eHooke: A tool for automated image analysis of spherical bacteria based on cell cycle progression

Fluorescence microscopy is a critical tool for cell biology studies on bacterial cell division and morphogenesis. Because the analysis of fluorescence microscopy images evolved beyond initial qualitative studies, numerous images analysis tools were developed to extract quantitative parameters on cel...

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Bibliographic Details
Published in:Biological imaging (Cambridge, England) England), 2021, Vol.1, p.e3-e3, Article e3
Main Authors: Saraiva, Bruno M, Krippahl, Ludwig, Filipe, Sérgio R, Henriques, Ricardo, Pinho, Mariana G
Format: Article
Language:English
Subjects:
Algorithms
Antibiotics
Automation
Bacteria
Cell cycle
Cell division
Classification
Cytology
Cytoplasm
Datasets
Deep learning
Drug resistance
Fluorescence microscopy
Image processing
Localization
Microscopy
Morphogenesis
Morphology
Neural networks
Pathogens
Software
Software Report
User training
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Summary:Fluorescence microscopy is a critical tool for cell biology studies on bacterial cell division and morphogenesis. Because the analysis of fluorescence microscopy images evolved beyond initial qualitative studies, numerous images analysis tools were developed to extract quantitative parameters on cell morphology and organization. To understand cellular processes required for bacterial growth and division, it is particularly important to perform such analysis in the context of cell cycle progression. However, manual assignment of cell cycle stages is laborious and prone to user bias. Although cell elongation can be used as a proxy for cell cycle progression in rod-shaped or ovoid bacteria, that is not the case for cocci, such as Here, we describe eHooke, an image analysis framework developed specifically for automated analysis of microscopy images of spherical bacterial cells. eHooke contains a trained artificial neural network to automatically classify the cell cycle phase of individual cells. Users can then apply various functions to obtain biologically relevant information on morphological features of individual cells and cellular localization of proteins, in the context of the cell cycle.
ISSN:2633-903X
2633-903X
DOI:10.1017/S2633903X21000027