My present work, in a nutshell

A Negative Feedback Loop Operating at the level of Translation in Yeast

Translation termination in Saccharomyces cerevisiae requires the essential protein eRF1 (eukaryotic release factor 1). eRF1 has a tRNA-like structure and interacts specifically with any of the three possible stop codons. This allows the release of the newly synthesised peptide from the ribosomal complex. Therefore eRF1 is crucial for determining the correct length of proteins in yeast.

We have identified four nonsense mutations in the eRF1 gene SUP45, which allow cell viability, despite correctly translated eRF1 being essential. This is due to negative feedback at the translational level. Truncated eRF1 produced from a nonsense mutation will not be able to terminate translation correctly, including termination at a nonsense mutation site. Consequently there is read-through of the nonsense mutation, resulting in increased amounts of full-length functional eRF1, which in turn will terminate efficiently at nonsense mutations producing increased amounts of truncated eRF1.

We are modelling this system not only as an elegant example of feedback, but also as there are biological examples of such negative feedback loops. For example; the bacterial release factor RF2 which recognises UGA and UAA stop codons, negatively regulates itself due to a premature UGA stop codon. Pausing at this stop codon (due to inefficient termination) causes a +1 frameshift and translation of the full-length RF2.

Initial results have concentrated on elucidating parameters for the model. E.g., numbers of release factor molecules per S. cerevisiae cell, half-life of proteins, and proportion of read-through of nonsense mutations.

We aim to perturb the system biologically as well as mathematically by regulating the amount of eRF1 or suppressor tRNAs for example. This will give us information on how robust the system is as well as being able to validate the model with experimental results.