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...

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Main Authors: Wadduwage, Dushan N., Kay, Jennifer, Singh, Vijay Raj, Kiraly, Orsolya, Sukup-Jackson, Michelle R., Rajapakse, Jagath, Engelward, Bevin P., So, Peter T. C.
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89695
http://hdl.handle.net/10220/46313
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-896952020-03-07T11:48:54Z Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice Wadduwage, Dushan N. Kay, Jennifer Singh, Vijay Raj Kiraly, Orsolya Sukup-Jackson, Michelle R. Rajapakse, Jagath Engelward, Bevin P. So, Peter T. C. School of Computer Science and Engineering Singapore-MIT Alliance Programme Homologous Recombination Fluorescent Mutant Cells DRNTU::Engineering::Computer science and engineering 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. NRF (Natl Research Foundation, S’pore) Published version 2018-10-15T06:06:09Z 2019-12-06T17:31:23Z 2018-10-15T06:06:09Z 2019-12-06T17:31:23Z 2018 Journal Article Wadduwage, D. N., Kay, J., Singh, V. R., Kiraly, O., Sukup-Jackson, M. R., Rajapakse, J., . . . So, P. T. C. (2018). Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice. Scientific Reports, 8(1), 12108-. doi:10.1038/s41598-018-30557-9 https://hdl.handle.net/10356/89695 http://hdl.handle.net/10220/46313 10.1038/s41598-018-30557-9 en Scientific Reports © 2018 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. 11 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Homologous Recombination
Fluorescent Mutant Cells
DRNTU::Engineering::Computer science and engineering
spellingShingle Homologous Recombination
Fluorescent Mutant Cells
DRNTU::Engineering::Computer science and engineering
Wadduwage, Dushan N.
Kay, Jennifer
Singh, Vijay Raj
Kiraly, Orsolya
Sukup-Jackson, Michelle R.
Rajapakse, Jagath
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
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.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Wadduwage, Dushan N.
Kay, Jennifer
Singh, Vijay Raj
Kiraly, Orsolya
Sukup-Jackson, Michelle R.
Rajapakse, Jagath
Engelward, Bevin P.
So, Peter T. C.
format Article
author Wadduwage, Dushan N.
Kay, Jennifer
Singh, Vijay Raj
Kiraly, Orsolya
Sukup-Jackson, Michelle R.
Rajapakse, Jagath
Engelward, Bevin P.
So, Peter T. C.
author_sort Wadduwage, Dushan N.
title 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_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_sort automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of radr mice
publishDate 2018
url https://hdl.handle.net/10356/89695
http://hdl.handle.net/10220/46313
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