Cargando…

Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Culley, Siân, Towers, Greg J., Selwood, David L., Henriques, Ricardo, Grove, Joe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974536/
https://www.ncbi.nlm.nih.gov/pubmed/27455304
http://dx.doi.org/10.3390/v8070201
_version_ 1782446563302309888
author Culley, Siân
Towers, Greg J.
Selwood, David L.
Henriques, Ricardo
Grove, Joe
author_facet Culley, Siân
Towers, Greg J.
Selwood, David L.
Henriques, Ricardo
Grove, Joe
author_sort Culley, Siân
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4974536
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-49745362016-08-08 Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy Culley, Siân Towers, Greg J. Selwood, David L. Henriques, Ricardo Grove, Joe Viruses Article 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. MDPI 2016-07-21 /pmc/articles/PMC4974536/ /pubmed/27455304 http://dx.doi.org/10.3390/v8070201 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Culley, Siân
Towers, Greg J.
Selwood, David L.
Henriques, Ricardo
Grove, Joe
Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title_full Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title_fullStr Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title_full_unstemmed Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title_short Infection Counter: Automated Quantification of in Vitro Virus Replication by Fluorescence Microscopy
title_sort infection counter: automated quantification of in vitro virus replication by fluorescence microscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974536/
https://www.ncbi.nlm.nih.gov/pubmed/27455304
http://dx.doi.org/10.3390/v8070201
work_keys_str_mv AT culleysian infectioncounterautomatedquantificationofinvitrovirusreplicationbyfluorescencemicroscopy
AT towersgregj infectioncounterautomatedquantificationofinvitrovirusreplicationbyfluorescencemicroscopy
AT selwooddavidl infectioncounterautomatedquantificationofinvitrovirusreplicationbyfluorescencemicroscopy
AT henriquesricardo infectioncounterautomatedquantificationofinvitrovirusreplicationbyfluorescencemicroscopy
AT grovejoe infectioncounterautomatedquantificationofinvitrovirusreplicationbyfluorescencemicroscopy