Virus Infection Model Research Articles

Application of Pseudotyped Viruses.

Highly pathogenic emerging and reemerging viruses have serious public health and socioeconomic implications. Although conventional live virus research methods can more reliably investigate disease pathogenicity and evaluate antiviral products, they usually depend on high-level biosafety laboratories and skilled researchers; these requirements hinder in vitro assessments of efficacy, as well as efforts to test vaccines and antibody drugs. In contrast, pseudotyped viruses (i.e., single-round infectious viruses that mimic the membrane structures of various live viruses) are widely used in studies of highly pathogenic viruses because they can be handled in biosafety level 2 facilities. This chapter provides a concise overview of various aspects of pseudotyped virus technologies, including (1) exploration of the mechanisms of viral infection; (2) evaluation of the efficacies of vaccines and monoclonal antibodies based on pseudovirion-based neutralization assay; (3) assessment of antiviral agents (i.e., antibody-based drugs and inhibitors); (4) establishment of animal models of pseudotyped virus infection in vivo; (5) investigation of the evolution, infectivity, and antigenicity of viral variants and viral glycosylation; and (6) prediction of antibody-dependent cell-mediated cytotoxic activity.

Establishment of Transgenic Mouse Leukemia Cell Lines Expressing Human CD4/CCR5/CyclinT1 Infected with HIV-1.

Establishing a cross-species animal model of human immunodeficiency virus (HIV) infection is crucial for the study of HIV/acquired immunodeficiency syndrome (AIDS). However, due to the species-specific characteristics of HIV-1, the virus can only infect directly humans and a small number of non-human primates. It cannot directly infect mouse cells across species. A mouse leukemia cell line with high CD4 (clusters of differentiation 4)/CCR5 (CC-chemokine receptor 5)/CyclinT1 expression was constructed in this study. First, CD4/CCR5/CyclinT1 lentiviral vector was used to infect a murine leukemia cell line L1210 to express the receptor CD4, co-receptor CCR5 and tat protein driving factor CyclinT1, which are required to infect L1210 cells with HIV-1. The results of sequencing identification and fluorescence expression showed that the plasmid expressing CD4, CCR5, and CyclinT1 vector was successfully constructed and wrapped as the lentiviral vector. Moreover, it was observed that CD4, CCR5, and CyclinT1 proteins were highly expressed in mouse leukemia cells L1210 compared to empty lentiviral vector-transfected cells. Next, viral entry and replication were demonstrated when HIV-1 RNA was detected in body cells and cultured supernatants. Transgenic mice cells L1210 showed significantly greater content of HIV-1 RNA compared to control L1210 cells. Finally, CEMx174 was infected with cell culture supernatants to clarify that the progeny virus is an active virus with infection ability. HIV-1 RNA was highly expressed in CEMx174 cells. This study made the foundation for future studies evaluating HIV-1 cross-species infection in a murine animal model. The results provided new direction for studies investigating the development of vaccines, antiviral drugs screening, and HIV/AIDS pathogenesis.

Global dynamics of deterministic-stochastic dengue infection model including multi specific receptors via crossover effects

<abstract><p>Dengue viruses have distinct viral regularities due to the their serotypes. Dengue can be aggravated from a simple fever in an acute infection to a presumably fatal secondary pathogen. This article investigates a deterministic-stochastic secondary dengue viral infection (SDVI) model including logistic growth and a nonlinear incidence rate through the use of piecewise fractional differential equations. This framework accounts for the fact that the dengue virus can penetrate various kinds of specific receptors. Because of the supplementary infection, the system comprises both heterologous and homologous antibody. For the deterministic case, we determine the invariant region and threshold for the aforesaid model. Besides that, we demonstrate that the suggested stochastic SDVI model yields a global and non-negative solution. Taking into consideration effective Lyapunov candidates, the sufficient requirements for the presence of an ergodic stationary distribution of the solution to the stochastic SDVI model are generated. This report basically utilizes a novel idea of piecewise differentiation and integration. This method aids in the acquisition of mechanisms, including crossover impacts. Graphical illustrations of piecewise modeling techniques for chaos challenges are demonstrated. A piecewise numerical scheme is addressed. For various cases, numerical simulations are presented.</p></abstract>

