The impact of host immune status on the within-host and population dynamics of antigenic immune escape

Antigenically evolving pathogens such as influenza viruses are difficult to control owing to their ability to evade host immunity by producing immune escape variants. Experimental studies have repeatedly demonstrated that viral immune escape variants emerge more often from immunized hosts than from naive hosts. This empirical relationship between host immune status and within-host immune escape is not fully understood theoretically, nor has its impact on antigenic evolution at the population level been evaluated. Here, we show that this relationship can be understood as a trade-off between the probability that a new antigenic variant is produced and the level of viraemia it reaches within a host. Scaling up this intra-host level trade-off to a simple population level model, we obtain a distribution for variant persistence times that is consistent with influenza A/H3N2 antigenic variant data. At the within-host level, our results show that target cell limitation, or a functional equivalent, provides a parsimonious explanation for how host immune status drives the generation of immune escape mutants. At the population level, our analysis also offers an alternative explanation for the observed tempo of antigenic evolution, namely that the production rate of immune escape variants is driven by the accumulation of herd immunity. Overall, our results suggest that disease control strategies should be further assessed by considering the impact that increased immunity—through vaccination—has on the production of new antigenic variants.     

Minimal within-host dengue models highlight the specific roles of the immune response in primary and secondary dengue infections

In recent years, the within-host viral dynamics of dengue infections have been increasingly characterized, and the relationship between aspects of these dynamics and the manifestation of severe disease has been increasingly probed. Despite this progress, there are few mathematical models of within-host dengue dynamics, and the ones that exist focus primarily on the general role of immune cells in the clearance of infected cells, while neglecting other components of the immune response in limiting viraemia. Here, by considering a suite of mathematical within-host dengue models of increasing complexity, we aim to isolate the critical components of the innate and the adaptive immune response that suffice in the reproduction of several well-characterized features of primary and secondary dengue infections. By building up from a simple target cell limited model, we show that only the innate immune response is needed to recover the characteristic features of a primary symptomatic dengue infection, while a higher rate of viral infectivity (indicative of antibody-dependent enhancement) and infected cell clearance by T cells are further needed to recover the characteristic features of a secondary dengue infection. We show that these minimal models can reproduce the increased risk of disease associated with secondary heterologous infections that arises as a result of a cytokine storm, and, further, that they are consistent with virological indicators that predict the onset of severe disease, such as the magnitude of peak viraemia, time to peak viral load, and viral clearance rate. Finally, we show that the effectiveness of these virological indicators to predict the onset of severe disease depends on the contribution of T cells in fuelling the cytokine storm.     

Within-host viral dynamics of dengue serotype 1 infection

Dengue, the most common mosquito-borne viral infection of humans, is endemic across much of the world, including much of tropical Asia and is increasing in its geographical range. Here, we present a mathematical model of dengue virus dynamics within infected individuals, detailing the interaction between virus and a simple immune response. We fit this model to measurements of plasma viral titre from cases of primary and secondary DENV 1 infection in Vietnam. We show that variation in model parameters governing the immune response is sufficient to create the observed variation in virus dynamics between individuals. Estimating model parameter values, we find parameter differences between primary and secondary cases consistent with the theory of antibody-dependent enhancement (namely enhanced rates of viral entry to target cells in secondary cases). Finally, we use our model to examine the potential impact of an antiviral drug on the within-host dynamics of dengue. We conclude that the impact of antiviral therapy on virus dynamics is likely to be limited if therapy is only started at the onset of symptoms, owing to the typically late stage of viral pathogenesis reached by the time symptoms are manifested and thus treatment is started.     

