Search Results (29)

HIV latency, driven by a complex interplay of host factors, remains a key barrier to viral clearance. Current latency-reversing agents (LRAs) demonstrate limited efficacy and specificity, and none have been approved for clinical use. Although natural products have shown promise as LRAs, the therapeutic potential of fungal metabolites remains underexplored. Candida albicans, a prevalent human commensal and opportunistic pathogen, produces diverse secondary metabolites that can influence host pathways, affecting latency dynamics. This study aimed to investigate the latency-modulating potential of secondary metabolites of C. albicans using an integrative network pharmacology and computational pipeline. C. albicans secondary metabolites were retrieved from the literature, screened for drug-likeness, and mapped to human targets and biological pathways annotated in HIV latency. Key metabolites, hub genes, and pathways were systematically characterized through network and computational analyses. Six drug-like candidates, identified from 185 absorption, distribution, metabolism, excretion, and toxicity (ADMET)-screened metabolites, collectively mapped to 369 human genes with a 6.5% overlap in HIV latency (176 shared and 20 hub genes). These overlapping genes were significantly enriched for signal transduction, membrane localization, and adaptive responses to chemical stimuli. Kyoto encyclopedia of genes and genomes (KEGG) enrichment revealed oncogenic diseases (non-small cell lung, pancreatic, and prostate cancers) and latency-associated cascades, including PD-L1/PD-1, HIF-1, Ras, PI3K-Akt, calcium, and cAMP signaling. Six hub targets (MAPK1, PIK3CA, MAPK3, EGFR, MTOR, and AKT1) were consistently annotated within the top 30 KEGG pathways and displayed strong binding affinities for MET 15 and MET 119. Molecular dynamics (MD) simulations confirmed favorable binding free energies (BFEs) and stable conformational dynamics for the top-ranked metabolite MET 15. C. albicans secondary metabolites preferentially target oncogenic signaling networks central to HIV latency maintenance, notably PI3K/AKT/MTOR and MAPK/ERK, which regulate cell survival, metabolic homeostasis, and viral transcriptional repression. MET 15 is a top-ranked candidate metabolite for HIV latency-reversing therapeutics and warrants experimental validation in established latency models. Full article

We present a comprehensive mathematical analysis of a within-host dual-target HIV dynamics model, which explicitly incorporates the virus’s interactions with its two primary cellular targets: CD4⁺ T cells and macrophages. The model is formulated as a system of five nonlinear delay differential equations, integrating three distinct discrete time delays to account for critical intracellular processes such as the development of productively infected cells and the maturation of new virions. We first establish the model’s biological well-posedness by proving the non-negativity and boundedness of solutions, ensuring all trajectories remain within a feasible region. The basic reproduction number, ${\mathcal{R}}_0^d$, is derived using the next-generation matrix method and serves as a sharp threshold for disease dynamics. Analytical results demonstrate that the infection-free equilibrium is globally asymptotically stable (GAS) when ${\mathcal{R}}_0^d\le 1$, guaranteeing viral eradication from any initial state. Conversely, when ${\mathcal{R}}_0^d>1$, a unique endemic equilibrium emerges and is proven to be GAS, representing a state of chronic infection. These global stability properties are rigorously established for both the non-delayed and delayed systems using carefully constructed Lyapunov functions and functionals, coupled with LaSalle’s invariance principle. A sensitivity analysis identifies viral production rates ($p_1,p_2$) and infection rates (${\beta }_1,{\beta }_2$) as the most influential parameters on ${\mathcal{R}}_0^d$, while the viral clearance rate (m) and maturation delay (${\tau }_3$) have a suppressive effect. The model is extended to evaluate antiretroviral therapy (ART), revealing a critical treatment efficacy threshold ${ϵ}^{cr}$ required to suppress the virus. Numerical simulations validate all theoretical findings and further investigate the dynamics under varying treatment efficacies and maturation delays, highlighting how these factors can shift the system from persistence to clearance. This study provides a rigorous mathematical framework for understanding HIV dynamics, with actionable insights for designing targeted treatment protocols aimed at achieving viral suppression. Full article

