Engineering of a robust Escherichia coli chassis and exploitation for large-scale production processes.

In large-scale bioprocesses microbes are exposed to heterogeneous substrate availability reducing the overall process performance. A series of deletion strains was constructed from E. coli MG1655 aiming for a robust phenotype in heterogeneous fermentations with transient starvation.

Transcriptional profiling of the stringent response mutant strain E. coli SR reveals enhanced robustness to large-scale conditions.

In large-scale fed-batch production processes, microbes are exposed to heterogeneous substrate availability caused by long mixing times. Escherichia coli, the most common industrial host for recombinant protein production, reacts by recurring accumulation of the alarmone ppGpp and energetically wasteful transcriptional strategies. Here, we compare the regulatory responses of the stringent response mutant strain E.

Methylthioadenosine (MTA) boosts cell-specific productivities of Chinese hamster ovary cultures: dosage effects on proliferation, cell cycle and gene expression.

A major goal for process and cell engineering in the biopharmaceutical industry is enhancing production through increasing volumetric and cell-specific productivities (CSP). Here, we present 5'-deoxy-5'-(methylthio)adenosine (MTA), the degradation product of S-(5'-adenosyl)-L-methionine (SAM), as a highly attractive native additive which can boost CSP by 79% when added to exponentially growing cells at a concentration of 250-300 μm. Notably, cell viability and cell size remain higher than in non-treated cultures.

Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors.

Eulerian-Lagrangian approach to investigate cellular responses in a bioreactor has become the center of attention in recent years. It was introduced to biotechnological processes about two decades ago, but within the last few years, it proved itself as a powerful tool to address scale-up and -down topics of bioprocesses. It can capture the history of a cell and reveal invaluable information for, not only, bioprocess control and design but also strain engineering.

Data-driven in silico prediction of regulation heterogeneity and ATP demands of Escherichia coli in large-scale bioreactors.

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.

Physiological Response of to Increasingly Nutrient-Rich Growth Conditions.

To ensure economic competitiveness, bioprocesses should achieve maximum productivities enabled by high growth rates (μ) and equally high substrate consumption rates (q) as a prerequisite of sufficient carbon-to-product conversion. Both traits were investigated and improved via bioprocess engineering approaches studying the industrial work horse . Standard minimal medium CGXII with glucose as sole carbon source was supplemented with complex brain-heart-infusion (BHI) or amino acid (AA) cocktails.

In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models.

Industrial bioreactors range from 10.000 to 700.000 L and characteristically show different zones of substrate availabilities, dissolved gas concentrations and pH values reflecting physical, technical and economic constraints of scale-up.