一类带有特异性免疫细胞钟形增殖率的慢性病毒感染模型的全局动力学性态

特异性免疫应答对控制宿主体内的病毒感染起着非常重要的作用.本文提出并研究了一类具有特异性免疫细胞钟形增殖率的慢性病毒感染模型.这里免疫细胞的钟形增殖意指当病毒载量足够大时其繁殖率会降低.病毒对免疫应答的损害也在本文的模型中被考虑.在找到该模型免疫应答基本再生数的同时,完整分析了其局部动力学行为.为了确定其全局动力学性态,应用中心流型理论对一些临界情形进行了分析,并通过构造适当的Dulac函数排除了该模型周期解的存在性.本文得到的结果显示在一定条件下模型会出现后向分支,这意味着模型的动力学性质会因初始状态的不同而改变.最后的数值模拟说明最终的单调和持续震荡对病毒种群和免疫应答都是有可能发生的.     

How selection forces dictate the variant surface antigens used by malaria parasites

Red blood cells infected by the malaria parasite Plasmodium falciparum express variant surface antigens (VSAs) that evade host immunity and allow the parasites to persist in the human population. There exist many different VSAs and the differential expression of these VSAs is associated with the virulence (damage to the host) of the parasites. The aim of this study is to unravel the differences in the effect key selection forces have on parasites expressing different VSAs such that we can better understand how VSAs enable the parasites to adapt to changes in their environment (like control measures) and how this may impact the virulence of the circulating parasites. To this end, we have built an individual-based model that captures the main selective forces on malaria parasites, namely parasite competition, host immunity, host death and mosquito abundance at both the within- and between-host levels. VSAs are defined by the net growth rates they infer to the parasites and the model keeps track of the expression of, and antibody build-up against, each VSA in all hosts. Our results show an ordered acquisition of VSA-specific antibodies with host age, which causes a dichotomy between the more virulent VSAs that reach high parasitaemias but are restricted to young relatively non-immune hosts, and less virulent VSAs that do not reach such high parasitaemias but can infect a wider range of hosts. The outcome of a change in the parasite''s environment in terms of parasite virulence depends on the exact balance between the selection forces, which sets the limiting factor for parasite survival. Parasites will evolve towards expressing more virulent VSAs when the limiting factor for parasite survival is the within-host parasite growth and the parasites are able to minimize this limitation by expressing more virulent VSAs.     

The evolutionary dynamics of within-generation immune priming in invertebrate hosts

While invertebrates lack the machinery necessary for ‘acquired immunity’, there is increasing empirical evidence that exposure to low levels of disease may ‘prime’ an invertebrate''s immune response, increasing its defence to subsequent exposure. Despite this increasing empirical data, there has been little theoretical attention paid to immune priming. Here, we investigate the evolution of immune priming, focusing on the role of the unique feedbacks generated by a newly developed susceptible–primed–infected epidemiological model. Contrasting our results with previous models on the evolution of acquired immunity, we highlight that there are important implications to the evolution of immunity through priming owing to these different epidemiological feedbacks. In particular, we find that in contrast to acquired immunity, priming is strongly selected for at high as well as intermediate pathogen virulence. We also find that priming may be greatest at either intermediate or high host lifespans depending on the severity of disease. Furthermore, hosts faced with more severe pathogens are more likely to evolve diversity in priming. Finally, we show when the evolution of priming leads to the exclusion of the pathogens or hosts experiencing population cycles. Overall the model acts as a baseline for understanding the evolution of priming in host–pathogen systems.     

Effect of the initial dose of foot-and-mouth disease virus on the early viral dynamics within pigs

This paper investigates the early viral dynamics of foot-and-mouth disease (FMD) within infected pigs. Using an existing within-host model, we investigate whether individual variation can be explained by the effect of the initial dose of FMD virus. To do this, we consider the experimental data on the concentration of FMD virus genomes in the blood (viral load). In this experiment, 12 pigs were inoculated with one of three different doses of FMD virus: low; medium; or high. Measurements of the viral load were recorded over a time course of approximately 11 days for every 8 hours. The model is a set of deterministic differential equations with the following variables: viral load; virus in the interstitial space; and the proportion of epithelial cells available for infection, infected and uninfected. The model was fitted to the data for each animal individually and also simultaneously over all animals varying only the initial dose. We show that the general trend in the data can be explained by varying only the initial dose. The higher the initial dose the earlier the development of a detectable viral load.     

