Virus Infection Model Research Articles

A Model of Hepatitis B Viral Dynamics with Delays

Hepatitis B is a liver disease caused by the human hepatitis B virus (HBV). Mathematical models help further the understanding of the processes involved and help make predictions. The basic reproduction number, R0, is an index that predicts whether the disease will be chronic or not. This is the single most-important information that a mathematical model can give. Within-host virus processes involve delays. We study two within-host hepatitis B virus infection models without and with delay. One is a standard one, and the other considering additional processes and with two delays is new. We analyze the basic reproduction number and alternative threshold indices. The values of R0 and the alternative indices change depending on the model. All these indices predict whether the infection will persist or not, but they do not give the same rate of growth of the infection when it is starting. Therefore, the choice of the model is very important in establishing whether the infection is chronic or not and how fast it initially grows. We analyze these indices to see how to decrease their value. We study the effect of adding delays and how the threshold indices depend on how the delays are included. We do this by studying the local asymptotic stability of the disease-free equilibrium or by using an equivalent method. We show that, for some models, the indices do not change by introducing delays, but they change when the delays are introduced differently. Numerical simulations are presented to confirm the results. Finally, some conclusions are presented.

Infectious bursal disease virus VP5 triggers host shutoff in a transcription-dependent manner.

Viruses have evolved intricate mechanisms to evade host antiviral responses and exploit cellular resources by manipulating the expression profile of host genes. During infection, viruses encode proteins with shutoff activity to globally inhibit host protein synthesis, which is an effective strategy for immune evasion. In this study, compelling evidence shows that infectious bursal disease virus (IBDV) infection triggers the suppression of host protein synthesis. Furthermore, using both in vitro and in vivo viral infection models, we have identified that IBDV specifically impedes the transcription of host genes via the shutoff activity of viral VP5, simultaneously conferring advantages to IBDV infection in these circumstances. The proposed mechanism suggests that VP5 competitively binds to RanBP1, disrupting the RanGDP/GTP gradient. This disruption interferes with cellular nucleocytoplasmic transport, impairing the nuclear import of proteins bearing nuclear localization signals. The nuclear transport of pivotal transcriptional regulatory factors, such as p65 and IFN regulatory factor 7, is also compromised, leading to the inhibition of pro-inflammatory cytokines and interferon expression. This newly discovered strategy employed by IBDV enables them to manipulate host gene expression, providing novel insights into how viruses evade host immune responses and establish infections.IMPORTANCEViruses manipulate host processes at various levels to regulate or evade both innate and adaptive immune responses, promoting self-survival and efficient transmission. The "host shutoff," a global suppression of host gene expression mediated by various viruses, is considered a critical mechanism for evading immunity. In this study, we have validated the presence of host shutoff during infectious bursal disease virus (IBDV) infection and additionally uncovered that the viral protein VP5 plays a pivotal role in inhibiting the overall synthesis of host proteins, including cytokines, through a transcription-dependent pathway. VP5 competitively binds with RanBP1, leading to disruption of the Ran protein cycle and consequently interfering with nucleocytoplasmic transport, which ultimately results in the suppression of host gene transcription. These findings unveil a novel strategy employed by IBDV to evade host innate immunity and rapidly establish infection. This study also suggests a novel supplement to understanding the pathway through which viruses inhibit host protein synthesis.

Identifiability investigation of within-host models of acute virus infection

<p>Uncertainty in parameter estimates from fitting within-host models to empirical data limits the model's ability to uncover mechanisms of infection, disease progression, and to guide pharmaceutical interventions. Understanding the effect of model structure and data availability on model predictions is important for informing model development and experimental design. To address sources of uncertainty in parameter estimation, we used four mathematical models of influenza A infection with increased degrees of biological realism. We tested the ability of each model to reveal its parameters in the presence of unlimited data by performing structural identifiability analyses. We then refined the results by predicting practical identifiability of parameters under daily influenza A virus titers alone or together with daily adaptive immune cell data. Using these approaches, we presented insight into the sources of uncertainty in parameter estimation and provided guidelines for the types of model assumptions, optimal experimental design, and biological information needed for improved predictions.</p>

The diffusion scattering parameters identification for a modified model of viral infection in the conditions of logistic dynamics of immunological cells

Based on the modification of the infectious disease model, taking into account diffusion disturbances and logistic dynamics of immunological cells, separate approaches to the diffusion scattering parameters identification for different types of functional dependence of diffusion coefficients and given redefinition conditions are proposed. A special step-by-step procedure for numerically asymptotic approximation of the solution to the corresponding singularly perturbed model problem with a delay has been improved. The results of computer experiments on identifying the unknown diffusion scattering parameters are presented. It is noted that the identification and application of variable diffusion coefficients will provide a more accurate prediction of the dynamics of an infectious disease, which is significant in decision-making regarding the use of various medical procedures.

