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A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies

BACKGROUND: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such...

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Autores principales: Wang, Yinhai, Ledgerwood, Craig, Grills, Claire, Fitzgerald, Denise C., Hamilton, Peter W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3281864/
https://www.ncbi.nlm.nih.gov/pubmed/22363456
http://dx.doi.org/10.1371/journal.pone.0030632
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author Wang, Yinhai
Ledgerwood, Craig
Grills, Claire
Fitzgerald, Denise C.
Hamilton, Peter W.
author_facet Wang, Yinhai
Ledgerwood, Craig
Grills, Claire
Fitzgerald, Denise C.
Hamilton, Peter W.
author_sort Wang, Yinhai
collection PubMed
description BACKGROUND: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes. METHOD: In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co-localisations even when images are polluted with a range of noises. RESULTS: The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capable of removing a large amount of false positivity, such as non-specific cross-overs. Performance of this method of measurement is significantly more accurate than existing measurements, as determined statistically using pseudo datasets of known values. This method provides an important and reliable tool for fluorescent 3D neurobiological studies, and will benefit other biological studies which measure fluorescence co-localisation in 3D.
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spelling pubmed-32818642012-02-23 A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies Wang, Yinhai Ledgerwood, Craig Grills, Claire Fitzgerald, Denise C. Hamilton, Peter W. PLoS One Research Article BACKGROUND: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes. METHOD: In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co-localisations even when images are polluted with a range of noises. RESULTS: The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capable of removing a large amount of false positivity, such as non-specific cross-overs. Performance of this method of measurement is significantly more accurate than existing measurements, as determined statistically using pseudo datasets of known values. This method provides an important and reliable tool for fluorescent 3D neurobiological studies, and will benefit other biological studies which measure fluorescence co-localisation in 3D. Public Library of Science 2012-02-17 /pmc/articles/PMC3281864/ /pubmed/22363456 http://dx.doi.org/10.1371/journal.pone.0030632 Text en Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wang, Yinhai
Ledgerwood, Craig
Grills, Claire
Fitzgerald, Denise C.
Hamilton, Peter W.
A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title_full A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title_fullStr A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title_full_unstemmed A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title_short A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies
title_sort robust co-localisation measurement utilising z-stack image intensity similarities for biological studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3281864/
https://www.ncbi.nlm.nih.gov/pubmed/22363456
http://dx.doi.org/10.1371/journal.pone.0030632
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