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Empirical Bayes method using surrounding pixel information for number and brightness analysis.

Ryosuke Fukushima1, Johtaro Yamamoto2, Masataka Kinjo3

  • 1Laboratory of Molecular Cell Dynamics, Graduate School of Life Science, Hokkaido University, Sapporo, Japan.

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Summary

This study introduces EB-MAP-N&B, an improved method for Number and Brightness (N&B) analysis in fluorescence imaging. It enhances accuracy and precision in determining protein concentration and oligomeric states within cells.

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Area of Science:

  • Cellular and Molecular Biology
  • Biophysics
  • Fluorescence Microscopy

Background:

  • Number and Brightness (N&B) analysis quantifies protein concentration and oligomeric states using fluorescence imaging.
  • Traditional methods like the method of moments (MoM) suffer from limited accuracy and precision due to experimental constraints.
  • Outliers in MoM analysis can obscure cellular structures and spatial distribution information.

Purpose of the Study:

  • To develop a more accurate and precise N&B analysis method for fluorescence imaging.
  • To improve the visualization of spatial distribution and cellular structures in N&B analysis.
  • To enhance the quantification of protein concentration and oligomeric states in biological samples.

Main Methods:

  • Application of maximum likelihood (ML) and maximum a posteriori (MAP) estimation, combined with empirical Bayes (EB) methods (EB-MAP).
  • Construction of a prior distribution for pixels to leverage information from surrounding pixels.
  • Comparison of EB-MAP with MoM and ML using simulations and experimental data.

Main Results:

  • EB-MAP significantly reduced outliers compared to MoM, improving the visibility of spatial distribution and cellular structures.
  • The precision of EB-MAP for particle number was an order of magnitude better than MoM.
  • EB-MAP showed 1.5 times better precision for particle brightness compared to MoM.

Conclusions:

  • The developed EB-MAP-N&B method offers superior accuracy and precision for N&B analysis in fluorescence imaging.
  • This method aids in accurately recognizing changes in protein concentration and oligomeric states within cells.
  • Quantifying these parameters is crucial for understanding dynamic molecular mechanisms in cells.