Category: Success Stories

Funding secured after BioProNET projects

To date, BioProNET-funded projects have leveraged over £830,000 of funding from industry to support collaborative bioprocessing projects.

Below are details of funding that has been secured following on from, or as a result of a BioProNET-funded project.

Innovate UK funding of £70K for the project ‘Development of a novel membrane photobioreactor for cultivation of Haematococcus pluvialis as a biofilm’ to Varicon Aqua Solutions (following from BIV_Aug15_Allen)

Funding of £681K from the BBSRC and the US NSF for the project ‘synthetic gene circuits to measure and mitigate translational stress during heterologous protein expression’ to Ian Stanfield (following on from the BioProNET sandpit meeting).

Funding of £1.5M from the EPSRC awarded to Paul Dalby et al. for the project ‘Enabling rapid liquid and freeze-dried formulation design for the manufacture and delivery of novel biopharmaceuticals’ (from PoC_Dec14_Warwicker).

Publications from BioProNET funding

Details of all BioProNET-funded projects have moved – please click here.

In vitro model for predicting bioavailability of subcutaneously injected monoclonal antibodies
Hanne KinnunenBown, Catherine Bonn, Stefan Yohe, Daniela Bumbaca Yadav, Thomas W.Patapoff, Ann Daugherty, Randall J.Mrsny
Journal of Controlled Release, Volume 273, Pages 13-20 10.1016/j.jconrel.2018.01.015

Codon-depedent translational accuracy controls protein quality in Eschericha coli but not Saccharomyces cerevisiae
Lyne Jossé, Connor D. D. Sampson, Mick F. Tuite, Kevin Howland,Tobias von der Haar
doi: (preprint)

TatA complexes exhibit a marked change in organisation in response to expression of the TatBC complex
Sarah M. Smith, Andrew Yarwood, Roland A. Fleck, Colin Robinson, and Corinne J. Smith
Biochem J. 474, 1495–1508, 2017

Protein-Sol: A web tool for predicting protein solubility from sequence
Hebditch M, Alejandro Carballo-Amador M, Charonis S, Curtis R, Warwicker J.
Bioinformatics doi: 10.1093/bioinformatics/btx345 May 29 2017

A poly-omics machine-learning method to predict metabolite production in CHO cells
Zampieri, G., Coggins, M., Valle, G. and Angione, C. Proceedings of the The 2nd International Electronic Conference on Metabolomics, 20–27 November 2017; doi:10.3390/iecm-2-04993

Case studies of BioProNET-funded projects

Here are some highlights of completed BioProNET-funded projects – proof of concept funding, business interaction vouchers, workshop funding and scientific exchange awards.

Clicking on each title will open a pdf version of that case study. To see all the case studies in full on this website, click on the purple bar below the titles.

Scientific exchange visit boosts separation technologies collaboration
Speeding up and slowing down: altering translation speed to enhance protein yield
Hijacking intracellular storage bodies to produce difficult to express proteins
Developing a novel fluorescence-based biopharmaceutical quality control technology
Design & testing of a membrane
for advanced biologic production
Collaborative development of glycolipid separation technology to reduce costs
BioProNET funding drives the use of motor proteins for nanopore DNA sequencing
BIV funding grows algae bioprocessing collaboration
BIV funding lights up collaboration on fluorescent protein expression in microalgae
PoC study shows protein synthesis errors can cause activity losses in recombinant protein
Warwick and JEOL Strike Gold in Electron Microscopy Collaboration
Dynamic partnership aims to reduce cell harvest time
Cobra and Lancaster partnership helps unravel new analytical tool for DNA topology
Collaboration creates a recipe for success in cell-free protein synthesis
Edinburgh and Recyclatech Join Forces to Recover Microbial By-Products
Sandpit Meeting Builds Collaboration Workshop
Exchange visit funding seeds early career researcher collaborations
Scissor technology cuts out a collaboration between Bath and Arecor

BioProNET meetings ignite collaborative project on biologic production

Professor Ian Stansfield from the University of Aberdeen has recently been awarded funding
for a collaborative project investigating how to optimize the production of biologics, which was catalyzed by his participation at BioProNET events.

The production of vaccines, antibodies and other proteins in cell lines can induce cellular stress, which can lead to errors in translation — including ribosome frameshift errors. Such mistranslation can compromise the yield and quality of the protein product, and hence the safety and efficacy of biologics. Ian’s project will pursue a better understanding of causes of translational error through the design and application of novel reporters of mistranslation.

“Initial discussions on this project were started as a result of the BioProNET sandpit meeting, held in June 2015, when I made initial contact with a scientist from the biotechnology company Fujifilm Diosynth Biotechnologies,” says Ian.

As a result of this networking meeting, Ian co-organized a BioProNet-sponsored workshop on recombinant protein authenticity, together with colleagues Mick Tuite and Tobias von der Haar from the University of Kent. Ian commented “The attendance of scientists from Fujifilm at our BioProNET-sponsored workshop in London consolidated ideas for the project”.

The project includes collaboration partner Professor Phil Farabaugh, a molecular biologist from University of Maryland, USA, and physicist Dr Mamen Romano (University of Aberdeen) who will be mathematically modelling gene expression processes. Ian’s group will then use synthetic biology approaches to  couple the output from the new mistranslation sensors to recombinant protein expression, in order to autoregulate mistranslation and the quality of the recombinant protein product.

Fujifilm will test these synthetic gene circuits in in yeast and E.coli to maximise the impact of this research on industrial biotechnology.

More about the project, which is jointly funded by the BBSRC (to Ian Stansfield and Mamen Romano) and the US National Science Foundation (to Phil Farabaugh) can be found here.