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Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues
Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MyJove Corporation
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3144599/ https://www.ncbi.nlm.nih.gov/pubmed/22157949 http://dx.doi.org/10.3791/1733 |
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author | Hernandez-Garcia, Carlos M. Chiera, Joseph M. Finer, John J. |
author_facet | Hernandez-Garcia, Carlos M. Chiera, Joseph M. Finer, John J. |
author_sort | Hernandez-Garcia, Carlos M. |
collection | PubMed |
description | Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections. |
format | Online Article Text |
id | pubmed-3144599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | MyJove Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-31445992011-08-03 Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues Hernandez-Garcia, Carlos M. Chiera, Joseph M. Finer, John J. J Vis Exp Plant Biology Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections. MyJove Corporation 2010-05-05 /pmc/articles/PMC3144599/ /pubmed/22157949 http://dx.doi.org/10.3791/1733 Text en Copyright © 2010, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Plant Biology Hernandez-Garcia, Carlos M. Chiera, Joseph M. Finer, John J. Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title | Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title_full | Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title_fullStr | Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title_full_unstemmed | Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title_short | Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues |
title_sort | robotics and dynamic image analysis for studies of gene expression in plant tissues |
topic | Plant Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3144599/ https://www.ncbi.nlm.nih.gov/pubmed/22157949 http://dx.doi.org/10.3791/1733 |
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