Browsing by Author "Leber, Andrew"

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    Abscisic Acid: A Novel Nutraceutical for Glycemic Control
    Zocchi, Elena; Hontecillas, Raquel; Leber, Andrew; Einerhand, Alexandra; Carbo, Adria; Bruzzone, Santina; Tubau-Juni, Nuria; Philipson, Noah; Zoccoli-Rodriguez, Victoria; Sturla, Laura; Bassaganya-Riera, Josep (Frontiers, 2017-06-13)
    Abscisic acid is naturally present in fruits and vegetables, and it plays an important role in managing glucose homeostasis in humans. According to the latest U.S. dietary survey, about 92% of the population might have a deficient intake of ABA due to their deficient intake of fruits and vegetables. This review summarizes the in vitro, preclinical, mechanistic, and human translational findings obtained over the past 15 years in the study of the role of ABA in glycemic control. In 2007, dietary ABA was first reported to ameliorate glucose tolerance and obesity-related inflammation in mice. The most recent findings regarding the topic of ABA and its proposed receptor lanthionine synthetase C-like 2 in glycemic control and their interplay with insulin and glucagon-like peptide-1 suggest a major role for ABA in the physiological response to a glucose load in humans. Moreover, emerging evidence suggests that the ABA response might be dysfunctional in diabetic subjects. Follow on intervention studies in healthy individuals show that low-dose dietary ABA administration exerts a beneficial effect on the glycemia and insulinemia profiles after oral glucose load. These recent findings showing benefits in humans, together with extensive efficacy data in mouse models of diabetes and inflammatory disease, suggest the need for reference ABA values and its possible exploitation of the glycemia-lowering effects of ABA for preventative purposes. Larger clinical studies on healthy, prediabetic, and diabetic subjects are needed to determine whether addressing the widespread dietary ABA deficiency improves glucose control in humans.
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    Enemy of My Enemy: A Novel Insect-Specific Flavivirus Offers a Promising Platform for a Zika Virus Vaccine
    Porier, Danielle L.; Wilson, Sarah N.; Auguste, Dawn I.; Leber, Andrew; Coutermarsh-Ott, Sheryl; Allen, Irving C.; Caswell, Clayton C.; Budnick, James A.; Bassaganya-Riera, Josep; Hontecillas, Raquel; Weger-Lucarelli, James; Weaver, Scott C.; Auguste, A. Jonathan (MDPI, 2021-10-07)
    Vaccination remains critical for viral disease outbreak prevention and control, but conventional vaccine development typically involves trade-offs between safety and immunogenicity. We used a recently discovered insect-specific flavivirus as a vector in order to develop an exceptionally safe, flavivirus vaccine candidate with single-dose efficacy. To evaluate the safety and efficacy of this platform, we created a chimeric Zika virus (ZIKV) vaccine candidate, designated Aripo/Zika virus (ARPV/ZIKV). ZIKV has caused immense economic and public health impacts throughout the Americas and remains a significant public health threat. ARPV/ZIKV vaccination showed exceptional safety due to ARPV/ZIKV’s inherent vertebrate host-restriction. ARPV/ZIKV showed no evidence of replication or translation in vitro and showed no hematological, histological or pathogenic effects in vivo. A single-dose immunization with ARPV/ZIKV induced rapid and robust neutralizing antibody and cellular responses, which offered complete protection against ZIKV-induced morbidity, mortality and in utero transmission in immune-competent and -compromised murine models. Splenocytes derived from vaccinated mice demonstrated significant CD4+ and CD8+ responses and significant cytokine production post-antigen exposure. Altogether, our results further support that chimeric insect-specific flaviviruses are a promising strategy to restrict flavivirus emergence via vaccine development.
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    High-resolution computational modeling of immune responses in the gut
    Verma, 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.
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    Modeling the Mechanisms by Which HIV Associated Immunosuppression Influences HPV Persistence at the Oral Mucosa
    Verma, 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.