Vaccine-induced pathogen strain replacement: what are the mechanisms?

Host immune systems impose natural selection on pathogen populations, which respond by evolving different antigenic signatures. Like many evolutionary processes, pathogen evolution reflects an interaction between different levels of selection; pathogens can win in between-strain competition by taking over individual hosts (within-host level) or by infecting more hosts (population level). Vaccination, which intensifies and modifies selection by protecting hosts against one or more pathogen strains, can drive the emergence of new dominant pathogen strains-a phenomenon called vaccine-induced pathogen strain replacement. Here, we review reports of increased incidence of subdominant variants after vaccination campaigns and extend the current model for pathogen strain replacement, which assumes that pathogen strain replacement occurs only through the differential effectiveness of vaccines against different pathogen strains. Based on a recent theoretical study, we suggest a broader range of possible mechanisms, some of which allow pathogen strain replacement even when vaccines are perfect-that is, they protect all vaccinated individuals completely against all pathogen strains. We draw an analogy with ecological and evolutionary explanations for competitive dominance and coexistence that allow for tradeoffs between different competitive and life-history traits.     

Competition–colonization trade-off promotes coexistence of low-virulence viral strains

RNA viruses exist as genetically diverse populations displaying a range of virulence degrees. The evolution of virulence in viral populations is, however, poorly understood. On the basis of the experimental observation of an RNA virus clone in cell culture diversifying into two subpopulations of different virulence, we study the dynamics of mutating virus populations with varying virulence. We introduce a competition–colonization trade-off into standard mathematical models of intra-host viral infection. Colonizers are fast-spreading virulent strains, whereas the competitors are less-virulent variants but more successful within co-infected cells. We observe a two-step dynamics of the population. Early in the infection, the population is dominated by colonizers, which later are outcompeted by competitors. Our simulations suggest the existence of steady state in which all virulence classes coexist but are dominated by the most competitive ones. This equilibrium implies collective virulence attenuation in the population, in contrast to previous models predicting evolution of the population towards increased virulence.     

Non-random biodiversity loss underlies predictable increases in viral disease prevalence

Disease dilution (reduced disease prevalence with increasing biodiversity) has been described for many different pathogens. Although the mechanisms causing this phenomenon remain unclear, the disassembly of communities to predictable subsets of species, which can be caused by changing climate, land use or invasive species, underlies one important hypothesis. In this case, infection prevalence could reflect the competence of the remaining hosts. To test this hypothesis, we measured local host species abundance and prevalence of four generalist aphid-vectored pathogens (barley and cereal yellow dwarf viruses) in a ubiquitous annual grass host at 10 sites spanning 2000 km along the North American West Coast. In laboratory and field trials, we measured viral infection as well as aphid fecundity and feeding preference on several host species. Virus prevalence increased as local host richness declined. Community disassembly was non-random: ubiquitous hosts dominating species-poor assemblages were among the most competent for vector production and virus transmission. This suggests that non-random biodiversity loss led to increased virus prevalence. Because diversity loss is occurring globally in response to anthropogenic changes, such work can inform medical, agricultural and veterinary disease research by providing insights into the dynamics of pathogens nested within a complex web of environmental forces.     

