Next Article in Journal
Enhanced Ability of Oligomeric Nanobodies Targeting MERS Coronavirus Receptor-Binding Domain
Next Article in Special Issue
A Needle in A Haystack: Tracing Bivalve-Associated Viruses in High-Throughput Transcriptomic Data
Previous Article in Journal
Current Understanding of the Molecular Basis of Venezuelan Equine Encephalitis Virus Pathogenesis and Vaccine Development
Previous Article in Special Issue
Exploring the Papillomaviral Proteome to Identify Potential Candidates for a Chimeric Vaccine against Cervix Papilloma Using Immunomics and Computational Structural Vaccinology
Open AccessTechnical Note

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

by Lynda Handala 1,†, Tony Fiore 1,†, Yves Rouillé 2,* and Francois Helle 1,*
1
EA4294, Agents Infectieux, Résistance et Chimiothérapie, Centre Universitaire de Recherche en Santé, Centre Hospitalier Universitaire et Université de Picardie Jules Verne, 80054 Amiens, France
2
University of Lille, CNRS, INSERM, CHU Lille, Pasteur Institute of Lille, U1019-UMR8204-CIIL-Center for Infection and Immunity of Lille, 59019 Lille, France
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Viruses 2019, 11(2), 165; https://doi.org/10.3390/v11020165
Received: 21 January 2019 / Revised: 12 February 2019 / Accepted: 17 February 2019 / Published: 19 February 2019
(This article belongs to the Special Issue Virus Bioinformatics)
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. View Full-Text
Keywords: virus; infection; fluorescent reporter protein; image quantification; Hepatitis C virus; Yellow Fever Virus; polyomavirus; Coxsackievirus B4 virus; infection; fluorescent reporter protein; image quantification; Hepatitis C virus; Yellow Fever Virus; polyomavirus; Coxsackievirus B4
Show Figures

Figure 1

MDPI and ACS Style

Handala, L.; Fiore, T.; Rouillé, Y.; Helle, F. QuantIF: An ImageJ Macro to Automatically Determine the Percentage of Infected Cells after Immunofluorescence. Viruses 2019, 11, 165.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop