah, there are. I think there have been reports in the -- previous reports, before CoV-2 where people were shown that there are CD169 null patients. This is work from Javier Martinez-Picado and R.C. Kasia as well as Noriel Esquerdo. And they've shown that there are these patients who they can isolate CD169 null macrophages from. We haven't had access to those cells, but maybe it's worth testing those in this context.
DR. CLAYTON: Okay. Thank you very much, Rahm. I appreciate your answers here. So, Vincent, we'll move on to you. There's a few for you. So first one: "Why did you choose atorvastatin when pitavastatin is currently under investigation in the REPRIEVE trial? Also, do you think choosing a less lipophilic statin, like" -- I'm going to -- I'm going to brutalize this word -- "rosuvastatin would make a difference?"
DR. MARCONI: Yeah. No, terrific question there. That largely had to do with access and availability. We're actually reaching out to get additional statins, especially in light of the use of pitavastatin in REPRIEVE. And I do think actually that more lipophilic drugs could potentially at least get better activity. Whether or not they're going to have a greater difference in either in anti-inflammatory, antiviral effects I think remains to be seen.
DR. CLAYTON: Okay. Excellent. Next question: "Is the risk of cardiovascular disease in people living with HIV on ART still elevated compared to the general population?"
DR. MARCONI: Yeah, that's great question. I think it depends on the cohort that you look at, but most of the cohorts in the U.S. have shown increased risk. So the VA cohort, this is a cohort of veterans, the VAC -- the Veterans Agent Cohort study which had matched HIV negative controls to age, gender, ethnicity, and site, did show an increased risk both through the matched cohort, but also after adjusting for additional covariates that are known to cause cardiovascular disease. So in that population it showed at -- the New York City HIV Surveillance Registry study showed the same, although their risk was primarily within the 25 to 64 years of age showing an increased risk. But then once they got above the 65 years of age, it wasn't as much of a significant difference. And then a famous Italian cohort also looked at this, and they didn't see a difference compared to the general population for either cardiovascular disease or hypertension, but there were higher rates for other risk factors such as dyslipidemia, chronic kidney disease, and type II diabetes.
DR. CLAYTON: Well, I guess a kind of follow-up question I have on that is, for some of these studies when they're comparing obviously your healthy non-HIV-infected group and your HIV-infected group, do they also control for a certain lifestyle factors, like smoking or drinking, anything that would increase the inflammation?
DR. MARCONI: Yeah, great question. In the VAC study they did. They were able to control for -- at least for smoking, and they did have some AUDIT-C data I think they were able to use as well. But not all cohorts have that level of granularity, and so that's all Often left out -- sedentary lifestyle and diet and other things like that -- so it's hard to completely control for that. But I can say in the VA study, this is a population that's already at a higher risk because these are individuals who are only eligible if they are HIV-negative for having, you know, severe diseases, so it's a bit sort of higher risk population to begin with. And even despite all of those risk factors, whether it be illicit substances -- alcohol or smoking -- even still above that, general healthy HIV-positive individuals have higher risk of cardiovascular disease.
DR. CLAYTON: Okay. Excellent. And kind of one follow-up final question. So in terms of, you know, using these drugs to limit the inflammation that's caused by the macrophages, do you think long-term use of these drugs would have any detrimental effects in terms of making people more susceptible to other infections? Like, I know for TNF-alpha blockade, you know, you have to get TB screened, for example, to make sure that your TB won't come up, so that kind of thing. You know, is it -- do you think it's feasible to have people on these kinds of drugs to lower their inflammation?
DR. MARCONI: Yeah, it's a great question, Kier, and I'm glad you asked this. I actually don't think the use of anti-inflammatories for people with HIV needs to be a chronic therapy in the way that we look at statins, et cetera. I actually think there's an imbalance for people with HIV, and also similarly we see in COVID for an individual's ability to clear pathogens, what would be termed immunocompetence and levels of inflammation. This balance is offset. And we see that, for example, the use of JAK-STAT inhibitors, like baricitinib, that this balance seems to reset. Not only is inflammation improved, but actually immunocompetence is improved as well.
And we don't think that probably long-term treatment is needed for that balance to be reset and go into homeostasis. I think once that occurs, if you don't continue stimulation with HIV or other pathogens, it's likely that balance can be maintained after a short-term treatment.
DR. CLAYTON: Perfect. We're at time right now, so it is ready to go to the break. I wanted to thank all the speaker's. It's been a fantastic per session. Looking forward to the next talks. And, again, thank you everyone for your questions. We will get back to you individually. We just want to make sure that, you know, we do address the questions that you do have to the speakers.
So I believe the break is going to be until 12:40, so if everyone would like to get back on in about half an hour, we can start promptly with Session Number 2.
DR. HOPE: I am delighted to have the opportunity to share the session, "Challenges to Studying HIV/SIV and Myeloid reservoir." We have four speakers: Yanique Thomas from Northwestern University, Bhavesh Kevadiya from the University of Nebraska Medical Center, Rebecca Veenhuis from Johns Hopkins University, and Katharine Bar from the University of Pennsylvania. I pass the baton to Yanique.
DR. THOMAS: Thank you, everyone, for the opportunity to present some of my research today. And I'll be talking about how we have been using PET/CT scanning and subsequent multiscale imaging to define the dynamics of SIV infection and rebound after treatment interruption.
So some background on rebound. We have some -- certain principles that we accept within the field about how the virus progresses after infection when ART is involved. So based -- looking at this over here, we see that initially there is a high viral load where the virus then establishes itself and infects many cells and sets up its reservoir. And after a patient goes onto antiretroviral therapy, this viral load decreases to below detectable levels. So at this point, apart from potentially a few blips that may be noticed in testing during ART, the patient has no viremia. There is no viral load detectable, and for all intents and purposes, this virus is being controlled by the antiretrovirals.
Now, what we have, when this person comes off of ART is something that is pretty standard. We have robust rebound of the virus. And the idea that we have been working with for -- within the field of this viral reservoir being made up of a small population of memory T cells that become infected and are able to hold onto the virus and allow the virus to persist really does not match up with what we see when someone who has been on long-term ART stops the therapy and we have this robust rebound. In fact, what we see is, apart from a few exceptions to the rule, the majority of people have rebound happening quite rapidly and quite robustly.
So in our work, we were interested in looking at what was -- what is a dynamic that goes from -- through this rebound when the treatment is interrupted and you have this robust return of the virus, and also to investigate what cell population really makes up this viral reservoir.
So for this, we use a very important tool, which is our PET/CT scanning. The way we're able to do this is we have this antibody, and antibody to SIV, so this study is done using the Rhesus Macaque Non-Human Primate Model. And we amend this antibody by removing the FC portion of the antibody and only using the antigen binding portion of the antibody here. And we label this portion of the antibody with Copper 64. That is the radioisotope that we use for our studies, and that's what allows us to visualize virus or, I should say, virally-infected cells within the body using the PET scan.
So this down here is a schematic of our experiment. Most of our monkeys have been female, so we challenged the monkeys, both rectally and/or vaginally, and four days after viral challenge with SIV, these animals are put on to antiretroviral therapy. They are maintained on a regular daily antiretroviral therapy for about six months. During this period, we do take PET scans using our antibody labeled with Copper 64 to have a look at where the virally-infected cells are located within the whole body of the life animal. At the end of ART, after the six-month period, we stop treatment and we necropsy these animals very close to the end of ART. So our period after treatment interruption is quite short. We have four, five, seven, and 10 days after treatment interruption, then we necropsy the animals and harvest these tissues.
There are a couple of different experiments we did that different from this slightly. One of those is that we have a couple of animals that we necropsy early on ART, so these animals represent the reservoir during the early ART stages. This animal has not gone on for the entire six months, nor has an animal ever been taken off of ART. And then we have the animals that we use for our viremia study where basically, after four days ATI -- after treatment interruption -- we have a surgery where we resect a piece of tissue, and that tissue represents a short ATI period of four days. And then we allow this animal to recover and to go on until we can detect virus in the blood, at which point the animal is then necropsied.
So we use this data in two ways, and the first way I'm going to talk about is a quantifiable approach to studying the reservoir location and the dynamics of the infection throughout the long-term experiment. And in this method I use this specialized radiology software to go in and isolate specific regions of interest. So in this example here, I'm just showing you a monkey where I've isolated the liver, and I can quantify this in three dimensions and take that three-dimensional volume and quantify the radioactive signal within that volume. I can copy that same volume onto every scan we have for the same animals so we're looking at the same region, and see how that -- these values differ over time so we can get an idea as to what's happening as the animal goes onto and comes off of ART.
So what does that look like? So this is one animal, and I'm showing three of the scans. This is an early ART scan -- a late ART scan, so at the end of our six-month period and four days after treatment interruption. And what we're seeing here at the top are PET scans and at the bottom here are PET/CT overlays, and this is representing a cross-section through this region of interest here. So this is a three-dimensional area that I have selected, and this -- in this region we can see that in the early ART stage there is a signal here. It is established. It is a defined signal that I can detect and I can map out using the software that I mentioned before. After six months, you see that this signal reduces to almost background levels, but four days after treatment interruption we see the signal returning to the same area and returning quite robustly in the same area. And this can be seen again in these cross-sections here.
And of course we have many scans, so these were three of the scans, but this is the same animal, and we have six different scans. Four of those are early on ART. One is at the end of ART, and one is four days after treatment interruption. And as we can see, qualitatively, you can see that there are signals and that they fluctuate, but it's good to be able to quantify this data because these are scans that we do have, and this is useful data for us so we can represent it like this.
Now, I'm going to point out one thing; that is, we do not have any scans during this period of time. We have scans early on ART, and we have scans at the end of ART, and in our ATI when we do our necropsy, but we do not have scans here. So I'm not trying to suggest that there is a linear decline from this point to this point, but this is -- basically, what we get out of this is from the early ART scans, we can see that we establish -- this region of interest has a signal that is clear and defined, and that after six months, in that exact region, that signal has diminished. But only four days after treatment interruption, we see a robust return of this signal in that exact volume.
Now, this is not always so well presented. For example, this is another animal and this animal was seven days after treatment interruption. And this one I selected three different areas because -- three different regions of interest because none of them were as obvious as in the previous animal. And as we can see, there is a similar trend where there is a signal established at the beginning that does decline over time and does seem to increase towards our necropsy dates after we stopped treatment, but it's not as robust as what we saw before. So some of these areas are not as well controlled by the antiretrovirals, but this is one way of monitoring this experiment throughout the entire time period, and having more scans here would actually give us more of an idea of what the dynamics are using this PET scanning method.
The second way we use our PET scanning is to help us target our necropsy for the purposes of our multiscale imaging. So we can take a scan of the whole animal here, and then necropsy the animal and scan the tissues, and easily define tissues that have little to no signal, like the brain, or intense signals like the FRT or portions of the intestines. We can then use this to guide us into dissecting these tissues into tiny pieces in order for us to go ahead and use these for sectioning for our microscopy to look for infected cells. And when we look for them, we find them quite easily.
So in these pieces of tissue, this is an example of a piece of heart tissue. This is stained for nuclei and for SIV core protein, and we see here that we can find infected cells within these pieces of tissue when we use our PET-guided necropsy, and we discovered a few things. Some things became very apparent to us immediately, and one of those was that the cells that we see are not T cells. We stained for T cells. In this panel here I'm showing staining for SIV envelope and for CD3, and none of the cells we have found have been CD3 positive. Also all the cells that are SIV positive are of a different morphology. As you can see they don't have that small tight T cell morphology. They look more like myeloid cells. And though there are T cells surrounding these cells, we really do not see, and in all of our tissues we are not coming across a population of infected T cells. In fact, all of our infected cells appear to be myeloid-like.
So another observation that we made, and right now this is what is ongoing, we are attempting to phenotype these cells to figure out what this cell population is that we are finding in these cells that are in early ATI periods and also animals that are on ART. And one of the things that we have found is cells that are CD68 positive. This is a couple -- these are a couple of examples here from this panel. I have them here in black and white showing the individual stainings and then the overlay here in color, and you can see that some of these cells are staining positive for both CD68 and for SIV envelope. So we are finding some infected macrophages myeloid cells.
So in summary, I'm going to say that we found that the PET/CT is an excellent, efficient way of studying long-term experiments monitoring infection over a long period of time in a whole animal system, and it also allows us to effectively target tissues for our multiscale imaging for looking through microscopy and other methods. We've also found that we can find infected cells in these tissues even though the animals are not viremic because, in our experiment, we put the animals on ART four days after challenge, and then we necropsy four to 10 days after treatment interruption. So at no point in most of these experiments are the animals viremic, so we are finding these cells in these tissues of these aviremic animals quite easily using the PET.
