GreenerRPP

Greener, more sustainable platforms for high-value recombinant protein production

The GreenerRPP consortium aims to develop entirely novel variants of protein production platforms. We will design, test and validate a series of new strains and processes that can be used to produce the challenging new formats that are emerging. Particular emphasis will be placed on difficult-to-express proteins. Throughout the project we will enhance product yield and fidelity, with the aim of making production processes less wasteful and significantly 'greener'. We will maximise impact by not only establishing a world-leading European network in this field, but also initiating the development of a global network that incorporates research centres in Thailand, Malaysia and Vietnam, with the explicit aim of helping these countries to develop their own RPP programmes. This is fully in line with EU policies which recognise that 'multilateral research and innovation initiatives are the most effective way to tackle challenges facing our world - climate, health, food, energy and water - that are global by nature. Working together reduces the global burden, pools resources and achieves greater impact'.

Four interlinked research work packages (WPs) address the key problems in this field. WP1 will develop new strategies to express target proteins in the three selected host chassis, using a series of innovations to (i) produce such proteins in high amounts in the bacterial cytoplasm, (ii) export them to the periplasm or growth medium and (iii), secrete high amounts of biotherapeutics in mammalian cells. Success will be measured in terms of enhanced product yields and quality, resulting in reduced product losses upon downstream processing. WP2, on the other hand, is effectively the ‘strain clinic’ that will identify the best candidates among the new host strains, using proteomics and transcriptomics to (i) mitigate the stress and adaptive responses induced in WP1 and (ii) minimize product heterogeneity. Success will be measured in terms of high strain 'robustness' and reduced product heterogeneity. WP3 is the bridge between WP1 and WP2. It will integrate the acquired data with previously published data on stress responses using Artifical Intelligence (A.I.) and Machine Learning approaches to understand the consequences of the strain engineering and identify mitigation strategies. These will be fed back to WPs 1/2 for validation and design of next-generation chassis. Finally, WP4 will benchmark the new strains for industrial applications, by identifying factors that are only evident in industrial setups, feeding information to WP3 and ensuring that the new strains from WPs 1/2 are fit for purpose for the biotechnology sector.