...this was fine (once I'd gotten over the unexpected nausea), it got me data and I enjoyed the moments when I peered down at my experiment and realised maybe, just maybe, I'd discovered something. However, manual counting of cells is slow, tedious and prone to error; so when I set up the Grove Lab I decided to find another way.
To be clear, the cells I'm talking about here are those infected with hepatitis C virus and we identify them by immunofluoresent labelling. By quantifying the number of infected cells we can measure viral replication; this is a cornerstone technique in many of our experiments.
During my postdoc at the LMCB I got a comprehensive training in microscopy and image analysis, and when I returned to the HCV field I put these new skills to use by designing Infection Counter, an ImageJ plugin for automated quantification of infected cells. This approach uses images of cells that have been labelled for viral antigen and cellular nuclei using DAPI; the plugin first approximates the location of each cell using the nuclei then scores them as positive or negative for viral antigen. It's a simple analysis, but very robust. By exploiting the plate-reading capabilities of our microscope we can easily image and quantify hundreds of samples every week with relatively little effort. A significant improvement on me, feeling sick, clicking away on a tally counter for hours upon end.
We recently published a description of Infection Counter in Viruses, where we give a detailed account of how it works and provide data to validate the technique. The plugin is free to download so we encourage y'all to give it go on your virus of choice.
This work was done in collaboration with the Henriques Lab at the LMCB and the Towers Lab in Infection and Immunity. It was supported by the Wellcome Trust, Royal Society and Medical Research Council.