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.     

Towards a quantitative understanding of the within-host dynamics of influenza A infections

Although the influenza A virus has been extensively studied, a quantitative understanding of the infection dynamics is still lacking. To make progress in this direction, we designed several mathematical models and compared them with data from influenza A infections of mice. We find that the immune response (IR) plays an important part in the infection dynamics. Both an innate and an adaptive IR are required to provide adequate explanation of the data. In contrast, regrowth of epithelial cells did not seem to be an important mechanism on the time scale of the infection. We also find that different model variants for both innate and adaptive responses fit the data well, indicating the need for additional data to allow further model discrimination.     

Effect of different modes of viral spread on the dynamics of multiply infected cells in human immunodeficiency virus infection

Infection of individual cells with more than one HIV particle is an important feature of HIV replication, which may contribute to HIV pathogenesis via the occurrence of recombination, viral complementation and other outcomes that influence HIV replication and evolutionary dynamics. A previous mathematical model of co-infection has shown that the number of cells infected with i viruses correlates with the ith power of the singly infected cell population, and this has partly been observed in experiments. This model, however, assumed that virus spread from cell to cell occurs only via free virus particles, and that viruses and cells mix perfectly. Here, we introduce a cellular automaton model that takes into account different modes of virus spread among cells, including cell to cell transmission via the virological synapse, and spatially constrained virus spread. In these scenarios, it is found that the number of multiply infected cells correlates linearly with the number of singly infected cells, meaning that co-infection plays a greater role at lower virus loads. The model further indicates that current experimental systems that are used to study co-infection dynamics fail to reflect the true dynamics of multiply infected cells under these specific assumptions, and that new experimental techniques need to be designed to distinguish between the different assumptions.     

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.     

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.     

Occurrence of HIV eradication for preexposure prophylaxis treatment with a deterministic HIV model

The authors examine the human immunodeficiency virus (HIV) eradication in this study using a mathematical model and analyse the occurrence of virus eradication during the early stage of infection. To this end they use a deterministic HIV‐infection model, modify it to describe the pharmacological dynamics of antiretroviral HIV drugs, and consider the clinical experimental results of preexposure prophylaxis HIV treatment. They also use numerical simulation to model the experimental scenario, thereby supporting the clinical results with a model‐based explanation. The study results indicate that the protocol employed in the experiment can eradicate HIV in infected patients at the early stage of the infection.Inspec keywords: diseases, numerical analysis, drugs, patient treatmentOther keywords: preexposure prophylaxis HIV treatment, antiretroviral HIV drug, pharmacological dynamics, deterministic HIV‐infection model, early infection stage, virus eradication, mathematical model, human immunodeficiency virus, HIV eradication     

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.     

HIV-1核心蛋白Gag与IL-6共表达重组鸡痘病毒的构建及其免疫原性研究

分别将IL-6和HIV-1gag基因插入到鸡痘病毒表达载体质粒pUTAL串联启动子和复合启动子(ATI-P7．5)下游，构建了重组鸡痘病毒表达质粒pUTA-GAG-IL6。经同源重组和Western blot检测，获得重组鸡痘病毒，并将该重组病毒免疫BALB／c小鼠，检测免疫小鼠血清抗体水平和特异性CTL杀伤活性。结果获得的重组鸡痘病毒可同时表达HIV-1核心蛋白和IL-6，并在感染细胞内形成病毒样粒子。重组病毒具有良好的免疫原性，可诱导小鼠产生特异性体液免疫和细胞免疫。     

PLGA nanodepots co-encapsulating prostratin and anti-CD25 enhance primary natural killer cell antiviral and antitumor function

Nano Research - Natural killer (NK) cells are attractive effector cells of the innate immune system against human immunodeficiency virus (HIV) and cancer. However, NK cell therapies are limited by...     

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.     

Modelling the influence of activation-induced apoptosis of CD4+ and CD8+ T-cells on the immune system response of a HIV-infected patient.

