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Automated 96-well format high throughput colony formation assay for siRNA library screen
The colony formation assay is the gold-standard technique to assess cell viability after treatment with cytotoxic reagents, ionizing radiation, and cytotoxic combinatorial treatments. This protocol describes a high-throughput automated and high-content imaging approach to screen siRNA molecular libr...
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/PMC9079112/ https://www.ncbi.nlm.nih.gov/pubmed/35542177 http://dx.doi.org/10.1016/j.xpro.2022.101355 |
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author | Hatch, Stephanie B. Prevo, Remko Chan, Tiffany Millar, Val Cornelissen, Bart Higgins, Geoff Ebner, Daniel |
author_facet | Hatch, Stephanie B. Prevo, Remko Chan, Tiffany Millar, Val Cornelissen, Bart Higgins, Geoff Ebner, Daniel |
author_sort | Hatch, Stephanie B. |
collection | PubMed |
description | The colony formation assay is the gold-standard technique to assess cell viability after treatment with cytotoxic reagents, ionizing radiation, and cytotoxic combinatorial treatments. This protocol describes a high-throughput automated and high-content imaging approach to screen siRNA molecular libraries in HeLa cervical cancer cells in 96-well format. We detail reverse transfection of cells with siRNAs, followed by ionizing radiation, fixing, and staining of the plates for automated colony counting. This protocol can be used across a broad range of cell types. For complete details on the use and execution of this protocol, please refer to Tiwana et al. (2015). |
format | Online Article Text |
id | pubmed-9079112 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90791122022-05-09 Automated 96-well format high throughput colony formation assay for siRNA library screen Hatch, Stephanie B. Prevo, Remko Chan, Tiffany Millar, Val Cornelissen, Bart Higgins, Geoff Ebner, Daniel STAR Protoc Protocol The colony formation assay is the gold-standard technique to assess cell viability after treatment with cytotoxic reagents, ionizing radiation, and cytotoxic combinatorial treatments. This protocol describes a high-throughput automated and high-content imaging approach to screen siRNA molecular libraries in HeLa cervical cancer cells in 96-well format. We detail reverse transfection of cells with siRNAs, followed by ionizing radiation, fixing, and staining of the plates for automated colony counting. This protocol can be used across a broad range of cell types. For complete details on the use and execution of this protocol, please refer to Tiwana et al. (2015). Elsevier 2022-05-01 /pmc/articles/PMC9079112/ /pubmed/35542177 http://dx.doi.org/10.1016/j.xpro.2022.101355 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol Hatch, Stephanie B. Prevo, Remko Chan, Tiffany Millar, Val Cornelissen, Bart Higgins, Geoff Ebner, Daniel Automated 96-well format high throughput colony formation assay for siRNA library screen |
title | Automated 96-well format high throughput colony formation assay for siRNA library screen |
title_full | Automated 96-well format high throughput colony formation assay for siRNA library screen |
title_fullStr | Automated 96-well format high throughput colony formation assay for siRNA library screen |
title_full_unstemmed | Automated 96-well format high throughput colony formation assay for siRNA library screen |
title_short | Automated 96-well format high throughput colony formation assay for siRNA library screen |
title_sort | automated 96-well format high throughput colony formation assay for sirna library screen |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079112/ https://www.ncbi.nlm.nih.gov/pubmed/35542177 http://dx.doi.org/10.1016/j.xpro.2022.101355 |
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