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  BacStalk: A comprehensive and interactive image analysis software tool for bacterial cell biology

Hartmann, R., van Teeseling, M. C. F., Thanbichler, M., & Drescher, K. (2020). BacStalk: A comprehensive and interactive image analysis software tool for bacterial cell biology. MOLECULAR MICROBIOLOGY, 114(1), 140-150. doi:10.1111/mmi.14501.

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License: CC BY
OA-Status:
Hybrid

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 Creators:
Hartmann, Raimo1, Author           
van Teeseling, Muriel C. F.2, Author
Thanbichler, Martin3, Author           
Drescher, Knut1, Author           
Affiliations:
1Max Planck Research Group Bacterial Biofilms, Max Planck Institute for Terrestrial Microbiology, Max Planck Society, ou_3266298              
2external, ou_persistent22              
3Max Planck Fellow Bacterial Cell Biology, Max Planck Institute for Terrestrial Microbiology, Max Planck Society, ou_3266301              

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 Abstract: Prokaryotic cells display a striking subcellular organization. Studies
of the underlying mechanisms in different species have greatly enhanced
our understanding of the morphological and physiological adaptation of
bacteria to different environmental niches. The image analysis software
tool BacStalk is designed to extract comprehensive quantitative
information from the images of morphologically complex bacteria with
stalks, flagella, or other appendages. The resulting data can be
visualized in interactive demographs, kymographs, cell lineage plots,
and scatter plots to enable fast and thorough data analysis and
representation. Notably, BacStalk can generate demographs and kymographs
that display fluorescence signals within the two-dimensional cellular
outlines, to accurately represent their subcellular location. Beyond
organisms with visible appendages, BacStalk is also suitable for
established, non-stalked model organisms with common or uncommon cell
shapes. BacStalk, therefore, contributes to the advancement of
prokaryotic cell biology and physiology, as it widens the spectrum of
easily accessible model organisms and enables highly intuitive and
interactive data analysis and visualization.

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 Dates: 2020-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 000525889200001
DOI: 10.1111/mmi.14501
 Degree: -

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Title: MOLECULAR MICROBIOLOGY
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 114 (1) Sequence Number: - Start / End Page: 140 - 150 Identifier: ISSN: 0950-382X
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