4.3 Article

Prediction of recombinant protein production by Escherichia coli derived online from indicators of metabolic burden

期刊

BIOTECHNOLOGY PROGRESS
卷 34, 期 6, 页码 1543-1552

出版社

WILEY
DOI: 10.1002/btpr.2704

关键词

Scattered light; oxygen transfer rate; E. coli; microtiter plate; recombinant protein

资金

  1. German federal and state governments to promote science and research at German universities

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\ Background: The oxygen transfer rate (OTR) and the biomass concentration are two important parameters describing a microbial fermentation. It has been shown before that from the course of these parameters over time information on metabolic burden during heterologous protein production can be obtained. While online monitoring in large fermenters is ubiquitously established, it is still not a common practice in small-scale cultures. Nevertheless, several techniques like the Respiration Activity MOnitoring System (RAMOS) device for online monitoring of the OTR in shake flasks and the BioLector device for measuring scattered light (ScL) representing biomass in microtiter plates have been developed. Results: A new microtiter plate-based method is presented that reveals how online derived ScL signals can be transformed into signals that are proportional to the courses of OTR over time for Escherichia coli. The transformed signal is obtained by simply taking the first derivative of ScL (dScL/dt). The proportionality of both parameters is successfully validated for the strains E. coli BL21(DE3) and Tuner(DE3) expressing cellulases and the fluorescent protein FbFP, respectively. Relative amounts of produced heterologous proteins are predicted exclusively based on the course of the transformed ScL signal. A variety of induction conditions with varying inducer concentration and induction time were investigated with this method. Conclusion: The presented method based on ScL measurement allows for high-throughput online determination of signals proportional to OTR courses. They enable the interpretation of physiological states and offer the possibility to predict the recombinant protein production in E. coli. (c) 2018 American Institute of Chemical Engineers

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