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Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis

BACKGROUND: Cellular components are controlled by genetic and physiological factors that define their shape and size. However, quantitively capturing the morphological characteristics and movement of cellular organelles from micrograph images is challenging, because the analysis deals with complexit...

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Autores principales: Basak, Arpan Kumar, Mirzaei, Mohamadreza, Strzałka, Kazimierz, Yamada, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549183/
https://www.ncbi.nlm.nih.gov/pubmed/34702318
http://dx.doi.org/10.1186/s13007-021-00810-w
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author Basak, Arpan Kumar
Mirzaei, Mohamadreza
Strzałka, Kazimierz
Yamada, Kenji
author_facet Basak, Arpan Kumar
Mirzaei, Mohamadreza
Strzałka, Kazimierz
Yamada, Kenji
author_sort Basak, Arpan Kumar
collection PubMed
description BACKGROUND: Cellular components are controlled by genetic and physiological factors that define their shape and size. However, quantitively capturing the morphological characteristics and movement of cellular organelles from micrograph images is challenging, because the analysis deals with complexities of images that frequently lead to inaccuracy in the estimation of the features. Here we show a unique quantitative method to overcome biases and inaccuracy of biological samples from confocal micrographs. RESULTS: We generated 2D images of cell walls and spindle-shaped cellular organelles, namely ER bodies, with a maximum contrast projection of 3D confocal fluorescent microscope images. The projected images were further processed and segmented by adaptive thresholding of the fluorescent levels in the cell walls. Micrographs are composed of pixels, which have information on position and intensity. From the pixel information we calculated three types of features (spatial, intensity and Haralick) in ER bodies corresponding to segmented cells. The spatial features include basic information on shape, e.g., surface area and perimeter. The intensity features include information on mean, standard deviation and quantile of fluorescence intensities within an ER body. Haralick features describe the texture features, which can be calculated mathematically from the interrelationship between the pixel information. Together these parameters were subjected to multivariate analysis to estimate the morphological diversity. Additionally, we calculated the displacement of the ER bodies using the positional information in time-lapse images. We captured similar morphological diversity and movement within ER body phenotypes in several microscopy experiments performed in different settings and scanned under different objectives. We then described differences in morphology and movement of ER bodies between A. thaliana wild type and mutants deficient in ER body-related genes. CONCLUSIONS: The findings unexpectedly revealed multiple genetic factors that are involved in the shape and size of ER bodies in A. thaliana. This is the first report showing morphological characteristics in addition to the movement of cellular components and it quantitatively summarises plant phenotypic differences even in plants that show similar cellular components. The estimation of morphological diversity was independent of the cell staining method and the objective lens used in the microscopy. Hence, our study enables a robust estimation of plant phenotypes by recognizing small differences in complex cell organelle shapes and their movement, which is beneficial in a comprehensive analysis of the molecular mechanism for cell organelle formation that is independent of technical variations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-021-00810-w.
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spelling pubmed-85491832021-10-27 Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis Basak, Arpan Kumar Mirzaei, Mohamadreza Strzałka, Kazimierz Yamada, Kenji Plant Methods Research BACKGROUND: Cellular components are controlled by genetic and physiological factors that define their shape and size. However, quantitively capturing the morphological characteristics and movement of cellular organelles from micrograph images is challenging, because the analysis deals with complexities of images that frequently lead to inaccuracy in the estimation of the features. Here we show a unique quantitative method to overcome biases and inaccuracy of biological samples from confocal micrographs. RESULTS: We generated 2D images of cell walls and spindle-shaped cellular organelles, namely ER bodies, with a maximum contrast projection of 3D confocal fluorescent microscope images. The projected images were further processed and segmented by adaptive thresholding of the fluorescent levels in the cell walls. Micrographs are composed of pixels, which have information on position and intensity. From the pixel information we calculated three types of features (spatial, intensity and Haralick) in ER bodies corresponding to segmented cells. The spatial features include basic information on shape, e.g., surface area and perimeter. The intensity features include information on mean, standard deviation and quantile of fluorescence intensities within an ER body. Haralick features describe the texture features, which can be calculated mathematically from the interrelationship between the pixel information. Together these parameters were subjected to multivariate analysis to estimate the morphological diversity. Additionally, we calculated the displacement of the ER bodies using the positional information in time-lapse images. We captured similar morphological diversity and movement within ER body phenotypes in several microscopy experiments performed in different settings and scanned under different objectives. We then described differences in morphology and movement of ER bodies between A. thaliana wild type and mutants deficient in ER body-related genes. CONCLUSIONS: The findings unexpectedly revealed multiple genetic factors that are involved in the shape and size of ER bodies in A. thaliana. This is the first report showing morphological characteristics in addition to the movement of cellular components and it quantitatively summarises plant phenotypic differences even in plants that show similar cellular components. The estimation of morphological diversity was independent of the cell staining method and the objective lens used in the microscopy. Hence, our study enables a robust estimation of plant phenotypes by recognizing small differences in complex cell organelle shapes and their movement, which is beneficial in a comprehensive analysis of the molecular mechanism for cell organelle formation that is independent of technical variations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-021-00810-w. BioMed Central 2021-10-26 /pmc/articles/PMC8549183/ /pubmed/34702318 http://dx.doi.org/10.1186/s13007-021-00810-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Basak, Arpan Kumar
Mirzaei, Mohamadreza
Strzałka, Kazimierz
Yamada, Kenji
Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title_full Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title_fullStr Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title_full_unstemmed Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title_short Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis
title_sort texture feature extraction from microscope images enables a robust estimation of er body phenotype in arabidopsis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549183/
https://www.ncbi.nlm.nih.gov/pubmed/34702318
http://dx.doi.org/10.1186/s13007-021-00810-w
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AT strzałkakazimierz texturefeatureextractionfrommicroscopeimagesenablesarobustestimationoferbodyphenotypeinarabidopsis
AT yamadakenji texturefeatureextractionfrommicroscopeimagesenablesarobustestimationoferbodyphenotypeinarabidopsis