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Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single Cell Data.

Fabian Konrath1, Alexander Loewer2, Jana Wolf3,4

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Methods in Molecular Biology (Clifton, N.J.)
|April 19, 2023
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Summary
This summary is machine-generated.

This study introduces a new method to systematically predict interactions between signaling pathways by observing how perturbing one pathway affects another. This approach successfully identified multiple crosstalk points between the NF-κB and p53 pathways.

Keywords:
Genotoxic stressIKKβLive cell imagingNF-κB signalingQuantitative modelingSignaling crosstalkSingle cell analysisSubpopulation-specific modelingp53 signaling

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Area of Science:

  • Systems Biology
  • Molecular Biology
  • Cell Signaling

Background:

  • Signaling pathway crosstalk modulates cellular responses.
  • Understanding molecular network interactions is crucial for comprehensive cellular response analysis.

Purpose of the Study:

  • To develop a systematic approach for predicting interaction points between signaling pathways.
  • To investigate the crosstalk between the NF-κB and p53 signaling pathways.

Main Methods:

  • Perturbing one signaling pathway and quantifying changes in a second pathway's response.
  • Utilizing ordinary differential equation-based modeling to extract crosstalk information.
  • Employing time-resolved single-cell data and subpopulation-based modeling.

Main Results:

  • Successfully predicted interaction points between signaling pathways.
  • Identified multiple simultaneous interaction points between NF-κB and p53 signaling.
  • Demonstrated the utility of the approach in analyzing pathway crosstalk.

Conclusions:

  • The developed approach enables systematic prediction of signaling pathway crosstalk.
  • The NF-κB and p53 pathways exhibit complex crosstalk with multiple interaction points.
  • This method provides a robust framework for dissecting complex cellular signaling networks.