The Influence of Saturated and Bilinear Incidence Functions on the Dynamical Behavior of HIV Model Using Galerkin Scheme Having a Polynomial of Order Two

Mathematical modelling has been extensively used to measure intervention strategies for the control of contagious conditions. Alignment between different models is pivotal for furnishing strong substantiation for policymakers because the differences in model features can impact their prognostications. Mathematical modelling has been widely used in order to better understand the transmission, treatment, and prevention of infectious diseases. Herein, we study the dynamics of a human immunodeficiency virus (HIV) infection model with four variables: S (t), I (t), C (t), and A (t) the susceptible individuals; HIV infected individuals (with no clinical symptoms of AIDS); HIV infected individuals (under ART with a viral load remaining low), and HIV infected individuals (with two different incidence functions (bilinear and saturated incidence functions). A novel numerical scheme called the continuous Galerkin-Petrov method is implemented for the solution of the model. The influence of different clinical parameters on the dynamical behavior of S (t), I (t), C (t) and A (t) is described and analyzed. All the results are depicted graphically. On the other hand, we explore the time-dependent movement of nanofluid in porous media on an extending sheet under the influence of thermal radiation, heat flux, hall impact, variable heat source, and nanomaterial. The flow is considered to be 2D, boundary layer, viscous, incompressible, laminar, and unsteady. Sufficient transformations turn governing connected PDEs into ODEs, which are solved using the proposed scheme. To justify the envisaged problem, a comparison of the current work with previous literature is presented.

THE WITHIN-HOST VIRAL KINETICS OF SARS-COV-2

Understanding the dynamics of SARS-COV-2 infection in vivo is crucial for exploring more effective treatments. This paper presents a series of dynamic models of viral infection in host. We use affine invariant set Monte Carlo algorithm to achieve parameter fitting and model selection, and study the structural identifiability of these models to determine if the clinical data could specify the model parameters. Then we analyze the actual identifiability and numerical simulation of the selected optimal model. Research shows that all models are structurally identifiable, and data noise has little effect on the actual identifiability of key parameters. Through numerical simulation we found the key factors that may cause cytokine storms. In addition, we also obtain some qualitative conclusions of the model, including the infection threshold, the stability of the equilibrium state and the periodic solution. Studies have found that viral load may exhibit complex periodic motions in some cases, which may provide new evidence to handle repeated reactivations among new corona virus infections.

Partly inhibiting of blow-up by chemotactic repulsion in a cross-diffusion model for virus infection

This work extends the May-Nowak model for virus dynamics to a cross-diffusion version, additionally illustrating diffusion in all components and chemotactically biased migration of healthy cells toward density gradients of infected cells as well as the repulsion of free viruses by infected cells, in which a quasi-steady-state approximation is applied to the equation describing the evolution of infected cells. It is firstly proven that for any given suitably regular initial data and for fixed other model parameters, one can find a number $ \chi_0>0 $ such that whenever the attractive chemotaxis coefficient $ \chi $ satisfying $ \chi\le \chi_0 $, the corresponding spatially two-dimensional no-flux initial-boundary problem admits a global classical solution that is uniform bounded. Moreover, our numerical simulations show that when the attractive chemotaxis coefficient $ \chi $ is sufficiently large, the solution blows up in a finite time; on the other hand, our numerical results also imply that the above-mentioned repulsion can partially suppress the blow-up in some sense.

Dynamic analysis of a cytokine-enhanced viral infection model with infection age.

