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Updated: May 10, 2026
10:56
Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Published on: May 17, 2014
Translational cross talk in gene networks.
William H Mather1, Jeff Hasty, Lev S Tsimring
1Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Biophysical Journal
|June 11, 2013
Summary
Competition for ribosomes by mRNAs can cause anticorrelated protein counts. A stochastic model reveals this phenomenon, showing strong negative correlations emerge when transcripts significantly exceed ribosomes, especially with mRNA fluctuations.
Area of Science:
- Molecular Biology
- Biophysics
- Systems Biology
Background:
- Competition for limited cellular resources, such as ribosomes, by messenger RNAs (mRNAs) is a known factor influencing protein production.
- Experimental evidence suggests this competition can lead to anticorrelations in the counts of different proteins.
Purpose of the Study:
- To investigate a stochastic model explaining the anticorrelation of protein counts due to competition for translational resources.
- To analyze the impact of system load (underloaded vs. overloaded) on protein count statistics.
Main Methods:
- Utilizing concepts from multiclass queueing theory to model the competition.
- Developing and solving simplified stochastic models with fixed mRNA and ribosome numbers.
- Extending analysis to more realistic models with fluctuating mRNA and ribosome abundances.
Main Results:
- A simplified model showed weak positive correlations when transcript numbers slightly exceeded ribosome numbers, and strong negative correlations when significantly exceeding them.
- Fluctuations in mRNA negatively contributed to correlations, while ribosomal fluctuations contributed positively.
- A strong anticorrelation extremum was observed near the underloaded-to-overloaded transition when mRNA fluctuations dominated.
Conclusions:
- The study provides a theoretical framework for understanding how competition for ribosomes shapes protein count distributions.
- The transition from an underloaded to an overloaded state significantly alters protein count correlations.
- mRNA and ribosome fluctuations play distinct and crucial roles in determining the degree of protein count anticorrelation.
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