And lastly, the infected cells are not T cells. We are not finding any infected T cells, and they all seem to display a myeloid morphology. So currently we are working on identifying and phenotyping these cells fully, and that is what I wanted to present for you today. So I think I was really good on time. I didn't want to go over, so with that I will say thank you to everyone who's involved in the project and everyone for giving me a chance to speak today. And I will pass it on to Bhavesh. Thank you.
DR. KEVADIYA: So good morning. I would say really good afternoon for everyone because it's Eastern Time, everyone. Today I am going to talk on the HIV theranostics.
What is actually HIV theranostics? The term "nanotheranostic" is combination of three word: nanotechnology, therapy, and diagnostic. Nanotheranostic hold great promises because of the combination of diagnostic imaging and treatment of the disease with exciting possibility of the monitoring in real-time drug release, distribution, and, thus, validity and effectiveness of therapy. We are working toward the common goal in mind at UNMC and the multidisciplinary approach toward the HIV program. That include conducting long-acting individual therapy, theranostic gene delivery, pharmokinetic and (inaudible). Altogether, all our technology we're testing the humanized mice to monkey.
Why so much nanotheranostic is important for HIV? Here are key bullet points. Antiretroviral drug by diffusion imaging, define the viral reservoir by imaging, writing migration of CD4 positive T cells and macrophages in the tissues, image-guided delivery of the antiviral drugs, gene and monotherapeutics, monitoring of the HIV elimination process in the real time by using molecular imaging technologies.
For HIV, as you know, as I explained it, HIV infections microphage in T cell our primary cell and tracking of T cell is very important. So nano probes size, chip composition for microphase. On the left panel you see both imaging particles for tracking by distribution of formulated antiretroviral drug particles. Use of this particle in parallel allow us to track drug effect using imaging technology and conventional pharmacokinetic and biodistribution. Our previous study, we have shown the microphage more effectively affect rho-shaped particles compared to spherical particles compared to spiracle particles. Based on my work today I am presenting, I use of the rho-shaped particles to maximize -- the maximize -- macrophage effect and showing the real-time biodistribution by molecular image.
So one of our latest study we show there, Rocha nanoparticle higher uptake, and here we use the Bismuth sulfide as an imaging contrast agent and RPV as therapeutic particles. Both particles operated in parallel, and both particle are similar size, shape, and have imaging carrier, and second was selected as a therapeutic proposal. Both particle injected into animals, tested both therapeutics and imaging capability through the pharmacokinetics, biodistribution using molecular imaging technology. And finally, both data are evaluated through multiplex imaging. You can look at the right side of the panel here.
So how we created this nanoprobe. You can look at the top panel that -- like, for imaging prop. For example, we used metal precursor plus with the radioisotope intensity radio level. We have developed a unique technology that has developed the radioisotope very stable and unique, and it's not letting out. And uniformed radio particles prepare it, and we file it and keep it to further test the biocompatibility in the cells animal. Second type of particle -- we can look at the down list -- therapeutic particles. We use the recovery as antiretroviral drug mixed with the poloxamer with higher-pressure homogenization to create the unique nanocrystals, and also is biocompatible.
So before we could work this particle for biological testing, we had to make new state-of-the-art characterization. If you look at the left side panel showing the imaging of the particles where -- imaging particles where the right section in the panel, the therapeutic particle characterization. So imaging particle with thoroughly state-of-art characterization like high-resolution transmission, electron microscope, single crystal, elemental mapping, X-ray diffraction, elemental distribution, size, (inaudible) properties, hydro and (inaudible) lipid-coated particles, their property hydrophobic -- hydro-felicity, and is compared next to nano-formulated drug particulate if you look at the bottom panel of this.
And we also found that imaging particle right size, shape, composition, and it's closely matched with the characterization beta. The right side of the panel at the top, the atomic force microscopy, transmission electron microscopy of the therapeutic particle mimics same size and same shape, and size and shape PDI, and reduced the ability of us assessing the different medias and, like, texture that is not letting out and highly stable shown in the table.
So further, next.
After the (inaudible) synthesis of particles we tested, like, in vitro. So in order to test, we did the in vitro tests to determine appropriate dose as well as difference in both particles, in vitro toxicity of the particles in human macrophage cells, and we count particle that are non-toxic if you look at the top panel. And the second panel, also if you look at the in the visual particle -- visual assessment by staining, microphase in particle, you can look at the blood found in the cytoplasm of the microphage and compared to controlled particles -- controlled cells. And one microphase particle uptake retention we've shown time and concentration-dependent cells, and observation of further validity of the correlation with the data if you look at the right top panels. (Inaudible) and transmission electron microscope further validate, each and every cell picking up this particle and harboring it and stay inside the cell longer period of time and is non-toxic. And we found that behavior pattern of the imaging particle are closely matched with the theranostic particles or the therapeutic particle in macrophage.
So further, we validated the functional -- next. Yeah.
Now, after characterization, further we validated this particle functional activity. So in order to test it, we loaded the theranostic particle with the antiretroviral activity and therapeutic particles parallelly. So in order to test the antiretroviral activity, we tested in the macrophage. Antiretroviral activity of particle was determined in macrophage with the drug-related particle, then infected with the HIV challenging, and HIV provider very own production was determined by p24 staining. You can look at the violet color. Staining is p24 staining. As you can see, that compared the drug treatment, theranostic particle (inaudible) and control cell are looking -- theranostic cells look similar. So it's holding that theranostic activity or therapeutic activity and antiviral activity of the -- compared to positive control in the left-hand panel. There is infection cells of the macrophages in different time intervals.
So further, after the in vitro characterization, we went in the -- further test in animals. So we further tested this particle in vivo for real-time biodistribution multimodal in mouse studies. So we use here -- spec CT imaging was used to assess the biodistribution of (inaudible) of particles. So you can look here in the top panel, left panel, whole body spec CT imaging were collected at various time after injection, and we found the particle in earliest standpoint is depreciated in the liver, and over period of time, particle transported it from the liver to lymph nodes, spleen, and GI tract, and other lymphoid organs. And this further confirmation, if you look at this Panel C, that autoradiography imaging show the accumulation of particle in the liver tissue was decreased over a period of time, and increase in the spleen, vice versa, in the same way with quantitation of the dissected tissue that run the gamma circulation spectroscopic quantitation analysis showing the similar result, a significant higher number of particles because deposited in stream over a period of time compared to liver.
The spec CDT-dimensional imaging in vitro, the ROI volume of each and every organ and quantitation by viral imaging and found a similar result. In short, it indicate this -- like, this particle is behaving and taking macrophage and depositing in the liver, in lymphoid tissues. And here is proof of principle -- also we publish in Theranostic -- that we tested the similar kind of particles for different contrast areas and tested in the red and rhesus macaque and found that similar matched result with the rho-shaped particles. And here in the lower panel, you can look at the monkey data. The main driving force, we are taking a particle by macrophage from circulation and deposit it in the macrophage lymphoid tissues. In short, this study we're showing the imaging particle biodistribution is closely matched with the therapeutic particles behavior in vivo, of course, over time.
So next. Next. Yep. Next.
So cellular distribution of particle, we want to see that. Where is the particle exactly located in the particular tissue or organ? So we select the spleen because, based on the in vivo data, we collected the spleen, dissect it, and prepare the slide and run the mass spec imaging. So cellular distribution of particle post-investigation by mass spec imaging by the slow staining, and the result indicate the particle deposited in spleen to (inaudible) on day five compared to day two. Further, distribution of particles patterned in marginal zone of the spleen was much higher compared to distribution in white pulp and red pulp of spleen.
So quantification, if you look at the lower panel here in the quantitation data that showing that -- quantitative data show that marginal zone has a higher number of particles if you compare it to other part of the counterpart of spleen that indicate the maximum number of microphage located in the marginal zone compared to white pulp and red pulp, that indicate that particle is further confirmation in taking up the different part of the body and deposited in microphase reach environment of the lymphoid tissues.
So further we validated this -- our observation by dissecting the -- each and every tissue, particularly liver and spleen. For example, we run the transmission electron microscope, and we found that particle is located in the microphage of the tissues. So if you look at the -- compare day five and day two, liver and spleen with significantly higher number of particle deposited in the endosomal compartment of the spleen of the macrophage. And it stay up to day five in the rho-shaped particle, if you look at the black sunk of the particle deposited in the macrophage cytoplasm, compared to liver.
So after this imaging validation, mass spec imaging, and transmission electron microscope ex vivo analysis, further we're down to pharmacokinetics and biodistribution. In order to do that, we dissect each and every organ, run the mass spectrometry analysis and imaging analysis, coordination each and every data of the nano-formulated particles and multimodal imaging particles, pharmacokinetic and biodistribution pattern of obtaining each and every particle, if you look at the right side panel, comparable therapeutic particles. And data is fitted in the multiplex data analysis. When you look at the ribbon-shaped graph from the top to down, A, B, C, is the liver, spleen, and lymph node, it's showing that data is closely tied and observation is likely matched with the -- closely with the therapeutic particle, drug particles, where this drug is going, where the imaging is showing. So this result are cross-validated by statistical models, by framework, predictive assessment of the drug biodistribution, and activity in impacted host.
So then after the particle creation to testing in the animals, and then you can ask me that -- why is particle looks good. This particle is safe or not? So in order to test particle toxicity, we select the toxicity assessment. We measure major organs -- liver, spleen, and kidney -- and compare with the treatment and non-treatment group. And we found there is not significant damage of the -- any organs after treatment of the particles the same as control treatments. So particle is safe, reliable, and is used further for the next approach.
So in summarize -- next slide.
In the summarize, we established and published so many studies on the nanoprops, imaging props, combined with the antiretroviral therapeutic agents, characterized and then tested in vitro and in vivo, real-time imaging of the macrophage in T cells by non-invasively. And now, next phase of the therapeutics, we are targeting, like, a gene therapeutic of the HIV eliminations. The next phase of the nanotheranostic work, transition from the nano delivery -- antiretroviral delivery -- to gene delivery. We are aiming to use theranostic particle applied to then imaging-guided CRISPR therapeutic particles. And here, what we did, we created similar kind of (inaudible) based on (inaudible) label thoroughly characterized in vitro, in vivo. And further, we designed our own guide RNA through therapeutic that particularly target the broad spectrum of the HIV virus strain and successfully cut down the virus-integrated genome from the host genome.
So the mRNA form of the CRISPR therapeutics combined with the imaging agent, and in cases with the special type of the lipids, particularly bad lipids, healthy lipids, structural lipid, and particularly, cationic lipids that grossly, strongly complex session with the mRNA therapeutics and successfully encapsulated in the microfluidic channel. And we in case with this type of the particle, gene therapy target, and this uniqueness of particle that precisely we can locate by the multimodal imaging technology, and also simultaneously it show the -- shown the -- it dissect the virus genome from the host. And this type of the work, if you are interested, you can attend that tomorrow. My collaborator present, Dr. Howard Gendelman.
And last, next slide. Next.
Last, I would like to thank my excellent team members and students. Special thanks to my collaborator, Howard Gendelman. I would like to thank funding agencies support my research work. If you have any question, I'll address now or reply to (inaudible). Thank you.
DR. VEENHUIS: Hi, everyone. I'm Rebecca Veenhuis, and I'm -- I will be presenting about monocyte-derived macrophages that we have harvested from ART-suppressed HIV-infected individuals, and that they can contain reactivatable HIV. And the focus of the talk will be about a method we've developed in order to be able to detect the reactivable HIV.
So I don't need to tell this group, but obviously our largest barrier to HIV exists as the fact that there is a reservoir that cannot be eradicated by ART alone. This was shown early on in primarily CD4 T cells with further data that showed that the barrier not only exists, but ART alone would take decades in order to actually make the reservoir get smaller in CD4 T cells, and this was shown primarily originally by the Siciliano group. But there's a lot of data only focused on CD4 T cells and not how some of this applies to macrophage cells or myeloid cells of origin.
So we know that ART initiation in CD4 T cells reduces immune activation and dysfunction. It leads to CD4 levels that recover over time and obviously an establishment of a latent viral reservoir. But in macrophages, as a few individuals have already said earlier on in this talk or earlier on in the session, it's not clearly defined exactly what ART does to macrophages. We don't know how well ART penetrates all macrophages, if it's as effective in macrophages as it is in T cells. We do know that it reduces immune activation in general and it produces a lot of dysfunction of macrophages, because with the initiation of ART, we see milder forms of myeloid-associated issues, such as HIV neurocognitive disorder. But we also suspect and are pretty certain that there is an establishment of a latent reservoir in macrophages as well as CD4 T cells with the initiation of ART.