Recent studies reveal that pyroptosis is associated with the release of inflammatory cytokines which can attract more target cells to be infected. In this paper, a novel age-structured virus infection model incorporating cytokine-enhanced infection is investigated. The asymptotic smoothness of the semiflow is studied. With the help of characteristic equations and Lyapunov functionals, we have proved that both the local and global stabilities of the equilibria are completely determined by the threshold $ \mathcal{R}_0 $. The result shows that cytokine-enhanced viral infection also contributes to the basic reproduction number $ \mathcal{R}_0 $, implying that it may not be enough to eliminate the infection by decreasing the basic reproduction number of the model without considering the cytokine-enhanced viral infection mode. Numerical simulations are carried out to illustrate the theoretical results.

A Novel Viral Infection Model to Guide Optimal Mpox Treatment

A Novel Viral Infection Model to Guide Optimal Mpox Treatment

Stationary distribution for a three-dimensional stochastic viral infection model with general distributed delay.

This work examines a stochastic viral infection model with a general distributed delay. We transform the model with weak kernel case into an equivalent system through the linear chain technique. First, we establish that a global positive solution to the stochastic system exists and is unique. We establish the existence of a stationary distribution of a positive solution under the stochastic condition $ R^s > 0 $, also referred to as a stationary solution, by building appropriate Lyapunov functions. Finally, numerical simulation is proved to verify our analytical result and reveals the impact of stochastic perturbations on disease transmission.

Threshold asymptotic dynamics for a spatial age-dependent cell-to-cell transmission model with nonlocal disperse

This research is concerned to study the global threshold dynamics of a hybrid viral infection model, with the assumption that all parameters are space dependent. The considered hybrid model contains three principal equations, the first is an ordinary differential equation that represents the uninfected cells, an age-structured equation modeled by the transport equation for infected-cells, and a diffusive equation that studies the evolution of the virus. The challenging mathematical aspect of this research lies in the fact that the model is partially degenerate and the solution map is not compact. Also, understanding the global threshold dynamics in terms of this partial degeneracy, mostly with age-structured equation and nonlocal diffusion is the ultimate challenging point of this research. The existence and the uniqueness of a global solution are proved. Further, the existence of a global compact attractor is shown. Moreover, the basic reproduction number $ \mathfrak{R}_0 $ is identified for the model with its threshold role: If $ \mathfrak{R}_0<1 $, the infection-free-steady state is globally asymptotically stable; for $ \mathfrak{R}_0>1 $, the solution of the studied model is uniformly persistent and the pathogen persists in a unique positive steady state, which it is shown using the Lyapunov approach. The results are supported by some graphical representations for illustrating the finding.

A General Fractional-Order Viral Infection Model with Cell-to-Cell Transmission and Adaptive Immunity

A General Fractional-Order Viral Infection Model with Cell-to-Cell Transmission and Adaptive Immunity

Comparison of the Antiviral Activity of Remdesivir, Chloroquine, and Interferon-β as Single or Dual Agents Against the Human Beta-Coronavirus OC43.

The human beta-coronavirus strain, OC43, provides a useful model for testing the antiviral activity of various agents. We compared the activity of several antiviral drugs against OC43, including remdesivir, chloroquine, interferon (IFN)-β, IFN-λ1, and IFN-λ4, in two distinct cell types: human colorectal carcinoma cell line (HCT-8 cells) and normal human bronchial epithelial (NHBE) cells. We also tested whether these agents mediate additive, synergistic, or antagonistic activity against OC43 infection when used in combination. When used as single agents, remdesivir exhibited stronger antiviral activity than chloroquine, and IFN-β exhibited stronger activity than IFN-λ1 or IFN-λ4 against OC43 in both HCT-8 and NHBE cells. Anakinra (IL-1 inhibitor) and tocilizumab (IL-6 inhibitor) did not mediate any antiviral activity. The combination of IFN-β plus chloroquine or remdesivir resulted in higher synergy scores and higher expression of IFN-stimulated genes than did IFN-β alone. In contrast, the combination of remdesivir plus chloroquine resulted in an antagonistic interaction in NHBE cells. Our findings indicate that the combined use of IFN-β plus remdesivir or chloroquine induces maximal antiviral activity against human coronavirus strain OC43 in primary human respiratory epithelial cells. Furthermore, our experimental OC43 virus infection model provides an excellent method for evaluating the biological activity of antiviral drugs.

