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      Immune Network Modeling Predicts Specific Nasopharyngeal and Peripheral Immune Dysregulation in Otitis-Prone Children

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          Abstract

          Acute otitis media (AOM) pathogenesis involves nasopharyngeal colonization by potential otopathogens and a viral co-infection. Stringently-defined otitis prone (sOP) children show characteristic patterns of immune dysfunction. We hypothesized that otitis proneness is largely a result of altered signaling between immune components that are otherwise competent, resulting in increased susceptibility to infection by bacterial otopathogens. To test this, we constructed a regulatory immune network model linking immune cells and signaling elements known to be involved in AOM and/or dysregulated in sOP children. The alignment of immune response mechanisms with data from in vivo and in vitro experimental observations produced 82 putative immune network models, each describing variants of immune regulatory networks consistent with available observations. Analysis of these models suggested that new measurements of serum levels of IL-4 and CXCL8 could refine competing models and resulted in the elimination of 38 of the models. Further analysis of the remaining 44 models suggested specific deviations in the predicted regulation of nasopharyngeal and peripheral immunity during response to AOM. Specifically, immune responses active in sOP children during AOM were characterized by early and constitutive activation of pro-inflammatory signaling in the nasopharynx and a Th2- and Treg-dominated profile in the periphery. We conclude that sOP children have altered regulation of key immune mediators during both health and pathogenesis. This altered regulation may be amenable to therapeutic intervention.

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          Most cited references48

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          Cellular effectors mediating Th17-dependent clearance of pneumococcal colonization in mice.

          Microbial colonization of mucosal surfaces may be an initial event in the progression to disease, and it is often a transient process. For the extracellular pathogen Streptococcus pneumoniae studied in a mouse model, nasopharyngeal carriage is eliminated over a period of weeks and requires cellular rather than humoral immunity. Here, we demonstrate that primary infection led to TLR2-dependent recruitment of monocyte/macrophages into the upper airway lumen, where they engulfed pneumococci. Pharmacologic depletion of luminal monocyte/macrophages by intranasal instillation of liposomal clodronate diminished pneumococcal clearance. Efficient clearance of colonization required TLR2 signaling to generate a population of pneumococcal-specific IL-17-expressing CD4+ T cells. Depletion of either IL-17A or CD4+ T cells was sufficient to block the recruitment of monocyte/macrophages that allowed for effective late pneumococcal clearance. In contrast with naive mice, previously colonized mice showed enhanced early clearance that correlated with a more robust influx of luminal neutrophils. As for primary colonization, these cellular responses required Th17 immunity. Our findings demonstrate that monocyte/macrophages and neutrophils recruited to the mucosal surface are key effectors in clearing primary and secondary bacterial colonization, respectively.
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            Missing and spurious interactions and the reconstruction of complex networks.

            Network analysis is currently used in a myriad of contexts, from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies and from finding friends to uncovering criminal activity. Despite the promise of the network approach, the reliability of network data is a source of great concern in all fields where complex networks are studied. Here, we present a general mathematical and computational framework to deal with the problem of data reliability in complex networks. In particular, we are able to reliably identify both missing and spurious interactions in noisy network observations. Remarkably, our approach also enables us to obtain, from those noisy observations, network reconstructions that yield estimates of the true network properties that are more accurate than those provided by the observations themselves. Our approach has the potential to guide experiments, to better characterize network data sets, and to drive new discoveries.
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              Regulation of human helper T cell subset differentiation by cytokines.

              Since the discovery of Th1 and Th2 cells in the late 1980s, the family of effector CD4(+) helper T (Th) cell subsets has expanded. The differentiation of naïve CD4(+) T cells is largely determined when they interact with dendritic cells (DCs) in lymphoid organs, and cytokines play a major role in the regulation of Th differentiation in the early stages. Recent studies show that the developmental mechanism of certain Th subsets is not fully shared between mice and humans. Here we will review recent discoveries on the roles of cytokines in the regulation of Th differentiation in humans, and discuss the differences between mice and humans in the developmental mechanisms of several Th subsets, including Th17 cells and T follicular helper (Tfh) cells. We propose that the differentiation of human Th subsets is largely regulated by the three cytokines, IL-12, IL-23, and TGF-β.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                11 June 2020
                2020
                : 11
                : 1168
                Affiliations
                [1] 1Center for Clinical Systems Biology, Research Institute, Rochester General Hospital , Rochester, NY, United States
                [2] 2Center for Infectious Diseases and Immunology, Research Institute, Rochester General Hospital , Rochester, NY, United States
                [3] 3Department of Biomedical Engineering, Rochester Institute of Technology , Rochester, NY, United States
                Author notes

                Edited by: Mats Bemark, University of Gothenburg, Sweden

                Reviewed by: Paul King, Monash University, Australia; Paola Marchisio, University of Milan, Italy

                *Correspondence: Michael E. Pichichero michael.pichichero@ 123456rochesterregional.org

                This article was submitted to Mucosal Immunity, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2020.01168
                7301607
                4bf52f03-e6a1-4412-adc4-fca789ca70ac
                Copyright © 2020 Morris, Chapman, Pichichero and Broderick.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 November 2019
                : 12 May 2020
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 63, Pages: 15, Words: 9570
                Funding
                Funded by: National Institute on Deafness and Other Communication Disorders 10.13039/100000055
                Funded by: Congressionally Directed Medical Research Programs 10.13039/100000090
                Funded by: Elsevier Foundation 10.13039/100005201
                Categories
                Immunology
                Original Research

                Immunology
                pediatric population,systems biology,otitis,immune signaling,numerical models,regulatory logic,immune homeostasis

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