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Noisy translation: modelling of stochastic effects on protein production

  • Full or part time

    Prof I Stansfield
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

This project will focus on the mathematical modelling of a fundamental process in the cell: translation of the messenger RNA into a protein. A messenger RNA (mRNA) contains the sequence of nucleotides transcribed from the DNA that encode a certain protein.

Molecular machines called ribosomes bind to the mRNA sequence and move along the nucleotide sequence thereby translating the sequence of codons (groups of 3 consecutive nucleotides) into the sequence of amino acids that form the protein. Like cars on a narrow countryside road, ribosomes cannot overtake each other, so that queues of ribosomes can form on mRNAs.
In this project we will develop a mathematical model to describe how ribosomes move along the mRNA sequence, thereby predicting protein production rates. This is a fundamental problem in molecular biology, as the amount of different kinds of proteins produced largely determined the behaviour of a cell.

In particular, we will focus on stochastic effects of the process of translation, predicting the extent of fluctuations in protein production expected from different mRNAs, taking into account effects such as codon composition, mRNA secondary structures and global competition for translation resources. Model predictions will be directly compared with experimental results so that a series of rounds of model refinement and validation can be performed.

The PhD student will work in a dynamic and interdisciplinary team of researchers working at the interface between physics and biology, integrating theoretical and experimental results.

Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in Physics or Applied Mathematics or Chemical/Bioengineering along with knowledge of Differential equations, statistical physics; knowledge/interest in dynamical systems, stochastic systems, modelling of biological systems.

APPLICATION PROCEDURE:

• Apply for Degree of Doctor of Philosophy in Physics
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form

When applying please ensure all required documents are attached:

• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV
• Details of 2 academic referees

Informal inquiries can be made to Prof M Carmen Romano () with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ()

Funding Notes

This project is advertised in relation to the research areas of the discipline of physics/applied mathematics. The successful applicant will be expected to provide the funding for Tuition fees, living expenses and maintenance. Details of the cost of study can be found by visiting View Website. THERE IS NO FUNDING ATTACHED TO THESE PROJECTS

References

[1] M. C. Romano, M. Thiel, I. Stansfield, and C. Grebogi, “Queueing Phase Transition: Theory of Translation”, Phys. Rev. Lett. 102, 198104 (2009).

[2] C. A. Brackley, M. C. Romano, C. Grebogi, and M. Thiel, “Limited Resources in a Driven Diffusion Process”, Phys. Rev. Lett. 105, 078102 (2010).

[3] C. A. Brackley, M. C. Romano, and M. Thiel, “The Dynamics of Supply and Demand in mRNA translation”, PLoS Comput. Biol. 7, e1002203 (2011).

[4] Ciandrini, L., Stansfield, I. & Romano, MC. (2013). 'Ribosome traffic on mRNAs maps to gene ontology: genome-wide quantification of translation initiation rates and polysome size regulation'. PLoS Computational Biology, vol 9, no. 1, e1002866.

[5] Marshall, E., Stansfield, I., and Romano, M.C. (2014) “Ribosome recycling induces optimal translation rate at low ribosomal availability”, J. R. Soc. Interface 11: 20140589

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