Project No.2454

STANDARD PROJECT

Primary Supervisor

Dr Owen Rackham – University of Southampton

Co-Supervisor(s)

Prof Mark Smales – University of Kent

Summary

The role of translational regulation in coordinating biological phenomenon and optimising biologics manufacturing is increasingly recognised.

Despite this, compared to transcriptional regulation, we are still in our infancy in terms of understanding, controlling and manipulating translation. As such, in this project, the student will build on recent work from the Rackham Lab in (1) identifying regulators of translation and (2) creating the first high-resolution atlas of human translation to create a generative AI tool for mRNAs that display cell-type specific translation. This tool will generate testable hypotheses for experimental validation in the Smales Lab. Specifically, we will use AI to generate sequences of model transcripts (e.g. nanoLuciferase, RBD domain of SARS-CoV-2 spike protein) that are predicted to be translated at faster or slower speeds in a cell-specific manner. We will then experimentally determine how ‘tunable’ the expression of these different cell types is using cell culture models when delivered either through plasmid DNA or as in vitro transcribed mRNAs (IVTmRNAs). 

This project will provide the student with an environment in which they can (a) develop their computational biology skills with a view to processing, analysing and visualising omics data (RNA-seq and Ribo-Seq), (b) create AI tools for the advancement of biological problems and (c) design and execute experimental validations. Ultimately, we expect this project to create valuable commercial IP, help us better understand the “rules of life”, and offer diverse publication opportunities. For instance, the creation of such a platform could be used to increase the rate at which biologics are manufactured, allow for the targeting of RNA-based therapeutics such that these are translated in a cell or tissue-specific manner, and (critically) allow us to understand better the rules that govern translational regulation in humans (and beyond). 

The candidate should have some experience in programming and an interest in developing both computational and experimental skills throughout their Ph.D. An interest in achieving impact through publication and commercialisation may also benefit this project.