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How to build next-generation regulatory devices to control the production of biotherapeutics


   School of Life Sciences

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  Prof J McCarthy, Dr Alexander Darlington  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Introduction

Bioscientists are progressively learning how to engineer biological systems like cells and regulatory circuits in ways that give rise to predictable outcomes. Pursuing this fascinating path of research has two major types of benefit: 1. By trying to engineer biosystems we understand them better; 2. Engineered biosystems are useful in many areas, including medicine, agriculture, energy and the environment, and thus such work is important in industry.

It is often the case that we want to construct a genetic system that can be tightly regulated. For example, if we engineer a cluster of genes that encode the enzymes that catalyse the respective steps of a biosynthetic pathway, it can be useful to control exactly when that pathway is turned on or off. The most obvious reason for doing this is that when the pathway is operating it may be imposing a significant burden on cellular resources so that we need to constrain the overall impact on growth.

So what is the best way to regulate a synthetic biosystem such as a pathway? Up to now, this has largely been achieved using transcriptional components (promoters, transcription factors). Relying on circuitry built at this level in an important host organism like yeast limits our options because there are not many suitable transcriptional components available. In this project, you will examine whether an alternative route is possible, i.e. one that relies on translational regulatory devices built using synthetic mRNA 5’untranslated regions, aptamers, aptazymes and/or RNA-binding proteins (these are reviewed in McCarthy, 2021).

Experimental work

Saccharomyces cerevisiae and other yeasts are important industrial host organisms for the production of biotherapeutics that are widely used in medicine. Examples of relevant molecular products are shikimate, bikaverin and lycopene. We want to move away from the more traditional (transcriptional) regulatory circuitry used to control the production of such important molecules and establish a toolbox of faster-reacting and more tightly controlled posttranscriptional circuitry.

Cutting-edge quantitative methods involving flow cytometry, robotics and single-cell RNAseq will be used to characterise these systems in yeast cells growing on different media. This will yield an overview of the impact of regulation of gene expression directed by the respective genetic devices on cell physiology and growth, thus increasing our understanding of these systems and also providing data that inform their potential use in industrial processes. The work will also involve assessment of the heterogeneity in response at the single cell level. Novel combinations of the devices will also be considered.

Modelling

Students will also work with Dr Darlington to apply a new yeast modelling framework which captures key physiological processes, gene expression and growth. Using these methods, we will explore how host physiology is impacted by the choice of regulatory expression system and design new systems which have both improved dynamic performance, increased yields and reduced impact on growth.

Overall, this project will provide training in sought-after experimental and computational techniques, and also generate valuable new data on important genetic and physiological processes and relationships in living cells. There is a high probability of co-authorship on at least one research publication.

BBSRC Strategic Research Priority: Understanding the rules of life  Systems Biology and Microbiology, Renewable Resources and Clean Growth - Industrial Biotechnology, and Integrated Understanding of Health - Pharmaceuticals.

Techniques that will be undertaken during the project:

Genome editing using CRISPR/Cas9, flow cytometry, robotics, single-cell RNAseq, microscopy, proteomics and computational modelling. These cutting-edge methods are highly valued and play important roles in both academic and industrial contexts. 


Funding Notes

Studentships provide:
Full Tuition fees
A tax free annual stipend for living expenses (in academic year 2022-23 this was £17,668)
A travel / conference budget
A generous consumables budget
Use of a laptop for the duration of the programme.
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