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

BMC Bioinformatics

Software

Conor Lawless¹  Stephen G Addinall¹  David A Lydall¹  Darren J Wilkinson²  Alexander Young³ 

[1] Centre for Integrated Systems Biology of Ageing and Nutrition, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, NE4 5PL, Newcastle-Upon-Tyne, UK;Centre for Integrated Systems Biology of Ageing and Nutrition, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, NE4 5PL, Newcastle-Upon-Tyne, UK;School of Mathematics & Statistics, Herschel Building, Newcastle University, NE1 7RU, Newcastle-Upon-Tyne, UK;School of Mathematics & Statistics, Herschel Building, Newcastle University, NE1 7RU, Newcastle-Upon-Tyne, UK;

关键词: Cell Density;    Pixel Intensity;    Culture Area;    Integrate Optical Density;    Lighting Gradient;   

DOI  :  10.1186/1471-2105-11-287

 received in 2009-11-20, accepted in 2010-05-28,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundHigh-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.ResultsColonyzer 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.ConclusionColonyzer 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.

【 授权许可】

CC BY   
© Lawless et al; licensee BioMed Central Ltd. 2010