On the basis of the human immunodeficiency virus (HIV) infection dynamics model proposed by Adams, the authors propose an extended model that aims at incorporating the influence of activation-induced apoptosis of CD4+ and CD8+ T-cells on the immune system response of HIV-infected patients. Through this model, the authors study the influence of this phenomenon on the time evolution of specific cell populations such as plasma concentrations of HIV copies, or blood concentrations of CD4+ and CD8+ T-cells. In particular, this study shows that depending on its intensity, the apoptosis phenomenon can either favour or mitigate the long-term evolution of the HIV infection.     

Aptamer‐Engineered Natural Killer Cells for Cell‐Specific Adaptive Immunotherapy

Natural killer (NK) cells are a key component of the innate immune system as they can attack cancer cells without prior sensitization. However, due to lack of cell‐specific receptors, NK cells are not innately able to perform targeted cancer immunotherapy. Aptamers are short single‐stranded oligonucleotides that specifically recognize their targets with high affinity in a similar manner to antibodies. To render NK cells with target‐specificity, synthetic CD30‐specific aptamers are anchored on cell surfaces to produce aptamer‐engineered NK cells (ApEn‐NK) without genetic alteration or cell damage. Under surface‐anchored aptamer guidance, ApEn‐NK specifically bind to CD30‐expressing lymphoma cells but do not react to off‐target cells. The resulting specific cell binding of ApEn‐NK triggers higher apoptosis/death rates of lymphoma cells compared to parental NK cells. Additionally, experiments with primary human NK cells demonstrate the potential of ApEn‐NK to specifically target and kill lymphoma cells, thus presenting a potential new approach for targeted immunotherapy by NK cells.     

Modelling HIV-1 2-LTR dynamics following raltegravir intensification

A model of reservoir activation and viral replication is introduced accounting for the production of 2-LTR HIV-1 DNA circles following antiviral intensification with the HIV integrase inhibitor raltegravir, considering contributions of de novo infection events and exogenous sources of infected cells, including quiescent infected cell activation. The model shows that a monotonic increase in measured 2-LTR concentration post intensification is consistent with limited de novo infection primarily maintained by sources of infected cells unaffected by raltegravir, such as quiescent cell activation, while a transient increase in measured 2-LTR concentration is consistent with significant levels of efficient (R₀ > 1) de novo infection. The model is validated against patient data from the INTEGRAL study and is shown to have a statistically significant fit relative to the null hypothesis of random measurement variation about a mean. We obtain estimates and confidence intervals for the model parameters, including 2-LTR half-life. Seven of the 13 patients with detectable 2-LTR concentrations from the INTEGRAL study have measured 2-LTR dynamics consistent with significant levels of efficient replication of the virus prior to treatment intensification.     

Role of high-dose exposure in transmission hot zones as a driver of SARS-CoV-2 dynamics

Epidemiological data about SARS-CoV-2 spread indicate that the virus is not transmitted uniformly in the population. The transmission tends to be more effective in select settings that involve exposure to relatively high viral dose, such as in crowded indoor settings, assisted living facilities, prisons or food processing plants. To explore the effect on infection dynamics, we describe a new mathematical model where transmission can occur (i) in the community at large, characterized by low-dose exposure and mostly mild disease, and (ii) in so-called transmission hot zones, characterized by high-dose exposure that can be associated with more severe disease. The model yields different types of epidemiological dynamics, depending on the relative importance of hot zone and community transmission. Interesting dynamics occur if the rate of virus release/deposition from severely infected people is larger than that of mildly infected individuals. Under this assumption, we find that successful infection spread can hinge upon high-dose hot zone transmission, yet the majority of infections are predicted to occur in the community at large with mild disease. In this regime, residual hot zone transmission can account for continued virus spread during community lockdowns, and the suppression of hot zones after community interventions are relaxed can cause a prolonged lack of infection resurgence following the reopening of society. This gives rise to the notion that targeted interventions specifically reducing virus transmission in the hot zones have the potential to suppress overall infection spread, including in the community at large. Epidemiological trends in the USA and Europe are interpreted in light of this model.     

