Background Escherichia coli (E. coli) is the most abundant expression host for recombinant proteins. The production efficiency is dependent on a multitude of parameters. Therefore, high-throughput applications have become an increasingly frequent technique to investigate the main factors. Within this study, the effects of temperature, induction time and inducer concentration on the metabolic state and the product formation were extensively examined. Induction profiling of E. coli Tuner(DE3) pRhotHi-2-EcFbFP was performed in 48-well Flowerplates and standard 96-well plates using a robotic platform. In parallel shake flask cultivations, the respiration activity of the microorganisms was analyzed. Therefore, two online-monitoring systems were applied: the BioLector for microtiter plates and the RAMOS-device for shake flasks. The impact of different induction conditions on biomass and product formation as well as on the oxygen transfer rate was surveyed.ResultsDifferent optimal induction conditions were obtained for temperatures of 28, 30, 34, and 37 °C. The best inducer concentrations were determined to be between 0.05 and 0.1 mM IPTG for all investigated temperatures. This is 10–20 times lower than conventional guidelines suggest. The induction time was less relevant when the correct inducer concentration was chosen. Furthermore, there was a stronger impact on growth and respiration activity at higher temperatures. This indicated a higher metabolic burden. Therefore, lower IPTG concentrations were advantageous at elevated temperatures. Very similar results were obtained in standard 96-well plates.ConclusionTwo online-monitoring systems were successfully used to investigate the optimal induction conditions for the E. coli Tuner(DE3) pRhotHi-2-EcFbFP strain (lacY deletion mutant) at four different temperatures. The experimental effort was reduced to a minimum by integrating a liquid handling robot. To reach the maximum product formation, a detailed induction analysis was necessary. Whenever the cultivation temperature was changed, the induction conditions have to be adapted. Due to the experimental options provided by the BioLector technology, it was found that the higher the cultivation temperature, the lower the inducer concentration that has to be applied.Electronic supplementary materialThe online version of this article (10.1186/s12934-017-0832-4) contains supplementary material, which is available to authorized users.

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. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1543–1552, 2018