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    Modeling the Role of Lanthionine Synthetase C-Like 2 (LANCL2) in the Modulation of Immune Responses to Helicobacter pylori Infection
    Leber, Andrew; Bassaganya-Riera, Josep; Tubau-Juni, Nuria; Zoccoli-Rodriguez, Victoria; Viladomiu, Monica; Abedi, Vida; Lu, Pinyi; Hontecillas, Raquel (PLOS, 2016-12-09)
    Immune responses to Helicobacter pylori are orchestrated through complex balances of host-bacterial interactions, including inflammatory and regulatory immune responses across scales that can lead to the development of the gastric disease or the promotion of beneficial systemic effects. While inflammation in response to the bacterium has been reasonably characterized, the regulatory pathways that contribute to preventing inflammatory events during H. pylori infection are incompletely understood. To aid in this effort, we have generated a computational model incorporating recent developments in the understanding of H. pylori-host interactions. Sensitivity analysis of this model reveals that a regulatory macrophage population is critical in maintaining high H. pylori colonization without the generation of an inflammatory response. To address how this myeloid cell subset arises, we developed a second model describing an intracellular signaling network for the differentiation of macrophages. Modeling studies predicted that LANCL2 is a central regulator of inflammatory and effector pathways and its activation promotes regulatory responses characterized by IL-10 production while suppressing effector responses. The predicted impairment of regulatory macrophage differentiation by the loss of LANCL2 was simulated based on multiscale linkages between the tissue-level gastric mucosa and the intracellular models. The simulated deletion of LANCL2 resulted in a greater clearance of H. pylori, but also greater IFNγ responses and damage to the epithelium. The model predictions were validated within a mouse model of H. pylori colonization in wild-type (WT), LANCL2 whole body KO and myeloid-specific LANCL2-/- (LANCL2Myeloid) mice, which displayed similar decreases in H. pylori burden, CX3CR1+ IL-10-producing macrophages, and type 1 regulatory (Tr1) T cells. This study shows the importance of LANCL2 in the induction of regulatory responses in macrophages and T cells during H. pylori infection.
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    Modeling-Enabled Characterization of Novel NLRX1 Ligands
    Lu, Pinyi; Hontecillas, Raquel; Abedi, Vida; Kale, Shiv D.; Leber, Andrew; Heltzel, Chase; Langowski, Mark; Godfrey, Victoria; Philipson, Casandra; Tubau-Juni, Nuria; Carbo, Adria; Girardin, Stephen; Uren, Aykut; Bassaganya-Riera, Josep (PLOS, 2015-12-29)
    Nucleotide-binding domain and leucine-rich repeat containing (NLR) family are intracellular sentinels of cytosolic homeostasis that orchestrate immune and inflammatory responses in infectious and immune-mediated diseases. NLRX1 is a mitochondrial-associated NOD-like receptor involved in the modulation of immune and metabolic responses. This study utilizes molecular docking approaches to investigate the structure of NLRX1 and experimentally assesses binding to naturally occurring compounds from several natural product and lipid databases. Screening of compound libraries predicts targeting of NLRX1 by conjugated trienes, polyketides, prenol lipids, sterol lipids, and coenzyme A-containing fatty acids for activating the NLRX1 pathway. The ligands of NLRX1 were identified by docking punicic acid (PUA), eleostearic acid (ESA), and docosahexaenoic acid (DHA) to the C-terminal fragment of the human NLRX1 (cNLRX1). Their binding and that of positive control RNA to cNLRX1 were experimentally determined by surface plasmon resonance (SPR) spectroscopy. In addition, the ligand binding sites of cNLRX1 were predicted in silico and validated experimentally. Target mutagenesis studies demonstrate that mutation of 4 critical residues ASP677, PHE680, PHE681, and GLU684 to alanine resulted in diminished affinity of PUA, ESA, and DHA to NLRX1. Consistent with the regulatory actions of NLRX1 on the NF-κB pathway, treatment of bone marrow derived macrophages (BMDM)s with PUA and DHA suppressed NF-κB activity in a NLRX1 dependent mechanism. In addition, a series of pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the regulatory function of PUA on colitis is NLRX1 dependent. Thus, we identified novel small molecules that bind to NLRX1 and exert anti-inflammatory actions.
