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Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulations.
1Department of Chemistry, IIT Bombay, Mumbai, India.
Methods in Molecular Biology (Clifton, N.J.)
|April 19, 2023
Summary
This study introduces a novel stochastic simulation algorithm to accurately measure both intrinsic and extrinsic fluctuations in biological systems. The new method helps understand cell fate decisions and transcriptional heterogeneity.
Area of Science:
- Systems Biology
- Computational Biology
- Molecular Biology
Background:
- Biological processes are influenced by molecular fluctuations.
- Intrinsic fluctuations (due to low molecule numbers) are well-studied.
- Extrinsic fluctuations (e.g., cell division, epigenetics) are less understood but impact gene expression.
Purpose of the Study:
- To develop a method for quantifying extrinsic fluctuations.
- To analyze transcriptional heterogeneity in biological networks.
- To improve understanding of cell-fate decisions.
Main Methods:
- Proposed a new stochastic simulation algorithm.
- Applied the algorithm to bidirectional transcriptional reporter systems.
- Utilized the Nanog transcriptional regulatory network for illustration.
Main Results:
- The algorithm efficiently estimates extrinsic fluctuations alongside intrinsic variability.
- The method reconciled experimental observations for Nanog transcription.
- The approach generated new predictions for Nanog network dynamics.
Conclusions:
- The developed algorithm accurately quantifies both intrinsic and extrinsic fluctuations.
- This method is applicable to various transcriptional regulatory networks.
- Understanding these fluctuations is crucial for cell biology and disease research.
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