Persistence is a strategy used by many viruses to evade eradication by the immune system, ensuring their permanence and transmission within the host and optimizing viral fitness. During persistence, viruses can trigger various phenomena, including target organ damage, mainly due to an inflammatory state induced by infection, as well as cell proliferation and/or immortalization. In addition to immune evasion and chronic inflammation, factors contributing to viral persistence include low-level viral replication, the accumulation of viral mutants, and, most importantly, maintenance of the viral genome and reliance on viral oncoprotein production. This review focuses on the process of genome integration, which may occur at different stages of infection (e.g., HBV), during the chronic phase of infection (e.g., HPV, EBV), or as an essential part of the viral life cycle, as seen in retroviruses (HIV, HTLV-1). It also explores the close relationship between integration, persistence, and oncogenesis. Several models have been proposed to describe the genome integration process, including non-homologous recombination, looping, and microhomology models. Integration can occur either randomly or at specific genomic sites, often leading to genome destabilization. In some cases, integration results in the loss of genomic regions or impairs the regulation of oncogene and/or oncosuppressor expression, contributing to tumor development. Full article

This study examines the interactions between healthy target cells, infected target cells, virus particles, and immune cells within an HIV model. The model exhibits two equilibrium points: an infection-free equilibrium and an infection equilibrium. Stability analysis shows that the infection-free equilibrium is locally asymptotically stable when ${\mathcal{R}}_0<1$. Further, it is unstable when ${\mathcal{R}}_0>1$. The infection equilibrium is locally asymptotically stable when ${\mathcal{R}}_0>1$. The structural and practical identifiabilities of the within-host model for HIV infection dynamics were investigated using differential algebra techniques and Monte Carlo simulations. The HIV model was structurally identifiable by observing the total uninfected and infected target cells, immune cells, and viral load. Monte Carlo simulations assessed the practical identifiability of parameters. The production rate of target cells $\left(\lambda \right)$, the death rate of healthy target cells $\left(d\right)$, the death rate of infected target cells $\left(\delta \right)$, and the viral production rate by infected cells $\left(\pi \right)$ were practically identifiable. The rate of infection of target cells by the virus $\left(\beta \right)$, the death rate of infected cells by immune cells $\left(\mathsf{\Psi }\right)$, and antigen-driven proliferation rate of immune cells $\left(b\right)$ were not practically identifiable. Practical identifiability was constrained by the noise and sparsity of the data. Analysis shows that increasing the frequency of data collection can significantly improve the identifiability of all parameters. This highlights the importance of optimal data sampling in HIV clinical studies, as it determines the best time points, frequency, and the number of sample points required to accurately capture the dynamics of the HIV infection within a host. Full article

We used a previously introduced HIV within-host model with sensitive and resistant strains and validated it with two data sets. The first data set is from a clinical study that investigated multi-drug treatments and measured the total CD4⁺ cell count and viral load. All nine patients in this data set experienced virologic failure. The second data set includes a unique patient who was treated with a unique drug and for whom both the sensitive and resistant strains were measured as well as the CD4⁺ cells. We studied the structural identifiability of the model with respect to each data set. With respect to the first data set, the model was structurally identifiable when the viral production rate of the sensitive strain was fixed and distinct from the viral production rate of the resistant strain. With respect to the second data set, the model was always structurally identifiable. We fit the model to the first data set using nonlinear mixed effect modeling in Monolix and estimated the population-level parameters. We inferred that the average time to emergence of a resistant strain is 844 days after treatment starts. We fit the model to the second data set and found out that the all the parameters except the mutation rate were practically identifiable. Full article

HIV-1 encodes four accesory proteins in addition to its structural and regulatory genes. Uniquely amongst them, Vpr is abundantly present within virions, meaning it is poised to exert various biological effects on the host cell upon delivery. In this way, Vpr contributes towards the establishment of a successful infection, as evidenced by the extent to which HIV-1 depends on this factor to achieve full pathogenicity in vivo. Although HIV infects various cell types in the host organism, CD4⁺ T cells are preferentially targeted since they are highly permissive towards productive infection, concomitantly bringing about the hallmark immune dysfunction that accompanies HIV-1 spread. The last several decades have seen unprecedented progress in unraveling the activities Vpr possesses in the host cell at the molecular scale, increasingly underscoring the importance of this viral component. Nevertheless, it remains controversial whether some of these advances bear in vivo relevance, since commonly employed cellular models significantly differ from primary T lymphocytes. One prominent example is the “established” ability of Vpr to induce G2 cell cycle arrest, with enigmatic physiological relevance in infected primary T lymphocytes. The objective of this review is to present these discoveries in their biological context to illustrate the mechanisms whereby Vpr supports HIV-1 infection in CD4⁺ T cells, whilst identifying findings that require validation in physiologically relevant models. Full article

