From the plethora of possible microbial hosts, Escherichia coli remains the most widely used “microbial factory” for recombinant protein production (RPP). However, despite the numerous advances, RPP in E. coli is still a significant challenge. Strong promoters to achieve high expression and protein production levels are often used, however, the underlying effects on the host physiology are often unseen. This thesis reports the development of “stress-minimisation” approaches for the production of recombinant proteins, either targeting the cytoplasm or the periplasmic space. First, the fermentation conditions for the production of TNFα in the cytoplasm were optimised. The expression vector, culture medium, temperature, inducer concentration and induction point were optimised, yielding 5.35 g ∙ L-1 of rhTNFα, 70% being accumulated as a soluble product. Second, different approaches for the production of recombinant proteins targeting the periplasm were evaluated, using an antibody fragment, scFv163R4, as a model protein. The effect of different growth conditions and signal peptides on the production of the scFv163R4 were evaluated. However, the selection of the optimal signal peptide was proven to be challenging, establishing the requirement of a high-throughput screening assay. This resulted in the development of a screening assay using β-lactamase as a reporter protein, for the evaluation of mutant signal peptide libraries with improved translocation activity. Initial evaluations resulted in the selection of two mutant signal peptides with enhanced translocation of scFv163R4-A, yielding almost 1 g ∙ L-1 of periplasmic scFv163R4-A. The generation of mutant signal peptide libraries in combination with the β-lactamase screening assay represents an important advance for the production of disulphide bonded proteins for the biotechnology industry.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:760301 |
| Date | January 2017 |
| Creators | Selas Castiñeiras, Tania |
| Publisher | University of Birmingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.bham.ac.uk//id/eprint/7985/ |
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