Longitudinal Analysis of the Phenotype, Transcriptional Profile, and Anatomic Location of Memory CD8 T Cell Subsets after Acute Viral Infection.

Increased demand for novel, highly effective vaccination strategies necessitates a better understanding of long-lived memory CD8 T cell differentiation. To achieve this understanding, we used the mouse model of acute lymphocytic choriomeningitis virus (LCMV) infection. We reexamined classical memory CD8 T cell subsets and performed in-depth, longitudinal analysis of their phenotype, transcriptional programming, and anatomic location within the spleen. All analyses were performed at multiple time points from 8 days to 1 year postinfection. Memory subsets are conventionally defined by their expression of KLRG1 and IL-7Rα, as follows: KLRG1+IL-7Rα- terminal effectors (TEs) and KLRG1-IL-7Rα+ memory precursors (MPs). But we also characterized a third KLRG1+IL-7Rα+ subset which we refer to as KLRG1+ MPs. In these analyses, we defined a comprehensive memory phenotype that is associated with higher levels of CD28 expression. We also demonstrated that MPs, KLRG1+ MPs, and TEs have distinct localization programs within the spleen. We found that MPs became preferentially enriched in the white pulp as early as 1 to 2 weeks postinfection, and their predominance in the white pulp was maintained throughout the course of a year. On the other hand, KLRG1+ MPs and TEs localized to the red pulp just as early, and they consistently localized to the red pulp thereafter. These findings indicate that location may be crucial for memory formation and that white pulp-derived signals may contribute to long-term memory survival. Achieving robust memory responses following vaccination may require more deliberate consideration of which memory phenotypes are induced, as well as where they traffic, as these factors could impact their longevity. IMPORTANCE CD8 T cells play a critical role in viral immunity and it is important to understand how memory cells are formed and what processes lead to their long-term maintenance. Here, we use a mouse model of acute infection to perform an in-depth, longitudinal analysis of memory CD8 T cell differentiation, examining the phenotype and location of memory cells out to 1 year postinfection.

Transcriptomic reveals the ferroptosis features of host response in a mouse model of Zika virus infection.

Zika virus (ZIKV) is a neurotropic flavivirus. The outbreak of ZIKV in 2016 created a global health emergency. However, the underlying pathogenic mechanisms remain elusive. We investigated the host response features of in vivo replication in a mouse model of ZIKV infection, by performing a series of transcriptomic and bioinformatic analyses of ZIKV and mock-infected brain tissue. Tissue damage, inflammatory cells infiltration and high viral replication were observed in the brain tissue of ZIKV infected mice. RNA-Seq of the brain indicated the activation of ferroptosis pathways. Enrichment analysis of ferroptosis regulators revealed their involvement in pathways such as mineral absorption, fatty acid biosynthesis, fatty acid degradation, PPAR signaling pathway, peroxidase, and adipokinesine signalling pathway. We then identified 12 interacted hub ferroptosis regulators (CYBB, HMOX1, CP, SAT1, TF, SLC39A14, FTL, LPCAT3, FTH1, SLC3A2, TP53, and SLC40A1) that were related to the differential expression of CD8+ T cells, microglia and monocytes. CYBB, HMOX1, SALT, and SLAC40A1 were selected as potential biomarkers of ZIKV infection. Finally, we validated our results using RT-qPCR and outside available datasets. For the first time, we proposed a possible mechanism of ferroptosis in brain tissue infected by ZIKV in mice and identified the four key ferroptosis regulators.

