Browsing by Author "Verma, Meghna"
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- Challenges in Personalized Nutrition and HealthVerma, Meghna; Hontecillas, Raquel; Tubau-Juni, Nuria; Abedi, Vida; Bassaganya-Riera, Josep (Frontiers, 2018-11-29)
- High-resolution computational modeling of immune responses in the gutVerma, Meghna; Bassaganya-Riera, Josep; Leber, Andrew; Tubau-Juni, Nuria; Hoops, Stefan; Abedi, Vida; Chen, Xi; Hontecillas, Raquel (Oxford University Press, 2019-06-01)Background: Helicobacter pylori causes gastric cancer in 1-2% of cases but is also beneficial for protection against allergies and gastroesophageal diseases. An estimated 85% of H. pylori-colonized individuals experience no detrimental effects. To study the mechanisms promoting host tolerance to the bacterium in the gastrointestinal mucosa and systemic regulatory effects, we investigated the dynamics of immunoregulatory mechanisms triggered by H. pylori using a high-performance computing-driven ENteric Immunity SImulator multiscale model. Immune responses were simulated by integrating an agent-based model, ordinary, and partial differential equations. Results: The outputs were analyzed using 2 sequential stages: The first used a partial rank correlation coefficient regression-based and the second a metamodel-based global sensitivity analysis. The influential parameters screened from the first stage were selected to be varied for the second stage. The outputs from both stages were combined as a training dataset to build a spatiotemporal metamodel. The Sobol indices measured time-varying impact of input parameters during initiation, peak, and chronic phases of infection. The study identified epithelial cell proliferation and epithelial cell death as key parameters that control infection outcomes. In silico validation showed that colonization with H. pylori decreased with a decrease in epithelial cell proliferation, which was linked to regulatory macrophages and tolerogenic dendritic cells. Conclusions: The hybrid model of H. pylori infection identified epithelial cell proliferation as a key factor for successful colonization of the gastric niche and highlighted the role of tolerogenic dendritic cells and regulatory macrophages in modulating the host responses and shaping infection outcomes.
- Modeling Host Immune Responses in Infectious DiseasesVerma, Meghna (Virginia Tech, 2019-12-17)Infectious diseases caused by bacteria, fungi, viruses and parasites have affected humans historically. Infectious diseases remain a major cause of premature death and a public health concern globally with increased mortality and significant economic burden. Unvaccinated individuals, people with suppressed and compromised immune systems are at higher risk of suffering from infectious diseases. In spite of significant advancements in infectious diseases research, the control or treatment process faces challenges. The mucosal immune system plays a crucial role in safeguarding the body from harmful pathogens, while being constantly exposed to the environment. To develop treatment options for infectious diseases, it is vital to understand the immune responses that occur during infection. The two infectious diseases presented here are: i) Helicobacter pylori infection and ii) human immunodeficiency (HIV) and human papillomavirus (HPV) co-infection. H pylori, is a bacterium that colonizes the stomach and causes gastric cancer in 1-2% but is beneficial for protection against allergies and gastroesophageal diseases. An estimated 85% of H pylori colonized individuals show no detrimental effects. HIV is a virus that causes AIDS, one of the deadliest and most persistent epidemics. HIV-infected patients are at an increased risk of co-infection with HPV, and report an increased incidence of oral cancer. The goal of this thesis is to elucidate the host immune responses in infectious diseases via the use of computational and mathematical models. First, the thesis reviews the need for computational and mathematical models to study the immune responses in the course of infectious diseases. Second, it presents a novel sensitivity analysis method that identifies important parameters in a hybrid (agent-based/equation-based) model of H. pylori infection. Third, it introduces a novel model representing the HIV/HPV coinfection and compares the simulation results with a clinical study. Fourth, it discusses the need of advanced modeling technologies to achieve a personalized systems wide approach and the challenges that can be encountered in the process. Taken together, the work in this dissertation presents modeling approaches that could lead to the identification of host immune factors in infectious diseases in a predictive and more resource-efficient manner.
- Modeling the Mechanisms by Which HIV Associated Immunosuppression Influences HPV Persistence at the Oral MucosaVerma, Meghna; Erwin, Samantha; Abedi, Vida; Hontecillas, Raquel; Hoops, Stefan; Leber, Andrew; Bassaganya-Riera, Josep; Ciupe, Stanca M. (PLOS, 2017-01-06)Human immunodeficiency virus (HIV)-infected patients are at an increased risk of co-infection with human papilloma virus (HPV), and subsequent malignancies such as oral cancer. To determine the role of HIV-associated immune suppression on HPV persistence and pathogenesis, and to investigate the mechanisms underlying the modulation of HPV infection and oral cancer by HIV, we developed a mathematical model of HIV/HPV co-infection. Our model captures known immunological and molecular features such as impaired HPV-specific effector T helper 1 (Th1) cell responses, and enhanced HPV infection due to HIV. We used the model to determine HPV prognosis in the presence of HIV infection, and identified conditions under which HIV infection alters HPV persistence in the oral mucosa system. The model predicts that conditions leading to HPV persistence during HIV/HPV co-infection are the permissive immune environment created by HIV and molecular interactions between the two viruses. The model also determines when HPV infection continues to persist in the short run in a co-infected patient undergoing antiretroviral therapy. Lastly, the model predicts that, under efficacious antiretroviral treatment, HPV infections will decrease in the long run due to the restoration of CD4+ T cell numbers and protective immune responses.
