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Colonyzer: automated quantification of micro-organism growth characteristics on solid agar

BACKGROUND: High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after...

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Autores principales: Lawless, Conor, Wilkinson, Darren J, Young, Alexander, Addinall, Stephen G, Lydall, David A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901369/
https://www.ncbi.nlm.nih.gov/pubmed/20509870
http://dx.doi.org/10.1186/1471-2105-11-287
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author Lawless, Conor
Wilkinson, Darren J
Young, Alexander
Addinall, Stephen G
Lydall, David A
author_facet Lawless, Conor
Wilkinson, Darren J
Young, Alexander
Addinall, Stephen G
Lydall, David A
author_sort Lawless, Conor
collection PubMed
description BACKGROUND: High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required. RESULTS: Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures. CONCLUSION: Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development.
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spelling pubmed-29013692010-07-10 Colonyzer: automated quantification of micro-organism growth characteristics on solid agar Lawless, Conor Wilkinson, Darren J Young, Alexander Addinall, Stephen G Lydall, David A BMC Bioinformatics Software BACKGROUND: High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required. RESULTS: Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures. CONCLUSION: Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development. BioMed Central 2010-05-28 /pmc/articles/PMC2901369/ /pubmed/20509870 http://dx.doi.org/10.1186/1471-2105-11-287 Text en Copyright ©2010 Lawless et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Lawless, Conor
Wilkinson, Darren J
Young, Alexander
Addinall, Stephen G
Lydall, David A
Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title_full Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title_fullStr Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title_full_unstemmed Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title_short Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
title_sort colonyzer: automated quantification of micro-organism growth characteristics on solid agar
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901369/
https://www.ncbi.nlm.nih.gov/pubmed/20509870
http://dx.doi.org/10.1186/1471-2105-11-287
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