eHooke

eHooke automates analysis of fluorescence microscopy images of spherical bacteria to classify cell cycle stages and quantify cell morphology and protein localization for studies of bacterial growth and division.

Key Features:

• Automated Cell Cycle Classification: Uses a trained artificial neural network to classify the cell cycle phase of individual Staphylococcus aureus cells from fluorescence microscopy images.
• Quantitative Image Analysis: Extracts quantitative parameters describing cell morphology and protein localization from fluorescence microscopy images in the context of the bacterial cell cycle.
• Application-Specific Design: Tailored for spherical bacteria (cocci) such as Staphylococcus aureus where cell elongation is not a valid proxy for cell cycle progression.

Scientific Applications:

• Cell Division and Morphogenesis Studies: Enables analysis of morphological changes and protein localization dynamics during bacterial cell cycle progression in cocci.
• Cell Cycle–Dependent Localization Analyses: Facilitates investigation of how protein localization varies across classified cell cycle stages in Staphylococcus aureus.

Methodology:

Uses a trained artificial neural network to recognize and classify cell cycle stages from fluorescence microscopy image data, enabling high-throughput analysis of large datasets.