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Related Experiment Video

Updated: Sep 16, 2025

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Measuring Regulatory Network Inheritance in Dividing Yeast Cells Using Ordinary Differential Equations.

Wenbin Wu1, Taylor Kennedy2, Orlando Arguello-Miranda2

  • 1Department of Statistics, University of Washington.

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|July 9, 2025
PubMed
Summary
This summary is machine-generated.

We developed ODEinherit, a new method using ordinary differential equations (ODEs) to quantify how much protein regulation is inherited during cell division. This framework reveals significant variation in inheritance across cell generations.

Keywords:
Asymmetric cell divisionCellular dynamicsLive-cell imagingOrdinary differential equationProtein regulatory network

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Area of Science:

  • Cell biology
  • Systems biology
  • Quantitative biology

Background:

  • Inheritance of protein regulation during asymmetric cell division is complex and lacks formal mathematical definition.
  • Understanding this inheritance is crucial for predicting cell fate and responses to stress.

Purpose of the Study:

  • To introduce ODEinherit, a novel statistical framework for quantifying protein regulatory network inheritance during cell division.
  • To address the challenge of measuring how much of a mother cell's regulatory network is passed to its daughters.

Main Methods:

  • Utilizing ordinary differential equations (ODEs) to estimate cell-specific regulatory networks.
  • Incorporating adjustments for non-oscillatory trajectories and network density.
  • Quantifying inheritance by assessing a mother's network's explanatory power for daughter cell trajectories.

Main Results:

  • ODEinherit accurately quantifies inheritance, with precise measurement depending on network density adjustments.
  • Benchmarked on simulated data and applied to live-cell microscopy of 85 dividing S. cerevisiae cells.
  • Revealed substantial heterogeneity in inheritance rates among mother-daughter cell pairs.

Conclusions:

  • ODEinherit provides a robust method for quantifying protein regulatory inheritance.
  • The observed heterogeneity has implications for understanding cellular stress response and cell-fate prediction.
  • This framework opens new avenues for studying inheritance across cell generations.