Modelling and analysis of a delayed viral infection model with follicular dendritic cell

Modelling and analysis of a delayed viral infection model with follicular dendritic cell

Mammalian Target of Rapamycin Complex 1 Activation in Macrophages Contributes to Persistent Lung Inflammation following Respiratory Tract Viral Infection

Respiratory virus infections cause millions of hospitalizations worldwide each year. Severe infections lead to lung damage that coincides with persistent inflammation and a lengthy repair period. Vaccination and anti-viral therapy help to mitigate severe infections prior to or during the acute stage of disease, but there are currently limited specific treatment options available to individuals suffering from the long-term sequelae of respiratory viral infection. C57BL/6 mice were infected with influenza A/PR/8/34 as a model for severe viral lung infection and allowed to recover for 21 days. Mice were treated with rapamycin, a well characterized mTORC1 inhibitor on days 12 to 20 post infection; a time period after viral clearance. Persistent inflammation following severe influenza infection in mice was primarily driven by macrophages and T cells. UMAP analysis of flow cytometry data revealed that lung macrophages had high activation of mTORC1, an energy sensing kinase involved in inflammatory immune cell effector functions. Rapamycin treatment reduced lung inflammation and the frequency of exudate macrophages, T cells, and B cells in the lung, while not impacting epithelial progenitor cells or adaptive immune memory. These data highlight mTORC1’s role in sustaining persistent inflammation following clearance of a viral respiratory pathogen and suggest a possible intervention for post-viral chronic lung inflammation.

Antiviral Activity of Double-Stranded Ribonucleic Acid and Interferon Alpha Composition in the Model of Experimental Influenza Infection of Mice

High variability of influenza viruses requires the development of agents for nonspecific resistance stimulation, along with the development of new drugs for prevention and treatment. Among the antiviral drugs, interferons and their inducers are known to exhibit a universally wide spectrum of action. The Institute of Medical Biotechnology, a branch of SRC VB «Vector», Rospotrebnadzor, has developed the technology and obtained pharmaceutical compositions containing an interferon inducer — double stranded ribonucleic acid (dsRNA) from the killer strain of Saccharomyces cerevisiae yeast and recombinant human interferon-alpha-2b (IFN- alpha-2b). The specific antiviral activity of the preparations and synergistic effect of the components within the compositions were shown in L-68 and L-929 cell cultures. The aim of this work was to study antiviral activity of intranasal forms of the pharmaceutical compositions containing yeast dsRNA and recombinant human interferon-alpha-2b in a model of lethal influenza infection in mice. The outbred ICR/CD1 mice were intranasally infected with influenza A/Aichi/2/68 (H3N2) virus. The study compositions were intranasally administered 3 hours before infection with influenza virus, as well as 1 and 3 days post infection. The doses of active components in the administered compositions were as follows: for dsRNA — 2.5 mg/kg, for IFN-alpha-2b — 500 IU/kg, 2500 IU/kg, or 5000 IU/kg. The antiviral activity of the drugs was assessed based on the mortality rate and the average life expectancy of mice. It was shown that a three-time intranasal administration of the composition of dsRNA (2.5 mg/kg) and IFN-alpha-2b (2500 IU) into the infected mice according to therapeutic-prophylactic regimen led to an increase in the rates of survival and average life expectancy of animals, which were comparable to the effect of Tamiflu. The comparison preparations — dsRNA and IFN-alpha-2b — administered intranasally at the same doses and regimen exerted no antiviral effect in this mouse model of viral infection. The data obtained confirm the prospects for further development of new dosage forms of dsRNA and interferons for intranasal application as agents for prevention and treatment of influenza.

