Modelling ribosome kinetics and translational control on dynamic mRNA.

Area of Science:

• Molecular Biology
• Computational Biology
• Virology

Background:

• Cellular homeostasis relies on precise control of protein synthesis and levels.
• Regulation occurs transcriptionally (mRNA levels) or translationally (mRNA-ribosome interactions).
• Positive-sense single-stranded RNA viruses often utilize translational control for protein regulation.

Purpose of the Study:

• To develop a computational method for simulating stochastic protein synthesis on dynamic messenger RNA.
• To incorporate co-translational mRNA folding influenced by ribosome movement.
• To validate the model using the bacteriophage MS2 virus.

Main Methods:

• Gillespie algorithm for stochastic simulation.
• Modeling dynamic messenger RNA with co-translational folding.
• Application to bacteriophage MS2 coat protein synthesis and translational repression.

Main Results:

• The computational model accurately reproduced experimental measurements of MS2 coat protein production.
• The model successfully simulated translational repression of viral RNA-dependent RNA polymerase at high coat protein concentrations.
• Demonstrated the model's ability to capture key aspects of viral protein synthesis regulation.

Conclusions:

• The developed computational technique allows for detailed examination of viral infection dynamics at the genomic RNA level.
• This approach can be used to study general translation control mechanisms in polycistronic mRNAs.
• Opens new avenues for understanding ssRNA virus replication and host-cell interactions.