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Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
Published on: January 13, 2016
Exploring the host response in infected lung organoids using NanoString technology: A statistical analysis of gene
Mostafa Rezapour1, Stephen J Walker2, David A Ornelles3
1Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC, United States of America.
This study used a 3D airway organ tissue equivalent (OTE) model to analyze gene expression changes caused by Influenza A virus (IAV), Human metapneumovirus (MPV), and Parainfluenza virus type 3 (PIV3). The research identified distinct viral response patterns and highlighted the crucial role of interferon-stimulated genes (ISGs) in antiviral defense.
Area of Science:
- Virology and Immunology
- Respiratory Tract Infections
- Gene Expression Analysis
Background:
- Human airway physiology is complex and challenging to model in vitro.
- Understanding differential gene expression in response to respiratory viruses is crucial for developing effective treatments.
- Existing models may not fully capture the dynamic interplay between host and virus at the cellular level.
Purpose of the Study:
- To investigate the host gene expression response to Influenza A virus (IAV), Human metapneumovirus (MPV), and Parainfluenza virus type 3 (PIV3) using a 3D airway organ tissue equivalent (OTE) model.
- To analyze gene expression profiles at 24 and 72 hours post-infection.
- To introduce and utilize a novel Magnitude-Altitude Score (MAS) algorithm for robust identification of biologically relevant differentially expressed genes.
Main Methods:
- Development and utilization of a three-dimensional airway organ tissue equivalent (OTE) model at an air-liquid interface (ALI).
- Infection of OTE models with IAV, MPV, and PIV3, with appropriate control conditions.
- Gene expression profiling of 773 specific genes using the NanoString platform at 24 and 72 hours post-infection.
- Application of the novel Magnitude-Altitude Score (MAS) algorithm to integrate fold change and adjusted p-values for gene identification.
Main Results:
- IAV infection induced a strong interferon-stimulated gene (ISG) response at 24 hours, which persisted at 72 hours.
- MPV infection elicited a dual innate and adaptive immune response at 24 hours, shifting towards IL17A and signaling genes by 72 hours.
- PIV3 infection triggered an ISG-dominant response with immune cell recruitment and inflammation modulation at 24 hours, maintaining an interferon-centric profile at 72 hours.
- The MAS algorithm successfully identified biologically significant differentially expressed genes, revealing distinct host responses to each virus.
Conclusions:
- Interferon-stimulated genes (ISGs) play a pivotal and universal role in the host's antiviral defense against IAV, MPV, and PIV3.
- Temporal gene expression patterns demonstrate host adaptation and fine-tuning of the immune response over time.
- Distinct host-specific responses were identified for each virus, with IAV showing sustained impact and PIV3 exhibiting a delayed genomic response.
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