506. Neonatal CD8+ T Cells Demonstrate PD-1 Dependent Impairment Following Human Metapneumovirus Infection

Abstract Background Human metapneumovirus (HMPV) is a leading cause of pediatric acute respiratory illness, accounting for 14.2 million acute lower respiratory tract infections and 500,000 hospitalizations per year in children less than 5 years of age globally. Infants and neonates are particularly susceptible to severe HMPV disease. Our prior studies in adult mice demonstrated CD8+ T cells were critical for clearance of HMPV infection, although these cells show impaired function due to PD-1:PD-L1 signaling. However, the immune system in the neonatal lung skews towards an anti-inflammatory and tolerogenic response when compared to adults. We therefore sought to explore the roles CD8+ T cell and PD-1 signaling in neonatal mice to recapitulate the population at highest risk. Methods C57BL/6 or Pdcd1-/- pups were infected intranasally with 1.0x106 PFU/g of a clinical isolate of HMPV (TN94-49) on day of life 4-6. Viral burden was assessed via plaque assay and cellular responses were characterized by multispectral flow cytometry. Results HMPV infection led to stunted weight gain in pups compared to mock-infected controls. HMPV-infected neonatal mice had a robust innate immune response comprised of neutrophils, CD103+ dendritic cells, and interstitial macrophages, all of which demonstrated upregulation of PD-L1. From an adaptive perspective, neonatal mice mounted an antigen-specific CD8+ T cell response and resolved HMPV infection by day 8 post-infection. Similar to our prior studies in adult mice, neonatal CD8+ T cells upregulated expression of several inhibitory receptors, such as PD-1, LAG-3, and TIM-3. Neonatal CD8+T cells demonstrated limited effector cytokine production, such as IFN-γ and granzyme B, following ex vivo stimulation with a class I HMPV-specific peptide. Pdcd1-/- mice (lacking PD-1) also mounted an antigen-specific CD8+ T cell response, but had markedly increased production of IFN-γ and granzyme B. Conclusion These data demonstrate that PD-1 signaling on CD8+ T cells constrains the antiviral response in a novel model of neonatal respiratory viral infection. Understanding the mechanisms that inhibit neonatal anti-viral responses could present opportunities for novel therapeutic strategies for common infections with high morbidity and mortality in neonates and infants. Disclosures John Williams, MD, GlaxoSmithKline: Advisor/Consultant|Quidel: Advisor/Consultant.

Viral Infection Model with Diffusion and Distributed Delay: Finite-Dimensional Global Attractor.

We study a virus dynamics model with reaction-diffusion, logistic growth terms and a general non-linear infection rate functional response. The model has a distributed delay, including the case of state-selective delay. We construct a dynamical system in a Hilbert space and prove the existence of a finite-dimensional global attractor.

Chikungunya patient transcriptional signatures faithfully recapitulated in a C57BL/6J mouse model.

An adult wild-type C57BL/6J mouse model of chikungunya virus (CHIKV) infection and disease has been extensively used to study the alphaviral arthritic immunopathology and to evaluate new interventions. How well mouse models recapitulate the gene expression profiles seen in humans remains controversial. Herein we perform a comparative transcriptomics analysis using RNA-Seq datasets from the C57BL/6J CHIKV mouse model with datasets obtained from adults and children acutely infected with CHIKV. Despite sampling quite different tissues, peripheral blood from humans and feet from mice, gene expression profiles were quite similar, with an overlap of up to ≈50% for up-regulated single copy orthologue differentially expressed genes. Furthermore, high levels of significant concordance between mouse and human were seen for immune pathways and signatures, which were dominated by interferons, T cells and monocyte/macrophages. Importantly, predicted responses to a series of anti-inflammatory drug and biologic treatments also showed cogent similarities between species. Comparative transcriptomics and subsequent pathway analysis provides a detailed picture of how a given model recapitulates human gene expression. Using this method, we show that the C57BL/6J CHIKV mouse model provides a reliable and representative system in which to study CHIKV immunopathology and evaluate new treatments.

