A scalable screening of E. coli strains for recombinant protein expression

Autor(es)

Morao, Luana G. ; Manzine, Livia R. ; Clementino, Livia Oliveira D. ; Wrenger, Carsten ; Nascimento, Alessandro S.

• Tipo de documento: Artigo Científico
• Fonte: PLoS One; v. 17, n. 7, p. 10-pg., 2022-07-25.

Resumo

Structural biology projects are highly dependent on the large-scale expression of soluble protein and, for this purpose, heterologous expression using bacteria or yeast as host systems is usually employed. In this scenario, some of the parameters to be optimized include (i) those related to the protein construct, such as the use of a fusion protein, the choice of an N-terminus fusion/tag or a C-terminus fusion/tag; (ii) those related to the expression stage, such as the concentration and selection of inducer agent and temperature expression and (iii) the choice of the host system, which includes the selection of a prokaryotic or eukaryotic cell and the adoption of a strain. The optimization of some of the parameters related to protein expression, stage (0, is straightforward. On the other hand, the determination of the most suitable parameters related to protein construction requires a new cycle of gene cloning, while the optimization of the host cell is less straightforward. Here, we evaluated a scalable approach for the screening of host cells for protein expression in a structural biology pipeline. We evaluated four Escherichia co/i strains looking for the best yield of soluble heterologous protein expression using the same strategy for protein construction and gene cloning and comparing it to our standard strain, Rosetta 2 (DE3). Using a liquid handling device (robot), E. coli pT-GroE, Lemo21 (DE3), Arctic Express (DE3), and Rosetta Gami 2 (DE3) strains were screened for the maximal yield of soluble heterologous protein recovery. For the genes used in this experiment, the Arctic Express (DE3) strain resulted in better yields of soluble heterologous proteins. We propose that screening of host cell/strain is feasible, even for smaller laboratories and the experiment as proposed can easily be scalable to a high-throughput approach. (AU)

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