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Related Experiment Video

Updated: Feb 17, 2026

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers

Published on: July 28, 2018

Cellular reprogramming dynamics follow a simple 1D reaction coordinate.

Sai Teja Pusuluri^1,2, Alex H Lang^3,4,2, Pankaj Mehta^3,4

¹Department of Physics and Astronomy and Nanoscale and Quantum Phenomena Institute, Ohio University, Athens, OH, 45701, United States of America.

Physical Biology

|December 7, 2017

Summary

This summary is machine-generated.

Cellular reprogramming to induced pluripotent stem cells (iPSCs) follows a single, universal gene expression path. This optimal trajectory is independent of experimental methods or time, simplifying our understanding of cell fate changes.

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Last Updated: Feb 17, 2026

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers

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Area of Science:

Cellular and Molecular Biology
Developmental Biology
Systems Biology

Background:

Cellular reprogramming involves global gene expression changes, crucial for converting cell types.
Understanding the dynamics of these gene expression alterations during reprogramming is a significant challenge.

Purpose of the Study:

To analyze gene expression dynamics during cellular reprogramming to induced pluripotent stem cells (iPSCs).
To identify a unifying principle governing gene expression changes across different reprogramming protocols and timelines.

Main Methods:

Reanalysis of time-course data from cellular reprogramming experiments.
Application of dimensionality reduction techniques to identify key gene expression trajectories.
Monte Carlo simulations based on epigenetic landscape models.

Main Results:

Gene expression dynamics during reprogramming follow a simple, one-dimensional (1D) reaction coordinate.
This coordinate is invariant to the duration of reprogramming and specific experimental protocols.
Simulations support a 'barrier-crossing' model where reprogramming follows an optimal path.

Conclusions:

Cellular reprogramming exhibits a canonical gene expression trajectory, suggesting an underlying optimal path.
This finding simplifies the complex process of cell fate conversion.
The identified reaction coordinate provides a fundamental framework for studying reprogramming dynamics.