Exocrine gland-resident memory CD8+ T cells use mechanosensing for tissue surveillance.

Tissue-resident CD8+ T cells (TRM) continuously scan peptide-MHC (pMHC) complexes in their organ of residence to intercept microbial invaders. Recent data showed that TRM lodged in exocrine glands scan tissue in the absence of any chemoattractant or adhesion receptor signaling, thus bypassing the requirement for canonical migration-promoting factors. The signals eliciting this noncanonical motility and its relevance for organ surveillance have remained unknown. Using mouse models of viral infections, we report that exocrine gland TRM autonomously generated front-to-back F-actin flow for locomotion, accompanied by high cortical actomyosin contractility, and leading-edge bleb formation. The distinctive mode of exocrine gland TRM locomotion was triggered by sensing physical confinement and was closely correlated with nuclear deformation, which acts as a mechanosensor via an arachidonic acid and Ca2+ signaling pathway. By contrast, naïve CD8+ T cells or TRM surveilling microbe-exposed epithelial barriers did not show mechanosensing capacity. Inhibition of nuclear mechanosensing disrupted exocrine gland TRM scanning and impaired their ability to intercept target cells. These findings indicate that confinement is sufficient to elicit autonomous T cell surveillance in glands with restricted chemokine expression and constitutes a scanning strategy that complements chemosensing-dependent migration.

Mucosal immune responses of gut IgM in common carp (Cyprinus carpio) following infection with spring viremia of carp virus (SVCV)

Immunoglobulin M (IgM) specifically recognizes various antigens and can activate complement, mediate cytotoxicity, opsonize and agglutinate pathogens to induce phagocytosis, all of which play an important role in immunity. However, the IgM response of common carp (Cyprinus carpio) in the intestinal mucosa after viral infection has not been thoroughly. Therefore, we successfully produced an anti-carp IgM monoclonal antibody and developed a model of viral infection to study the kinetics of immune responses after viral infection. Our results showed that the expression of IL1-β and Igs were dramatically increased, implying that common carp exhibited a significant innate and adaptive immune response to viral infection. Furthermore, we found that the IgM responses varied between the two infection strategies. At 14 days post-infection (DPI), a significant population of IgM+ B cells were observed in the gut, accompanied by a sharp rise in IgM levels. The immune response to secondary infection started at 7 DPI, suggesting that the IgM response is faster in the gut after re-infection. Importantly, we also explored the variability of different gut compartments to viral infection, and result revealed a stronger immune response in the hindgut than in the foregut and midgut. Overall, our findings indicate that IgM plays an important role in the intestinal immune response following primary and secondary viral infection, in which the hindgut plays a major immune function.

Differential kinetics of splenic CD169+ macrophage death is one underlying cause of virus infection fate regulation

Acute infection and chronic infection are the two most common fates of pathogenic virus infections. While several factors that contribute to these fates are described, the critical control points and the mechanisms that underlie infection fate regulation are incompletely understood. Using the acute and chronic lymphocytic choriomeningitis virus (LCMV) infection model of mice, we find that the early dynamic pattern of the IFN-I response is a differentiating trait between both infection fates. Acute-infected mice generate a 2-wave IFN-I response while chronic-infected mice generate only a 1-wave response. The underlying cause is a temporal difference in CD8 T cell-mediated killing of splenic marginal zone CD169+ macrophages. It occurs later in acute infection and thus enables CD169+ marginal zone macrophages to produce the 2nd IFN-I wave. This is required for subsequent immune events including induction of inflammatory macrophages, generation of effector CD8+ T cells and virus clearance. Importantly, these benefits come at a cost for the host in the form of spleen fibrosis. Due to an earlier marginal zone destruction, these ordered immune events are deregulated in chronic infection. Our findings demonstrate the critical importance of kinetically well-coordinated sequential immune events for acute infection control and highlights that it may come at a cost for the host organism.