Mathematical analysis of fractional-order Caputo’s derivative of coronavirus disease model via Laplace Adomian decomposition method

BackgroundThe world's survival ability has been threatened by the COVID-19 outbreak. The possibility of the virus reemerging in the future should not be disregarded, even if it has been confined to certain areas of the world after wreaking such havoc. This is because it is impossible to prove that the virus has been totally eliminated. This research attempts to investigate the spread and control of the COVID-19 virus in Nigeria using the Caputo fractional order derivative in a proposed model.ResultsWe proposed a competent nine-compartment model of Corona virus infection. It starts by demonstrating that the model is epidemiologically sound in terms of solution existence and uniqueness. The basic reproduction threshold R0 was determined using the next-generation matrix technique. We applied the Laplace-Adomian decomposition method to the fractional-order Caputo's derivative model of the Corona virus disease to produce the approximate solution of the model analytically. The obtained results, in the form of an infinite series, were simulated using the MAPLE 18 package to investigate the effect of fractional order derivative on the dynamics of COVID-19 transmission in the model and shed light on methods of eradication. The graphical interpretations of the simulation process were shown and discussed accordingly.ConclusionsThe study reveals the effect of the Caputo fractional order derivative in the transmission dynamics of the disease. Individual recovery was found to be greatest at an integer order, which represents the full implementation of other factors such as treatment, vaccination, and disease transmission reduction. Hence, we advised that researchers, government officials, and health care workers make use of the findings of this study to provide ways in which disease transmission will be reduced to a minimum to stop the prevalence of COVID-19 by applying the findings of this study.

Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumour cells.

Oncolytic virotherapy is a promising form of cancer treatment that uses native or genetically engineered viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is not effective in a substantial proportion of cancer patients, partly due to the occurrence of infection-resistant tumour cells. To shed new light on the mechanisms underlying therapeutic failure and to discover strategies that improve therapeutic efficacy we designed a cell-based model of viral infection. The model allows us to investigate the dynamics of infection-sensitive and infection-resistant cells in tumour tissue in presence of the virus. To reflect the importance of the spatial configuration of the tumour on the efficacy of virotherapy, we compare three variants of the model: two 2D models of a monolayer of tumour cells and a 3D model. In all model variants, we systematically investigate how the therapeutic outcome is affected by the properties of the virus (e.g. the rate of viral spread), the tumour (e.g. production rate of resistant cells, cost of resistance), the healthy stromal cells (e.g. degree of resistance to the virus) and the timing of treatment. We find that various therapeutic outcomes are possible when resistant cancer cells arise at low frequency in the tumour. These outcomes depend in an intricate but predictable way on the death rate of infected cells, where faster death leads to rapid virus clearance and cancer persistence. Our simulations reveal three different causes of therapy failure: rapid clearance of the virus, rapid selection of resistant cancer cells, and a low rate of viral spread due to the presence of infection-resistant healthy cells. Our models suggest that improved therapeutic efficacy can be achieved by sensitizing healthy stromal cells to infection, although this remedy has to be weighed against the toxicity induced in the healthy tissue.

A class of diffusive delayed viral infection models with general incidence function and cellular proliferation

We propose and analyze a new class of three dimensional space models that describes infectious diseases caused by viruses such as hepatitis B virus (HBV) and hepatitis C virus (HCV). This work constructs a Reaction–Diffusion-Ordinary Differential Equation model of virus dynamics, including absorption effect, cell proliferation, time delay, and a generalized incidence rate function. By constructing suitable Lyapunov functionals, we show that the model has threshold dynamics: if the basic reproduction number mathcal {R}_{0}(tau ) le 1 , then the uninfected equilibrium is globally asymptotically stable, whereas if mathcal {R}_{0}(tau ) > 1, and under certain conditions, the infected equilibrium is globally asymptotically stable. This precedes a careful study of local asymptotic stability. We pay particular attention to prove boundedness, positivity, existence and uniqueness of the solution to the obtained initial and boundary value problem. Finally, we perform some numerical simulations to illustrate the theoretical results obtained in one-dimensional space. Our results improve and generalize some known results in the framework of virus dynamics.