Abstract
The ability to accurately and reliably quantify viral infection is essential to basic and translational virology research. Here, we describe a simple and robust automated method for using fluorescence microscopy to estimate the proportion of virally infected cells in a monolayer. We provide details of the automated analysis workflow along with a freely available open-source ImageJ plugin, Infection Counter, for performing image quantification. Using hepatitis C virus (HCV) as an example, we have experimentally verified our method, demonstrating that it is equivalent, if not better, than the established focus-forming assay. Finally, we used Infection Counter to assess the anti-HCV activity of SMBz-CsA, a non-immunosuppressive cyclosporine analogue.
Highlights
Robust and reliable infectivity assays are an essential part of a virologist’s tool kit
Experimental observations indicate that hepatitis C virus (HCV) protein synthesis and genome replication is detectable within 10–24 h and de novo virion production is apparent by 18–48 h [6,7,8]
1–2 rounds of replication to occur within 48 h of inoculation. At this time point HCVcc for 1–2 rounds of replication to occur within 48 h of inoculation
Summary
Robust and reliable infectivity assays are an essential part of a virologist’s tool kit. A related technique, the focus-forming assay (FFA), can be used to titer non-cytopathic viruses. This relies on the detection of infected cells by immunostaining for viral antigen or via a genetically encoded fluorescent reporter. The FFA typically requires manual identification and counting of foci by fluorescence microscopy; this is extremely time consuming, vulnerable to human error and has a limited linear dynamic range. Various groups have developed in-house automated quantification methods [1,2,3]; these generally require bespoke equipment and/or proprietary software, and often possess the same limited dynamic range of the FFA
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