BACMMAN

BACMMAN performs automated analysis of high-throughput 2D and 3D time-series images from mother machine experiments to segment and track single bacterial cells and intracellular fluorescent spots for quantitative single-cell studies.

Key Features:

• Segmentation and Tracking: Performs segmentation and time-resolved tracking of bacterial cells and intracellular fluorescent spots in mother machine images.
• Configurable Image-Processing Pipeline: Provides a highly configurable image-processing pipeline adaptable to different dataset types and experimental conditions.
• Integration with Data Analysis Software: Supports coupling and data export to external data analysis software for downstream analysis of data subsets.
• Performance and Modularity: Implements a modular architecture with configuration options to enable fast automated processing of large time-series datasets.

Scientific Applications:

• Single-cell heterogeneity analysis: Quantifies cellular heterogeneity in bacterial populations using mother machine time-series.
• Cell growth and division dynamics: Analyzes single-cell growth and division events over time.
• Intracellular fluorescent spot dynamics: Tracks the spatiotemporal behavior of intracellular fluorescent spots within single cells.
• High-throughput time-lapse imaging analysis: Processes and quantitatively analyzes large 2D and 3D time-series datasets from mother machine experiments.

Methodology:

Implements automated image-analysis algorithms with high modularity and configuration options; a reported example processes a single-position, single-channel dataset of 1,000 frames (~2 GB) in about six minutes on a regular computer.