The Influence of Flavonoid Compositions on Nrf2 Transcription Factor Expression in Case of Infections Triggered by Influenza A Virus and Transmissible Gastroenteritis Coronavirus

Background. Viral infections trigger transcription factors, including Nrf2, which regulate the expression of genes related to cytokines, chemokines, and more. Nuclear factor erythroid 2-related factor 2 (Nrf2) participates in complex regulatory networks controlling the expression of cytoprotective genes and immune responses. Recently, new roles have been attributed to Nrf2, including the regulation of antiviral responses. Objective. The aim of the study was to analyze Nrf2 activation in influenza virus infection in vivo and in transmissible gastroenteritis coronavirus (TGEV) infection in vitro, as well as the effects of the flavonoid compositions Proteflazidum® and Protoil on the Nrf2 expression in these two experimental models of viral infection. Methods. Outbred white mice were infected with influenza A virus (A/FM/1/47/H1N1 strain). Jurkat cells were infected with TGEV, previously adapted to these cells. Flavonoid compositions Proteflazidum® and Protoil (Ecopharm, Ukraine), containing the mixture of tricin, luteolin, apigenin, quercetin, and rhamnosin, were used in corresponding dilutions. Real-Time PCR was employed to analyze Nrf2 RNA expression in the lungs of mice and in both uninfected and virus-infected cells. Additionally, ELISA was used to assess the expression of Nrf2 peptide. Results. The Nrf2 expression in the lungs of influenza virus-infected mice showed a tendency to increase within a 100-fold range. In virus-infected mice treated with Proteflazidum® or Protoil, the level of Nrf2 expression in the lungs decreased about 10-fold compared to infected untreated mice. TGEV infection resulted in 100-fold increase in Nrf2 expression in Jurkat cells. Both Proteflazidum® and Protoil decreased Nrf2 expression in TGEV-infected cells, while their effects on Nrf2 expression in the intact cells on Day 1 were not detected. Conclusions. Flavonoid compositions have only a slight effect on Nrf2 expression in intact cells. However, in case of virus infection, both in vivo and in vitro, they counteract the extensive up-regulation of Nrf2 expression due to viral infection.

Armstrong strain lymphocytic choriomeningitis virus infection after accidental laboratory exposure

BackgroundLymphocytic choriomeningitis virus (LCMV) is a human pathogen naturally present in wild rodents. In addition, LCMV is routinely used in immunology research as a model of viral infection in mice. The Armstrong common laboratory strain and the Clone-13 variant induce acute and chronic infections in mice, respectively. The frequent use of this virus in laboratory settings is associated with a risk of human infection for laboratory personnel. In contrast to LCMV Clone-13, few human laboratory infections with LCMV Armstrong have been reported, leading to a poor understanding of symptoms related to infection with this specific LCMV strain.Case presentationA researcher accidentally infected herself percutaneously with LCMV Armstrong. Symptoms including headaches, dizziness, eye pain and nausea appeared seven days post-exposure and lasted ten days. LCMV-IgM antibodies were detected at 28 days post-infection and IgG seroconversion was observed later. Complete recovery was confirmed three months post exposure.ConclusionsResearch involving live viruses comes with the risk of infection for research personnel. This case is the first reported accidental human infection with LCMV Armstrong. The symptoms differed from reported infections with LCMV Clone-13, by the absence of fever and vomiting, and presence of leg numbness. This report will therefore help clinicians and public health authorities to recognize the symptoms associated with LCMV Armstrong infections and to offer appropriate counselling to individuals who accidentally expose themselves.

A quantitative model for virus uncoating predicts influenza A infectivity

For virus infection of new host cells, the disassembly of the protective outer protein shell (capsid) is a critical step, but the mechanisms and host-virus interactions underlying the dynamic, active, and regulated uncoating process are largely unknown. Here, we develop an experimentally supported, multiscale kinetics model that elucidates mechanisms of influenza A virus (IAV) uncoating in cells. Biophysical modeling demonstrates that interactions between capsid M1 proteins, host histone deacetylase 6 (HDAC6), and molecular motors can physically break the capsid in a tug-of-war mechanism. Biochemical analysis and biochemical-biophysical modeling identify unanchored ubiquitin chains as essential and allow robust prediction of uncoating efficiency in cells. Remarkably, the different infectivity of two clinical strains can be ascribed to a single amino acid variation in M1 that affects binding to HDAC6. By identifying crucial modules of viral infection kinetics, the mechanisms and models presented here could help formulate novel strategies for broad-range antiviral treatment.

