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(A*STAR) Bacterial glycosyltransferases for bioengineering of biologics

Project Description

Within industry, biologics are usually produced in large bioreactors which are subject to slight manufacturing changes in production and purification which induce variations in glycosylation. Variation in glycosylation of bio-therapeutic drugs can have profound effects on its safety and efficacy. Despite its importance, in-vivo control of biologic glycosylation, remains a particularly uncertain process.

Recently, we (Sabine Flitsch and BTI) have been successful in developing an in-vitro glyco-engineering approach using bacterial glycotransferases to a recombinant glycoprotein alpha-1 anti-trypsin. This has significant potential to increase the yield of high quality product after culturing/fermentation. Furthermore, the technology has significant potential to produce higher value, cheaper bio-better products for the clinic. Whilst this is an attractive proposition, much work still is required to develop a scalable process along with analytical development which can compete with current production modalities.

We seek to develop a method to refine a scalable process to increase the hyper-sialylation of recombinant products with the accompanying analytics for validation.

Project Description
The project aims to develop a robust, scalable in-vitro glyco-engineering platform to control the glycosylation of recombinant glycoprotein biologics. This will be performed using bacterial glyco-transferases. The project will also involve developing the necessary glyco-analytics which can be used to monitor processes and quality control for assessment.
Specific Objectives:
1. Development of a cost-effective in-vitro glyco-engineering platform for the hyper-sialylation of therapeutic recombinant glycoproteins
2. Develop a fermentation process to increase the production of bacterial sialyl-transferases important in the hyper glycosylation of therapeutic recombinant glycoproteins.
3. Application of current advanced glyco-analytical approaches to monitor the quality of the glyco-engineered product

Entry Requirements:
Applications should be submitted online and candidates should make direct contact with the Manchester supervisor to discuss their application directly. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.

Funding Notes

This project is available to UK/EU candidates. Funding covers fees (UK/EU rate) and stipend for four years. Overseas candidates can apply providing they can pay the difference in fees and are from an eligible country. Candidates will be required to split their time between Manchester and Singapore, as outlined on View Website.

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.


Edward Pallister†‡, Matthew Choo†, Jien Nee Tai†, Pauline Rudd†, Kun Huang‡, Andrea Marchasi‡, Peter Both‡, Sabine L. Flitsch‡ and Terry Nguyen-Khuong, In Vitro Hyper-Digalacto-Sialylation of Recombinant Alpha-1-Antitrypsin using Photobacterium Dameselae α2,6 Sialyltransferase - Manuscript in preparation

Walsh I, Nguyen-Khuong T, Wongtrakul-Kish K, Tay SJ, Chew D, Tasha J, Taron CH, Rudd PM. GlycanAnalyzer: Software for Automated Interpretation of N-Glycan Profiles after Exoglycosidase Digestions. Bioinformatics. 2018 Aug 7. doi: 10.1093/bioinformatics/bty681. [Epub ahead of print] PubMed PMID: 30101321.

Zhao S, Walsh I, Abrahams JL, Royle L, Nguyen-Khuong T, Spencer D, Fernandes DL, Packer NH, Rudd PM, Campbell MP. GlycoStore: a database of retention properties for glycan analysis. Bioinformatics. 2018 Sep 15;34(18):3231-3232. doi: 10.1093/bioinformatics/bty319. PubMed PMID: 29897488.

Pralow A, Hoffmann M, Nguyen-Khuong T, Rapp E, Reichl U. Improvement of the glycoproteomic toolbox with the discovery of a unique C-terminal cleavage specificity of flavastacin for N-glycosylated asparagine. Sci Rep. 2017 Sep
12;7(1):11419. doi: 10.1038/s41598-017-11668-1. PubMed PMID: 28900186; PubMed Central PMCID: PMC5595805.

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