(560d) Modeling Viral Replication and Cytokine Response to Reveal Mechanisms of Inflammation | AIChE

(560d) Modeling Viral Replication and Cytokine Response to Reveal Mechanisms of Inflammation


Shoemaker, J. E., University of Pittsburgh
Influenza remains a global health concern, causing an annual 3 - 5 million infections and 290,000 – 650,000 deaths1. The disease presents a significant pediatric burden, causing 374,000 annual hospitalizations of children under 1 years old, globally2. Seasonal monovalent vaccines have achieved only 69% efficacy3, leaving room for improvement through fundamental understanding of the immune response to viral detection. The adaptive immune response, vaccines’ primary route of protection, is predicated by the actions of the innate immune response to create an immunocompetent environment during vaccination or infection4. Improper innate immune activation has been implicated in a wide range of pathologies from inflammatory bowel5 and liver6 diseases to Alzheimer’s Disease7 and beyond.

Immune responses can help or hinder an organism’s ability to overcome an infection; excessively inflammatory responses8 can cause greater tissue damage, higher mortality, and slow recovery9, while an adequate and well-regulated response to a threat is a prerequisite for survival and the management of the adaptive immune system. Thus, tight regulation of the immune response is critical. The first step to occur during an immune response is the detection of the pathogens, leading to the early, localized, innate immune response10. This response to viral infection leads to the production of Type I Interferons (IFNs). Interferons serve to establish an antiviral state by activating and inducing Mx proteins, RNA-activated protein kinase, and the 2-5A system11; they also regulate other immune responses by acting on NK cells, T cells, B cells, DCs, and phagocytic cells12. Without the initial sensing protein activity, no immune responses would be mounted. Understanding the dynamics of these sensors is vital to quantifying the innate immune response. The presence of influenza virus is primarily sensed by cytoplasmic retinoic acid-inducible gene 1 (RIG-I) and endosomal Toll-like receptors (TLR)13,14. RIG-I senses viral RNA in the cytoplasm15, but is antagonized by influenza A nonstructural protein I (NS1) to varying, strain-specific magnitudes16,17; TLR7 is free of this antagonism18,19, but is only activated after the influenza envelop has been degraded by endosomal proteases20. The activation of either sensor leads to the phosphorylation of IRF7 and the production of IFN to act as a signaling cytokine. IFN induces secondary messenger molecules, ultimately leading to the induction of immune activity, inflammation, and antiviral genes21

Ordinary Differential Equations (ODEs) have become a common approach in systems biology after their demonstrable success in analyzing the robustness of biological signaling22–24, the highly dynamic behaviors of NF-kB25, and Xenopus oocytes’ ultrasensitive cell fate binary response26. ODE’s allow for interpolation of the dynamics between a finite number of time points at which RNA profiles have been measured, based on hypothesis of the mechanisms regulating the system’s components.

Here, a novel ODE model was constructed to quantify the innate immune response of human bronchial epithelial cells (HBECs) to influenza A infection. The model incorporates both the classical viral dynamic model27,28 and the proportionality of sensor protein activity to vRNA levels in the cytoplasm, the first such integration of intracellular immune dynamics and viral replication. The feedback of interferon production on viral replication through the induction of the interferon stimulated gene (ISG) family28 is included. Sensitivity analysis of the model revealed IRF7 phosphorylation and induction as the primary drivers of IFN production in the model. An NS1 knockout strain was simulated as a validation study, revealing lower cell lethality, lower peak viral titers, and a stronger cytokine response, with only the removal of RIG-I antagonism. This work establishes the first cell-level model of interferon signaling induced by influenza infection that can be used to compare host responses between infections with different infecting agents and antagonism motifs through modification of the sensor proteins’ kinetics

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