So how would the establishment of the HIV myeloid reservoir potentially occur? Well, there are possibilities of HIV-infected monocytes traveling in the blood into the brain, crossing the blood-brain barrier, and then differentiating into perivascular macrophages, which then infect resident microglial cells. There have been reports of monocytes that can travel through the blood and into lymph -- excuse me -- lymphoid organs, become infected there, and then leave those organs back into the blood as intermediate or non-classical monocytes. And then there's the possibility of a progenitor in the bone marrow that is infected with HIV because of high levels of CCR5 expression that then leaves the bone marrow and enters the blood as an HIV-infected monocyte. Regardless necessarily of the avenue in which monocytes can become infected, they do likely travel from the blood and enter tissues where they can infect tissue-resident macrophages and potentially develop a long-lived tissue reservoir of myeloid origin.
So the Retrovirus Lab at Johns Hopkins has elucidated a lot of the macrophage reservoir using SIV macaque models. We've used two models, one that is a an SIV model of neuropathy, and another one, SIVmac251, which is supposed to be more akin to HIV infection progression on its own without a rapid neuropathy component. And we've shown that both in the brain and in peripheral tissues, macrophages isolated from these tissues can produce replication competent virus, ex vivo, an QVOA form of an assay. But the large question still remains whether or not this translates into ART-suppressed HIV infection.
I don't have to tell most individuals on this call that limited access to relevant tissues plays a very big role in this. We have a difficult time getting access to brain, and to lung, and to spleen, and even bone marrow of HIV-infected individuals. But there are a lot of historical data that point to this being a relevant reservoir. HIV DNA has been found in brain tissue postmortem primarily in macrophages and microglial cells of origin. HIV DNA is found in monocytes isolated from blood from ART-suppressed individuals. Even the most stringent purification techniques can find HIV DNA in blood monocytes, though they're just definitely not as readily found as in T cells, but it's there.
Myeloid-associated comorbidities throughout ART suppression still occur -- cardiovascular disease, cancers, HIV neurocognitive disorder, and neurocognitive impairment -- and it's not abnormal. Other lentiviruses infect monocytes and macrophages leading to the development of lentiviral reservoirs with other viruses. So the fact that a lentivirus infects the macrophage, produces a viral reservoir in a macrophage is not an abnormal phenomenon here.
So our group sought to develop a quantitative viral algorithm assay that was myeloid specific. The bulk majority of data out there are taking myeloid cells and putting them into a CD 4-centric assay as opposed to developing an assay specifically for this cell type as monocytes and myeloid cells are very different than CD4 T cells. So in order to do this, we received blood draws from HIV individuals. In the case -- the data I'm going to present are 10 ART-suppressed males who have been suppressed for a minimum of two years. We then isolated PBMCs, selected CD4 T cells from half of the PBMCs and then monocytes from the other half. And I'm not going to spend time focused on the CD4 QVOA because it's your standard CD 4 QVOA, but I will spend a little bit of extra time focusing on the myeloid QVOA assay and what we're calling the MDM QVOA.
So from our selected monocytes, we take some to set aside for RNA and DNA analysis and flow cytometry, and the remaining get plated at limiting dilution. These cells are then cultured in M-CSF and antiretroviral media so -- for seven days so that they can differentiate from monocytes into macrophages. And this is key as the bulk majority of the literature out there take monocytes and activate monocytes immediately and then look for viral outgrowth and don't see anything. So allowing them to differentiate into macrophages has -- is a key aspect of this assay. After seven days, we add MT-4 cells to amplify viral outgrowth signal and PMA to activate the cells. We then collect supernatant and re-feed the cells every three days for 12 days. At the end of the assay, we collect all supernatant and cells. And I'll go into a few key details of the assay now.
I alluded to the fact that differentiating into macrophages is key. We have data from individuals where we isolate CD4s, monocytes, and then differentiate monocytes into macrophages, and provirus is very difficult to detect in monocytes alone. However, in monocyte-derived macrophages from the same individuals, we can readily detect provirus. So the data in monocytes matches a lot of what is seen published already in the literature in that other individuals have a very difficult time detecting viral DNA in monocytes. But in monocyte-derived macrophages, we see a major increase in our ability to detect the DNA.
Other key points are that we use RNA as a measurement output and not p24. The reason for this is because macrophages are not like CD4s in that they don't massively proliferate, creating more basically, like, fodder for the flame to produce more and more virus in the -- in the system. They are slow growers and they produce some virus that gets amplified by MT-4s, but we don't have a massive proliferation of cells leading to a huge output of virus. The virus does require to be measured by RNA as opposed to protein, and we do further steps later in the assay to prove that It is actually replication competent. We also isolate macrophages from one of our control wells, which only contain macrophages, to look at DNA and RNA from the cell-associated -- cell-associated DNA and RNA.
The other thing I'll point out is that we have a lot of purity analysis built into the system specifically because we need to prove that we were just looking at myeloid cells and not the possible contamination of T cells. The first thing we do is we set aside cells for flow cytometry. We look at cells that express TLR2, which is an excellent marker for monocytes and cells that are negative for TLR2. The negative TLR2 cells, we look for a CD3 positive and then CD4 positive to determine what percentage of cells when we plate are actually CD4s and potentially adding to our signal.
The next thing we do is we also look in our TCR control wells, and they're called TCR control wells so that we can look for the presence of CD4 spread in our -- in our control wells after the assay to see if there were any CD4s present that could contribute to signal. And we look for TCR beta RNA as well as CD3 RNA to determine if there are any CD4 cells present once we differentiate. So we use these measurements in addition to measuring the IUPM and CD4s from the same individual at the same blood draw to calculate a percent chance that an infected CD4 is present in our MDM-QVOA wells.
So to go into the data, as others have seen and is expected, CD4 cells have low levels of gag RNA, very low levels of TAT/REV RNA, and high levels of gag DNA, and these are from the 10 male individuals who have been on ART for a minimum of two years. And those same individuals, when you take monocytes and differentiate them into macrophages, we see very low levels of gag RNA, TAT/REV RNA, but comparable levels of gag DNA. So when you compare the CD4s and the macrophage gag DNA levels between individuals, they are very similar. Some individuals were run multiple times to be sure that we were getting a reliable measurement, and in those cases, they are shown in the same colored dots. At the same time we looked for TCR beta expression in the monocyte-derived macrophages and found very little to no T cells present in the wells. So this is not being driven by a CD4 signal. This is actually the signal coming from the MDMs.
Okay. Sorry. The slide didn't change.
So next, when we look at reactivatable reservoirs, we see that nine out of 10 individuals, we were able to reactivate CD4s to produce virus in the in the CD4 QVOA, whereas five out of our 10 individuals, so about 50 percent, we were able to activate the monocyte-derived macrophages to produce virus in the QVOA. Overall, we used large amounts of cells in the QVOA because our best chance of actually detecting an infected macrophages is put as many cells as you can. And a bare minimum, we put about five million cells into the assay, but we try to aim for closer to 10 million when an option. We also do this so that it can significantly lower our limit of detection and our likelihood of catching a positive signal.
So of the five individuals that had positive IEPMs in the MDM QVOA, we were able to bring three back, and these visits are between six and nine months apart from each other and repeat their QVOAs. In one case, one individual we were able to repeat CD4 QVOA, and in three we repeated both the MDM and CD4. I'm sorry. One individual we repeated CD4 and macrophage. In the other two we just repeated their MDM QVOA, and we saw that at two different timepoints, we had detectable viral outgrowth from monocyte-derived macrophages of the same individual six to nine months apart. So it wasn't just a one-time fluke.
I alluded to this earlier, but when we calculated the likelihood that CD4s were contaminating our wells, we had very, very low percent chances that that was the case. One sample actually had an almost a .1 percent chance, but it was actually a sample that had a negative -- that had no detectable virus in that -- in the QVOA well, so it was not due to contamination. Additionally, we took supernatants from the positive QVOA wells, and we spinoculated activated CD4 T cells from a healthy donor. When using normalized amounts of virus, we saw that the viral outgrowth occurred relatively similar between both the positive CD4 QVOA wells versus the positive MDM QVOA wells, with only one individual actually going into logarithmic growth. But this is likely due to the sheer that we put in so little input. But three out of our five positive QVOA wells did continuously grow for the 21-day infection. One started to grow but then sort of petered out.
And if you break it up and look at each individual, you can see that viral isolates do differ. So we had multiple positive wells from one individual's QVOA we would infect with every positive well, and in some cases they would continuously grow. In some cases they would grow and then they'd sort of sputter out, and this was observed in a couple of different individuals. And in some individuals, the virus would not grow out from the MDM but would grow out from CD4 QVOA. So there was a lot of difference in the viral isolates that we observed.
So the final thing that we did was we looked at viral sequences, and this is NEF sequencing from MDM and CD4 QVOAs, and we saw that they do group from -- so the mom the MDM QVOA is grouped together and the CD4 QVOA is grouped together from the same individual, and each individual groups with itself as expected, but that the sequences do differ in the monocyte-derived macrophage QVOAs compared to the CD4 QVOAs. It's not necessarily that we have CD4s contaminating and producing virus that's very similar to the other CD4 virus, but there was a lot of difference observed.
So with that, in conclusion, monocyte-derived macrophages likely do constitute a latent viral reservoir. We've shown that MDMs from long-term ART-suppressed individuals have equivalent levels of HIV DNA compared to CD4 T cells. They have little to no HIV RNA expression, can be reactivated to produce virus in a QVOA as long as that QVOA is developed for their cell type, and can be -- and contain different proviral sequences, though I didn't have time to show that data compared to their CD4 counterparts. And then we've also shown that MDM reactivable virus is replication competent. It can infect activated CD4 T cells, so it could lead to further spread in an in vivo system. The sequences do differ when comparing virus produced by the CD4s isolated from the same individual as the monocyte-derived macrophages.
And with that, I'd really like to acknowledge especially the participants and Dr. Joel Blankson of Infectious Disease at Hopkins. He was able to get me the participant samples. And then I'd like to highlight Janice Clements and Lucio Gamma. Celina Abreu has been completely my counterpart in this. We have worked on this together very closely. And then I'd love to thank the technical help of Erin Shirk, Janaysha Ratcliff, and Ferreira. I'm happy to take questions at the end. And with that, I will pass it on to Katharine Bar.
DR. BAR: Well, thank you very much for the opportunity to present today. This has been a really fun group of talks so far, and I'm excited to hear more discussion.
So for the -- for the past few years, myself and collaborators have been working on developing a transmitted SHIV model of persistence, systemic persistence, so that we can understand reservoirs and test cure strategies. And more recently, we've adopted this model to try to look at CNS persistence, and so here, what I want to talk to you about today are some data validating one particular SHIV as a potential model for CNS persistence.
So when do we think about a model of CNS persistence for SHIVs, there's three -- sort of three goals that I think are really important. First, we want to be able to encode authentic and relevant HIV-1 envs, so either transmitted founder viruses, primary viruses, or some envelope that's relevant to whatever your experimental question is. Second, we want to recapitulate key features of HIV-1 immunopathogenesis. We want to see appropriate viral kinetics. We want to see depletion of CD4 T cells within the tissues, systemic symptoms, and appropriate adaptive immune responses. And then finally, for a CNS model, we want to be able to show infection and inflammation within the brain as well as persistence on antiretrovirals.
So as many of you may be aware, our TF SHIV platform is based on the goal of expressing minimally-adapted HIV-1 envelopes. And so the strategy to do this is to modify just one position, 375, with an envelope. This position is very important for CD4 binding. It's found within this phenylalanine 43 cavity, and it was seen looking at sequences across HIV-1 group M, that this virus is -- that serine is highly preserved -- conserved across HIV-1 group M, whereas in SIVs, we see largely larger hydrophobic amino acids in that position. And so by making this chimeric virus with an SIV backbone and HIV 1 envelope with just this mutation at 375, we're able to represent this HIV-1 envelope, but have much more effective replication within CD4 T cells from rhesus macaques as well as, you know, in vivo in these animals.
And so if you look here in a virus in the SHIV-D virus where we have either serine or these hydrophobic amino acids, you can see the serine replicates quite well in human CD4 T cells but is much more limited in rhesus. And these other -- these other amino acids confer replication or rescue replication within the rhesus cells. However, it's difficult in vitro across multiple donors to pick out exactly which one of these amino acids is context dependent or best, and so we look to a competition experiment within animals to sort of help us discern which is the most effective replicators. And this is the way we choose the specific mutation at 375.
