Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice
Homologous recombination (HR) events are key drivers of cancer-promoting mutations, and the ability to visualize these events in situ provides important information regarding mutant cell type, location, and clonal expansion. We have previously created the Rosa26 Direct Repeat (RaDR) mouse model wher...
| Main Authors: | , , , , , , , |
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| Format: | Article |
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Nature Publishing Group
2018
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| Online Access: | http://hdl.handle.net/1721.1/117657 https://orcid.org/0000-0001-5891-0689 https://orcid.org/0000-0001-6880-9509 https://orcid.org/0000-0003-4322-3573 https://orcid.org/0000-0003-4698-6488 |
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| author | Rajapakse, Jagath Wadduwage, Dushan Nawoda Kay, Jennifer Elizabeth Singh, Vijay Raj Kiraly, Orsolya Sukup Jackson, Michelle Rae Engelward, Bevin P So, Peter T. C. |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Rajapakse, Jagath Wadduwage, Dushan Nawoda Kay, Jennifer Elizabeth Singh, Vijay Raj Kiraly, Orsolya Sukup Jackson, Michelle Rae Engelward, Bevin P So, Peter T. C. |
| author_sort | Rajapakse, Jagath |
| collection | MIT |
| description | Homologous recombination (HR) events are key drivers of cancer-promoting mutations, and the ability to visualize these events in situ provides important information regarding mutant cell type, location, and clonal expansion. We have previously created the Rosa26 Direct Repeat (RaDR) mouse model wherein HR at an integrated substrate gives rise to a fluorescent cell. To fully leverage this in situ approach, we need better ways to quantify rare fluorescent cells deep within tissues. Here, we present a robust, automated event quantification algorithm that uses image intensity and gradient features to detect fluorescent cells in deep tissue specimens. To analyze the performance of our algorithm, we simulate fluorescence behavior in tissue using Monte Carlo methods. Importantly, this approach reduces the potential for bias in manual counting and enables quantification of samples with highly dense HR events. Using this approach, we measured the relative frequency of HR within a chromosome and between chromosomes and found that HR within a chromosome is more frequent, which is consistent with the close proximity of sister chromatids. Our approach is both objective and highly rapid, providing a powerful tool, not only to researchers interested in HR, but also to many other researchers who are similarly using fluorescence as a marker for understanding mammalian biology in tissues. |
| first_indexed | 2024-09-23T09:57:28Z |
| format | Article |
| id | mit-1721.1/117657 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T09:57:28Z |
| publishDate | 2018 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1176572022-09-26T14:50:10Z Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice Rajapakse, Jagath Wadduwage, Dushan Nawoda Kay, Jennifer Elizabeth Singh, Vijay Raj Kiraly, Orsolya Sukup Jackson, Michelle Rae Engelward, Bevin P So, Peter T. C. Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Department of Mechanical Engineering Wadduwage, Dushan Nawoda Kay, Jennifer Elizabeth Singh, Vijay Raj Kiraly, Orsolya Sukup Jackson, Michelle Rae Engelward, Bevin P So, Peter T. C. Homologous recombination (HR) events are key drivers of cancer-promoting mutations, and the ability to visualize these events in situ provides important information regarding mutant cell type, location, and clonal expansion. We have previously created the Rosa26 Direct Repeat (RaDR) mouse model wherein HR at an integrated substrate gives rise to a fluorescent cell. To fully leverage this in situ approach, we need better ways to quantify rare fluorescent cells deep within tissues. Here, we present a robust, automated event quantification algorithm that uses image intensity and gradient features to detect fluorescent cells in deep tissue specimens. To analyze the performance of our algorithm, we simulate fluorescence behavior in tissue using Monte Carlo methods. Importantly, this approach reduces the potential for bias in manual counting and enables quantification of samples with highly dense HR events. Using this approach, we measured the relative frequency of HR within a chromosome and between chromosomes and found that HR within a chromosome is more frequent, which is consistent with the close proximity of sister chromatids. Our approach is both objective and highly rapid, providing a powerful tool, not only to researchers interested in HR, but also to many other researchers who are similarly using fluorescence as a marker for understanding mammalian biology in tissues. National Institutes of Health (U.S.) (Grant P01-CA026731) National Institutes of Health (U.S.) (Grant 9P41EB015871) National Institutes of Health (U.S.) (Grant 5R01NS051320) National Institutes of Health (U.S.) (Grant 4R44EB012415) National Institutes of Health (U.S.) (Grant 1R01HL121386-01A) 2018-09-06T19:19:33Z 2018-09-06T19:19:33Z 2018-08 2017-09 2018-08-28T17:43:55Z Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/117657 Wadduwage, Dushan N. et al. “Automated Fluorescence Intensity and Gradient Analysis Enables Detection of Rare Fluorescent Mutant Cells Deep Within the Tissue of RaDR Mice.” Scientific Reports 8, 1 (August 2018): 12108 https://orcid.org/0000-0001-5891-0689 https://orcid.org/0000-0001-6880-9509 https://orcid.org/0000-0003-4322-3573 https://orcid.org/0000-0003-4698-6488 http://dx.doi.org/10.1038/s41598-018-30557-9 Scientific Reports Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Rajapakse, Jagath Wadduwage, Dushan Nawoda Kay, Jennifer Elizabeth Singh, Vijay Raj Kiraly, Orsolya Sukup Jackson, Michelle Rae Engelward, Bevin P So, Peter T. C. Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title | Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title_full | Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title_fullStr | Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title_full_unstemmed | Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title_short | Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice |
| title_sort | automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of radr mice |
| url | http://hdl.handle.net/1721.1/117657 https://orcid.org/0000-0001-5891-0689 https://orcid.org/0000-0001-6880-9509 https://orcid.org/0000-0003-4322-3573 https://orcid.org/0000-0003-4698-6488 |
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