Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions

Rev Sci Instrum. 2015 Dec;86(12):126104. doi: 10.1063/1.4937479.


We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Bacterial Adhesion / physiology*
  • Cell Tracking / methods*
  • Escherichia coli O157 / cytology*
  • Escherichia coli O157 / physiology*
  • Image Interpretation, Computer-Assisted / methods
  • Machine Learning
  • Microscopy / methods*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique