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mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis
Mitochondrial DNA (mtDNA) encodes the core subunits for OXPHOS, essential in near-all eukaryotes. Packed into distinct foci (nucleoids) inside mitochondria, the number of mtDNA copies differs between cell-types and is affected in several human diseases. Currently, common protocols estimate per-cell...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681798/ https://www.ncbi.nlm.nih.gov/pubmed/37850644 http://dx.doi.org/10.1093/nar/gkad864 |
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author | Rey, Timo Tábara, Luis Carlos Prudent, Julien Minczuk, Michal |
author_facet | Rey, Timo Tábara, Luis Carlos Prudent, Julien Minczuk, Michal |
author_sort | Rey, Timo |
collection | PubMed |
description | Mitochondrial DNA (mtDNA) encodes the core subunits for OXPHOS, essential in near-all eukaryotes. Packed into distinct foci (nucleoids) inside mitochondria, the number of mtDNA copies differs between cell-types and is affected in several human diseases. Currently, common protocols estimate per-cell mtDNA-molecule numbers by sequencing or qPCR from bulk samples. However, this does not allow insight into cell-to-cell heterogeneity and can mask phenotypical sub-populations. Here, we present mtFociCounter, a single-cell image analysis tool for reproducible quantification of nucleoids and other foci. mtFociCounter is a light-weight, open-source freeware and overcomes current limitations to reproducible single-cell analysis of mitochondrial foci. We demonstrate its use by analysing 2165 single fibroblasts, and observe a large cell-to-cell heterogeneity in nucleoid numbers. In addition, mtFociCounter quantifies mitochondrial content and our results show good correlation (R = 0.90) between nucleoid number and mitochondrial area, and we find nucleoid density is less variable than nucleoid numbers in wild-type cells. Finally, we demonstrate mtFociCounter readily detects differences in foci-numbers upon sample treatment, and applies to Mitochondrial RNA Granules and superresolution microscopy. mtFociCounter provides a versatile solution to reproducibly quantify cellular foci in single cells and our results highlight the importance of accounting for cell-to-cell variance and mitochondrial context in mitochondrial foci analysis. |
format | Online Article Text |
id | pubmed-10681798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106817982023-10-18 mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis Rey, Timo Tábara, Luis Carlos Prudent, Julien Minczuk, Michal Nucleic Acids Res Methods Mitochondrial DNA (mtDNA) encodes the core subunits for OXPHOS, essential in near-all eukaryotes. Packed into distinct foci (nucleoids) inside mitochondria, the number of mtDNA copies differs between cell-types and is affected in several human diseases. Currently, common protocols estimate per-cell mtDNA-molecule numbers by sequencing or qPCR from bulk samples. However, this does not allow insight into cell-to-cell heterogeneity and can mask phenotypical sub-populations. Here, we present mtFociCounter, a single-cell image analysis tool for reproducible quantification of nucleoids and other foci. mtFociCounter is a light-weight, open-source freeware and overcomes current limitations to reproducible single-cell analysis of mitochondrial foci. We demonstrate its use by analysing 2165 single fibroblasts, and observe a large cell-to-cell heterogeneity in nucleoid numbers. In addition, mtFociCounter quantifies mitochondrial content and our results show good correlation (R = 0.90) between nucleoid number and mitochondrial area, and we find nucleoid density is less variable than nucleoid numbers in wild-type cells. Finally, we demonstrate mtFociCounter readily detects differences in foci-numbers upon sample treatment, and applies to Mitochondrial RNA Granules and superresolution microscopy. mtFociCounter provides a versatile solution to reproducibly quantify cellular foci in single cells and our results highlight the importance of accounting for cell-to-cell variance and mitochondrial context in mitochondrial foci analysis. Oxford University Press 2023-10-18 /pmc/articles/PMC10681798/ /pubmed/37850644 http://dx.doi.org/10.1093/nar/gkad864 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Rey, Timo Tábara, Luis Carlos Prudent, Julien Minczuk, Michal mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title | mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title_full | mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title_fullStr | mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title_full_unstemmed | mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title_short | mtFociCounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
title_sort | mtfocicounter for automated single-cell mitochondrial nucleoid quantification and reproducible foci analysis |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681798/ https://www.ncbi.nlm.nih.gov/pubmed/37850644 http://dx.doi.org/10.1093/nar/gkad864 |
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