Dynamics of killer T cell inflation in viral infections

Upon acute viral infection, a typical cytotoxic T lymphocyte (CTL) response is characterized by a phase of expansion and contraction after which it settles at a relatively stable memory level. Recently, experimental data from mice infected with murine cytomegalovirus (MCMV) showed different and unusual dynamics. After acute infection had resolved, some antigen specific CTL started to expand over time despite the fact that no replicative virus was detectable. This phenomenon has been termed as "CTL memory inflation". In order to examine the dynamics of this system further, we developed a mathematical model analysing the impact of innate and adaptive immune responses. According to this model, a potentially important contributor to CTL inflation is competition between the specific CTL response and an innate natural killer (NK) cell response. Inflation occurs most readily if the NK cell response is more efficient than the CTL at reducing virus load during acute infection, but thereafter maintains a chronic virus load which is sufficient to induce CTL proliferation. The model further suggests that weaker NK cell mediated protection can correlate with more pronounced CTL inflation dynamics over time. We present experimental data from mice infected with MCMV which are consistent with the theoretical predictions. This model provides valuable information and may help to explain the inflation of CMV specific CD8+T cells seen in humans as they age.     

HIV recombination: what is the impact on antiretroviral therapy?

Retroviral recombination is a potential mechanism for the development of multiply drug resistant viral strains but the impact on the clinical outcomes of antiretroviral therapy in HIV-infected patients is unclear. Recombination can favour resistance by combining single-point mutations into a multiply resistant genome but can also hinder resistance by breaking up associations between mutations. Previous analyses, based on population genetic models, have suggested that whether recombination is favoured or hindered depends on the fitness interactions between loci, or epistasis. In this paper, a mathematical model is developed that includes viral dynamics during therapy and shows that population dynamics interact non-trivially with population genetics. The outcome of therapy depends critically on the changes to the frequency of cell co-infection and I review the evidence available. Where recombination does have an effect on therapy, it is always to slow or even halt the emergence of multiply resistant strains. I also find that for patients newly infected with multiply resistant strains, recombination can act to prevent reversion to wild-type virus. The analysis suggests that treatment targeted at multiple parts of the viral life-cycle may be less prone to drug resistance due to the genetic barrier caused by recombination but that, once selected, mutants resistant to such regimens may be better able to persist in the population.     

Maintenance of phenotypic diversity within a set of virulence encoding genes of the malaria parasite Plasmodium falciparum

Infection by the human malaria parasite Plasmodium falciparum results in a broad spectrum of clinical outcomes, ranging from severe and potentially life-threatening malaria to asymptomatic carriage. In a process of naturally acquired immunity, individuals living in malaria-endemic regions build up a level of clinical protection, which attenuates infection severity in an exposure-dependent manner. Underlying this shift in the immunoepidemiology as well as the observed range in malaria pathogenesis is the var multigene family and the phenotypic diversity embedded within. The var gene-encoded surface proteins Plasmodium falciparum erythrocyte membrane protein 1 mediate variant-specific binding of infected red blood cells to a diverse set of host receptors that has been linked to specific disease manifestations, including cerebral and pregnancy-associated malaria. Here, we show that cross-reactive immune responses, which minimize the within-host benefit of each additionally expressed gene during infection, can cause selection for maximum phenotypic diversity at the genome level. We further show that differential functional constraints on protein diversification stably maintain uneven ratios between phenotypic groups, in line with empirical observation. Our results thus suggest that the maintenance of phenotypic diversity within P. falciparum is driven by an evolutionary trade-off that optimizes between within-host parasite fitness and between-host selection pressure.     

Protocols for sampling viral sequences to study epidemic dynamics

With more emphasis being put on global infectious disease monitoring, viral genetic data are being collected at an astounding rate, both within and without the context of a long-term disease surveillance plan. Concurrent with this increase have come improvements to the sophisticated and generalized statistical techniques used for extracting population-level information from genetic sequence data. However, little research has been done on how the collection of these viral sequence data can or does affect the efficacy of the phylogenetic algorithms used to analyse and interpret them. In this study, we use epidemic simulations to consider how the collection of viral sequence data clarifies or distorts the picture, provided by the phylogenetic algorithms, of the underlying population dynamics of the simulated viral infection over many epidemic cycles. We find that sampling protocols purposefully designed to capture sequences at specific points in the epidemic cycle, such as is done for seasonal influenza surveillance, lead to a significantly better view of the underlying population dynamics than do less-focused collection protocols. Our results suggest that the temporal distribution of samples can have a significant effect on what can be inferred from genetic data, and thus highlight the importance of considering this distribution when designing or evaluating protocols and analysing the data collected thereunder.     

