ColTapp

ColTapp quantifies bacterial colony growth dynamics from endpoint and time-lapse images of agar plates to assess phenotypic heterogeneity, including colony lag time, growth rate, and the detection of persister cells.

Key Features:

• Automated colony detection and tracking: Automatically detects colonies on agar plates and tracks colony radius over time from endpoint and time-lapse images.
• Quantitative analysis capabilities: Computes colony lag time and growth rate and analyzes changes in colony size, color, and morphology over time.
• Bias correction for dense plates: Corrects bias from early saturation by accounting for the area available for each colony's growth, improving lag-time estimates from endpoint images.
• Support for population-level inference: Enables quantitative interpretation of phenotypic heterogeneity relevant to population survival and responses to antibiotic exposure.

Scientific Applications:

• Staphylococcus aureus colony analysis: Applied to Staphylococcus aureus time-lapse colony datasets to study population-level growth behaviors.
• Phenotypic heterogeneity and persistence: Infers metabolic-state distributions and identifies subpopulations, including persister cells, that resume growth later than actively dividing cells.
• Antibiotic response profiling: Quantifies growth dynamics to assess population survival and heterogeneity under antibiotic exposure.

Methodology:

Performs image analysis to detect colonies and measure radius over time from endpoint and time-lapse images; computes lag time and growth rate via built-in downstream analyses; corrects density-induced bias by estimating the area available per colony; monitors size, color, and morphology changes; distributed in MATLAB source code format and as executables for MacOS/Windows.