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Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

Correlated receptor transport processes buffer single-cell heterogeneity.

Stefan M Kallenberger¹, Anne L Unger², Stefan Legewie³

¹Department for Bioinformatics and Functional Genomics, Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany.

Plos Computational Biology

|September 26, 2017

Summary

This summary is machine-generated.

Cellular responses to erythropoietin receptor (EpoR) signaling vary due to differences in EpoR trafficking. Mathematical modeling revealed conserved EpoR dynamics and a buffering system that stabilizes signaling despite cell-to-cell variability.

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Area of Science:

Cellular Biology
Biophysics
Systems Biology

Background:

Cellular responses to extracellular ligands, such as erythropoietin (Epo), are highly variable.
Receptor trafficking dynamics significantly influence signal transduction and cellular response variability.
Understanding receptor transport is crucial for deciphering cell signaling mechanisms.

Purpose of the Study:

To quantitatively characterize single-cell variability in erythropoietin receptor (EpoR) trafficking.
To identify key parameters governing EpoR dynamics using mathematical modeling.
To investigate the conservation of EpoR trafficking dynamics across different cell types.

Main Methods:

Live-cell imaging to track EpoR dynamics at the single-cell level.
Development of ensembles of single-cell mathematical models to reduce parameter uncertainty.
Quantitative analysis of EpoR turnover, internalization, recycling, and degradation.

Main Results:

Rapid EpoR turnover, recycling to the plasma membrane, and degradation of Epo-EpoR complexes are essential for EpoR trafficking.
EpoR trafficking dynamics in adherent lung cancer cells are conserved compared to suspension cells.
Significant cell-to-cell variability (one order of magnitude) was observed in EpoR transport processes.

Conclusions:

EpoR trafficking dynamics are widely conserved across different cellular contexts.
Correlated kinetics of opposing transport processes act as a buffering system, reducing variability in activated Epo-EpoR complex concentration.
Single-cell mathematical modeling is a powerful approach to dissect complex cellular dynamics and variability.