QuantIF: An ImageJ Macro to Automatically Determine the Percentage of Infected Cells after Immunofluorescence

Lynda Handala (1) , Tony Fiore (1) , Yves Rouillé (2) , Francois Helle (1)

1 AGIR - Agents infectieux, résistance et chimiothérapie - UR UPJV 4294
2 CIIL - Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204

Counting labeled cells, after immunofluorescence or expression of a genetically fluorescent reporter protein, is frequently used to quantify viral infection. However, this can be very tedious without a high content screening apparatus. For this reason, we have developed QuantIF, an ImageJ macro that automatically determines the total number of cells and the number of labeled cells from two images of the same field, using DAPI-and specific-stainings, respectively. QuantIF can automatically analyze hundreds of images, taking approximately one second for each field. It is freely available as supplementary data online at MDPI.com and has been developed using ImageJ, a free image processing program that can run on any computer with a Java virtual machine, which is distributed for Windows, Mac, and Linux. It is routinely used in our labs to quantify viral infections in vitro, but can easily be used for other applications that require quantification of labeled cells.

Mots clés: image quantification; virus; fluorescent reporter protein; infection; Coxsackievirus B4; polyomavirus; Hepatitis C virus; Yellow Fever Virus

Domaines: Organisation et fonctions cellulaires [q-bio.SC]; Virologie

Lynda Handala, Tony Fiore, Yves Rouillé, Francois Helle. QuantIF: An ImageJ Macro to Automatically Determine the Percentage of Infected Cells after Immunofluorescence. Viruses, 2019, 11 (2), pp.165. ⟨10.3390/v11020165⟩. ⟨hal-02114383⟩