Prediction of Escherichia coli expression performance in microtiter plates by analyzing only the temporal development of scattered light during culture

Abstract Background Escherichia coli is often used for recombinant protein production. The expression of recombinant proteins negatively affects the microbial growth, thus, a balance between protein expression and biomass formation is preferable to reach high product- and space-time-yield. Already in screening experiments, suboptimal conditions causing too weak or too strong induction must be avoided. High-throughput screening devices such as the BioLector are often applied for screening experiments. The BioLector allows optical online monitoring of each well in a continuously orbitally shaken microtiter plate via scattered light and fluorescence measurements. This technique enables a fast identification of promising clones. However, to determine the expression performance of non-fluorescent products elaborated offline analysis is often required. Methods A mathematical method is developed to distinguish between cultures, which are insufficiently, optimally or too strongly induced. Therefore, just the temporal development of the scattered light intensity signal is investigated. It is found that discrimination between the different intensities of induction is possible via principal component analysis. By fitting an extended sigmoidal function to the trajectory of the scattered light over time, two characteristic parameters are found. These are used in an empirical model to predict the expression performance. Results The method was established for a wide range of culture conditions based on 625 E. coli cultures. Three E. coli host strains (Tuner(DE3), BL21(DE3), and BL21-Gold(DE3)) expressing either flavin-mononucleotide-based fluorescent protein (FbFP) or Cellulase celA2 were investigated. Cultures were conducted in two different types of microtiter plates (48- and 96-wells), in two online measurement devices at four temperatures (28 °C, 30 °C, 34 °C, and 37 °C). More than 95% of the predicted values are in agreement with the offline measured expression performances with a satisfying accuracy of ±30%. Conclusions The properties of cultures studied can be represented by only two characteristic parameters (slope at and time of the inflection point) received from fitting an extended sigmoidal function to the respective scattered light trajectory. Based on these two characteristic parameters, predictions of the standardized expression performance are possible and for a first screen elaborated offline analysis can be avoided. To the best of our knowledge, this is the first work presenting a method for the general prediction of expression performance of E. coli based solely on the temporal development of scattered light signals