Taking into account the effects of the immune response and delay, and complexity on HIV-1 transmission, a multiscale AIDS/HIV-1 model is formulated in this paper. The multiscale model is described by a within-host fast time model with intracellular delay and immune delay, and a between-host slow time model with latency delay. The dynamics of the fast time model is analyzed, and includes the stability of equilibria and properties of Hopf bifurcation. Further, for the coupled slow time model without an immune response, the basic reproduction number ${\mathcal{R}}_0^h$ is defined, which determines whether the model may have zero, one, or two positive equilibria under different conditions. This implies that the slow time model demonstrates more complex dynamic behaviors, including saddle-node bifurcation, backward bifurcation, and Hopf bifurcation. For the other case, that is, the coupled slow time model with an immune response, the threshold dynamics, based on the basic reproduction number ${\tilde{\mathcal{R}}}_0^h$, is rigorously investigated. More specifically, if ${\tilde{\mathcal{R}}}_0^h<1$, the disease-free equilibrium is globally asymptotically stable; if ${\tilde{\mathcal{R}}}_0^h>1$, the model exhibits a unique endemic equilibrium that is globally asymptotically stable. With regard to the coupled slow time model with an immune response and stable periodic solution, the basic reproduction number ${\mathcal{R}}_0$ is derived, which serves as a threshold value determining whether the disease will die out or lead to periodic oscillations in its prevalence. The research results suggest that the disease is more easily controlled when hosts have an extensive immune response and the time required for new immune particles to emerge in response to antigenic stimulation is within a certain range. Finally, numerical simulations are presented to validate the main results and provide some recommendations for controlling the spread of HIV-1. Full article

Understanding infectious disease pathogenesis and evaluating novel candidate treatment interventions for human use frequently requires prior or parallel analysis in animal model systems. While rodent species are frequently applied in such studies, there are situations where non-human primate (NHP) species are advantageous or required. These include studies of animals that are anatomically more akin to humans, where there is a need to interrogate the complexity of more advanced biological systems or simply reflect susceptibility to a specific infectious agent. The contribution of different arms of the immune response may be addressed in a variety of NHP species or subspecies in specific physiological compartments. Such studies provide insights into immune repertoires not always possible from human studies. However, genetic variation in outbred NHP models may confound, or significantly impact the outcome of a particular study. Thus, host factors need to be considered when undertaking such studies. Considerable knowledge of the impact of host immunogenetics on infection dynamics was elucidated from HIV/SIV research. NHP models are now important for studies of emerging infections. They have contributed to delineating the pathogenesis of SARS-CoV-2/COVID-19, which identified differences in outcomes attributable to the selected NHP host. Moreover, their use was crucial in evaluating the immunogenicity and efficacy of vaccines against COVID-19 and establishing putative correlates of vaccine protection. More broadly, neglected or highly pathogenic emerging or re-emergent viruses may be studied in selected NHPs. These studies characterise protective immune responses following infection or the administration of candidate immunogens which may be central to the accelerated licensing of new vaccines. Here, we review selected aspects of host immunogenetics, specifically MHC background and TRIM5 polymorphism as exemplars of adaptive and innate immunity, in commonly used Old and New World host species. Understanding this variation within and between NHP species will ensure that this valuable laboratory source is used most effectively to combat established and emerging virus infections and improve human health worldwide. Full article

This paper formulates and analyzes two mathematical models that describe the within-host dynamics of human immunodeficiency virus type 1 (HIV-1) with impairment of both cytotoxic T lymphocytes (CTLs) and B cells. Both viral transmission (VT) and cellular infection (CT) mechanisms are considered. The second model is a generalization of the first model that includes distributed time delays. For the two models, we establish the non-negativity and boundedness of the solutions, find the basic reproductive numbers, determine all possible steady states and establish the global asymptotic stability properties of all steady states by means of the Lyapunov method. We confirm the theoretical results by conducting numerical simulations. We conduct a sensitivity analysis to show the effect of the values of the parameters on the basic reproductive number. We discuss the results, showing that impaired B cells and CTLs, time delay and latent CT have significant effects on the HIV-1 dynamics. Full article