Automated control of the immune response to the causants of infectious disease

The problems that arose as a result of the rapid spread of the new coronavirus infection COVID-19 and the inability of health care institutions to provide the necessary medical care to a large number of patients in a timely manner showed the need to develop new approaches to diagnosis and the formation of an individual treatment program. Important in this direction is the development and implementation of specialized decision support systems based on the integration of expert systems for the analysis and interpretation of medical data and mathematical modeling tools. In order to form effective treatment programs, it is necessary to ensure the availability of reliable tools for predicting the dynamics of the disease in the conditions of external medical influences, various protection mechanisms, spatial effects, mixed infections etc. The purpose of this work is to generalize the basic model of viral infection to predict the complex controlled influence of adsorption and immune therapy on the development of the disease, taking into account diffusion disturbance and temperature response of the body, which is an important element of specialized decision-making systems for the formation of effective treatment programs. To find the solution of the original model singularly perturbed problem with delays, the procedure of stepwise numerical asymptotic approximation of the solutions of the corresponding specially constructed sequence of problems without delay has been modernized. Based on the obtained results of computer modeling, it was confirmed that the introduction of adsorbents during periods of intensive growth of the number of viral elements makes it possible to sufficiently effectively reduce the rate of their reproduction, and, therefore, provides an additional way of controlling the number of antigens in the body and preventing their supercritical growth. It is emphasized that taking into account the features of the action of adsorption drugs is important for making optimized decisions regarding the use of adsorption therapy

Lipin-2 regulates the antiviral and anti-inflammatory responses to interferon.

Interferons (IFN) are crucial antiviral and immunomodulatory cytokines that exert their function through the regulation of a myriad of genes, many of which are not yet characterized. Here, we reveal that lipin-2, a phosphatidic acid phosphatase whose mutations produce an autoinflammatory syndrome known as Majeed syndrome in humans, is regulated by IFN in a STAT-1-dependent manner. Lipin-2 inhibits viral replication both in vitro and in vivo. Moreover, lipin-2 also acts as a regulator of inflammation in a viral context by reducing the signaling through TLR3 and the generation of ROS and release of mtDNA that ultimately activate the NLRP3 inflammasome. Inhibitors of mtDNA release from mitochondria restrict IL-1β production in lipin-2-deficient animals in a model of viral infection. Finally, analyses of databases from COVID-19 patients show that LPIN2 expression levels negatively correlate with the severity of the disease. Overall, these results uncover novel regulatory mechanisms of the IFN response driven by lipin-2 and open new perspectives for the future management of patients with LPIN2 mutations.

SARS-CoV-2 viral persistence in lung alveolar macrophages is controlled by IFN-γ and NK cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA generally becomes undetectable in upper airways after a few days or weeks postinfection. Here we used a model of viral infection in macaques to address whether SARS-CoV-2 persists in the body and which mechanisms regulate its persistence. Replication-competent virus was detected in bronchioalveolar lavage (BAL) macrophages beyond 6 months postinfection. Viral propagation in BAL macrophages occurred from cell to cell and was inhibited by interferon-γ (IFN-γ). IFN-γ production was strongest in BAL NKG2r+CD8+ T cells and NKG2Alo natural killer (NK) cells and was further increased in NKG2Alo NK cells after spike protein stimulation. However, IFN-γ production was impaired in NK cells from macaques with persisting virus. Moreover, IFN-γ also enhanced the expression of major histocompatibility complex (MHC)-E on BAL macrophages, possibly inhibiting NK cell-mediated killing. Macaques with less persisting virus mounted adaptive NK cells that escaped the MHC-E-dependent inhibition. Our findings reveal an interplay between NK cells and macrophages that regulated SARS-CoV-2 persistence in macrophages and was mediated by IFN-γ.

A novel approach to state estimation of HIV infection dynamics using fixed-time fractional order observer

This paper presents a novel approach to designing a fixed-time fractional order observer for estimating the states of the dynamic model of human immunodeficiency virus (HIV) infection. The proposed approach combines output injection terminal sliding mode and RBF neural network strategies to achieve a robust and efficient estimation of the states of the HIV model within a fixed time frame. The main contributions of this work are the introduction of an output injection observer that ensures the stability of the error system along with a novel nonlinear sliding surface that guarantees the fixed-time error convergence to the neighborhood of zero. Moreover, the closed-loop scheme of the observer design is proven to be bounded, and the fixed-time stability of the observer error is obtained using the fractional Lyapunov stability approach. Simulation results show that the proposed fixed-time fractional order observer design provides accurate and efficient estimation of the states of the HIV model.