Prediction of the containment of HIV infection by antiretroviral therapy – a variable structure control approach

It is demonstrated that the reachability paradigm from variable structure control theory is a suitable framework to monitor and predict the progression of the human immunodeficiency virus (HIV) infection following initiation of antiretroviral therapy (ART). A manifold is selected which characterises the infection‐free steady‐state. A model of HIV infection together with an associated reachability analysis is used to formulate a dynamical condition for the containment of HIV infection on the manifold. This condition is tested using data from two different HIV clinical trials which contain measurements of the CD4+ T cell count and HIV load in the peripheral blood collected from HIV infected individuals for the six month period following initiation of ART. The biological rates of the model are estimated using the multi‐point identification method and data points collected in the initial period of the trial. Using the parameter estimates and the numerical solutions of the model, the predictions of the reachability analysis are shown to be consistent with the clinical diagnosis at the conclusion of the trial. The methodology captures the dynamical characteristics of eventual successful, failed and marginal outcomes. The findings evidence that the reachability analysis is an appropriate tool to monitor and develop personalised antiretroviral treatment.Inspec keywords: microorganisms, patient treatment, drugs, parameter estimationOther keywords: HIV infection, antiretroviral therapy, variable structure control theory, human immunodeficiency virus, antiretroviral drugs, multipoint identification method, parameter estimation, reachability analysis     

口蹄疫病毒二价DNA疫苗的构建及实验免疫研究

通过PCR方法从本室已构建的克隆载体pGEMT-P1-2A获得O型口蹄疫病毒主要保护性抗原VP1基因,以基因突变获得A型VP1基因。将这两种血清型的VP1基因串联后连接到真核表达载体PVAX1 PCMV启动子下游,构建成口蹄疫二价核酸疫苗pVAX1-OA。经Western blot和IFA检测,目的蛋白在HeLa细胞中获得正确表达。动物实验表明,免疫小鼠T淋巴细胞明显增殖,特异性CTL杀伤活性较对照组显著提高;血清抗体能分别与O型和A型抗原反应,抗体效价均高于空白对照组,但较灭活苗低。     

Robust control of HIV infection by antiretroviral therapy: a super‐twisting sliding mode control approach

Acquired immune deficiency syndrome is an epidemic infectious disease which is caused by the human immunodeficiency virus (HIV) and that has proliferated across worldwide. It has been a matter of concern for the scientific community to develop an antiretroviral therapy, which will prompt a rapid decline in viral abundance. With this motivation, this study proposes the design of a robust super twisting sliding mode controller based on output information for an uncertain HIV infection model. The control objective is to decrease the concentration of infected CD4+ T cells to a specified level by drug administration using only the output information of the uncertain HIV infection model which is total CD4+ T cell concentration. The robust output‐feedback controller has been developed in combination with a robust exact differentiator, functioning as an observer. The reported analysis demonstrates that the approach proposed here is capable of ensuring robust performance under several operating conditions, measurement and modelling error, parametric uncertainties and external disturbances and the simulation results prove the proficiency of the controller proposed.Inspec keywords: control system synthesis, observers, robust control, drugs, medical control systems, diseases, uncertain systems, variable structure systems, patient treatment, feedback, cellular biophysics, microorganismsOther keywords: robust control, antiretroviral therapy, sliding mode control approach, acquired immune deficiency syndrome, epidemic infectious disease, human immunodeficiency virus, scientific community, robust super, mode controller, output information, uncertain HIV infection model, control objective, infected CD4, total CD4, T cell concentration, robust output‐feedback controller, robust exact differentiator, robust performance     

Overcoming pancreatic cancer immune resistance by codelivery of CCR2 antagonist using a STING-activating gemcitabine-based nanocarrier

STING agonist has recently gained much attention for cancer treatment, but the therapeutic potential of STING agonist is hampered by STING-associated tumor immune resistance. In this work, guided by both bioinformatics and computer modeling, we rationally designed a “one stone hits two birds” nanoparticle-based strategy to simultaneously activate STING innate immune response while eliminating STING-associated immune resistance for the treatment of pancreatic ductal adenocarcinoma (PDAC). We discovered that the ultra-small sized micellar system based on gemcitabine-conjugated polymer (PGEM), which showed superior capacity of penetration in pancreatic tumor spheroid model and orthotopic tumor model, could serve as a novel “STING agonist”. The activation of STING signaling in dendritic cells (DCs) by PGEM increased both innate nature killer (NK) and adaptive anti-tumor T cell response. However, activation of STING signaling by PGEM in tumor cells also drove the induction of chemokines CCL2 and CCL7, resulting in immune resistance by recruiting tumor associated macrophage (TAM) and myeloid-derived suppressor cells (MDSCs). Through the combination of computer modeling and experimental screening, we developed a dual delivery modality by incorporating a CCR2 (the receptor shared by both CCL2 and CCL7) antagonist PF-6309 (PF) into PGEM micellar system. Our studies demonstrated that PGEM/PF formulation significantly reduced pancreatic tumor burden and induced potent anti-tumor immunity through reversing the CCL2/CCL7-mediated immunosuppression. Moreover, PGEM/PF sensitized PDAC tumors to anti-PD-1 therapy, leading to complete suppression/eradication of the tumors. Our work has shed light to the multi-faceted role of STING activation and provided a novel immunotherapy regimen to maximize the benefit of STING activation for PDAC treatment. In addition, this work paved a new way for bioinformatics and computer modeling-guided rational design of nanomedicine.     

Fluctuations in T cell receptor and pMHC interactions regulate T cell activation

Adaptive immune responses depend on interactions between T cell receptors (TCRs) and peptide major histocompatibility complex (pMHC) ligands located on the surface of T cells and antigen presenting cells (APCs), respectively. As TCRs and pMHCs are often only present at low copy numbers their interactions are inherently stochastic, yet the role of stochastic fluctuations on T cell function is unclear. Here, we introduce a minimal stochastic model of T cell activation that accounts for serial TCR-pMHC engagement, reversible TCR conformational change and TCR aggregation. Analysis of this model indicates that it is not the strength of binding between the T cell and the APC cell per se that elicits an immune response, but rather the information imparted to the T cell from the encounter, as assessed by the entropy rate of the TCR-pMHC binding dynamics. This view provides an information-theoretic interpretation of T cell activation that explains a range of experimental observations. Based on this analysis, we propose that effective T cell therapeutics may be enhanced by optimizing the inherent stochasticity of TCR-pMHC binding dynamics.     

Onset of virus systemic infection in plants is determined by speed of cell-to-cell movement and number of primary infection foci

The cornerstone of today''s plant virology consists of deciphering the molecular and mechanistic basis of host–pathogen interactions. Among these interactions, the onset of systemic infection is a fundamental variable in studying both within- and between-host infection dynamics, with implications in epidemiology. Here, we developed a mechanistic model using probabilistic and spatio-temporal concepts to explain dynamic signatures of virus systemic infection. The model dealt with the inherent characteristic of plant viruses to use two different and sequential stages for their within-host propagation: cell-to-cell movement from the initial infected cell and systemic spread by reaching the vascular system. We identified the speed of cell-to-cell movement and the number of primary infection foci in the inoculated leaf as the key factors governing this dynamic process. Our results allowed us to quantitatively understand the timing of the onset of systemic infection, describing this global process as a consequence of local spread of viral populations. Finally, we considered the significance of our predictions for the evolution of plant RNA viruses.