This research aims to formulate and analyze two mathematical models describing the within-host dynamics of human immunodeficiency virus type-1 (HIV-1) in case of impaired humoral immunity. These models consist of five compartments, including healthy CD4${}^{+}$ T cells, (HIV-1)-latently infected cells, (HIV-1)-actively infected cells, HIV-1 particles, and B-cells. We make the assumption that healthy cells can become infected when exposed to: (i) HIV-1 particles resulting from viral infection (VI), (ii) (HIV-1)-latently infected cells due to latent cellular infection (CI), and (iii) (HIV-1)-actively infected cells due to active CI. In the second model, we introduce distributed time-delays. For each of these systems, we demonstrate the non-negativity and boundedness of the solutions, calculate the basic reproductive number, identify all possible equilibrium states, and establish the global asymptotic stability of these equilibria. We employ the Lyapunov method in combination with LaSalle’s invariance principle to investigate the global stability of these equilibrium points. Theoretical findings are subsequently validated through numerical simulations. Additionally, we explore the impact of B-cell impairment, time-delays, and CI on HIV-1 dynamics. Our results indicate that weakened immunity significantly contributes to disease progression. Furthermore, the presence of time-delays can markedly decrease the basic reproductive number, thereby suppressing HIV-1 replication. Conversely, the existence of latent CI spread increases the basic reproductive number, intensifying the progression of HIV-1. Consequently, neglecting latent CI spread in the HIV-1 dynamics model can lead to an underestimation of the basic reproductive number, potentially resulting in inaccurate or insufficient drug therapies for eradicating HIV-1 from the body. These findings offer valuable insights that can enhance the understanding of HIV-1 dynamics within a host. Full article

This paper presents and analyzes two mathematical models for the human immunodeficiency virus type-1 (HIV-1) infection with Cytotoxic T Lymphocyte cell (CTL) immune impairment. These models describe the interactions between healthy CD$4^{+}$T cells, latently and actively infected cells, HIV-1 particles, and CTLs. The healthy CD$4^{+}$T cells might be infected when they make contact with: (i) HIV-1 particles due to virus-to-cell (VTC) contact; (ii) latently infected cells due to latent cell-to-cell (CTC) contact; and (iii) actively infected cells due to active CTC contact. Distributed time delays are considered in the second model. We show the nonnegativity and boundedness of the solutions of the systems. Further, we derive basic reproduction numbers ${\Re }_0$ and ${\tilde{\Re }}_0$, that determine the existence and stability of equilibria of our proposed systems. We establish the global asymptotic stability of all equilibria by using the Lyapunov method together with LaSalle’s invariance principle. We confirm the theoretical results by numerical simulations. The effect of immune impairment, time delay and CTC transmission on the HIV-1 dynamics are discussed. It is found that weak immunity contributes significantly to the development of the disease. Further, we have established that the presence of time delay can significantly decrease the basic reproduction number and then suppress the HIV-1 replication. On the other hand, the presence of latent CTC spread increases the basic reproduction number and then enhances the viral progression. Thus, neglecting the latent CTC spread in the HIV-1 infection model will lead to an underestimation of the basic reproduction number. Consequently, the designed drug therapies will not be accurate or sufficient to eradicate the viruses from the body. These findings may help to improve the understanding of the dynamics of HIV-1 within a host. Full article

In several publications, the dynamical system of HIV and HTLV mono-infections taking into account diffusion, as well as latently infected cells in cellular transmission has been mathematically analyzed. However, no work has been conducted on HTLV/HIV co-infection dynamics taking both factors into consideration. In this paper, a partial differential equations (PDEs) model of HTLV/HIV dual infection was developed and analyzed, considering the cells’ and viruses’ spatial mobility. CD$4^{+}$T cells are the primary target of both HTLV and HIV. For HIV, there are three routes of transmission: free-to-cell (FTC), latent infected-to-cell (ITC), and active ITC. In contrast, HTLV transmits horizontally through ITC contact and vertically through the mitosis of active HTLV-infected cells. In the beginning, the well-posedness of the model was investigated by proving the existence of global solutions and the boundedness. Eight threshold parameters that determine the existence and stability of the eight equilibria of the model were obtained. Lyapunov functions together with the Lyapunov–LaSalle asymptotic stability theorem were used to investigate the global stability of all equilibria. Finally, the theoretical results were verified utilizing numerical simulations. Full article

