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A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy
The ability to automatically analyze large quantities of image data is a valuable tool for many biochemical assays, as it rapidly provides reliable data. Here, we describe a fast and robust Fiji macro for the analysis of cellular fluorescence microscopy images with single-cell resolution. The macro...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490200/ https://www.ncbi.nlm.nih.gov/pubmed/36160109 http://dx.doi.org/10.1016/j.mex.2022.101834 |
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author | Kerkhoff, Yannic Wedepohl, Stefanie Nie, Chuanxiong Ahmadi, Vahid Haag, Rainer Block, Stephan |
author_facet | Kerkhoff, Yannic Wedepohl, Stefanie Nie, Chuanxiong Ahmadi, Vahid Haag, Rainer Block, Stephan |
author_sort | Kerkhoff, Yannic |
collection | PubMed |
description | The ability to automatically analyze large quantities of image data is a valuable tool for many biochemical assays, as it rapidly provides reliable data. Here, we describe a fast and robust Fiji macro for the analysis of cellular fluorescence microscopy images with single-cell resolution. The macro presented here was validated by successful reconstruction of fluorescent and non-fluorescent cell mixing ratios (for fluorescence fractions ranging between 0 and 100%) and applied to quantify the efficiency of transfection and virus infection inhibition. It performed well compared with manually obtained image quantification data. Its use is not limited to the cases shown here but is applicable for most monolayered cellular assays with nuclei staining. We provide a detailed description of how the macro works and how it is applied to image data. It can be downloaded free of charge and may be used by and modified according to the needs of the user. • Rapid, simple, and reproducible segmentation of eukaryotic cells in confluent cellular assays • Open-source software for use without technical or computational expertise • Single-cell analysis allows identification and quantification of virus infected cell populations and infection inhibition |
format | Online Article Text |
id | pubmed-9490200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94902002022-09-22 A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy Kerkhoff, Yannic Wedepohl, Stefanie Nie, Chuanxiong Ahmadi, Vahid Haag, Rainer Block, Stephan MethodsX Method Article The ability to automatically analyze large quantities of image data is a valuable tool for many biochemical assays, as it rapidly provides reliable data. Here, we describe a fast and robust Fiji macro for the analysis of cellular fluorescence microscopy images with single-cell resolution. The macro presented here was validated by successful reconstruction of fluorescent and non-fluorescent cell mixing ratios (for fluorescence fractions ranging between 0 and 100%) and applied to quantify the efficiency of transfection and virus infection inhibition. It performed well compared with manually obtained image quantification data. Its use is not limited to the cases shown here but is applicable for most monolayered cellular assays with nuclei staining. We provide a detailed description of how the macro works and how it is applied to image data. It can be downloaded free of charge and may be used by and modified according to the needs of the user. • Rapid, simple, and reproducible segmentation of eukaryotic cells in confluent cellular assays • Open-source software for use without technical or computational expertise • Single-cell analysis allows identification and quantification of virus infected cell populations and infection inhibition Elsevier 2022-09-02 /pmc/articles/PMC9490200/ /pubmed/36160109 http://dx.doi.org/10.1016/j.mex.2022.101834 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Method Article Kerkhoff, Yannic Wedepohl, Stefanie Nie, Chuanxiong Ahmadi, Vahid Haag, Rainer Block, Stephan A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title | A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title_full | A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title_fullStr | A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title_full_unstemmed | A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title_short | A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
title_sort | fast open-source fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490200/ https://www.ncbi.nlm.nih.gov/pubmed/36160109 http://dx.doi.org/10.1016/j.mex.2022.101834 |
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