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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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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 |
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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 |
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