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Optimisation of surface expression using the AIDA autotransporter



Optimisation of surface expression using the AIDA autotransporter



Microbial Cell Factories 10: 72



Bacterial surface display is of interest in many applications, including live vaccine development, screening of protein libraries and the development of whole cell biocatalysts. The goal of this work was to understand which parameters result in production of large quantities of cells that at the same time express desired levels of the chosen protein on the cell surface. For this purpose, staphylococcal protein Z was expressed using the AIDA autotransporter in Escherichia coli. The use of an OmpT-negative E. coli mutant resulted in successful expression of the protein on the surface, while a clear degradation pattern was found in the wild type. The expression in the mutant resulted also in a more narrow distribution of the surface-anchored protein within the population. Medium optimisation showed that minimal medium with glucose gave more than four times as high expression as LB-medium. Glucose limited fed-batch was used to increase the cell productivity and the highest protein levels were found at the highest feed rates. A maintained high surface expression up to cell dry weights of 18 g l-1 could also be achieved by repeated glucose additions in batch cultivation where production was eventually reduced by low oxygen levels. In spite of this, the distribution in the bacterial population of the surface protein was narrower using the batch technique. A number of parameters in recombinant protein production were seen to influence the surface expression of the model protein with respect both to the productivity and to the display on the individual cell. The choice of medium and the cell design to remove proteolytic cleavage were however the most important. Both fed-batch and batch processing can be successfully used, but prolonged batch processing is probably only possible if the chosen strain has a low acetic acid production.

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Accession: 036203328

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PMID: 21917130

DOI: 10.1186/1475-2859-10-72


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