So I'll just mention that in the past year or two we've developed some new adaptations to this platform because if you look at animals replicating over time and you look at their sequences, these viruses tend to sort of fix a couple of issues, some redundance sequences within TET and within REV by sort of deleting those redundancies. And so what we did is we took our backbone and incorporated these deletions so that it's ready from the get-go. And we see, in fact, that if we compare the old and the new version, which has the same on the cassette, but slightly different border regions, we see the new version outcompetes the old version but maintains the same antigenic confirmation. And so that's the platform that we're moving forward with.
And so with this platform, we have many, many distinct TF SHIVs. We can derive these in sort of authentic CD4 T cell-derived stocks that are highly infectious and quite nice for various mucosal inoculation strategies. We can also transfect 293 T cells and do things like genetic barcoding or make different mixes of unique stocks in order to have lots of experimental flexibility. But with these viruses we've been able to show really consistent virus replication, and we have a large body of work suggesting that we have really authentic immunopathogenesis as well. And I'll just mention one study that was published earlier this year by Ryan Roark and his colleagues in George Shaw's lab, which shows when you compare the virus evolution and the autologous antibody responses in the human from whom the transmitted founder virus was initially identified, and multiple outbred rhesus macaques infected with a SHIV encoding that envelope, you see identical patterns of virus and antibody evolution. And so these parallel viral and immune responses sort of indicate the authenticity of this -- of this SHIV to display that HIV-1 envelope.
Okay. So moving on to the specific virus that we're using for the CNS model. So SHIV.D.19859, or what I have been calling SHIV-D, this encodes a Clade D transmitted founder envelope that was identified from an acutely-infected Ugandan women about 10 or 15 years ago. So this virus is CCR-tropic, but like many clade D viruses, it replicates efficiently in both CD4 T cells and monocyte-derived macrophages.
So what I'm showing here is early viral kinetics from a recent experiment with this virus, so we're just looking at the first few months of infection. But what you can see in three different types of, you know, mucosal inoculation strategies is we see nice peak viremia, a nice early set point viremia, and sort of this desirable range that recapitulates what we see in the majority of people living with HIV. So what we've done in the past couple years is validate this specific SHIV for persistence on antiretrovirals. So what I'm showing here is a two-year experiment where we took 18 rhesus macaques and we IV inoculated them with a barcoded SHIV-D, and then we went through successive rounds of antiretrovirals and treatment interruption with antibodies. But what I want to highlight is the persistence on antiretrovirals.
So you can see early that we have -- we have nice peak viremias, and over the first four months of infection, we see a range of set points about 1,000 to a couple hundred thousand, so sort of what we see in most sort of normal progressors. We started in antiretrovirals, and within three to four weeks all of the animals are suppressed. They maintained suppression through six months of treatment. And then upon treatment interruption, and, again, some of these animals were treated with antibodies and some weren't, but eventually all of these animals experienced virus rebound. They reactivate with multiple -- with polyclonal virus, so we see multiple cells reactivating from latency to establish systemic replication during rebound, and then we go on to have persistent viremia. If we do another course of antiretrovirals, and this antiretroviral course was a bit prolonged given COVID restrictions. But after nine-plus months of antiretrovirals, if we interrupt therapy again, we see these viruses reactivate once again. And so we feel that this is a nice validation of this virus being able to persist long term in these animals on successive courses of antiretrovirals.
So one more experiment showing should SHIV-D persistence in animals, this is six animals that were first vaginally challenged and then IV challenged for the remaining two animals. They were allowed to replicate over six to 18 months before they were given a course of antiretrovirals, and all of the treated animals had virus rebound. We were able to show that they had, both before and on, ART levels of viral DNA that just dropped a little, and we characterized rebound virus. But what I want to talk about with these are the studies that we've done looking at the brains in these six animals.
So this was a collaboration with our colleagues down at Tulane and their Primate Center, and we worked together to develop a method to make sure we really flushed all of these tissues -- these brain tissues with PBS in the process of the necropsy so we can distinguish blood and tissue viruses, and really have, you know, CNS immunohistochemistry of the tissue, specific virus. And we were also able to necropsy these animals at different stages of infection. And I've tried to color code this here, but we have two animals that had pretty high level of viremia and Progressive Symptomatic Simeon AIDS -- EJ94 -- in orange and DE33 in blue. Those two animals were necropsied with this high level of viremia.
Another animal was written necropsied with viremia FE43 here. We have a fourth animal necropsied after spontaneously controlling virus, so this animal had about a six-month period of viremia before only small blips of infection and mostly spontaneous control. And then we have two animals that experienced several years of viremia out before being suppressed, again, on antiretrovirals and necropsied on suppressive antiretrovirals.
So if we look at those tissues, and I've left the little code up here, so hopefully you can remember which animals I'm referring to. But first, if we look at EJ94 which was an animal, again, with progressive disease, high level of viremia. And when we look at the brain tissues from multiple regions, from the frontal cortex all the way down to the brainstem, we can see looking at CD68 or macrophage staining that we have lots of inflammation within these brain tissues across all of these sections. In our viremic animals that were less viremic, less progressive, we similarly see levels of inflammation and smaller lesions throughout all these tissues, but it's markedly less sort of inflamed than our one more encephalitic animal. And then finally, in our animal that had spontaneous control, we see much lower levels of inflammation and mostly sort of perivascular cuffing or macrophage staining in the perivascular regions.
Now if we look at RNA scope for these -- for this shift virus, what we can see in our EJ 94 animal, again, is really frank viremia -- sorry -- frank replication in this encephalitic animal. However, in our three other animals that were either -- that were sampled either viremic or not on antiretrovirals, we see consistent staining for SHIV RNA, but more sparse and punctate viral RNA present throughout the tissues as opposed to this really overwhelming virus replication.
So if we dig into where these viruses seem to co-locate -- to co-localize, when we do microglial and RNA scope staining of the same sections, we can see that our RNA really localizes to the microglia and slightly less frequently to the macrophages. We've done some astrocyte and CD3 staining, but we have yet to see co-localization with those -- the virus and those cell types in the brain, but that work is ongoing.
So, again, when we look in these viremic animals, we see evidence of inflammation with macrophage staining. We see evidence of fairly high-level RNA staining throughout these tissues. And when we look at our two animals that were suppressed on antiretrovirals, we also see persistence of that macrophage staining or inflammation, and we see persistence of RNA, in fact, but at a much lower level. We have done DNA scope. It's a little bit more technically challenging for us, and we have -- we're working to get the resolution a little bit better. But when we do sort of quantitative PCR for cell-associated DNA throughout these tissues, we do see reasonable levels of cell-associated SHIV DNA across sections in our two ART-suppressed animals. And if we look in the tissue sections of these ART-suppressed animals, again we see that the RNA co-localizes with the microglia, and we have not seen it co-localize with other tissue or cell types at this point.
So in summary, SHIV-D encodes transmitted founder clade D envelope. It is R5-tropic. It replicates well in monocyte-derived macrophages as well as CD4 T cells. SHIV-D recapitulates key components of systemic immunopathogenesis. So we see desirable viral kinetics, we see induction of HIV-specific adaptive immunity, and we see eventual simian AIDS in a portion of our infected animals. When treated with antiretrovirals, we see this virus persists and we see polyclonal rebound consistently upon treatment interruption.
We also see that this virus, SHIV-D, leads to virus replication and inflammation in the central nervous system. We see this primarily within the microglia and perivascular macrophages, and we see that this infection persists in the CNS on antiretrovirals. We see persistent inflammation as well as low-level cell-associated RNA and DNA. And so for us, we feel this has met our criteria for this model of CNS persistence, and so we're sort of excited to move forward to further characterize persistence in the CNS as well as to test some various strategies.
So future work will be to -- or ongoing work will be to really continue to characterize and define these reservoirs, both systemically with a greater attention to macrophages in the rest of the body as well as looking at -- to better characterize over longer periods of antiretrovirals and with more diverse staining of the brain tissues in these ART-suppressed SHIV-D-infected rhesus macaque.
We're excited about the ability to assess curative strategies, and we currently have collaborations with several groups. Most notably, I should mention Tricia Burdo and her group at Temple University with whom we have one of these lovely myeloid reservoir grants to be able to really characterize these reservoirs and look at her CRISPR Cas9 eradication strategy, as well as collaborations to look at CAR T cells and antibodies. And we're excited to continue with this work. So finally I must acknowledge again Trisha Burdo and her group at Temple as well as the Tulane and Yerkes Primate Centers for sponsoring these studies.
And with that, I will pass this back to Tom Hope and look forward to taking questions in the near future.
DR. HOPE: Thank you very much, Katie. And so we do have a number of questions. They were four excellent presentations. The first question is from Henry van Brocklin to Yanique, and it's, "I may have missed this, but what is the antigen that you are targeting with your labeled antibody fragment?"
DR. THOMAS: So the label antibody is based on an antibody called p73. It is actually targeting the SIV envelope protein, so that is what we're using for our copper-labeled antibody for the PET.
DR. HOPE: Thank you. All right. And then We Li Kang wrote, "Did you look at the infected cells in the CMS of the of the monkey, and were there any positive cells microglia, et cetera?"
DR. THOMAS: So we have not looked at the CNS yet. We do have those tissues. The reason why it was not necessarily prioritized is because we were going off of the PET-guided necropsy, and PET guided -- using the PET to guide us to where we were going to look further with our microscopy. And so because the CNS never had any signal, we did not prioritize it. However, we do have those tissues, so eventually we will get to looking at that.
DR. HOPE: Thank you. And Rob Gruman asked if you found any viral RNA in these tissues at six months.
DR. THOMAS: So the tissues, of course it's going to be hard with the way that we're necropsying these animals to get good quality RNA from those tissues. But we are doing PCR on some of those tissues from our frozen sections and looking at that as another way to confirm. So we are looking for gag RNA to confirm that, in fact, we do have infected cells in these pieces of tissue so that we can say by PET, by PCR, as well as by microscopy we're seeing these infected cells.
DR. HOPE: All right. And then Norman Howdie asks, "Any comment on what types of cells you think are infected in your SIV model, and what are the -- you know, what are the CD8 and not T cells?"
DR. THOMAS: So this we do not know yet. We are in the process of trying hard to phenotype these cells. We've looked at quite a few markers, and so far, when it comes to what we're seeing, we're seeing somewhat of a mixed bag of cells. We have seen -- we've looked at CD11b, CD11c, CD68. We are trying to figure out what these cells are, but we -- hopefully we'll have more answers for you at some point in the future, but phenotyping is at the top of our list of things to do because we need to know what these cells are. But we have seen the morphology of them and we have seen that they are not T cells, so that's the two definite concrete things that we can say about these cells so far, that cell population.
And also we are looking at -- like I mentioned in my presentation, we do have some animals that are a bit different from the basic experimental setup. So we do have animals that -- we are still looking through all these tissues of course, but we have animals that we allowed to become viremic, and we have animals that we necropsied while they were in the early ART stages. So it's going to be interesting to see what those populations look like when we finally get to looking at all of these tissues and understanding what the dynamic is between these different parts of the lifeline of the experiment basically.
DR. HOPE: All right. And one last question is, "You mentioned you didn't see any infected T cells. You said that again, which is quite remarkable. Do you have any idea why this might be the case?"
DR. THOMAS: We have a few things going on with this experiment. One of those things is that we have a very short period of time between our initial challenge and when we put these monkeys on ART. It's four days. It's a very short window. And though we do see infected cells, we are thinking that, and this is something that we have in the works looking at experiments where we wait longer before we start ART to see if we can see a difference in the population of cells that we're observing. And again, once we look deeper into that, we have a very -- an animal that we necropsied that was on ART only for three weeks. That will be another interesting animal to look at because that's earlier on in the experiment.
But we are -- there is the fact that we have such a short challenge period, and then -- for most of the animals, such as short ATI period, and that might be why we're not seeing those T cells and that the cells that actually make up the reservoir that's established so early on are not necessarily T cells, but these other cells that we're observing.
DR. HOPE: Great. Thank you very much. There will be, I think, some other questions that you can answer online. So we'll move on to questions for Bhavesh Kevadiya. And so the question is from Josanne Profana. "There is low particle deposition in the lymph nodes for therapeutic purposes. Shouldn't your strategy target the sites of high viral replication rather than the liver where the drug will eventually get degraded?"