Modelling dynamics of the type I interferon response to in vitro viral infection.

Innate immunity is crucial in the early stages of resistance to novel viral infection. The family of cytokines known as the interferons (IFNs) forms an essential component of this system: they are responsible for signalling that an infection is underway and for promoting an antiviral response in susceptible cells. We construct a spatial stochastic model, parameterized by experimental data and informed by analytic approximation, to capture the dynamics of virus-IFN interaction during in vitro infection of Madin-Darby bovine kidney cell monolayers by Herpes simplex virus 1. The dose dependence of infection progression, subsequent monolayer destruction and IFN-beta production are investigated. Implications for in vivo infections, in particular the priming of susceptible cells by IFN-beta during infection, are considered.     

Challenges in forming inferences from limited data: a case study of malaria parasite maturation

Inferring biological processes from population dynamics is a common challenge in ecology, particularly when faced with incomplete data. This challenge extends to inferring parasite traits from within-host infection dynamics. We focus on rodent malaria infections (Plasmodium berghei), a system for which previous work inferred an immune-mediated extension in the length of the parasite development cycle within red blood cells. By developing a system of delay-differential equations to describe within-host infection dynamics and simulating data, we demonstrate the potential to obtain biased estimates of parasite (and host) traits when key biological processes are not considered. Despite generating infection dynamics using a fixed parasite developmental cycle length, we find that known sources of measurement bias in parasite stage and abundance data can affect estimates of parasite developmental duration, with stage misclassification driving inferences about extended cycle length. We discuss alternative protocols and statistical methods that can mitigate such misestimation.     

Timing HIV infection with a simple and accurate population viral dynamics model

Clinical trials for HIV prevention can require knowledge of infection times to subsequently determine protective drug levels. Yet, infection timing is difficult when study visits are sparse. Using population nonlinear mixed-effects (pNLME) statistical inference and viral loads from 46 RV217 study participants, we developed a relatively simple HIV primary infection model that achieved an excellent fit to all data. We also discovered that Aptima assay values from the study strongly correlated with viral loads, enabling imputation of very early viral loads for 28/46 participants. Estimated times between infecting exposures and first positives were generally longer than prior estimates (average of two weeks) and were robust to missing viral upslope data. On simulated data, we found that tighter sampling before diagnosis improved estimation more than tighter sampling after diagnosis. Sampling weekly before and monthly after diagnosis was a pragmatic design for good timing accuracy. Our pNLME timing approach is widely applicable to other infections with existing mathematical models. The present model could be used to simulate future HIV trials and may help estimate protective thresholds from the recently completed antibody-mediated prevention trials.     

The impact of antiretroviral therapy on population-level virulence evolution of HIV-1

In HIV-infected patients, an individual''s set point viral load (SPVL) strongly predicts disease progression. Some think that SPVL is evolving, indicating that the virulence of the virus may be changing, but the data are not consistent. In addition, the widespread use of antiretroviral therapy (ART) has the potential to drive virulence evolution. We develop a simple deterministic model designed to answer the following questions: what are the expected patterns of virulence change in the initial decades of an epidemic? Could administration of ART drive changes in virulence evolution and, what is the potential size and direction of this effect? We find that even without ART we would not expect monotonic changes in average virulence. Transient decreases in virulence following the peak of an epidemic are not necessarily indicative of eventual evolution to avirulence. In the short term, we would expect widespread ART to cause limited downward pressure on virulence. In the long term, the direction of the effect is determined by a threshold condition, which we define. We conclude that, given the surpassing benefits of ART to the individual and in reducing onward transmission, virulence evolution considerations need have little bearing on how we treat.