Translation in the cell under fierce competition for shared resources: a mathematical model

Area of Science:

• Molecular Biology
• Systems Biology
• Biophysics

Background:

• Cellular translation involves messenger RNAs (mRNAs) competing for shared resources like free ribosomes.
• Resource scarcity, common in stress, viral infections, or heterologous gene expression, can dramatically impact global translation dynamics.
• The pool of free ribosomes is a critical, often limited, resource for protein synthesis.

Purpose of the Study:

• To model the effects of competition for free ribosomes on overall protein production.
• To analyze how adding new mRNAs affects protein output from existing mRNAs.
• To understand the saturation dynamics of total protein synthesis as mRNA numbers increase.

Main Methods:

• Developed a network model comprising multiple ribosome flow models (RFMs) for individual mRNAs.
• Interconnected RFMs via a shared pool of free ribosomes to simulate resource competition.
• Analyzed the model assuming a large number of mRNAs leading to a starved ribosome pool.

Main Results:

• Adding a new mRNA increases total protein production but decreases output from other mRNAs due to ribosome scarcity.
• The marginal benefit of adding more mRNAs diminishes as their numbers increase.
• Total protein production rate saturates at a limiting value with increasing mRNA concentration.

Conclusions:

• Competition for ribosomes significantly influences cellular translation efficiency.
• The number of mRNAs in a system has a non-linear effect on total protein yield.
• The model provides insights into optimizing protein production in systems with limited resources, such as cell-free expression systems.