DR. KEVADIYA: Yeah, so thank you for the questions. So main thing is the -- our particle we design it and (inaudible). If you look at the spec CT data and other data, the particle also goes in the lymph node, but not -- I mean, you know, like, if you look and compare the volume of the liver with the lymph node, so lymph node relatively smaller. So it's like -- also if you look at the all the lymph nodes and all lymph nodes has also particle is evidenced in quantification of the -- successfully. But more effectively, we are going to now try and change the liquid composition of the surface deposition of the particles, targeting the CD4 T cells and macrophages with the monoclonal antibody. That goes to precise the lymph node cells and lymph node tissue, higher amount. That is our next goal, but tomorrow we will have an interesting talk. Dr. Howard Gendelman is talking about the nanoparticle lipid composition and how we are delivering this kind of (inaudible) in the specific cell type. So he's going to talk it. But right now we're in the process to make it more effective of the delivery in the lymph node. Thank you.
DR. HOPE: Thank you. A question from Amanda Brown. Hi, Amanda. "What is the distribution differences that you might see depending on the route of delivery?"
DR. KEVADIYA: So we are using the, like, IV delivery (inaudible) is IV, but whatever the next phase of the heterogeneic particles, we're using the IM plus IV. Each one is going to higher target based on the composition, shape, size, and charge of the particles and therapeutic payload.
DR. HOPE: All right. Thank you. And I guess there's a another -- people are very interested in distribution of your particles. But the question is, "Are your particles being cleared by the reticuloendothelial system?" Do you think that might be going on?
DR. KEVADIYA: Yeah. So we mentioned that this particle is going to activate and degradation on the reticuloendothelial system, yeah, the second point of the microphage. So whatever the way that design the targeted nanoparticles is taken by the lymphoid tissue or cells and immune cells, deposit individual (inaudible) and eventually it (inaudible) process and remove by the body, yeah, with fully biocompatible compartments.
DR. HOPE: All right. Thank you very much. So the following questions are going to be for Rebecca from Ken Williams. "Rebecca, nice talk and approach. What is your beginning number of monocytes used per well for MDM and viral assays?"
DR. VEENHUIS: That's a great question. It does vary. So macrophages -- monocytes and macrophages like to be close to each other, so when we do plate anything less than a million cells in a well, we use a very small weld plate, so like a 48 well plate or a 24 well plate, depending on the number. If we're plating large numbers, like three million or higher, we use a six-well plate. So because they do prefer to be in dense conditions, we will plate as little as three million cells in the well of a six-well plate, and then we go to smaller wells from there depending on the cell number we start with. But we try to start with a minimum of two million cells and replicate in our largest well.
DR. HOPE: Great. And, Rebecca, a question from Rahm Gummuluru. "Were you able to measure proviral copy number in the monocyte prior to differentiating them in into MDMs and compare them, both populations?"
DR. VEENHUIS: So that's another really good question. So I showed a little snippet of data from that. The monocytes and the macrophages from the same individuals where we measured provirus, we -- that was not from the exact same blood draws, so it was monocytes we had saved back from that same individual returned. We differentiated them into macrophages, and then we looked at the proviral DNA that way. We are now in the process of bringing individuals in where we can pull monocytes, save monocytes, and differentiate from the exact same blood draw so that we can make in a direct comparison of can we really not differentiate and not see the provirus versus differentiate and then see it. So we're still trying to work some of that out to figure out if that really is what's occurring, if there are some change in differentiation that now allows the DNA to be more readily detected.
DR. HOPE: Great. And then Livio Zoni asks, "What ARV or ARV mix be mixed you use for the macrophage QVOA?"
DR. VEENHUIS: We use two RO2 integrase inhibitors and an RTI. If you want the exact ones, I think it's raltegravir, dolutegravir, and AZT I believe.
DR. HOPE: Excellent. And then one more question: "What cell do you think is originally infected, monocyte or myeloid progenitor? What's your thoughts there?"
DR. VEENHUIS: That's a very controversial subject. It would make a lot of sense to me if it is coming from some progenitor in the bone marrow, potentially a progenitor that is past the CD4 -- CD34 positive and somewhere in between CD34 and CD33 positive. We do have some work now in the macaque models where we are trying to look at exactly this in the bone marrow from long-term ART-suppressed macaques, but we don't have data yet to definitively say yay or nay that it is coming from the bone marrow, but logically it would make a lot of sense that it is if I can detect it in monocytes isolated from an individual nine months apart since we heard at the very beginning that monocytes only last 20 to maybe 72 hours, depending on what they differentiate into in the blood. So it would make some logical sense that an individual on ART, it could be coming from the bone marrow, but I know that's very controversial.
DR. HOPE: Right. And this is a follow-up question from myself. Have you -- have you look at integration site or any sort of approaches that would help you to see if that was a precursor? If it was a precursor origination, it might have some characteristics that would give that away.
DR. VEENHUIS: So that's another area we're trying to actively work on. It's very difficult in the human cells because a single infected macrophage can produce a lot of virus whereas it takes -- T cells in general produce a lot of virus, so it's a different replication kinetic. So having one macrophage that has an intact genome can produce enough virus to detect, and then it's almost impossible to find that needle in the haystack, so it's even harder in the macrophages than in the CD4s. But we are actively working on some of that in the macaques as well to look at the integration site analysis because it's a little easier in the macaques. We have more sample.
DR. HOPE: Great. Thank you very much. So now in the last part of the session here we're going to move on to Kate, and -- sorry. Yes. "Do you look at the CSF viral load in your model during ART or the ATI phase?"
DR. BAR: Yeah, that's a good question. Many people asked. So we have not yet looked at the CSF. We have some animals that are being infected in the next couple months, and we have sequential CSF sampling, so hopefully we'll be able to answer that soon. But as of yet, we don't know.
DR. HOPE: Great. And then is Wonki Kim. "Is IBA-1 expressed on very vascular macrophages as well?"
DR. BAR: Oh yeah. So I didn't mean to say that there wasn't infection of perivascular macrophages. The tissue macrophages are also infected with the microglia. That is definitely the case. We just see a lot of co-localization of the SHIV with the microglia. We also see it in the perivascular and tissue macrophages.
DR. HOPE: All right. There are quite a few questions about the CSF viral loads, so once you have those --
DR. BAR: We clearly need to make sure -- in my retrospective scope we would have done that a few years ago, but moving forward, it is part of the plans.
DR. HOPE: All right. And then from GDE La Torre: "Katharine, how long would it take to have a SHIV be viral rebound after stopping long-term ART from the undetected level in plasma?"
DR. BAR: Yeah, that's a good question. So in our animals, these viruses -- I'm sorry. Yes, in our animals, the virus rebounds pretty quickly, so we see rebound between seven and -- seven days and sort of a month in almost all of our animals, and that's after infection. I mean, so there's many variables in the experiments, right? So we have infection of sometimes just a few months. We also have had long-term viremia prior to antiretrovirals. All of our antiretroviral time frames have been at least six months, but we've done longer than that as well, and we have seen on average between seven and sort of 28 days, we see virus reactivation with a couple stragglers in the second ATI that we did where animals were viremic, suppressed, viremic, suppressed. In that second ATI, there was a longer delay. So I think that's similar-ish to what we see in people living with HIV who have been suppressed for a long period of time on antiretrovirals.
DR. HOPE: Thank you. From Yu Yang Tang: "Which brain regions have the most infected cells and most macrophages?"
DR. BAR: Yeah. So we see -- and this work started with Dennis Colson who's characterized this in multiple different models. Similar to some of the SIV models, we see the posterior regions of the brain tend to have more infection, more inflammation, as well as some of the just frontal cortex. But the brain stem and the basal ganglia were really our most sort of infected I think.
DR. HOPE: All right. And from Wi Li Kang. "When see the HIV persisting in the CNS, do you think that is influenced by poor ability of ART to reach CNS?"
DR. BAR: That's obviously an important area of study. We have no -- we have no CNS levels or -- CSF or CNS ART levels. We are starting to look at that with our SHIV model as I know other groups have, and that's going to be an important part of characterizing why we see this low-level RNA persistence. So that that's an important and ongoing area of study.
DR. HOPE: All right. Great. So we're actually going to shift back to Rebecca here with a question from David McDonald. "Rebecca, can you explain where the viral DNA comes from after the MDM differentiation? Do you think the monocytes are harboring an integrated virus, and are you including RT and integration inhibitors during that culture of the differentiation?"
DR. VEENHUIS: So that is a great question and one that has been plaguing me since we saw -- we observed this data. We do include integrase inhibitors during the differentiation process, so it is bizarre to me that all of a sudden we can then detect the DNA if it is potentially in an unintegrated form, which logically would -- might be what is occurring, that it isn't an integrated form and then it integrates post-differentiation. But measurements that I showed are after ARVs have been removed, the cells are washed and left in culture for certain amount of time. So theoretically, it could've integrated post that seven days and a little bit later.
We're doing the direct head-to-head comparisons right now where we're taking the monocytes, differentiating, and then pulling immediately without removing the antiretrovirals, and then removing later when those antiretrovirals have been washed out to sea if potentially that is what we're seeing, the integrase inhibitor once it's washed out, then it integrates. I don't have an answer, but it something we're really actively working on to try to figure out because it has been plaguing me for a long time.
DR. HOPE: All right. And I guess I'll ask a question here as we're winding down. But one of the things I think that came out of the keynote that was really interesting and should be heard by all of us is that some of these macrophage populations divide -- they're self-renewing -- and that will change a lot of our perspectives on all of this. And to sort of add to that, we learned about all these different populations macrophages and cells inside of the body, and -- but we all sort of do this same simple trick to make them in the lab, what we call MDMs. And I'm not sure how well those match with any of the cells that are in the body, so that could be part of our problem, too, here.
So all right. I think that was a great session and great questions. There are still quite a few more and feel free to add more on, but we're going to answer those sort of one-on-one in the chat and in the question and answer. And I am supposed to announce the break according to the list, so yes. So we have a 10-minute break. Thank you very much to all the speakers who I think really just did an incredible job, and this meeting has been fantastic, and I'm sure it will continue to be so. Thank you.
DR. CLEMENTS: Good afternoon. So this group of speakers have been awarded an NIMH grant based on the funding opportunity that NIMH advertised. And the research goals and objective of the FOA are to contribute to the knowledge and understanding about how myeloid and microglial cells -- cell populations contribute to HIV persistence and/or viral rebound; mechanistic studies involved in establishing, maintenance, and resurgence of the myeloid reservoir in in relationship to effects and timing of ART; and strategies to target myeloid reservoirs were also encouraged. So this is broadly a group of people that are looking at myeloid cells. Rebecca, would you like to introduce the first speaker?
DR. VEENHUIS: Thanks, Janice. So I'd like to introduce Jin Wang of Methodist Hospital Research Institute in Houston, Texas, Dr. Olaf Kutsch of the University of Alabama at Birmingham, Ken Williams from Boston College, Eliseo Eugenin from University of Texas Medical Branch, Grant Campbell from the University of California-San Diego, and Howard Fox from the University of Nebraska Medical Center. Please take it away Jin Wang.
DR. WANG: This is Jing Wang from Houston Methodist Research Institute. I'm going to discuss a new strategy for HIV clearance called SECH for Selective Elimination of Host Cells Capable of Producing HIV. We and others have found that long-lived memory B cells and memory T cells depend on autophagy overage for their long-term survival. Interestingly, it is reported that TCR HIV reservoirs display memory T cell phenotype. Because autophagy is important for memory T cell survival, we asked whether it is possible to target autophagy for the clearance of HIV reservoirs in memory T cells.
We inhibited autophagy in memory T cells with latent HIV by silencing autophagy Gene 87 or using or autophagy inhibitors SAR 405. We then stimulated latent-infected cells with PHA followed by intracellular staining of p24 to detect HIV reservoirs. We found that inhibiting autophagy by this method reduced HIV reservoirs in memory T cells. However, a portion of the HIV-infected cells are still remaining, so inhibition of autophagy reduces, but does not eliminate, HIV reservoirs.
Latency reversal can induce expression of HIV genes to trigger cGAS. We stimulate T cells latently infected by HIV. We sent a latent reversal agent each 320 type IDB. We found that IDB induced apoptosis signaling in HIV-infected T cell as shown by caspase activation. Interestingly, IDB also induced the expression of anti-apoptotic molecules, including BXCR and MCL-1. IDB also operated LC3 that is characteristic of autophagy. So latency reversal by IDB not only induces apoptosis in HIV-infected cells, but also enhanced pro-survival BCXR, MCL-1, and autophagy.
Latency reversal similarly induced both cell tests and cell survival mechanisms in HIV-infected macrophages. So latency reversal induces both cell tests and cell survival signaling in T cells in the macrophages. While latency reversal can trigger cell death in HIV-infected cells, we need to suppress the upregulated pro-survival mechanism in order to enhance the cleaning of HIV-infected cells. We, therefore, designed a second regiment that has four components: latency reversal, promotion of apoptosis, inhibition of autophagy. We also include ART to prevent new infection.