Mathematical analysis of the transmission dynamics of viral infection with effective control policies via fractional derivative

Abstract It is well known that viral infections have a high impact on public health in multiple ways, including disease burden, outbreaks and pandemic, economic consequences, emergency response, strain on healthcare systems, psychological and social effects, and the importance of vaccination. Mathematical models of viral infections help policymakers and researchers to understand how diseases can spread, predict the potential impact of interventions, and make informed decisions to control and manage outbreaks. In this work, we formulate a mathematical model for the transmission dynamics of COVID-19 in the framework of a fractional derivative. For the analysis of the recommended model, the fundamental concepts and results are presented. For the validity of the model, we have proven that the solutions of the recommended model are positive and bounded. The qualitative and quantitative analyses of the proposed dynamics have been carried out in this research work. To ensure the existence and uniqueness of the proposed COVID-19 dynamics, we employ fixed-point theorems such as Schaefer and Banach. In addition to this, we establish stability results for the system of COVID-19 infection through mathematical skills. To assess the influence of input parameters on the proposed dynamics of the infection, we analyzed the solution pathways using the Laplace Adomian decomposition approach. Moreover, we performed different simulations to conceptualize the role of input parameters on the dynamics of the infection. These simulations provide visualizations of key factors and aid public health officials in implementing effective measures to control the spread of the virus.

A Strainer-Based Platform for the Collection and Immunolabeling of Porcine Epidemic Diarrhea Virus-Infected Porcine Intestinal Organoid.

The development of organoid research has raised new requirements for this methodology. In a previous study, we demonstrated that an emerging protocol achieved the collection, loading, and programmed immunolabeling of mouse intestinal organoids based on a strainer platform. To uncover the applied potential of this novel methodology on organoids from other species, the strainer platform was utilized to characterize the porcine epidemic diarrhea virus (PEDV)-infected porcine intestinal organoid model. Based on a previous study, some steps were changed to improve the efficiency of the assay by simplifying the reagent addition procedure. In addition, we redefined the range of strainer sizes on porcine intestinal organoids, showing that strainers with pore sizes of 40 and 70 μm matched the above protocol well. Notably, the strainer platform was successfully used to label viral proteins, laying the foundation for its application in the visualization of viral infection models. In summary, the potential of the strainer platform for organoid technology was explored further. More extensive exploration of this platform will contribute to the development of organoid technology.

Stability and optimal control of a cytokine-enhanced general HIV infection model with antibody immune response and CTLs immune response

In this article, a cytokine-enhanced viral infection model with cytotoxic T lymphocytes (CTLs) immune response and antibody immune response is proposed and analyzed. The model contains six compartments: uninfected CD4+T cells, infected CD4+T cells, inflammatory cytokines, viruses, CTLs and antibodies. Different from the previous works, this model not only considers virus-to-cell transmission and cell-to-cell transmission, but also includes a new infection mode, namely cytokine-enhanced viral infection. The incidence rates of the healthy CD4+T cells with viruses, infected cells and inflammatory cytokines are given by general functions. Moreover, the production/proliferation and removal/death rates of all compartments are represented by general functions. Firstly, we prove that all the solutions of the model are nonnegative and uniformly bounded. Then, five key parameters with strong biological significance, namely the virus basic reproduction number R 0, CTLs immune response reproduction number R 1, antibody immune response reproductive number R 2, CTLs immune competitive reproductive number R 3 and antibody immune competitive reproductive number R 4 are derived. Then, by using Lyapunov’s method and LaSalle’s invariance principle, we have shown the global stability of each equilibrium. In addition, the numerical simulation results also show that the theoretical results are correct. Finally, we formulate an optimal control problem and solve it using Pontryagins Maximum Principle and an efficient iterative numerical methods. The results of our numerical simulation show that it is very important to control the infection between viruses and cells and between cells and inflammatory cytokines for controlling HIV.