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    Modeling-enabled Systems Nutritional Immunology
    Verma, 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.
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    Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis
    Kale, Shiv D.; Ayubi, Tariq; Chung, Dawoon; Tubau-Juni, Nuria; Leber, Andrew; Dang, Ha X.; Karyala, Saikumar; Hontecillas, Raquel; Lawrence, Christopher B.; Cramer, Robert A.; Bassaganya-Riera, Josep (Springer Nature, 2017-12-06)
    Incidences of invasive pulmonary aspergillosis, an infection caused predominantly by Aspergillus fumigatus, have increased due to the growing number of immunocompromised individuals. While A. fumigatus is reliant upon deficiencies in the host to facilitate invasive disease, the distinct mechanisms that govern the host-pathogen interaction remain enigmatic, particularly in the context of distinct immune modulating therapies. To gain insights into these mechanisms, RNA-Seq technology was utilized to sequence RNA derived from lungs of 2 clinically relevant, but immunologically distinct murine models of IPA on days 2 and 3 post inoculation when infection is established and active disease present. Our findings identify notable differences in host gene expression between the chemotherapeutic and steroid models at the interface of immunity and metabolism. RT-qPCR verified model specific and nonspecific expression of 23 immune-associated genes. Deep sequencing facilitated identification of highly expressed fungal genes. We utilized sequence similarity and gene expression to categorize the A. fumigatus putative in vivo secretome. RT-qPCR suggests model specific gene expression for nine putative fungal secreted proteins. Our analysis identifies contrasting responses by the host and fungus from day 2 to 3 between the two models. These differences may help tailor the identification, development, and deployment of host-and/or fungal-targeted therapeutics.
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    Multi-Resolution Sensitivity Analysis of Model of Immune Response to Helicobacter pylori Infection via Spatio-Temporal Metamodeling
    Chen, 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.
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    Systems Modeling of Interactions between Mucosal Immunity and the Gut Microbiome during Clostridium difficile Infection
    Leber, Andrew; Viladomiu, Monica; Hontecillas, Raquel; Abedi, Vida; Philipson, Casandra; Hoops, Stefan; Howard, Brad; Bassaganya-Riera, Josep (PLOS, 2015-07-31)
    Clostridium difficile infections are associated with the use of broad-spectrum antibiotics and result in an exuberant inflammatory response, leading to nosocomial diarrhea, colitis and even death. To better understand the dynamics of mucosal immunity during C. difficile infection from initiation through expansion to resolution, we built a computational model of the mucosal immune response to the bacterium. The model was calibrated using data from a mouse model of C. difficile infection. The model demonstrates a crucial role of T helper 17 (Th17) effector responses in the colonic lamina propria and luminal commensal bacteria populations in the clearance of C. difficile and colonic pathology, whereas regulatory T (Treg) cells responses are associated with the recovery phase. In addition, the production of anti-microbial peptides by inflamed epithelial cells and activated neutrophils in response to C. difficile infection inhibit the re-growth of beneficial commensal bacterial species. Computational simulations suggest that the removal of neutrophil and epithelial cell derived anti-microbial inhibitions, separately and together, on commensal bacterial regrowth promote recovery and minimize colonic inflammatory pathology. Simulation results predict a decrease in colonic inflammatory markers, such as neutrophilic influx and Th17 cells in the colonic lamina propria, and length of infection with accelerated commensal bacteria re-growth through altered anti-microbial inhibition. Computational modeling provides novel insights on the therapeutic value of repopulating the colonic microbiome and inducing regulatory mucosal immune responses during C. difficile infection. Thus, modeling mucosal immunity-gut microbiota interactions has the potential to guide the development of targeted fecal transplantation therapies in the context of precision medicine interventions.