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Image analysis driven single-cell analytics for systems microbiology.

Athanasios D Balomenos1, Panagiotis Tsakanikas2, Zafiro Aspridou3

  • 1Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilissia, Greece.

BMC Systems Biology
|April 6, 2017
PubMed
Summary

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This summary is machine-generated.

Bacterial Image Analysis driven Single Cell Analytics (BaSCA) automates the analysis of complex bacterial cell movies. This computational pipeline enables high-throughput systems microbiology by accurately tracking cells and their properties.

Area of Science:

  • Microbiology
  • Systems Biology
  • Computational Biology

Background:

  • Time-lapse microscopy is crucial for studying bacterial dynamics at the single-cell level.
  • Current computational methods struggle with complex cell movies and lack automation.
  • This limits high-throughput analysis in systems microbiology.

Purpose of the Study:

  • To address limitations in analyzing complex bacterial cell movies.
  • To enable high-throughput systems microbiology through automation.
  • To provide accurate cell segmentation and tracking for bacterial communities.

Main Methods:

  • Development of the Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline.
  • Utilizes advanced image processing and machine learning for cell segmentation and tracking.
Keywords:
Bacterial image analysisCell segmentationColonies segmentationLineage tree constructionMachine learningSingle-cell analyticsSingle-cell informaticsTime-lapse microscopyVisualization

Related Experiment Videos

  • Automated extraction and organization of single-cell properties into a database.

    • Main Results:

    • BaSCA achieves over 95% accuracy in bacterial cell segmentation and tracking, even with imperfect image quality and dense colonies.
    • Successfully segments and tracks individual cells and their lineage trees within growing bacterial communities.
    • Enables spatiotemporal analysis of single-cell properties, revealing trends and epigenetic effects across generations.

    Conclusions:

    • BaSCA accurately and efficiently analyzes bacterial cell movies at both single-cell and community scales.
    • Facilitates research into bacterial community effects and epigenetic inheritance in phenomena like biofilm formation and persister cell emergence.
    • Allows investigation of single-cell stochasticity within the context of community-driven effects.