Automated recognition of intracellular organelles in confocal microscope images

Traffic. 2002 Jan;3(1):66-73. doi: 10.1034/j.1600-0854.2002.30109.x.


Recognition of the localisation of intracellular proteins is essential to the understanding of their function. It is usually made through knowledge of and comparison to the distribution of well-characterised intracellular organelles by experts in cell biology. We have automated this process in order to achieve a more objective and quantitative assessment of the protein distribution within the cell, which can be employed by the less experienced cell biologist and may be utilised as a training program for inexperienced users, or as a high throughput localisation program for novel genes in functional analysis. Here we describe the development and testing of a classification system based on a modular neural network trained with sets of confocal sections through cell lines fluorescently stained for markers of key intracellular structures. The system functioned well in spite of the variability in pattern that occurs between individual cells and performed with 97% accuracy, which gives us confidence in the method and in its future development. It is envisaged that this program will aid the design of further experiments utilising colocalisation with known organelle marker proteins, in order to confirm putative trafficking pathways and protein--protein interactions of the protein of interest.

MeSH terms

  • Animals
  • Cell Line
  • Cell Nucleus / ultrastructure
  • Endoplasmic Reticulum / ultrastructure
  • Endosomes / ultrastructure
  • Humans
  • Immunohistochemistry
  • Interphase
  • Lysosomes / ultrastructure
  • Microscopy, Confocal / methods*
  • Microscopy, Fluorescence / methods
  • Mitosis
  • Organelles / ultrastructure*
  • Protein Transport
  • Tumor Cells, Cultured
  • trans-Golgi Network / ultrastructure