Modelling HIV virulence evolution in the context of immune escape

Modelling HIV virulence evolution in the context of immune escape Christiaan H. van Dorp, Rob J. de Boer, Michiel van Boven 1: Theoretical Biology and Bioinformatics, Universiteit Utrecht, Utrecht, The Netherlands. 2: National Institute for Public Health and the Environment, Bilthoven, The Netherlands. A pathogen like HIV evolves rapidly under multiple levels of selection, and has to cope with a heterogeneous host population. Although these aspects have been studied before, the true nature of host-heterogeneity has not been addressed to our satisfaction. During (untreated) infection, HIV evades cellular immune responses and because of the massive polymorphism of the Human Leukocyte Antigen, the targets of these responses (epitopes) differ strongly between hosts. Supported by data, it has been suggested that HIV has evolved virulence levels that are optimal for transmission. Some models indeed predict this, but others caution that this mode of adaptation is not self-evident, mostly due to the short-sightedness of evolution during the infection of an individual host. Several theories have been proposed to better explain the evolution of virulence, and we aim to contribute to these attempts. We are developing a model of HIV's evolutionary dynamics that is highly detailed and realistic, and captures the interesting features of host-heterogeneity, immune escape and compensatory mutations, and selection on multiple levels. We hypothesise that these properties might be sufficient to explain HIV's observed virulence distribution. Disentangling human tolerance and resistance against HIV Roland R. Regoes, Paul J. McLaren, Manuel Battegay, Enos Bernasconi, Alexandra Calmy, Huldrych F. Günthard, Matthias Hoffmann, Andri Rauch, Amalio Telenti, Jacques Fellay and the Swiss HIV Cohort Study In evolutionary ecology, "tolerance" is defined as an evolutionary response of a host population against pathogen pressure, which is characterized by the lack of pathogenesis despite high pathogen loads. To-date tolerance has not been quantified and disentangled from host resistance in any clinically relevant infection of humans. Using data from the Swiss HIV Cohort Study, we studied if there is variation in tolerance to HIV in humans. We found that tolerance differs significantly across Human Leukocyte Antigen B (HLA-B) genotypes, while classical protective HLA-B alleles are associated with resistance but not with tolerance. Furthermore, we found increased tolerance against HIV in HLA-B heterozygotes and young individuals. Thus, tolerance is a feature of infection with HIV, and the identification of the mechanisms involved may pave the way to new treatment approaches. The coevolution of human antiviral protein APOBEC3G and HIV protein Vif: A theoretical study Akira Sasaki Department of Evolutionary Studies of Biosystems, The Graduate University for Advanced Studies (Sokendai), Hayama, Kanagawa 240-0193, Japan Apolipoprotein B mRNA-editing, catalytic polypeptide-like 3 G (A3G) is a key protein in human innate immune defense against human immune deficiency virus-1 (HIV-1). It induces G-to-A hypermutation in HIV cDNA to stop the viral replication in the infected cell. A viral infectivity factor (Vif) of HIV-1 is a countermeasure against A3G by binding A3G, thereby rolling the viral mutation rate back to below the error threshold. A simple mathematical model for the coevolution of A3G and Vif expression levels predicts coevolutionary cycles that are made up of a phase of the coescalation of A3G and Vif expression levels and a phase of their co-deceleration. In the co-escalation phase, the hosts tryto push up the viral mutation rate towards the error catastrophe by increasing A3G expression level, and viruses try to mitigate it by increasing Vif expression level. In the co-deceleration phase, the hosts try to pull down viral mutation rate to slow down the speed of the antigenic escape from immune response, and viruses try to enhance its mutability by decreasing Vif expression levels. We discuss the other coevolutionary outcomes and the condition for their occurrences in the parameter space. A more microscopic model for Vif expression regulation through the modification of multiple splicing rate is also discussed. Backward bifurcations in a model coupling within-host and between-host dynamics Zhilan Feng, Purdue University Analysis of a mathematical model that couples explicitly the within-host and between-host dynamics in an environmentally-driven infectious disease will be presented. The within-host sub-system is linked to a contaminated environment (E) via an inoculation rate g(E) for the hosts. The within-host parasite load V(E) can affect the environment contamination, which directly contributes to the infection rate of hosts for the between-host sub-system. When the two sub-systems are considered in isolation (i.e., g(E)=0), the dynamics are standard and simple. That is, either the infection-free equilibrium is stable or a unique positive equilibrium is stable depending on the relevant reproduction number being less or greater than 1. However, when the two sub-systems are explicitly coupled (i.e., g(E)>0), the full system exhibits more complex dynamics including backward bifurcations; that is, multiple positive equilibria can exist with one of which being stable even when the relevant reproduction number is less than 1. Analytic results are obtained which help determine the conditions for various bifurcations as well as global dynamics of the sub-systems. The analysis is carried out by separating the fast and slow variables based on the fact that the immunological and epidemiological processes occur on very different time scales, which provides the possibility to use tools from singular perturbation theory. Numerical simulations of the full system confirm the analytic results. Immunology and epidemiology of hepatitis C virus: plenty of data for a nested model approach. Dr Fabio Luciani Evolutionary dynamics of infectious diseases School of Medical Sciences University of New South Wales, Sydney, Australia Introductions Hepatitis C virus (HCV) evolves rapidly to escape host selective pressures. It is know that innate immune responses mediated by NK cells, HCV-specific neutralizing antibodies (NAbs), as well as T cell responses are critical determinants of the outcome of infection. HCV can be naturally cleared in 30% of the infected people, thus offering the unique opportunity to study the mechanisms with which the host immune response successfully drive viral clearance, or unsuccessfully lead to chronic infections and hence to the larger spread of the disease. Recent data showed that both host and viral genetic factors strongly affect the outcome of the infection. For instance, viral genome mutations have been discovered to drive immune escape, while host genetic polymorphisms in the Interferon Lambda λ3 region predicts viral clearance. Furthermore, the highly polymorphic HLA genes also drive the probability of viral recognition and consequently the probability of T cell response specific against evolving variants. Results Here I argue that the vast data set generated during the last decade, and the dichotomous outcome of this infection offer an ideal model to study how within host immunological and genetic factors affect the success of a viral infection, and ultimately its spread at the epidemiological level. These arguments can then be expanded to other rapidly mutating pathogens that cause chronic infection in humans. Here I will also review some experimental and theoretical work pointing towards this goal. I will present some phylogenetics analyses on viral sequences showing that viral genomes carry heritable traits, which affect disease outcome. Also, I will review recent experimental data convincingly showing the strong role played by host genetic factors in driving the success of the host immune response. Conclusions The lack of a vaccine for rapidly mutating viruses causing chronic infections (e.g. HIV, HCV) or their limited efficacy (Influenza) rely on the extreme and rapid adaptation dynamics of these viruses at both within and between host levels. Therefore, mathematical modeling that nest within-host into epidemiological models with the vast data available can now be developed to understand and eventually predict outcome of diseases. Identifying host immune factors that drive epidemic dynamics in a multi-scale model of tuberculosis Giorgio Guzzetta, Marco Ajelli, Denise Kirschner and Stefano Merler a Trento RISE, Trento, Italy b Bruno Kessler Foundation, Trento, Italy c University of Michigan Medical School, Ann Arbor, USA When a pathogen is transmitted from an infected individual to a susceptible host, many complex factors influence the outcome of transmission: whether the pathogen will cause disease, what are the lengths of latent and infectious periods, if protective immunity will arise and how long will immunity last (memory). Transmission models of disease are numerous and capture many epidemiological aspects. However, broad individual variability exists, that in classical compartmental models is captured by assuming Poisson processes for transitions between epidemiological states (e.g. infectious to removed). Using multi-scale models that explicitly account for the dynamics of host-specific immune responses operating in the population scale can allow a finer-grained description of outcomes of infection and ultimately a better understanding of transmission dynamics. In this study, we propose a multi-scale model for Mycobacterium Tuberculosis (Mtb), the bacterium that causes tuberculosis (TB). The multi-scale model bridges together two existing models: a sociodemographic, individual based model for TB transmission dynamics, and a mechanistic, validated ODE model for host Mtb immune response, expressly adapted for multi-scale integration. Changes to individual epidemiological status are driven by state variables of host imm