Escherichia coli exposed to industrial-scale heterogeneous mixing conditions respond to external stress by initiating short-term metabolic and long-term strategic transcriptional programs. In native habitats, long-term strategies allow survival in severe stress but are of limited use in large bioreactors, where microenvironmental conditions may change right after said programs are started. Related on/off switching of genes causes additional ATP burden that may reduce the cellular capacity for producing the desired product. Here, we present an agent-based data-driven model linked to computational fluid dynamics, finally allowing to predict additional ATP needs of Escherichia coli K12 W3110 exposed to realistic large-scale bioreactor conditions. The complex model describes transcriptional up-and downregulation dynamics of about 600 genes starting from subminute range covering 28 h. The data-based approach was extracted from comprehensive scale-down experiments. Simulating mixing and mass transfer conditions in a 54 m 3 stirred bioreactor, 120,000 E. coli cells were tracked while fluctuating between different zones of glucose availability. It was found that cellular ATP demands rise between 30% and 45% of growth decoupled maintenance needs, which may limit the production of ATP-intensive product formation accordingly. Furthermore, spatial analysis of individual cell transcriptional patterns reveal very heterogeneous gene amplifications with hot spots of 50%-80% messenger RNA upregulation in the upper region of the bioreactor. The phenomenon reflects the time-delayed regulatory response of the
Dedicated to Prof. Dr. Christian Wandrey on the occasion of his 80th birthday A comprehensive experimental characterization of a small-scale bubble column bioreactor (60 mL) is presented. Bubble size distribution (BSD), gas holdup, and k L a were determined for different types of liquids, relevant fermentation conditions and superficial gas velocities u G . The specific interfacial area a and liquid mass transfer coefficient k L have been identified independent of each other to unravel their individual impact on k L a. Results show that increasing u G leads to larger bubbles and higher gas holdup. As both parameters influence a in opposite ways, no increase of a with u G is found. Furthermore, k L increases with increasing bubble size outlining that improved oxygen transfer is not the result of higher a but of risen k L instead. The results build the foundation for further simulative investigations.
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