Modelling cellular stress during recombinant protein production for improving upstream biomanufacturing processes

Recombinant proteins are expressed non-endogenously by an organism, and they have wide applications in biotechnology ranging from the biomanufacture of industrially and agriculturally relevant enzymes to therapeutics and the manufacture of biologics. Due to this commercial interest, there is pressure to achieve high yields of high quality protein product by the host cells. However, all biological systems are optimised for their own survival, and not for the production of a heterologous entity, and therefore, the process of heterologous protein expression, particularly in a state of overproduction, creates a huge burden on the cell. The host has difficulty to achieve a high quality product, i.e. a correctly processed protein, under the stress imposed by high production demand. This stress triggers responses within the host to cope with the accumulation of the low quality, and therefore undesirable, product. These responses range from the formation of inclusion bodies by prokaryotic hosts such as bacteria, to the induction of unfolded protein response by eukaryotic hosts such as yeast and mammalian cells. This research will facilitate the development of quantitative models of this stress response and the utilisation of these models in the improvement and optimisation of upstream biomanufacturing processes of recombinant protein production. Within this domain, the research is expected to equip the industry with new research methods and tools, which will help them reduce time in cell and process development and assist the alleviation of costs and risks of product development. The benefits are directly associated with biopharmaceutical and biocatalysis activities, substantial contributors of sustainability, thus the outcomes of the project will benefit the society as a whole. The knowledge and the tools resulting from the project being offered to the service of relevant industries will also strengthen their position in the global markets allowing them to remain competitive in their respective fields of operation.
The aim of this research is to develop a formal understanding mammalian and microbial stress mechanisms that have an adverse impact on recombinant protein production capacity via a modelling framework. Its incorporation with data-driven models of upstream biomanufacturing will expand the predictive capability of model-driven analysis. In order to achieve this goal, the following objectives will be met:
- Population of a knowledge-base of existing numerical and descriptive data pertaining the stress mechanisms described above
- Development of a structured understanding of the existing know-how and identification of missing information creating bottlenecks in formulating a working model
- Hypothesis generation on the structure (i.e. the topology) of this mechanism to translate into a formal description
- Construction of a structured model of cellular stress in response to heterologous protein production
- Model implementation (mathematical + computational framework)
- Testing and improving the predictive/descriptive capacity of the model (via simulations or programming)
- Incorporation of the model into existing pipelines to improve current practice
Novel approaches in handling and modelling the data will be explored as needed based on the type and the nature of the data accumulating in the knowledge-base. It is expected that stochastic models and elaborate parameter estimation techniques will have to be employed.
This research project aligns with EPSRC's research themes of healthcare technologies and manufacturing the future, and with the following research areas: Biological informatics, manufacturing technologies, mathematical biology, and operational research. It also aligns with EPSRC's current research priorities in Digital Manufacturing and Sustainable Industries.
No companies or collaborators are currently involved in the project, in the event of any future collaborations, this information will be updated