Monitoring of protein profiles for the optimization of recombinant fermentation processes using public domain databases

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Abstract
The expression of human superoxide dismutase in fed-batch fermentation of E. coli HMS174(DE3)(pET3ahSOD) was studied as model system. Due to the frequently used strong T7 promoter system a high metabolic load is exerted, which triggers stress response mechanisms and finally leads to the differentiation of the host cell. As a consequence, host cell metabolism is partly shifted from growth to survival accompanied by significant alterations of the protein pattern. In terms of process optimization two-dimensional electrophoresis deserves as a powerful tool to monitor these changes on protein level. For the analysis of samples derived from different states of recombinant protein production wide-range Immobiline Dry Strips pH 3–10 were used. In order to establish an efficient procedure for accelerated process optimization and to avoid costly and time-consuming analysis like mass spectrometry (MS), a database approach for the identification of significant changes of the protein pattern was evaluated. On average, 935 spots per gel were detected, whereby 50 are presumably stress-relevant. Out of these, 24 proteins could be identified by using the SWISS-2DPAGE database (www.expasy.ch/ch2d/). The identified proteins are involved in regulatory networks, energy metabolism, purine and pyrimidine nucleotide synthesis and translation. By this database approach, significant fluctuations of individual proteins in relation to recombinant protein production could be identified. Seven proteins show strong alterations (>100%) directly after induction and can therefore be stated as reliable marker proteins for the assessment of stress response. For distinctive interpretation of this highly specific information, a bioinformatic and statistic tool would be essential in order to perceive the role and contribution of individual proteins in stress response.