TAMMiCol: Tool for analysis of the morphology of microbial colonies
TAMMiCol: Tool for analysis of the morphology of microbial colonies
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.
Tronnolone, Hayden
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Gardner, Jennifer M.
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Sundstrom, Joanna F.
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Jiranek, Vladimir
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Oliver, Stephen G.
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Binder, Benjamin J.
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December 2018
Tronnolone, Hayden
c17ba912-b652-49de-a1cc-7c120ee9a19c
Gardner, Jennifer M.
0d95188b-206d-4817-8437-e163351f6e7f
Sundstrom, Joanna F.
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Jiranek, Vladimir
8e5a8dfd-f5b2-43e3-928b-11dff324abc7
Oliver, Stephen G.
c3de796f-4c50-4812-a383-208f23b3cd32
Binder, Benjamin J.
4b861311-8ad2-417c-903a-1d35e541d14b
Tronnolone, Hayden, Gardner, Jennifer M., Sundstrom, Joanna F., Jiranek, Vladimir, Oliver, Stephen G. and Binder, Benjamin J.
(2018)
TAMMiCol: Tool for analysis of the morphology of microbial colonies.
PLoS Computational Biology, 14 (12), [e1006629].
(doi:10.1371/journal.pcbi.1006629).
Abstract
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.
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Published date: December 2018
Additional Information:
Funding Information:
HT and BJB were supported by Australian Research Council (http://www.arc.gov.au/) Discovery Project DP160102644 (awarded to BJB and SGO). VJ, JMG and JFS were supported by Australian Research Council (http://www.arc.gov.au/) Discovery Project DP130103547 (awarded to VJ and SGO).
Publisher Copyright:
© 2018 Tronnolone et al. http://creativecommons.org/licenses/by/4.0/.
Identifiers
Local EPrints ID: 482661
URI: http://eprints.soton.ac.uk/id/eprint/482661
ISSN: 1553-734X
PURE UUID: 42bb33f2-5a70-4a87-9446-1c4dc56f7b0b
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Date deposited: 11 Oct 2023 16:48
Last modified: 18 Mar 2024 04:12
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Contributors
Author:
Hayden Tronnolone
Author:
Jennifer M. Gardner
Author:
Joanna F. Sundstrom
Author:
Vladimir Jiranek
Author:
Stephen G. Oliver
Author:
Benjamin J. Binder
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