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Dot Scanner: open-source software for quantitative live-cell imaging in planta.

Holly Allen1, Brian Davis2, Jenna Patel1

  • 1Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania, 16802, USA.

The Plant Journal : for Cell and Molecular Biology
|February 4, 2024
PubMed
Summary
This summary is machine-generated.

Dot Scanner is a new Python program that automates the analysis of fluorescent particle movement in plant cells. This tool provides accurate and efficient live-cell imaging analysis, reducing bias and saving significant time.

Keywords:
automated data analysis softwarecellulose synthesisconfocal microscopylive‐cell imagingtechnical advance

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Area of Science:

  • Plant Biology
  • Cellular Imaging
  • Biophysics

Background:

  • Confocal microscopy is vital for studying plant growth and development.
  • Manual image analysis is time-consuming, prone to errors, and introduces bias.
  • Automated analysis is needed to improve efficiency and accuracy in live-cell imaging.

Purpose of the Study:

  • To develop an automated Python program, Dot Scanner, for analyzing fluorescently tagged particles in plant cells.
  • To overcome the limitations of manual image analysis in live-cell imaging studies.
  • To provide an unbiased and efficient tool for plant cell research.

Main Methods:

  • Development of Dot Scanner, a Python program for particle analysis.
  • Analysis of particle densities, lifetimes, and displacements.
  • Validation using side-by-side comparison with Fiji-ImageJ on cellulose biosynthesis particles.

Main Results:

  • Dot Scanner demonstrated comparable accuracy to Fiji-ImageJ for particle densities and lifetimes.
  • Dot Scanner significantly reduces selection bias compared to Fiji-ImageJ.
  • The program efficiently distinguishes weak signals from background noise caused by photobleaching.

Conclusions:

  • Dot Scanner offers a robust, efficient, and unbiased method for analyzing live-cell imaging data in plants.
  • The automation significantly shortens analysis workflows from weeks to minutes.
  • This free and accessible tool will greatly benefit plant cell biology research.