We first tested the SECH in vitro. We mixed HIV-infected cells with cell tracer level in unaffected cell in aquaculture system. We found that SECH specifically killed HIV-infected cells, but not uninfected bystanders. We then established a protocol for HIV infection and cure in humanized mice. Humanized mice were infected with HIV and treated by oral delivery of SECH components once every two days for 30 to 40 times over a two- to three-month period until we could no longer detect HIV in the peripheral blood. Then treatment were withdrawn for two months followed by determination of HIV clearance.
After withdrawal of SECH, some humanized mice showed a viral rebound. Interestingly, over 50 percent of mice had no viral rebound, and these mice which had no viral rebound also had no infectious HIV as shown by viral or growth assay. We also adopted transverse spleen and bone marrow CRs from treated mice into uninfected humanized mice. Mice with no HIV rebound also not infectious HIV in the spleen of bone marrow by this in vivo virus or growth assay using humanized mice. We next examined microglial cells in the brain of humanized mice after SECH treatments. In mice not clear of HIV we could detect HIV-1 p24 in microglial cells in the brain sections. In mice with clearance of HIV, we did not detect HIV-1 p24 in microglial cells. This suggests that SECH treatment could clear HIV infection in microglial cells in the brain.
Currently, ART treatment can greatly reduce, but cannot eliminate, HIV reservoir. Using SECH treatments, we could accelerate the elimination of HIV reservoir. SECH treatments can clear HIV within two to three months in over 50 percent humanized mice, and then these SECH particle could be developed as a cure for treating HIV infection. Thank you.
DR. KUTSCH: Hello, everyone. Today I will give a brief summary of our project studying the role of the phosphatase PPM1A and HIV-1 infection of macrophages. As for most of you, our goal is to be part of the effort to cure HIV-1 infection. We approach this based on the hypothesis that control of latent HIV-1 infection is a host cell phenomenon. Much of our data shows that the actual HIV-1 infection event permanently alters host cells at the transcriptomic and the proteomic level. These biomolecular changes constrain HIV-1 expression and quench the ability of the host cells to respond to activating triggers. For example, latently-infected T cells may simply not respond to cognate antigen recognition anymore. It is our hope that understanding this altered biomolecular phenotype will allow us to develop host cell-directed intervention strategies to therapeutically address latency.
I will first explain our methodological approach using published data and then present the data that led to our current proposal.
One example of how we approach studying host cell control of latent HIV-1 infection is described in this recent publication. This research extended on findings from the Siciliano group showing that part of the latent reservoir are not responsive to T cell activation. We wanted to explore this in more biomolecular detail and possibly find ways to render inert cells reactivation responses again. We could show that a significant portion of the latent reservoir is likely resistant to CD3/CD28 stimulation, the experimental equivalent of cognate antigen recognition, but still responsive to un-physiologically strong stimuli, such as PMA/ionomycin. This was true for primary T cells as well as immortalized T cell populations.
From the T cell line populations, we generated latently-infected single cell clones that both responded to PMA stimulation, but only one was CD3 responsive where the other one was CD3 inert. Transcriptomic analysis revealed major differences between control cells and the latently-infected T cells and between the responsive and activation inert latently-infected T cells, but surprisingly revealed no differences in regards to the T cell activation motif.
We thus explored whether we could identify differences between these cells at the proteomic level. For this purpose, we used antibody arrays from Kinexus on these arrays, but one cell and antibody spots provide information on protein expression levels and/or on the phosphorylation state of proteins. Relative to uninfected T cells here in gray, the proteomic profile of CD3 responsive latently-infected T cells here in red was not much changed, but the activation inert latently-infected T cells here in green had a considerably different proteomic profile. Also in these cells, pathway enrichment analysis actually immediately recognized the impairment of the T cell receptor signaling pathway.
Based on the list of all the proteins, we performed network analysis to see how these proteins would actually interact. This type of analysis allows us to rank the importance of altered signals not solely based on signal intensity changes, but based on the level of control specific proteins have in the interaction network. Targeting some of the central network hubs in this case indeed allowed to render large parts of the initially CD3-inert T cells again responsive to T cell receptor/CD3 stimulation, and that not only in T cell line-based models of latency, but also in primary T cells.
In this new project, we will now apply similar systems biology approach to the study of the biomolecule mechanisms controlling HIV-1 and macrophages, certainly with a focus on the phosphatase PPM1A which we have studied over the last few years. Leading to this application, we have already demonstrated a role for PPM1A in the control of monocyte to macrophage differentiation for the control of macrophage apoptosis and for the control of HIV-1 infection in macrophages. Importantly, other groups have reported that PPM1A actually regulates the antiviral response. We have demonstrated that PPM1A expression in primary macrophages is upregulated by HIV-1 infection. We could further demonstrate that other than for T cells, it cannot shut down active HIV-1 infection events into a latent state. Monocytes seem to be able to do this.
Immortalized T cell or monocyte populations that were infected with GFP reporter viruses were enriched for greater than 99 percent GFP expressing actively infected cells, and then active infection was followed over time. After two weeks, T cells had not shut down the active infection events. The gray and black bars represent TNF alpha and PMA-stimulated samples. In contrast, infected monocyte populations efficiently shut down active infection events indicated by the drop to a 50 percent GFP positive level, and PMA, or TNF alpha stimulation, revealed the presence of a newly-generated latent reservoir. We also demonstrated that PPM1A overexpressed -- if PPM1A is overexpressed in monocytes, this viral shutdown no longer is observed.
And the next two years we will use the above-introduced systems biology approach and begin to study how macrophages can shut down active HIV-1 infection events, how this intrinsic block and lock ability is controlled or affected by PPM1A, and how this process can be therapeutically boosted to eradicate the HIV-1 reservoir in macrophages. Thank you.
DR. WILLIAMS: This brief presentation is an overview of a grant recently funded to myself and Woong-Ki Kim. We studied effects of CSF1 receptor blockade on repopulation SIV reservoirs and the traffic in these cells to the periphery.
Overview of the grant is we used a rapid model of SIV infection with ART. It doesn't result in SIV encephalitis. We used a novel colony-stimulating factor CSF1 receptor inhibitor, BLZ045 that depletes macrophage selectively in the CNS with sequential SPION inoculation with different colors IC taken perivascular cells, and we studied traffic of these cells and virus out of the CNS. We did this to define the role of these perivascular cells trafficked out of the CNS with ART therapy and the potential for them to recede at periphery.
And as basic assumptions and background, one is that the -- these macrophage -- perivascular macrophages and monocytes are correlated with a series of HIV-associated comorbidities, including HAND. Within the CNS, you can find these cells that are viral infected as early as three to seven days post-infection and then you get RNA. Once they're detected, DNA in the brain sort of stays there, and you can get recrudescence or replication competent virus in humans and monkeys if they're taken off ART therapy. And these perivascular cells by DNA and RNA scope are consistently shown to be -- to have HIV SIV DNA.
Secondly, we're interested in these -- in these border macrophages turnover and repopulation that come from the bone marrow within the CNS. If you block their traffic from the bone marrow, you block the establishment and maintenance of the CNS reservoir. There's quite a bit of anecdotal and rodent evidence of these perivascular macrophage, meningeal cells, and resident cells emigrating to the periphery. They can go along the perivascular space in CNS vessels and meninges. If they're injected-directly cells into the CNS, they are found in the cribriform plate and leaving through different lymphatic pathways, which we will better define in this grant.
Woong-Ki-Kim has done extensive data, more so than since this was originally put in the grant, but he's done a dose response monocyte-derived macrophage in vitro, and he shows a good dose that you can selectively deplete these cells. We've done oral administration, a high and low dose 10 versus 30 milligram-per-kilogram of SIV-infected monkeys, and you get a nice depletion with a high dose versus low dose versus untreated animals. We've injected SPIONS inter-cerebrally into monkeys in the third ventricle. These are iron labeled but also dextran labeled, so you can see that the blue -- Persian blue iron staining of SPION-containing cells in the cortex and in the meninges. Here's an example of Prussian blue stained SPION-containing cells in the cortex. Here's an example of a cell in the cribriform plate. These are H&Es of cerebellum and brainstem, and you can these ions accumulate -- SPIONS accumulate in perivascular macrophage. They're actually taken up within these cells. They can't leak out of the CNS.
This is just a representation. If you look at one hour versus 28 days post-SPION injection in the monkeys, this is the distribution you have. Importantly, in hour they're only within the CNS, but 28 days later they're in the CNS up and down the spinal cord, dorsal root ganglia, but also outside in lymphoid tissues. Surgical draining lymph node, thymus, they go to the spleen. Here's a representation of normal animals versus SIV-infected animals, and you can see the SPION-labeled cells seven to 28 days after they leave. They leave also with SIV infection, although to a lesser extent, but we haven't studied that very thoroughly.
This is an example of a lymph node section of animal that just has one SPION-containing cells. You can see the multiple spine labeled green. This is a trabeculae and a deep cervical draining lymph node. These spine-containing macrophage consistent with cells that come into the afferent lymph. This is deep cervical lymph node of an animal that was infected, had SPIONS for 28 days. You can see two SIV protein-positive cells, one of which has SPIONS, which means within the last 28 days, the cell was in the CNS and it's outside the CMS and viral affected.
This is an example of counting the cortex of number of SPION-labeled cells in SIV-infected animals, ART treated and uninfected. So you have a lot with infection once with ART. This is the meninges of the same animals, untreated ART only, so it looks very similar. It's blood. It's different than within the CNS.
Our study design is basically six different groups. There are ART controls and ART on-and-off controls interrupted. Animals get BRDU to monitor monocytes over time activation. They're depleted. We give SPOINS at 111 days so that's it's an early SPION. We give them later at 171, and then animals are sacrificed with ART and/or after ARTs off for a month.
We have light BLZ treatment groups, so they're treated after the second SPION injection for four weeks. They're on ART therapy, and then they're taken off, and we look at the viral reservoir. We have another interruption group that's treated late with BLZ after the second SPION, so it would deplete green and red SPIONS. Then they're taken ART off and we're looking at rebounded virus in the perivascular cells in the brain and cells that left. Also we're looking at early ART treatment, so these guys are treated With BLZ on the CS1 receptor antagonist -- agonist after the first SPION injection so you're clearing these infected cells. Then we have ART therapy going on, and we sacrifice them at day 201. Then we have early BLZ treatment ablation of perivascular cells. Again, after this, green SPIONS and then they're off ART, and we sacrifice them.
Two aims for the study that are relatively similar, but first is to determine the extent of which the blockade eradicates SIV in the brain and blocks lymphocyte-dependent receipt in the virus in the periphery to the CNS, from the CNS to the periphery. And the second one looks at ART interruption and receiving, and the question is, if we ablate the perivascular macrophage in the CNS and/or ablate the perivascular macrophage the CNS with ART therapy and have engraftment of new uninfected cells because they turn over about every three to four months normally, will we prevent the receipt in the CNS reservoir with ART therapy.
So we do SIV infection, CD lymphocyte depletion, extensive flow cytometry, very extensive necropsy of tissues, draining lymphatics, DRGs, spleen, other the lymphoid organs with a veterinary pathologist to look at the path of these cells, the immune phenotype of these cells. We do counts of perivascular cells after ablation. With the SPION-labeled cells, we can do SIV, DNA, and RNA scope in the immune phenotype and location within tissues. We do SIV phylogenetic analysis, genomic analysis, replication confidence, and then we're putting MicroFil gel in the heart of these animals in the CSF, two different colored gels that will tell us and allow us to map out the draining lymphatic pathway compared to the blood pathway in the brain.
Collaborators on this project, Woong-Ki Kim, who's a co-PI; Andrew Miller, who's our veterinary pathologist who walks through all tissues and brains really quite well; Marcus Salemi, who's SIV viral analysis and evolution; Quingsheng Li, who does SIV, RNA, and DNA scope; and our collaborator Xavier Alvarez, who's done early SPION work. And that's the end of our very brief talk. Thank you.
DR. EUGENIN: Thank you so much for the invitation, guys. The title of my presentation is a "Metabolic Strategies to Eliminate CNS Myeloid Reservoirs." My name is Eliseo Eugenin, but everyone call me "Cheo." I am an associate professor in the Department of Neuroscience and Cell Biology in the Island of Galveston, and I'm part of the University of Texas Medical Branch. My proposal was based on five major findings. The first one was the development of an in vitro system using primary macrophages, microglia, and astrocytes to examine long-term active replication latency and reactivation.
Just to give you an example or flavor of what we do, here you can see HIV p24 release in function of time, and you can see that one infection of microglia is a really robust infection that reach a peak around 40 days after infection. And after that you can see that the virus becomes silent up to 120 to 150 days. More important than that, you can see if we take these cells from 120 to 150 days and then we apply reactive agents and this corresponds to one day, we can see that we can reactivate the virus with SAHA, TNF, an interferon, PHA, LPS, and methamphetamine, suggesting that the virus is latent in these cells.
More important, if we take cells around 120 to 150 days and we analyze them for electron microscopy, then we can see that the mitochondrial-ER-lipid droplet interactions, they are highly compromised in the HIV-infected cells. In this case, I'm showing you uninfected cells, so you can see really nice mitochondrias, lipid droplets, and the interaction with the ER. But in the HIV-infected cells that survive infection for extended periods of time, you can see that it's an enlargement of the mitochondria, constrictions of the mitochondria, and also an interaction with lipid droplets or lipid bodies in these cells. Also it's a really remarkable loss of the interaction of the ER with the mitochondria, suggesting that probably there's a metabolic change in these cells upon latency.
However, we didn't find any changes in cell analysis. The major changes that we found in these cells is the Major Finding Number 3, that most of the cells that survive infection, they rely on glutamine and glutamate to produce ATP. This is really unusual because uninfected cells, they don't use glutamine and glutamate to produce energy. More important, if we block fatty acid use and we block the glucose use, you can see that HIV-infected cells, they cannot use most glutamine or glutamate to produce energy. But uninfected cells, they really have the flexibility to use this source of energy really strongly.
In addition, HIV-infected cells cannot use more fatty acid and HIV-infected cells cannot use more glucose to produce energy, suggesting the first point that glutamine and glutamate, they are used as a major source of energy, but also HIV-infected cells, they lose the capacity to achieve between different carbon source. We use this information to try to kill the cells. This is 120 to 150 days after infection, and you can see that uninfected cells, they survive fine. HIV-infected cells, they survive fine. But we used two compounds to try to kill these cells, one that is a glutamate inhibitor that block this pathway here, and another compound that is called benzylamine that is one of the blockers the transporters of the glutamine/glutamate pathway inside of the mitochondria.
Both compounds, they don't compromise the survival of the uninfected cells at all, but when we apply these two compounds in a separate manner in the HIV-infected cells, you can see that we can kill up to 98 percent of the cells that are laterally infected with HIV, even without viral reactivation, suggesting that we can probably achieve a cure for HIV. More important, we can, in collaboration with the NTC, we got tissues from patients that they are positive for HIV, and we isolate with antiviral reservoirs in the brains of these patients. And we laser capture them with this machine, and we measure the proteins and enzymes and transporters required for the use of glutamine and glutamate. And all of them, they're upregulated in the viral reservoirs, but not in the neighbor cells of these patients, suggesting that this phenotype is also present in vivo.
Then our hypothesis is that brain myeloid reservoirs have a unique metabolic signature that can be exploited to eradicate them from the brain. Then in the proposal, we have four different aims. The first one is to complete and expand our characterization of this myeloid reservoirs in vivo and in vitro. The second one is to complete and expand the metabolic assessment of these CNS viral reservoirs, but with a focus in the glutamine -- glutamate pathway, especially in and out of this pathway. The third one is to proactively target the metabolic pathways and alter it for this HIV-infected reservoirs in vitro using the drugs that I showed you and some other ones. And the fourth one is to translate this in vitro data into an animal model, especially humanized animal models, to achieve eradication.
Then the take-home message of this presentation is that HIV reservoirs, especially microglia macrophages, they have a dysregulated mitochondrial-ER-lipid interaction that need to be exploited. HIV reservoirs, they have a unique metabolic signature that rely mostly on glutamine and glutamate to produce ATP, and also HIV reservoirs cannot shift between different carbon sources, like uninfected cells. And the last one is that we can use these pathways to kill viral reservoirs.
And I want to thank the National Institute of Mental Health and the National NeuroAIDS Tissue Consortium for their content support to our research, and also Silvana, Lisa, and Paul for working on this project, and also our collaborator, Santhi Gorantla, from the University of Nebraska, for providing all of the animal assistance for our research. Thank you so much.
DR. CAMPBELL: Hello. My name is Grant Campbell, and I'm from UC-San Diego. Our lab was awarded the grant for the project Targeting HIV Myeloid Reservoirs in the CNS by IAP and TREM1 Inhibition. In this presentation, I will briefly introduce the research that was proposed.
Although antiretroviral therapy has led to significant HIV suppression and improvement in immune function, HIV persists in long-lived cells, including perivascular macrophages and microglia. Thus, much like cancer, proviral latent HIV is a residual disease and any cure is limited by the persistence of these rare infection cells. To date, no HIV cure strategy has been able to overcome the challenge of eliminating proviral HIV latency or confirming viral suppression of ART at an individual level. Indeed, any cure strategy, either functional or sterilizing, needs to address these reservoirs of HIV.
Although latent HIV-infected macrophages and microglia lack specific identifiable markers of HIV infection, the transcriptional profile of these cells is altered to promote resistance and cytopathic effects of HIV infection and to CTL-mediated killing. This includes upregulation of a number of anti-apoptotic regulatory proteins. In our grant proposal, we decided to specifically look at inhibitor of apoptosis proteins and TREM1 as there was a visible and obvious gap in the knowledge base here, and asked the questions: how does HIV infection in microglia lead to the increase in IEP and TREM1 expression, and if the expression of these anti-apoptotic proteins is upregulated in infected cells, will targeted inhibition or removal of these proteins result in the death of the infected cell?
We look first at TREM1. Our first specific aim was to demonstrate that the HIV immediate increase in TREM1 expression ensure survival of HIV-infected microglia. We previously demonstrated that silencing TREM1 in HIV-infected macrophages will add to a decrease in Bcl-2 and Bcl-XL expression, and increase in proapoptotic Bak and Bax expression, and an increase in apoptosis, an effect we did not see in any other infected cells. Thus, our working hypothesis is that the HIV-mediate upregulation in TREM1 contributes to microglial resistance to HIV-induced cell deaths.
The model systems in which we will test our hypotheses are monocyte-derived macrophages and our independently verified, scalable, and reproducible monocyte-derived microglial model of HIV infection. A limitation of almost all studies is a consideration of cells as a bulk uniform population and not just individual cells. Doing this, we may potentially miss critical insights as these infected cells are inherently diverse with each provirus exhibiting a potentially unique combination of the effects of integration sites, epigenetic modifications, and infected cell phenotype. So one of the first thing we will do is perform a single cell RNA sequencing. We will then investigate and delineate the mechanism through which HIV upregulates TREM1 specifically targeting the TLR pathways using a series of RNA interferons and specific inhibitors against key components of these pathways.
The second part of this aim will be to determine how out TREM1 confers resistance to cell death, specifically looking at the roles of Bcl-2 family proteins on mitrofusions, both of which are upregulated by TREM1 signaling that inhibits the Bcl-2 and 11 media destruction of mitochondrial function and subsequent apoptosis that follows the release of cytochrome C. We will achieve the same using, amongst others, electrophoretic mobility shift assays, mitochondrial function assays, and targeted TREM1 silencing, and the changes that occur.
The second aims switches tack from TREM1 to investigating IEPs. IEPs are upregulated in HIV-infected macrophages, and upon treatment with SPAC mimetics, now known as DIABLO mimetics, IEPs undergo prosomal degradation, leading to the selective killing of HIV-infected macrophages in both subtype B-infected macrophages and subtype C-infected macrophages. The mechanism through which IEPs inhibit cell death are numerous. For example, and these are very simplified diagrams, when IEPs are present, TNF binding to the TNF receptor triggers Complex 1 formation, which IEPs BIRC2 and 3 evict RIPK1. While TLR4 TICAN1 results in IP media ubiquitination of RIPK3 and TRAF3. In both cases, this leads to pro-survival survival gene expression which blocks apoptosis or necroptosis depending on the circumstances.
The IEPs can also directly bind to and inhibit caspases inhibiting apoptosis. We will determine how HIV upregulates the expression of IEPs in microglia using a combination of inhibitors and RNA silencing to determine the rules of mitogen-activated protein kinases, ER stress, and, again, the TLR signaling. We will then determine how the upregulation of IEPs contributes to resistance to HIV-mediated cell death with an emphasis on RIPK1 ubiquitination and the role of autophagy.
The third aim will identify drugs and/or peptides that can be used to target the upregulation of TREM1 and/ IEPs in HIV-infected cells, and selectively kill these cells without the requirement for viral reactivation in the absence of both bystander cell death and reactivation of virus. And as can be seen here in our latest publication, we use nanoparticle encapsulated Diablo memetics to specifically kill HIV-infected macrophages. These nanoparticles are also able to specifically skill latent HIV-infected CD4 T cells. They do this through the de-ubiquitination of RIPK1 and the formation of a death and use signaling complex on autophagasal membranes derived from the endoplasmic reticulum.
We will methodically test compounds that target and inhibit TREM1 and/or IEPs to specifically kill HIV-infected microglia in the absence of both bystander cell death and increased viral release and define the mechanism through which they achieve this. Finally, we will test the ability of these drugs to traverse and use pluripotent stem cell model of the blood-brain barrier and kill infected microglial with no adverse effects on surrounding neurons. Overall, the results of this proposal will lead to a better understanding of the specific molecular mechanisms of how these cells are resistant to HIV-mediated cell death, which will in turn lead to development of new strategies to prevent HIV-associated neurocognitive disease and the achievement of an HIV cure.
Thank you for listening, and thanks to the laboratories of Steve Spector and Liangfang Zhang. Thanks also to the agencies listed for funding the work that led to this grant proposal.
DR. FOX: Hello, everybody. I'm Howard Fox from the University of Nebraska Medical Center and will present our recently-funded study on macrophages in microglia, gene expression, and chromatin, how we're going to eliminate the myeloid cells reservoir through single cell analysis. The goals of our project are similar of the goals of the program announcement, how myeloid microglial cells serve as a reservoir, and how to characterize them and try to rid them of virus in order to achieve a functional or sterilizing and cure for HIV.
So our goal in the first aim, we will uncover the SIV-infected cells in the brain in the presence of suppressive ART using anti-CD8 therapy within the CNS, and the second to examine the molecular mechanisms that are characterized in reservoir looking at epigenetics as well as gene expression. The approach will be to take four animals, all infected, all receiving suppressive ART, treat them with anti-CD8 by cisterna magna infusion as we've done before in that paper. Three days before necropsy, we'll monitor monthly, and after approximately six months of suppressive therapy, sacrifice or give anti-CD8, and then examine the brain.
We'll be examining the brain in traditional means as well as doing single-cell work, and here we'll do combined chromatin accessibility and gene expression from cells that were infected in vivo using combined single-cell ATAC, RNA seq. So we isolate microglia or microglia-enriched population of the brain, fax isolate valuable CD11B cells, isolate the nuclei, and then perform this combined single-cell analysis that's called single cell. Here it's really single nucleus. You need to isolate the nuclei in order to do the transposition for ATAC-C, and a diagram is shown, and this could be -- more explanation can be found on the 10x genomic sites or other websites.
Most of us are familiar with single cell or RNA-C congenital in general. ATAC-C, you may be less familiar with it. It stands for Assay for Transposable Accessible Chromatin, followed by high throughput sequencing, the TN5 transposase cut open chromatin and litigate in oligonucleotide adapters, which then you can PCR out, do high throughput sequencing with paired ends, and thus profile the regions of open chromatin, which, in general, correspond to express genes or important regions that control transcription.
So in the past, we've looked at chronically SIV-infected animals without C-ART, given anti-CD8 three days before sacrifice, and that does indeed uncover the SIV-infected cells in the brain when compared to historic controls or similar animals given IGG infusion. And we can detect them by in situ hybridization as well as by viral analysis in the brain where viral load goes up one to two logs, so nicely uncovers the virus.
We do have data ready from the ATAC seq, the SIV genome shown on the top, and most of the sites, of course, will be in the host chromatin, but here we see within the SIV genome with animals -- SIVE 1 and SIVE 2 -- cuts within the provirus. Most of these are down at the end of the LTRs, which makes sense. The LTR controls gene transcription, as I mentioned. That's what open chromatin and ATAC helps uncover. So we can see sites and sequences that are all in the host chromatin, sequences that are all in the pro-viral chromatin. But what we see here in listed as chimeric sites are when we sequence the ATAC fragments, we have one site in the virus and one site in the host. Therefore, when one sequences it, you can find out the integration sites.