Equine Infectious Anemia Virus (EIAV) is an important infection in equids, and its similarity to HIV creates hope for a potential vaccine. We analyze a within-host model of EIAV infection with antibody and cytotoxic T lymphocyte (CTL) responses. In this model, the stability of the biologically relevant endemic equilibrium, characterized by the coexistence of long-term antibody and CTL levels, relies upon a balance between CTL and antibody growth rates, which is needed to ensure persistent CTL levels. We determine the model parameter ranges at which CTL and antibody proliferation rates are simultaneously most influential in leading the system towards coexistence and can be used to derive a mathematical relationship between CTL and antibody production rates to explore the bifurcation curve that leads to coexistence. We employ Latin hypercube sampling and least squares to find the parameter ranges that equally divide the endemic and boundary equilibria. We then examine this relationship numerically via a local sensitivity analysis of the parameters. Our analysis is consistent with previous results showing that an intervention (such as a vaccine) intended to control a persistent viral infection with both immune responses should moderate the antibody response to allow for stimulation of the CTL response. Finally, we show that the CTL production rate can entirely determine the long-term outcome, regardless of the effect of other parameters, and we provide the conditions for this result in terms of the identified ranges for all model parameters. Full article

Infection with human immunodeficiency virus type 1 (HIV-1) or human T-lymphotropic virus type I (HTLV-I) or both can lead to mortality. CD4⁺T cells are the target for both HTLV-I and HIV-1. In addition, HIV-1 can infect macrophages. CD4⁺T cells and macrophages play important roles in the immune system response. This article develops and analyzes a discrete-time HTLV-I and HIV-1 co-infection model. The model depicts the within-host interaction of six compartments: uninfected CD4⁺T cells, HIV-1-infected CD4⁺T cells, uninfected macrophages, HIV-1-infected macrophages, free HIV-1 particles and HTLV-I-infected CD4⁺T cells. The discrete-time model is obtained by discretizing the continuous-time model via the nonstandard finite difference (NSFD) approach. We show that NSFD preserves the positivity and boundedness of the model’s solutions. We deduce four threshold parameters that control the existence and stability of the four equilibria of the model. The Lyapunov method is used to examine the global stability of all equilibria. The analytical findings are supported via numerical simulation. The model can be useful when one seeks to design optimal treatment schedules using optimal control theory. Full article

Human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) are two retroviruses which infect the same target, CD$4^{+}$ T cells. This type of cell is considered the main component of the immune system. Since both viruses have the same means of transmission between individuals, HIV-1-infected patients are more exposed to the chance of co-infection with HTLV-I, and vice versa, compared to the general population. The mathematical modeling and analysis of within-host HIV-1/HTLV-I co-infection dynamics can be considered a robust tool to support biological and medical research. In this study, we have formulated and analyzed an HIV-1/HTLV-I co-infection model with humoral immunity, taking into account both latent HIV-1-infected cells and HTLV-I-infected cells. The model considers two modes of HIV-1 dissemination, virus-to-cell (V-T-C) and cell-to-cell (C-T-C). We prove the nonnegativity and boundedness of the solutions of the model. We find all steady states of the model and establish their existence conditions. We utilize Lyapunov functions and LaSalle’s invariance principle to investigate the global stability of all the steady states of the model. Numerical simulations were performed to illustrate the corresponding theoretical results. The effects of humoral immunity and C-T-C transmission on the HIV-1/HTLV-I co-infection dynamics are discussed. We have shown that humoral immunity does not play the role of clearing an HIV-1 infection but it can control HIV-1 infection. Furthermore, we note that the omission of C-T-C transmission from the HIV-1/HTLV-I co-infection model leads to an under-evaluation of the basic HIV-1 mono-infection reproductive ratio. Full article