TAMMiCol: Tool for analysis of the morphology of microbial colonies
| Autor: | Jennifer M. Gardner, Benjamin J. Binder, Hayden Tronnolone, Vladimir Jiranek, Joanna F. Sundstrom, Stephen G. Oliver |
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| Přispěvatelé: | Tronnolone, Hayden [0000-0003-4532-2030], Sundstrom, Joanna F [0000-0002-4898-3101], Binder, Benjamin J [0000-0002-1812-6715], Apollo - University of Cambridge Repository |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Databases Factual Computer science Image Processing Yeast and Fungal Models Pathology and Laboratory Medicine Software Image Processing Computer-Assisted Medicine and Health Sciences Segmentation Biology (General) Candida Fungal Pathogens Ecology Sulfates Binary image Microbiota Applied Mathematics Simulation and Modeling Eukaryota Thresholding Chemistry Computational Theory and Mathematics Experimental Organism Systems Ammonium Sulfate Medical Microbiology Modeling and Simulation Binary data Physical Sciences Batch processing Engineering and Technology Pathogens Algorithms Bacillus subtilis Research Article QH301-705.5 Imaging Techniques ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Saccharomyces cerevisiae Image Analysis Mycology Research and Analysis Methods Microbiology 03 medical and health sciences Cellular and Molecular Neuroscience Saccharomyces Model Organisms Genetics Candida Albicans Molecular Biology Microbial Pathogens Ecology Evolution Behavior and Systematics Pixel business.industry Organisms Fungi Chemical Compounds Computational Biology Biology and Life Sciences Pattern recognition Yeast Culture Media 030104 developmental biology Biofilms Signal Processing Animal Studies Salts Artificial intelligence business Mathematics |
| Zdroj: | PLoS Computational Biology PLoS Computational Biology, Vol 14, Iss 12, p e1006629 (2018) |
| ISSN: | 1553-7358 |
| Popis: | Many microbes are studied by examining colony morphology via two-dimensional top-down images. The quantification of such images typically requires each pixel to be labelled as belonging to either the colony or background, producing a binary image. While this may be achieved manually for a single colony, this process is infeasible for large datasets containing thousands of images. The software Tool for Analysis of the Morphology of Microbial Colonies (TAMMiCol) has been developed to efficiently and automatically convert colony images to binary. TAMMiCol exploits the structure of the images to choose a thresholding tolerance and produce a binary image of the colony. The images produced are shown to compare favourably with images processed manually, while TAMMiCol is shown to outperform standard segmentation methods. Multiple images may be imported together for batch processing, while the binary data may be exported as a CSV or MATLAB MAT file for quantification, or analysed using statistics built into the software. Using the in-built statistics, it is found that images produced by TAMMiCol yield values close to those computed from binary images processed manually. Analysis of a new large dataset using TAMMiCol shows that colonies of Saccharomyces cerevisiae reach a maximum level of filamentous growth once the concentration of ammonium sulfate is reduced to 200 μM. TAMMiCol is accessed through a graphical user interface, making it easy to use for those without specialist knowledge of image processing, statistical methods or coding. Author summary Many microbes are studied by examining the colony morphology via a two-dimensional top-down image. In order to quantify such images, we typically need to label each pixel as belonging either to the colony or the background, creating a binary image. This task is laborious when performed manually and proves infeasible for large datasets. To overcome this, we have developed the software Tool for Analysis of the Morphology of Microbial Colonies (TAMMiCol), which automatically and efficiently converts colony images to binary. Multiple images may be imported and processed simultaneously, and TAMMiCol exploits the structure of the images to identify an appropriate threshold for the binary conversion of each image. The images produced by TAMMiCol, which take around 20 seconds each to process, compare favourably with images processed manually, which take anywhere up to 15 minutes, while TAMMiCol outperforms several standard image segmentation methods. After processing, the images may be exported as a CSV or MATLAB MAT file for further analysis, or may be quantified by TAMMiCol using the in-built statistics. Using TAMMiCol, we have found that colonies of S. cerevisiae reach a maximum level of filamentous growth once the concentration of ammonium sulfate is reduced to 200 μM. |
| Databáze: | OpenAIRE |
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