Application of 3D image analysis to facilitate the identification of antiviral inhibitors

Session

Microbial Imaging

Authors

Miss Lauren Orr (1), Miss Joanna Wojtus (1), Dr Chris Boutell (1)

Affiliations

1. MRC - University of Glasgow Centre for Virus Research

Keywords

virology, virus, antiviral, drug discovery, inhibitors, confocal microscopy, viral imaging, 3D

Abstract text

The global spread of SARS-CoV-2 has highlighted the necessity for more effective antiviral screening methods to facilitate the identification of direct acting antiviral inhibitors. Most small molecule inhibitors are initially identified through the use of 2D immortalised cell lines that are amenable to high-throughput drug screening. However, use of such cells fails to recapitulate the complex microenvironment of the lung and tissue-specific architecture. Consequently, many inhibitors fail to show antiviral activity when tested in more biologically relevant animal models; highlighting the importance of developing more appropriate in vitro models prior to animal testing. 3D cell culture models contain multiple cell types, mimic spatial organisation of the lung, and express gene profiles comparable to that observed in vivo. Here we aim to create improved 2D and 3D cell culture systems to identify drugs exhibiting antiviral activity against influenza virus. First, we establish a 2D real time assay to monitor virus replication kinetics using a fluorescently tagged (ZsGreen) influenza virus. We demonstrate this assay can be applied to drug discovery through measuring virus replication in real time in the presence of favipiravir and determine its inhibitory value. Findings from this assay show influenza virus replication kinetics can be monitored in real time over 48 hours of infection without fixation or staining procedures. Favipiravir was shown to inhibit influenza virus replication in MDCK cells with an IC50 value of ~25 μM – confirming we can use this assay to screen potential inhibitors for antiviral activity. Second, we establish the use of an air-liquid interface model to differentiate primary human bronchial epithelial cells into respiratory epithelium. Using confocal microscopy and image analysis software to track influenza virus replication in 3D, we show virus migration through multiple cell layers. We analysed the depth and volume of infection foci, alterations to tissue thickness, and percentage of cilia damage, to determine correlation factors of infection and efficacy of antiviral inhibitors. Our data demonstrate the potential utility of using near real time imaging and 3D models of infection to monitor respiratory virus replication and identify antiviral inhibitors. These findings can be implemented for future inhibitor studies against viral pathogens with pandemic potential.