So we started with SIVEs thinking that there's more infected cells and we could we refine the technique here. And we did find interesting findings as shown on the next slide. Two animals. Again, one we had 100 cells. The other we had 200 cells. And the integration sites were scattered throughout the genome, except we did see this area at the bottom here in white in each animal sites that were repeated in multiple cells. This could easily be an infected cell that replicates, although monocytes, microglia, macrophages don't replicate that much, but they can in this. Especially in the setting of encephalitis that may be occurring.
But what really struck us is between the two animals, we have sites in common, and so there's no way this can happen by cell reputation. These are independent animals, actually independent experiments, so they weren't even in the vivarium at the same time. And we see multiple three sites -- three exact sites that both animals had integration in as well as one region, almost a mega base in size, that both animals had numerous integration sites. And so this is a replication because it's 20, 40 different sites within the region and only one site in common between the two animals.
So we found really identical sites that SIV can integrate in in these myeloid cells as well as a chromosomal hotspot for regions of integration. Interestingly, integration sites have been characterized in CD4 positive T cells. There is nowhere where it tends -- HIV tends to integrate into introns of active genes. There was no predilection for genes here at all, and our bioinformatic analysis is ongoing.
We were asked to present our challenges, you know,. We have a number, 21 that's supposed to be risky. Will anti-CD8 be sufficient to enable the quiescent infected cells to then express viral RNA? We had done it before, but it wasn't in the presence of ART. We don't think ART will stop it, but we'll see. Will the anti-CD8 treatment alter the characteristics of the cells, complicating our interpretation and translation to the human condition? One problem is data from single-cell ATAC-seq is relatively sparse. You saw we only identified a few hundred cells in the presence of encephalitis. What are we going to find in the presence of suppression? We're working to try to improve the sensitivity of the technique. And finally, the research genome is not as well as characterized as a human, hindering some of the mapping. But we will -- we have great bioinformatics technicians, so that problem we'll work through.
I wanted to thank the organizers for inviting me, The National Institute of Health for being a long sponsor of our lab's work. This looks like a big Zoom picture, but in the upper right is my lab. We collaborate a lot with Kelly Stauch. Her lab is shown below. And specifically on the SMB monkey studies, we work with Dr. Buch, Byareddy, and Fletcher. Thank you very much.
DR. VEENHUIS: Well, I can start with the first question for Ken since you have your camera on, if you'd like. There is one -- there is a question for you as to whether there is evidence that uninfected macrophages or microglia migrate out of the brain.
DR. WILLIAMS: Absolutely. So certainly from our preliminary data, and we have a couple manuscripts now going out on this, but it's actually kind of amazing in in animals we find quite a bit of cells accumulated in the DRGs, almost like lymph nodes. And actually lymphatic pathway does go in parallel to the blood to the DRGs. A lot of cells in the spleen. We find them in the deep cervical draining of lymph nodes. We don't differentiate between microglia or perivascular cells, and then certainly there are sort of -- there's quite a bit, you know, evidence in in in rodent models. The problem with the rodent models is they typically are transplantation and cause an injury, but cells do leave you the with GFP. But in our model with infection looking much further out after spine injection, we find quite a bit of CD163, CDO2006, macrophage some of which are infected in multiple different areas.
DR. VEENHUIS: Okay.
DR. WILLIAMS: Bone marrow as well actually. After recrudescence and after -- we don't find a lot of sequins work early looking at phylogenetic trees and molecular clock, but we do see reseeding in the bone marrow with AIDS, and we do find SPION-labeled cells of macrophage lineage in the bone marrow.
DR. VEENHUIS: Okay. So that's sort of a nice segue to a question I had, was how your compound that specifically depletes perivascular macrophages does not affect microglia.
DR. WILLIAMS: Sure. I would -- there was more preliminary data in the grant, and Woong-Ki Kim, who's a collaborator, has that work. He's done that quite extensively on, I think, eight animals. I think his in vitro work shows that it has to do with the level of CSF1 receptor expression. So the perivascular cells, like other molecules and perivascular cells versus resin of microglia, like HLADR, CD4, CD28, they tend to have a lot higher levels, and that that level seems to be dependent on depletion of these cells. And it's similar in other organs, not just to the brain. So this agent's been used -- is being used in about 30 different clinical trials for cancer work, yeah.
DR. VEENHUIS: Okay. Interesting. So I see everyone has cameras on. I think I just missed some of them before. They weren't up at the top. I apologize for that. I'll move on to another question. This one is for Olaf. Maybe I missed this, but what do you think are the downstream targets of PPM1A that are influencing HIV replication?
DR. KUTSCH: I don't know. I really don't. This is what we are trying to find out in this grant. I mean, our goals are to figure this out and then see whether we can also induce the same pathways in T cells, but I really don't know. And if I vote, I would probably have a patent on it and not tell anyone anyway, but that's a different story.
DR. VEENHUIS: Fair enough. To that same -- that same thought process, do you think -- is PPM1A expressed differently in monocytes and macrophages? Does it become upregulated just at that differentiation step, or is it constitutively expressed in monocytes as well?
DR. KUTSCH: It is there. We have some publications on that, and what you can see that it is upregulated by infection, HIV-1 infection. It is upregulated also by bacterial infections in macrophages like MTB. And what it does, if it's upregulated, it seems to control cytokine production. It dampens cytokine production, and I would assume that the mechanisms by which it accomplishes that are also the mechanism by which it affects HIV-1 expression, but I don't know the details yet.
DR. VEENHUIS: So this next question is for Grant. "Have you looked at the relevant role of soluble TREM1 versus membrane-bound TREM1 in resistance to apoptosis?"
DR. CAMPBELL: No, we have not yet. That will be something that we will be doing, but we haven't done it as yet.
DR. VEENHUIS: So is TREM1 upregulated in other infections as well, or is it primarily an HIV infection?
DR. CAMPBELL: It is upregulated in other infections, including viral video infections, but we're just -- we're looking at HIV, but it's definitely upregulated through regular bacterial infections as well.
DR. VEENHUIS: So do you think that if you did come up with a pharmacological agent that could block TREM1, would that have other adverse effects?
DR. CAMPBELL: Quite possibly. This is one of the things we're going to be looking at.
DR. VEENHUIS: Janice, would you like to ask a question or I can keep going. I can keep going. I just didn't want to stop you --
DR. CLEMENTS: I don't see the questions. I can't see the questions. I only see --
DR. VEENHUIS: Okay.
DR. CLEMENTS: -- but I don't see the questions, so.
DR. VEENHUIS: Okay. I can keep going then. This question is for Eliseo. "In your figure, you showed microglia was cultured for more than 100 days. It must be challenging for the long-term culture. Is this IPSC-derived microglia or human primary microglia?"
DR. EUGENIN: Those are an excellent questions, and I think the reviewers because this was one of the questions that they have the reviewers. These are primary microglia, fetal primary microglia, and, yes, it's challenging to keep it for more than 100 days. And one of the comments of the grants was like how you are comparing apples to apples when the uninfected cells, most of them they die after 30 to 60 days. And this is one of the caveats of this figure that it's difficult to compare the cell that reactivate the HIV after 120 to 150 days with the original cell type because they die after 30 to 60 days. This is an excellent question, yeah.
DR. VEENHUIS: So that same person had a follow-up to that was that, "Are the LRAs toxic to the microglia."
DR. EUGENIN: We don't know. We never try any of these treatments yet. We can do it. Great idea. We want to do it.
DR. VEENHUIS: Okay. We'll go into the chat. So another question for you, Eliseo: "How are the metabolic differences seen in brain myeloid cells associated with homeostatic mechanisms and presence of ART?
DR. EUGENIN: Homeostatic part, I think -- I don't get the question, but I think I want to answer right in two ways. Then I think it's really smart for the viral reservoirs to change from glucose and fatty acid into glutamine and glutamate because it's one of the more abundant neurotransmitters in the brain. They have a huge amount of carbon source to produce energy even though you have a depletion of the blood vessels around where the vital reservoirs are. Then this is the homeostasis. Then I think the question also going how you compare these ones to the human brain, then in the human brain, we laser capture some of these cells. And in the humans, that they are under antiretrovirals and also in the animal models that they haven't taken retroviral, we find a really similar proteomic profile compared with our culture system of macrophages and primary microglia, suggesting that that profile of glutamine and glutamate use still is maintained in humans and probably is maintained in the animal models that we are proposing to use.
DR. VEENHUIS: Oh, and to follow up to that, someone just asked, "Are latent-infected microglia dependent on glutamine in vivo as well." So you sort of alluded to that, but.
DR. EUGENIN: Yes, then looks like that most of them are for glucose and fatty acid, even that I show you really nice pictures of mitochondrias associated with lipid bodies, but also you can see it in the patients, then they cannot use lipids and glucose for energy. Then it's something that we still would have to explore in the -- in the -- in the in the grant to see how limited is the use of these carbon sources in patients.
DR. VEENHUIS: Thank you. Here's a question for Jin. "Can you briefly elaborate on how you demonstrate that microglia in your mouse model are indeed human? It was my understanding that humanized mouse models that contained human microglia have remained elusive to the field."
DR. WANG: Great question. We did the staining for a human CDLMB, and also we did staining for the -- let me see -- the other P2RY -- P2RY3R markers, and it's the (inaudible) are positive for the human serum B and P2RY, which are positive. So they're (inaudible) that section due to the time constraint, but we did purify the cells out and analyze them over 50 percent of mice, which are cured of HIV, which have no viral after two months of withdrawal. We do not detect HIV in that purified mice as well -- in addition to the -- to the staining for HIV p24 intersections.
DR. VEENHUIS: So I actually have a question for you. You saw about 50 percent cure rate. Was that related to your acute viral loads in the mouse model, your graft -- like, your engraftment? Was it related to the suppression time? Did any of those play a role in what was cured versus was not?
DR. WANG: Yeah. When we report the paper last year, we recorded mostly that after 10 days after infection, at that time the viral load was pretty low. So we figured that because there's no HIV cure, when to start the cure of humanized mice as soon as we can detect virus. So we start from day 10 after infection, and since the infection and getting infection are rather high, and they are suppressed with ART and do the treatment. And, you know, recently we have reduced the -- our drug concentration by 25 to really improve the cure rate actually. The drug we use previous with a little bit higher than what we're using currently. So to answer your question, I worked on both acute and related infections, and they worked on TCRs and macrophage and microglial cells.
DR. VEENHUIS: Thank you. A question for Grant. "How faithful is the differentiation of monocytes into microglial phenotype in your assays?"
DR. CAMPBELL: When we're doing it, as long as we're using freshly-isolated blood, it's -- we get their differentiation 100 percent of the time. If we're using day old blood, then it doesn't work.
DR. VEENHUIS: So what's the phenotype you look for for the microglial?
DR. CAMPBELL: We're looking for the expression of certain markers on the surface, such as CXVCR1, IBA1, P2RY12, TMEM119, et cetera, by flow cytometry.
DR. VEENHUIS: Okay. So a question for Howard: "Can you talk a little bit about the genes that were repeated in the two animals? Are there particular classes of genes that preferentially had integrated provirus?" Just elaborate a little bit on what you saw.
DR. FOX: The three sites that were the exact same site really did it. Two of them were in genes, one wasn't and didn't have any particular class of gene nor likely expression or overexpression of macrophages. So there was nothing to indicate that. The other non-repeated sites did intend to be in genes, but we're still analyzing that, so this was in contrast the CD4 data. However, the region on monkey chromosome 14 that had 20-some sites spread over about a megabase corresponds to human chromosome 11l, which has been seen as frequent site for HIV integration, and it has the number of genes that typify lymphoid in myeloid cells.
So we're just getting the sequences now and mapping them, and we'll be repeating this in a few more. But it was striking and quite unexpected, so more to come. That's, you know, kind of brand new data off the press, off the sequencer, off the computer.
DR. VEENHUIS: Thank you. We've answered all of the questions in the chat and in the question and answer box. I don't -- unless anyone else has anything else, I don't think there are any further ones. Okay.
DR. VEENHUIS: No? Okay. So I'll turn it over to Kiera then.
DR. CLAYTON: Okay. Thank you, Rebecca and Janice. I really appreciate that. And to the speakers, that was excellent session..
So are finished for the day. It's been -- we've had a great series of talks. We've had some excellent questions and some great discussion, and we're all going to do it again tomorrow. So, again, thank you for everyone who's participated so far. Thank you to the participants for your questions and looking forward to another great day tomorrow. Take care, everybody.