- Modeling-enabled Systems Nutritional ImmunologyVerma, Meghna; Hontecillas, Raquel; Abedi, Vida; Leber, Andrew; Tubau-Juni, Nuria; Philipson, Casandra; Carbo, Adria; Bassaganya-Riera, Josep (Frontiers, 2016-02-16)This review highlights the fundamental role of nutrition in the maintenance of health, the immune response, and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition, and the immune system interact to delineate health and disease. The review sets an unconventional path to apply complex science methodologies to nutritional immunology research, discovery, and development through "use cases" centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, which include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism.
- Multi-Resolution Sensitivity Analysis of Model of Immune Response to Helicobacter pylori Infection via Spatio-Temporal MetamodelingChen, Xi; Wang, Wenjing; Xie, Guangrui; Hontecillas, Raquel; Verma, Meghna; Leber, Andrew; Bassaganya-Riera, Josep; Abedi, Vida (Frontiers, 2019-02-05)Computational immunology studies the interactions between the components of the immune system that includes the interplay between regulatory and inflammatory elements. It provides a solid framework that aids the conversion of pre-clinical and clinical data into mathematical equations to enable modeling and in silico experimentation. The modeling-driven insights shed lights on some of the most pressing immunological questions and aid the design of fruitful validation experiments. A typical system of equations, mapping the interaction among various immunological entities and a pathogen, consists of a high-dimensional input parameter space that could drive the stochastic system outputs in unpredictable directions. In this paper, we perform spatio-temporal metamodel-based sensitivity analysis of immune response to Helicobacter pylori infection using the computational model developed by the ENteric Immune SImulator (ENISI). We propose a two-stage metamodel-based procedure to obtain the estimates of the Sobol’ total and first-order indices for each input parameter, for quantifying their time-varying impacts on each output of interest. In particular, we fully reuse and exploit information from an existing simulated dataset, develop a novel sampling design for constructing the two-stage metamodels, and perform metamodel-based sensitivity analysis. The proposed procedure is scalable, easily interpretable, and adaptable to any multi-input multi-output complex systems of equations with a high-dimensional input parameter space.
- Reconstruction of endosomal organization and function by a combination of ODE and agent-based modeling strategiesMayorga, Luis S.; Cebrian, Ignacio; Verma, Meghna; Hoops, Stefan; Bassaganya-Riera, Josep (2018-11-23)Background Reproducing cell processes using an in silico system is an essential tool for understanding the underlying mechanisms and emergent properties of this extraordinary complex biological machine. However, computational models are seldom applied in the field of intracellular trafficking. In a cell, numerous molecular interactions occur on the surface or in the interior of membrane-bound compartments that continually change position and undergo dynamic processes of fusion and fission. At present, the available simulation tools are not suitable to develop models that incorporate the dynamic evolution of the cell organelles. Results We developed a modeling platform combining Repast (Agent-Based Modeling, ABM) and COPASI (Differential Equations, ODE) that can be used to reproduce complex networks of molecular interactions. These interactions occur in dynamic cell organelles that change position and composition over the course of time. These two modeling strategies are fundamentally different and comprise of complementary capabilities. The ODEs can easily model the networks of molecular interactions, signaling cascades, and complex metabolic reactions. On the other hand, ABM software is especially suited to simulate the movement, interaction, fusion, and fission of dynamic organelles. We used the combined ABM-ODE platform to simulate the transport of soluble and membrane-associated cargoes that move along an endocytic route composed of early, sorting, recycling and late endosomes. We showed that complex processes that strongly depend on transport can be modeled. As an example, the hydrolysis of a GM2-like glycolipid was programmed by adding a trans-Golgi network compartment, lysosomal enzyme trafficking, endosomal acidification, and cholesterol processing to the simulation model. Conclusions The model captures the highly dynamic nature of cell compartments that fuse and divide, creating different conditions for each organelle. We expect that this modeling strategy will be useful to understand the logic underlying the organization and function of the endomembrane system. Reviewers This article was reviewed by Drs. Rafael Fernández-Chacón, James Faeder, and Thomas Simmen.
- Volatile resistive switching in Cu/TaOx/delta-Cu/Pt devicesLiu, T.; Verma, Meghna; Kang, Y. H.; Orlowski, Marius K. (AIP Publishing, 2012-08-01)A volatile switching of conductive filament (CF) in a Cu/TaOx/delta-Cu/Pt device has been observed. The device differs from a conventional Cu/TaOx/Pt device by the insertion of a thin Cu-layer (delta-Cu) between the electrolyte and the inert electrode. The Cu CF is formed the same way as in the conventional nonvolatile devices. However, when applied voltage becomes zero, CF ruptures spontaneously. The dynamic balance between Cu+ field-supported hopping transport and the Cu self-diffusion explains the effect of CF volatility. The device can operate reliably in volatile and nonvolatile modes. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4746276]