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Tonic ISG expression promotes efficient induction of IFNL in response to influenza infection

ABSTRACT: The innate immune response, especially the interferon (IFN) response, plays a critical role in limiting initial dissemination of viruses from the site of infection. While the pathogen-associated molecular patterns (PAMPs) and pattern recognition receptors (PRRs) involved in sensing and inducing the innate immune response during influenza A virus (IAV) infections are well-characterized, the factors that regulate IFNL production in infected cells remain poorly understood. Previous studies have highlighted that most infected cells fail to express either type I or III IFNs in response to stimulus, suggesting a regulatory mechanism that controls the activation of IFNs during infection. To investigate the factors influencing IFNL induction during IAV infection, we performed single-cell RNA sequencing (scRNA-seq) of A549 cells infected with A/Perth/16/2009 and sampled at multiple time points post-infection. Using a novel pseudotime analysis approach tailored for temporal scRNA-seq data, we aim to identify host genes whose tonic expression modulates IFNL production in response to IAV infection.

ORGANISM(S): Homo sapiens

PROVIDER: GSE287024 | GEO | 2025/03/14

REPOSITORIES: GEO

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Project description:Miao2010 - Innate and adaptive immune responses to primary Influenza A Virus infection This model is described in the article: Quantifying the early immune response and adaptive immune response kinetics in mice infected with influenza A virus. Miao H, Hollenbaugh JA, Zand MS, Holden-Wiltse J, Mosmann TR, Perelson AS, Wu H, Topham DJ. J. Virol. 2010 Jul; 84(13): 6687-6698 Abstract: Seasonal and pandemic influenza A virus (IAV) continues to be a public health threat. However, we lack a detailed and quantitative understanding of the immune response kinetics to IAV infection and which biological parameters most strongly influence infection outcomes. To address these issues, we use modeling approaches combined with experimental data to quantitatively investigate the innate and adaptive immune responses to primary IAV infection. Mathematical models were developed to describe the dynamic interactions between target (epithelial) cells, influenza virus, cytotoxic T lymphocytes (CTLs), and virus-specific IgG and IgM. IAV and immune kinetic parameters were estimated by fitting models to a large data set obtained from primary H3N2 IAV infection of 340 mice. Prior to a detectable virus-specific immune response (before day 5), the estimated half-life of infected epithelial cells is approximately 1.2 days, and the half-life of free infectious IAV is approximately 4 h. During the adaptive immune response (after day 5), the average half-life of infected epithelial cells is approximately 0.5 days, and the average half-life of free infectious virus is approximately 1.8 min. During the adaptive phase, model fitting confirms that CD8(+) CTLs are crucial for limiting infected cells, while virus-specific IgM regulates free IAV levels. This may imply that CD4 T cells and class-switched IgG antibodies are more relevant for generating IAV-specific memory and preventing future infection via a more rapid secondary immune response. Also, simulation studies were performed to understand the relative contributions of biological parameters to IAV clearance. This study provides a basis to better understand and predict influenza virus immunity. This model is hosted on BioModels Database and identified by: BIOMD0000000546. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Baris Hancioglu, David Swigon & Gilles Clermont. A dynamical model of human immune response to influenza A virus infection. Journal of Theoretical Biology 246, 1 (2007). We present a simplified dynamical model of immune response to uncomplicated influenza A virus (IAV) infection, which focuses on the control of the infection by the innate and adaptive immunity. Innate immunity is represented by interferon-induced resistance to infection of respiratory epithelial cells and by removal of infected cells by effector cells (cytotoxic T-cells and natural killer cells). Adaptive immunity is represented by virus-specific antibodies. Similar in spirit to the recent model of Bocharov and Romanyukha [1994. Mathematical model of antiviral immune response. III. Influenza A virus infection. J. Theor. Biol. 167, 323-360], the model is constructed as a system of 10 ordinary differential equations with 27 parameters characterizing the rates of various processes contributing to the course of disease. The parameters are derived from published experimental data or estimated so as to reproduce available data about the time course of IAV infection in a naïve host. We explore the effect of initial viral load on the severity and duration of the disease, construct a phase diagram that sheds insight into the dynamics of the disease, and perform sensitivity analysis on the model parameters to explore which ones influence the most the onset, duration and severity of infection. To account for the variability and speed of adaptation of the adaptive response to a particular virus strain, we introduce a variable that quantifies the antigenic compatibility between the virus and the antibodies currently produced by the organism. We find that for small initial viral load the disease progresses through an asymptomatic course, for intermediate value it takes a typical course with constant duration and severity of infection but variable onset, and for large initial viral load the disease becomes severe. This behavior is robust to a wide range of parameter values. The absence of antibody response leads to recurrence of disease and appearance of a chronic state with nontrivial constant viral load.

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Tonic ISG expression promotes efficient induction of IFNL in response to influenza infection

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