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Automated modeling of protein accumulation at DNA damage sites using qFADD.py
Eukaryotic cells are constantly subject to DNA damage, often with detrimental consequences for the health of the organism. Cells mitigate this DNA damage through a variety of repair pathways involving a diverse and large number of different proteins. To better understand the cellular response to DNA...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9683346/ https://www.ncbi.nlm.nih.gov/pubmed/36424940 http://dx.doi.org/10.1017/s2633903x22000083 |
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author | Bowerman, Samuel Mahadevan, Jyothi Benson, Philip Rudolph, Johannes Luger, Karolin |
author_facet | Bowerman, Samuel Mahadevan, Jyothi Benson, Philip Rudolph, Johannes Luger, Karolin |
author_sort | Bowerman, Samuel |
collection | PubMed |
description | Eukaryotic cells are constantly subject to DNA damage, often with detrimental consequences for the health of the organism. Cells mitigate this DNA damage through a variety of repair pathways involving a diverse and large number of different proteins. To better understand the cellular response to DNA damage, one needs accurate measurements of the accumulation, retention, and dissipation timescales of these repair proteins. Here, we describe an automated implementation of the “quantitation of fluorescence accumulation after DNA damage” method that greatly enhances the analysis and quantitation of the widely used technique known as laser microirradiation, which is used to study the recruitment of DNA repair proteins to sites of DNA damage. This open-source implementation (“qFADD.py”) is available as a stand-alone software package that can be run on laptops or computer clusters. Our implementation includes corrections for nuclear drift, an automated grid search for the model of a best fit, and the ability to model both horizontal striping and speckle experiments. To improve statistical rigor, the grid-search algorithm also includes automated simulation of replicates. As a practical example, we present and discuss the recruitment dynamics of the early responder PARP1 to DNA damage sites. |
format | Online Article Text |
id | pubmed-9683346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-96833462022-11-23 Automated modeling of protein accumulation at DNA damage sites using qFADD.py Bowerman, Samuel Mahadevan, Jyothi Benson, Philip Rudolph, Johannes Luger, Karolin Biol Imaging Article Eukaryotic cells are constantly subject to DNA damage, often with detrimental consequences for the health of the organism. Cells mitigate this DNA damage through a variety of repair pathways involving a diverse and large number of different proteins. To better understand the cellular response to DNA damage, one needs accurate measurements of the accumulation, retention, and dissipation timescales of these repair proteins. Here, we describe an automated implementation of the “quantitation of fluorescence accumulation after DNA damage” method that greatly enhances the analysis and quantitation of the widely used technique known as laser microirradiation, which is used to study the recruitment of DNA repair proteins to sites of DNA damage. This open-source implementation (“qFADD.py”) is available as a stand-alone software package that can be run on laptops or computer clusters. Our implementation includes corrections for nuclear drift, an automated grid search for the model of a best fit, and the ability to model both horizontal striping and speckle experiments. To improve statistical rigor, the grid-search algorithm also includes automated simulation of replicates. As a practical example, we present and discuss the recruitment dynamics of the early responder PARP1 to DNA damage sites. 2022 2022-08-30 /pmc/articles/PMC9683346/ /pubmed/36424940 http://dx.doi.org/10.1017/s2633903x22000083 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Article Bowerman, Samuel Mahadevan, Jyothi Benson, Philip Rudolph, Johannes Luger, Karolin Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title | Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title_full | Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title_fullStr | Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title_full_unstemmed | Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title_short | Automated modeling of protein accumulation at DNA damage sites using qFADD.py |
title_sort | automated modeling of protein accumulation at dna damage sites using qfadd.py |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9683346/ https://www.ncbi.nlm.nih.gov/pubmed/36424940 http://dx.doi.org/10.1017/s2633903x22000083 |
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